social science research study

Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

Anol Bhattacherjee, University of South Florida

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

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Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

About the book.

Part I. Main Body

Science and scientific research
Thinking like a researcher
The research process
Theories in scientific research
Research design
Measurement of constructs
Scale reliability and validity
Survey research
Experimental research
Case research
Interpretive research
Qualitative analysis
Quantitative analysis: Descriptive statistics
Quantitative analysis: Inferential statistics
Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline, MIS Quarterly and Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of MIS Quarterly for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at http://ab2020.weebly.com .

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WashU Libraries

Conducting research.

The Process
Step 1: Exploring an idea
Step 2: Finding background info.
Step 3: Finding Print/E-Books
Step 4: Finding Articles (Current Research)
Step 5: Evaluating your sources
Step 6: Citing your sources
FAQs This link opens in a new window
Library Vocabulary
Research in the Humanities
Research in the Social Sciences
Research in the Sciences

Researching in the Social Sciences

Social scientists interpret and analyze human behavior, generally using empirical methods of research. Though original data gathering and analysis are central to social sciences research, researchers also use library and Web sources to--

obtain raw data for model building or analysis
locate information about a particular model, theory, or methodology to be used in a research project
review the literature to place new research in context

Subjects of study in the social sciences are often interdisciplinary, so your searching will likely need to be, as well. A review of the literature for a social sciences research project not only should identify what research has been done but also compare and contrast the available information and evaluate its significance.

Each of the social sciences has a well-developed set of research tools to help you find relevant material. Some of the WashU Libraries Research Guides listed below may give you ideas for beginning your research. You should also consult your subject librarian for help getting started or refining your search.

Find a Subject Librarian This is a list of the Subject Librarians by academic subject.

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Types of Sources

Types of sources

Primary sources are original material, created at the time of the event or by the subject you are studying. They may include statistics, survey and poll data, field notes, transcripts, photographs, and many other examples. This kind of material is the closest you can get to your actual subject, raw and unfiltered by later scholars and critics.

Secondary sources are works that analyze primary sources or other secondary sources. These include journal articles, monographs about a subject or person, and critical reviews. All of these can also act as primary sources, depending upon your subject of research.

Tertiary sources index or otherwise collect primary and secondary sources. Examples are encyclopedias, bibliographies, dictionaries, and online indicies. These sources tend to be most useful as jumping off points for your research, leading you to the more in-depth secondary and primary material that you will need to conduct a thorough study.

Conducting the Literature Review

The literature review is an important part of researching in the social sciences. Research and the literature review in particular are cyclical processes.

Where do I Start?
Where Should I Look?
How Do I Know I am Done?
How Do I Organize My Literature Review?

Where do I start? The Research Question Begin with what you know: What are the parameters of your research area? Do you have any particular interests in a relevant topic? Has something you've read or talked about in a class caught your attention? Brainstorm some keywords you know are related to your topic, and start searching. Do a search in a few of the Search Resources boxes on the Libraries' Website and see what comes up. Scan titles. Do a Google Scholar search. Read an encyclopedia article. Get as much background information as you can, taking note of the most important people, places, ideas, events. As you read, take notes-- these will be the building blocks of your future searches. It's probable your question will change over the course of your reading and research. No worries! If you're unsure about your topic, check with your faculty mentor.

Some tips Throw out a wide net and read, read, read. Consider the number and kinds of sources you'll need. Which citation style should you use? What time period should it cover? Is currency important? What do you need to be aware of related to scholarly versus popular materials?

Read widely but selectively.
Follow the citation trail -- building on previous research by reviewing bibliographies of articles and books that are close to your interest.
Synthesize previous research on the topic.
Aim to include both summary and synthesis.
Focus on ways to have the body of literature tell its own story. Do not add your own interpretations at this point.
Look for patterns and find ways of tying the pieces together.

Where should I look?

Databases, journals, books
Review articles
Organizations

How do I know I am done? One key factor in knowing you are done is that you keep running into the same articles and materials. With no new information being uncovered you can assume you've exhausted your current search and should modify search terms, or perhaps you have reached a point of exhaustion with the available research.

How do I organize my literature review?

Identify the organizational structure you want to use: chronologically, thematically, or methodologically.
Start writing: let the literature tell the story, find the best examples, summarize instead of quote, synthesize by rephrasing (but cite!) in context of your work.

Additional information available @ The Literature Review: A Few Tips on Conducting It (University of Toronto)

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Last Updated: Aug 14, 2024 7:12 AM
URL: https://libguides.wustl.edu/research

USC Libraries
Research Guides

Organizing Your Social Sciences Research Paper

6. The Methodology
Purpose of Guide
Design Flaws to Avoid
Independent and Dependent Variables
Glossary of Research Terms
Reading Research Effectively
Narrowing a Topic Idea
Broadening a Topic Idea
Extending the Timeliness of a Topic Idea
Academic Writing Style
Applying Critical Thinking
Choosing a Title
Making an Outline
Paragraph Development
Research Process Video Series
Executive Summary
The C.A.R.S. Model
Background Information
The Research Problem/Question
Theoretical Framework
Citation Tracking
Content Alert Services
Evaluating Sources
Primary Sources
Secondary Sources
Tiertiary Sources
Scholarly vs. Popular Publications
Qualitative Methods
Quantitative Methods
Insiderness
Using Non-Textual Elements
Limitations of the Study
Common Grammar Mistakes
Writing Concisely
Avoiding Plagiarism
Footnotes or Endnotes?
Further Readings
Generative AI and Writing
USC Libraries Tutorials and Other Guides
Bibliography

The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I. Groups of Research Methods

There are two main groups of research methods in the social sciences:

The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II. Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
Tools and methods used to identify and collect information, and how you identified relevant variables,
The ways in which you processed the data and the procedures you used to analyze that data, and
The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE: Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE: If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III. Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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Introduction & Top Questions

Effects of theology

Effects of the classics and of cartesianism.

Heritage of the Enlightenment
Major themes resulting from democratic and industrial change
New ideologies
New intellectual and philosophical tendencies
Political science
Cultural anthropology
Social psychology
Social statistics and social geography
Science and social science
Social science in the research universities
Early attempts at a science of humanity: Durkheim and Weber
Humanity as a symbolic phenomenon
Identity, will, and the thinking self
Institutions, nations, and civilizations
Applications of the science of humanity: nationalism, economic growth, and mental illness

Where was Émile Durkheim educated?
Where did Émile Durkheim work?
Why is Émile Durkheim significant?

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Table Of Contents

What is a social science?

A social science is any branch of academic study or science that deals with human behaviour in its social and cultural aspects. Usually included within the social sciences are cultural (or social) anthropology, sociology, psychology, political science, and economics.

What is the relationship between the terms behavioral science and social science ?

Beginning in the 1950s, the term behavioral sciences was often applied to disciplines categorized as social sciences. Some favored this term because it brought these disciplines closer to some of the sciences, such as physical anthropology, which also deal with human behavior.

Who named the social science discipline of sociology?

Auguste Comte gave the social science of sociology its name and established the new discipline in a systematic fashion.

What is cultural anthropology's relationship to the social sciences?

Cultural anthropology is a branch of the social sciences that deals with the study of culture in all of its aspects and that uses the methods, concepts, and data of archaeology, ethnography and ethnology, folklore, and linguistics.

What was Adolphe Quetelet's contribution to the social sciences?

Adolphe Quetelet was a key figure in the social statistics branch of the social sciences. He was the first person to call attention, in a systematic manner, to the kinds of structured behavior that could be observed and identified only through statistical means.

social science , any branch of academic study or science that deals with human behaviour in its social and cultural aspects. Usually included within the social sciences are cultural (or social) anthropology , sociology , psychology , political science , and economics . The discipline of historiography is regarded by many as a social science, and certain areas of historical study are almost indistinguishable from work done in the social sciences. Most historians, however, consider history as one of the humanities . In the United States , focused programs, such as African-American Studies, Latinx Studies, Women, Gender, and Sexuality Studies, are, as a rule , also included among the social sciences, as are often Latin American Studies and Middle Eastern Studies, while, for instance, French, German, or Italian Studies are commonly associated with humanities. In the past, Sovietology was always considered a social science discipline, in contrast to Russian Studies.

Beginning in the 1950s, the term behavioral sciences was often applied to the disciplines designated as the social sciences. Those who favoured this term did so in part because these disciplines were thus brought closer to some of the sciences, such as physical anthropology and physiological psychology , which also deal with human behaviour.

Strictly speaking, the social sciences, as distinct and recognized academic disciplines, emerged only on the cusp of the 20th century. But one must go back farther in time for the origins of some of their fundamental ideas and objectives. In the largest sense, the origins go all the way back to the ancient Greeks and their rationalist inquiries into human nature , the state , and morality . The heritage of both Greece and Rome is a powerful one in the history of social thought, as it is in other areas of Western society. Very probably, apart from the initial Greek determination to study all things in the spirit of dispassionate and rational inquiry, there would be no social sciences today. True, there have been long periods of time, as during the Western Middle Ages , when the Greek rationalist temper was lacking. But the recovery of this temper, through texts of the great classical philosophers, is the very essence of the Renaissance and the Enlightenment in modern European history. With the Enlightenment, in the 17th and 18th centuries, one may begin.

Heritage of the Middle Ages and the Renaissance

The same impulses that led people in that age to explore Earth , the stellar regions, and the nature of matter led them also to explore the institutions around them: state, economy, religion , morality , and, above all, human nature itself. It was the fragmentation of medieval philosophy and theory, and, with this, the shattering of the medieval worldview that had lain deep in thought until about the 16th century, that was the immediate basis of the rise of the several strands of specialized social thought that were in time to provide the inspiration for the social sciences.

Medieval theology , especially as it appears in St. Thomas Aquinas ’s Summa theologiae (1265/66–1273), contained and fashioned syntheses from ideas about humanity and society—ideas indeed that may be seen to be political, social, economic, anthropological, and geographical in their substance. But it is partly this close relation between medieval theology and ideas of the social sciences that accounts for the different trajectories of the social sciences, on the one hand, and the trajectories of the physical and life sciences, on the other. From the time of the English philosopher Roger Bacon in the 13th century, there were at least some rudiments of physical science that were largely independent of medieval theology and philosophy. Historians of physical science have no difficulty in tracing the continuation of this experimental tradition, primitive and irregular though it was by later standards, throughout the Middle Ages . Side by side with the kinds of experiment made notable by Bacon were impressive changes in technology through the medieval period and then, in striking degree , in the Renaissance . Efforts to improve agricultural productivity; the rising utilization of gunpowder , with consequent development of guns and the problems that they presented in ballistics; growing trade , leading to increased use of ships and improvements in the arts of navigation , including use of telescopes ; and the whole range of such mechanical arts in the Middle Ages and Renaissance as architecture , engineering , optics , and the construction of watches and clocks —all of this put a high premium on a pragmatic and operational understanding of at least the simpler principles of mechanics , physics , astronomy , and, in time, chemistry .

In short, by the time of Copernicus and Galileo in the 16th century, a fairly broad substratum of physical science existed, largely empirical but not without theoretical implications on which the edifice of modern physical science could be built. It is notable that the empirical foundations of physiology were being established in the studies of the human body being conducted in medieval schools of medicine and, as the career of Leonardo da Vinci so resplendently illustrates, among artists of the Renaissance, whose interest in accuracy and detail of painting and sculpture led to their careful studies of human anatomy .

Very different was the beginning of the social sciences. In the first place, the Roman Catholic Church , throughout the Middle Ages and even into the Renaissance and Reformation , was much more attentive to what scholars wrote and thought about the human mind and human behaviour in society than it was toward what was being studied and written in the physical sciences. From the church’s point of view, while it might be important to see to it that thought on the physical world corresponded as far as possible to what Scripture said—witnessed, for example, in the famous questioning of Galileo—it was far more important that such correspondence exist in matters affecting the human mind, spirit, and soul . Nearly all the subjects and questions that would form the bases of the social sciences in later centuries were tightly woven into the fabric of medieval Scholasticism , and it was not easy for even the boldest minds to break this fabric.

Then, when the hold of Scholasticism did begin to wane, two fresh influences, equally powerful, came on the scene to prevent anything comparable to the pragmatic and empirical foundations of the physical sciences from forming in the study of humanity and society. The first was the immense appeal of the Greek classics during the Renaissance, especially those of the philosophers Plato and Aristotle . A great deal of social thought during the Renaissance was little more than gloss or commentary on the Greek classics. One sees this throughout the 15th and 16th centuries.

Second, in the 17th century there appeared the powerful influence of the philosopher René Descartes . Cartesianism , as his philosophy was called, declared that the proper approach to understanding of the world, including humanity and society, was through a few simple, fundamental ideas of reality and, then, rigorous, almost geometrical deduction of more complex ideas and eventually of large, encompassing theories, from these simple ideas, all of which, Descartes insisted, were the stock of common sense—the mind that is common to all human beings at birth. It would be hard to exaggerate the impact of Cartesianism on social and political and moral thought during the century and a half following publication of his Discourse on Method (1637) and his Meditations on First Philosophy (1641). Through the Enlightenment into the later 18th century, the spell of Cartesianism was cast on nearly all those who were concerned with the problems of human nature and human society.

Great amounts of data pertinent to the study of human behaviour were becoming available in the 17th and 18th centuries. The emergence of nationalism and the associated impersonal state carried with it ever growing bureaucracies concerned with gathering information, chiefly for taxation , census , and trade purposes. The voluminous and widely published accounts of the great voyages that had begun in the 15th century, the records of soldiers, explorers, and missionaries who perforce had been brought into often long and close contact with indigenous and other non-Western peoples, provided still another great reservoir of data. Until the beginning of the 19th century, these and other empirical materials were used, if at all, solely for illustrative purposes in the writings of the social philosophers. Just as in the equally important area of the study of life, no philosophical framework as yet existed to allow for an objective and comprehensive interpretation of these empirical materials. Only in physics could this be done at the time.

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3 The research process

In Chapter 1, we saw that scientific research is the process of acquiring scientific knowledge using the scientific method. But how is such research conducted? This chapter delves into the process of scientific research, and the assumptions and outcomes of the research process.

Paradigms of social research

Our design and conduct of research is shaped by our mental models, or frames of reference that we use to organise our reasoning and observations. These mental models or frames (belief systems) are called paradigms . The word ‘paradigm’ was popularised by Thomas Kuhn (1962) [1] in his book The structure of scientific r evolutions , where he examined the history of the natural sciences to identify patterns of activities that shape the progress of science. Similar ideas are applicable to social sciences as well, where a social reality can be viewed by different people in different ways, which may constrain their thinking and reasoning about the observed phenomenon. For instance, conservatives and liberals tend to have very different perceptions of the role of government in people’s lives, and hence, have different opinions on how to solve social problems. Conservatives may believe that lowering taxes is the best way to stimulate a stagnant economy because it increases people’s disposable income and spending, which in turn expands business output and employment. In contrast, liberals may believe that governments should invest more directly in job creation programs such as public works and infrastructure projects, which will increase employment and people’s ability to consume and drive the economy. Likewise, Western societies place greater emphasis on individual rights, such as one’s right to privacy, right of free speech, and right to bear arms. In contrast, Asian societies tend to balance the rights of individuals against the rights of families, organisations, and the government, and therefore tend to be more communal and less individualistic in their policies. Such differences in perspective often lead Westerners to criticise Asian governments for being autocratic, while Asians criticise Western societies for being greedy, having high crime rates, and creating a ‘cult of the individual’. Our personal paradigms are like ‘coloured glasses’ that govern how we view the world and how we structure our thoughts about what we see in the world.

Paradigms are often hard to recognise, because they are implicit, assumed, and taken for granted. However, recognising these paradigms is key to making sense of and reconciling differences in people’s perceptions of the same social phenomenon. For instance, why do liberals believe that the best way to improve secondary education is to hire more teachers, while conservatives believe that privatising education (using such means as school vouchers) is more effective in achieving the same goal? Conservatives place more faith in competitive markets (i.e., in free competition between schools competing for education dollars), while liberals believe more in labour (i.e., in having more teachers and schools). Likewise, in social science research, to understand why a certain technology was successfully implemented in one organisation, but failed miserably in another, a researcher looking at the world through a ‘rational lens’ will look for rational explanations of the problem, such as inadequate technology or poor fit between technology and the task context where it is being utilised. Another researcher looking at the same problem through a ‘social lens’ may seek out social deficiencies such as inadequate user training or lack of management support. Those seeing it through a ‘political lens’ will look for instances of organisational politics that may subvert the technology implementation process. Hence, subconscious paradigms often constrain the concepts that researchers attempt to measure, their observations, and their subsequent interpretations of a phenomenon. However, given the complex nature of social phenomena, it is possible that all of the above paradigms are partially correct, and that a fuller understanding of the problem may require an understanding and application of multiple paradigms.

Two popular paradigms today among social science researchers are positivism and post-positivism. Positivism , based on the works of French philosopher Auguste Comte (1798–1857), was the dominant scientific paradigm until the mid-twentieth century. It holds that science or knowledge creation should be restricted to what can be observed and measured. Positivism tends to rely exclusively on theories that can be directly tested. Though positivism was originally an attempt to separate scientific inquiry from religion (where the precepts could not be objectively observed), positivism led to empiricism or a blind faith in observed data and a rejection of any attempt to extend or reason beyond observable facts. Since human thoughts and emotions could not be directly measured, they were not considered to be legitimate topics for scientific research. Frustrations with the strictly empirical nature of positivist philosophy led to the development of post-positivism (or postmodernism) during the mid-late twentieth century. Post-positivism argues that one can make reasonable inferences about a phenomenon by combining empirical observations with logical reasoning. Post-positivists view science as not certain but probabilistic (i.e., based on many contingencies), and often seek to explore these contingencies to understand social reality better. The post-positivist camp has further fragmented into subjectivists , who view the world as a subjective construction of our subjective minds rather than as an objective reality, and critical realists , who believe that there is an external reality that is independent of a person’s thinking but we can never know such reality with any degree of certainty.

Burrell and Morgan (1979), [2] in their seminal book Sociological p aradigms and organizational a nalysis , suggested that the way social science researchers view and study social phenomena is shaped by two fundamental sets of philosophical assumptions: ontology and epistemology. Ontology refers to our assumptions about how we see the world (e.g., does the world consist mostly of social order or constant change?). Epistemology refers to our assumptions about the best way to study the world (e.g., should we use an objective or subjective approach to study social reality?). Using these two sets of assumptions, we can categorise social science research as belonging to one of four categories (see Figure 3.1).

If researchers view the world as consisting mostly of social order (ontology) and hence seek to study patterns of ordered events or behaviours, and believe that the best way to study such a world is using an objective approach (epistemology) that is independent of the person conducting the observation or interpretation, such as by using standardised data collection tools like surveys, then they are adopting a paradigm of functionalism . However, if they believe that the best way to study social order is though the subjective interpretation of participants, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives, then they are employing an interpretivism paradigm. If researchers believe that the world consists of radical change and seek to understand or enact change using an objectivist approach, then they are employing a radical structuralism paradigm. If they wish to understand social change using the subjective perspectives of the participants involved, then they are following a radical humanism paradigm.

Four paradigms of social science research

To date, the majority of social science research has emulated the natural sciences, and followed the functionalist paradigm. Functionalists believe that social order or patterns can be understood in terms of their functional components, and therefore attempt to break down a problem into small components and studying one or more components in detail using objectivist techniques such as surveys and experimental research. However, with the emergence of post-positivist thinking, a small but growing number of social science researchers are attempting to understand social order using subjectivist techniques such as interviews and ethnographic studies. Radical humanism and radical structuralism continues to represent a negligible proportion of social science research, because scientists are primarily concerned with understanding generalisable patterns of behaviour, events, or phenomena, rather than idiosyncratic or changing events. Nevertheless, if you wish to study social change, such as why democratic movements are increasingly emerging in Middle Eastern countries, or why this movement was successful in Tunisia, took a longer path to success in Libya, and is still not successful in Syria, then perhaps radical humanism is the right approach for such a study. Social and organisational phenomena generally consist of elements of both order and change. For instance, organisational success depends on formalised business processes, work procedures, and job responsibilities, while being simultaneously constrained by a constantly changing mix of competitors, competing products, suppliers, and customer base in the business environment. Hence, a holistic and more complete understanding of social phenomena such as why some organisations are more successful than others, requires an appreciation and application of a multi-paradigmatic approach to research.

Overview of the research process

So how do our mental paradigms shape social science research? At its core, all scientific research is an iterative process of observation, rationalisation, and validation. In the observation phase, we observe a natural or social phenomenon, event, or behaviour that interests us. In the rationalisation phase, we try to make sense of the observed phenomenon, event, or behaviour by logically connecting the different pieces of the puzzle that we observe, which in some cases, may lead to the construction of a theory. Finally, in the validation phase, we test our theories using a scientific method through a process of data collection and analysis, and in doing so, possibly modify or extend our initial theory. However, research designs vary based on whether the researcher starts at observation and attempts to rationalise the observations (inductive research), or whether the researcher starts at an ex ante rationalisation or a theory and attempts to validate the theory (deductive research). Hence, the observation-rationalisation-validation cycle is very similar to the induction-deduction cycle of research discussed in Chapter 1.

Most traditional research tends to be deductive and functionalistic in nature. Figure 3.2 provides a schematic view of such a research project. This figure depicts a series of activities to be performed in functionalist research, categorised into three phases: exploration, research design, and research execution. Note that this generalised design is not a roadmap or flowchart for all research. It applies only to functionalistic research, and it can and should be modified to fit the needs of a specific project.

The first phase of research is exploration . This phase includes exploring and selecting research questions for further investigation, examining the published literature in the area of inquiry to understand the current state of knowledge in that area, and identifying theories that may help answer the research questions of interest.

The first step in the exploration phase is identifying one or more research questions dealing with a specific behaviour, event, or phenomena of interest. Research questions are specific questions about a behaviour, event, or phenomena of interest that you wish to seek answers for in your research. Examples include determining which factors motivate consumers to purchase goods and services online without knowing the vendors of these goods or services, how can we make high school students more creative, and why some people commit terrorist acts. Research questions can delve into issues of what, why, how, when, and so forth. More interesting research questions are those that appeal to a broader population (e.g., ‘how can firms innovate?’ is a more interesting research question than ‘how can Chinese firms innovate in the service-sector?’), address real and complex problems (in contrast to hypothetical or ‘toy’ problems), and where the answers are not obvious. Narrowly focused research questions (often with a binary yes/no answer) tend to be less useful and less interesting and less suited to capturing the subtle nuances of social phenomena. Uninteresting research questions generally lead to uninteresting and unpublishable research findings.

The next step is to conduct a literature review of the domain of interest. The purpose of a literature review is three-fold: one, to survey the current state of knowledge in the area of inquiry, two, to identify key authors, articles, theories, and findings in that area, and three, to identify gaps in knowledge in that research area. Literature review is commonly done today using computerised keyword searches in online databases. Keywords can be combined using Boolean operators such as ‘and’ and ‘or’ to narrow down or expand the search results. Once a shortlist of relevant articles is generated from the keyword search, the researcher must then manually browse through each article, or at least its abstract, to determine the suitability of that article for a detailed review. Literature reviews should be reasonably complete, and not restricted to a few journals, a few years, or a specific methodology. Reviewed articles may be summarised in the form of tables, and can be further structured using organising frameworks such as a concept matrix. A well-conducted literature review should indicate whether the initial research questions have already been addressed in the literature (which would obviate the need to study them again), whether there are newer or more interesting research questions available, and whether the original research questions should be modified or changed in light of the findings of the literature review. The review can also provide some intuitions or potential answers to the questions of interest and/or help identify theories that have previously been used to address similar questions.

Since functionalist (deductive) research involves theory-testing, the third step is to identify one or more theories can help address the desired research questions. While the literature review may uncover a wide range of concepts or constructs potentially related to the phenomenon of interest, a theory will help identify which of these constructs is logically relevant to the target phenomenon and how. Forgoing theories may result in measuring a wide range of less relevant, marginally relevant, or irrelevant constructs, while also minimising the chances of obtaining results that are meaningful and not by pure chance. In functionalist research, theories can be used as the logical basis for postulating hypotheses for empirical testing. Obviously, not all theories are well-suited for studying all social phenomena. Theories must be carefully selected based on their fit with the target problem and the extent to which their assumptions are consistent with that of the target problem. We will examine theories and the process of theorising in detail in the next chapter.

The next phase in the research process is research design . This process is concerned with creating a blueprint of the actions to take in order to satisfactorily answer the research questions identified in the exploration phase. This includes selecting a research method, operationalising constructs of interest, and devising an appropriate sampling strategy.

Operationalisation is the process of designing precise measures for abstract theoretical constructs. This is a major problem in social science research, given that many of the constructs, such as prejudice, alienation, and liberalism are hard to define, let alone measure accurately. Operationalisation starts with specifying an ‘operational definition’ (or ‘conceptualization’) of the constructs of interest. Next, the researcher can search the literature to see if there are existing pre-validated measures matching their operational definition that can be used directly or modified to measure their constructs of interest. If such measures are not available or if existing measures are poor or reflect a different conceptualisation than that intended by the researcher, new instruments may have to be designed for measuring those constructs. This means specifying exactly how exactly the desired construct will be measured (e.g., how many items, what items, and so forth). This can easily be a long and laborious process, with multiple rounds of pre-tests and modifications before the newly designed instrument can be accepted as ‘scientifically valid’. We will discuss operationalisation of constructs in a future chapter on measurement.

Simultaneously with operationalisation, the researcher must also decide what research method they wish to employ for collecting data to address their research questions of interest. Such methods may include quantitative methods such as experiments or survey research or qualitative methods such as case research or action research, or possibly a combination of both. If an experiment is desired, then what is the experimental design? If this is a survey, do you plan a mail survey, telephone survey, web survey, or a combination? For complex, uncertain, and multifaceted social phenomena, multi-method approaches may be more suitable, which may help leverage the unique strengths of each research method and generate insights that may not be obtained using a single method.

Researchers must also carefully choose the target population from which they wish to collect data, and a sampling strategy to select a sample from that population. For instance, should they survey individuals or firms or workgroups within firms? What types of individuals or firms do they wish to target? Sampling strategy is closely related to the unit of analysis in a research problem. While selecting a sample, reasonable care should be taken to avoid a biased sample (e.g., sample based on convenience) that may generate biased observations. Sampling is covered in depth in a later chapter.

At this stage, it is often a good idea to write a research proposal detailing all of the decisions made in the preceding stages of the research process and the rationale behind each decision. This multi-part proposal should address what research questions you wish to study and why, the prior state of knowledge in this area, theories you wish to employ along with hypotheses to be tested, how you intend to measure constructs, what research method is to be employed and why, and desired sampling strategy. Funding agencies typically require such a proposal in order to select the best proposals for funding. Even if funding is not sought for a research project, a proposal may serve as a useful vehicle for seeking feedback from other researchers and identifying potential problems with the research project (e.g., whether some important constructs were missing from the study) before starting data collection. This initial feedback is invaluable because it is often too late to correct critical problems after data is collected in a research study.

Having decided who to study (subjects), what to measure (concepts), and how to collect data (research method), the researcher is now ready to proceed to the research execution phase. This includes pilot testing the measurement instruments, data collection, and data analysis.

Pilot testing is an often overlooked but extremely important part of the research process. It helps detect potential problems in your research design and/or instrumentation (e.g., whether the questions asked are intelligible to the targeted sample), and to ensure that the measurement instruments used in the study are reliable and valid measures of the constructs of interest. The pilot sample is usually a small subset of the target population. After successful pilot testing, the researcher may then proceed with data collection using the sampled population. The data collected may be quantitative or qualitative, depending on the research method employed.

Following data collection, the data is analysed and interpreted for the purpose of drawing conclusions regarding the research questions of interest. Depending on the type of data collected (quantitative or qualitative), data analysis may be quantitative (e.g., employ statistical techniques such as regression or structural equation modelling) or qualitative (e.g., coding or content analysis).

The final phase of research involves preparing the final research report documenting the entire research process and its findings in the form of a research paper, dissertation, or monograph. This report should outline in detail all the choices made during the research process (e.g., theory used, constructs selected, measures used, research methods, sampling, etc.) and why, as well as the outcomes of each phase of the research process. The research process must be described in sufficient detail so as to allow other researchers to replicate your study, test the findings, or assess whether the inferences derived are scientifically acceptable. Of course, having a ready research proposal will greatly simplify and quicken the process of writing the finished report. Note that research is of no value unless the research process and outcomes are documented for future generations—such documentation is essential for the incremental progress of science.

Common mistakes in research

The research process is fraught with problems and pitfalls, and novice researchers often find, after investing substantial amounts of time and effort into a research project, that their research questions were not sufficiently answered, or that the findings were not interesting enough, or that the research was not of ‘acceptable’ scientific quality. Such problems typically result in research papers being rejected by journals. Some of the more frequent mistakes are described below.

Insufficiently motivated research questions. Often times, we choose our ‘pet’ problems that are interesting to us but not to the scientific community at large, i.e., it does not generate new knowledge or insight about the phenomenon being investigated. Because the research process involves a significant investment of time and effort on the researcher’s part, the researcher must be certain—and be able to convince others—that the research questions they seek to answer deal with real—and not hypothetical—problems that affect a substantial portion of a population and have not been adequately addressed in prior research.

Pursuing research fads. Another common mistake is pursuing ‘popular’ topics with limited shelf life. A typical example is studying technologies or practices that are popular today. Because research takes several years to complete and publish, it is possible that popular interest in these fads may die down by the time the research is completed and submitted for publication. A better strategy may be to study ‘timeless’ topics that have always persisted through the years.

Unresearchable problems. Some research problems may not be answered adequately based on observed evidence alone, or using currently accepted methods and procedures. Such problems are best avoided. However, some unresearchable, ambiguously defined problems may be modified or fine tuned into well-defined and useful researchable problems.

Favoured research methods. Many researchers have a tendency to recast a research problem so that it is amenable to their favourite research method (e.g., survey research). This is an unfortunate trend. Research methods should be chosen to best fit a research problem, and not the other way around.

Blind data mining. Some researchers have the tendency to collect data first (using instruments that are already available), and then figure out what to do with it. Note that data collection is only one step in a long and elaborate process of planning, designing, and executing research. In fact, a series of other activities are needed in a research process prior to data collection. If researchers jump into data collection without such elaborate planning, the data collected will likely be irrelevant, imperfect, or useless, and their data collection efforts may be entirely wasted. An abundance of data cannot make up for deficits in research planning and design, and particularly, for the lack of interesting research questions.

Kuhn, T. (1962). The structure of scientific revolutions . Chicago: University of Chicago Press. ↵
Burrell, G. & Morgan, G. (1979). Sociological paradigms and organisational analysis: elements of the sociology of corporate life . London: Heinemann Educational. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Understanding the Societal Impact of the Social Sciences and Humanities: Remarks on Roles, Challenges, and Expectations

Benedikt fecher.

1 Research Program Knowledge and Society, Alexander von Humboldt Institute for Internet and Society, Berlin, Germany

2 German Institute for Economic Research, Berlin, Germany

Freia Kuper

Nataliia sokolovska, alex fenton.

3 Research Area Research System and Science Dynamics, German Centre for Higher Education Research and Science Studies, Berlin, Germany

4 Department of Social Sciences, Humboldt University Berlin, Berlin, Germany

Stefan Hornbostel

Gert g. wagner.

5 Max Planck Institute for Human Development, Berlin, Germany

Hanna Hottenrott , Technical University of Munich, Germany

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Science is increasingly expected to help in solving complex societal problems in collaboration with societal stakeholders. However, it is often unclear under what conditions this can happen, i.e., what kind of challenges occur when science interacts with society and what kind of quality expectations prevail. This is particularly pertinent for Social Sciences and Humanities (SSH), which are part of the object they study and whose knowledge is always subject to provisionality. Here we discuss how SSH researchers can contribute to societal problems, what challenges might occur when they interact with societal stakeholders, and what quality expectations arise in these arrangements. We base our argumentation on the results of an online consultation among 125 experts in Germany (representatives from SSH, learned societies, stakeholders from different societal groups, and relevant intermediaries).

Introduction

Societal impact is an increasingly important evaluation paradigm in science governance. This trend can be seen in the implementation of large-scale impact agendas in various research and innovation systems over the past decade. Examples include the Research Excellence Framework in the United Kingdom, the Standard Evaluation Protocol in Netherlands, or the Excellence in Research framework in Australia ( van der Meulen and Rip, 2000 ; Geuna and Martin, 2003 ; Bornmann, 2013 ). Consequently, research is no longer assessed according to its scientific relevance alone but also according to the value it appears to generate for society. In Germany, where the present study was conducted, the societal impact of research is also at the top of the agenda of policymakers and research funders, although under a variety of terms. The German Ministry for Education and Research, for example, argues in a policy paper that a dialogue with society must become part of the logic of scientific reputation ( BMBF, 2019 ).

This gradual evolution of societal impact as an evaluation paradigm was preceded by a shift in the scholarly conception of the relationship between science and society, which can be summarized as a shift “from deficit to dialogue” ( Bucchi, 2008 ; Davies et al., 2009 ; Reincke et al., 2020 ). According to this view, science no longer provides knowledge to resolve a deficit but should develop “socially robust knowledge” together with societal stakeholders ( Nowotny et al., 2001 ). This shift in the conception of the science-society interface implies that societal impact requires interaction between scientific and societal stakeholders. As a result, evaluation frameworks increasingly focus on processes rather than outcomes, thus rely more heavily on narratives and on formative methods more than summative ones. An example of the latter is the SIAMPI approach, which focuses on ‘productive interactions’ between science and society ( Molas-Gallart and Tang, 2011 ; Spaapen and van Drooge, 2011 ).

The focus on societal impact in science governance and on interaction as a means to achieve this is particularly controversial for the social sciences and humanities (SSH), which we conceive of here as all research disciplines and subdisciplines that deal with social, societal, and cultural matters. On the one hand, from an internal scientific perspective, SSH disciplines investigate social life itself. This implies that subjects, investigators, and audiences tend to merge with one another and that value judgments might play a particularly important role ( Davies et al., 2008 ; Cassidy, 2014 ). As a result, when SSH researchers interact with societal stakeholders, questions of demarcation and boundary dissolution might arise ( Gieryn, 1983 ; Benneworth and Olmos-Peñuela, 2018 ). On the other hand, from an external perspective, evaluation exercises have rarely considered the particular epistemic conditions and specific utilization logics for SSH research ( Reale et al., 2018 ). Critics have noted the mismatch between indicators and SSH notions of quality, the lack of consideration for contributions that are critical rather than solution oriented, and the overly simple framing of societal impact as economic outputs, such as the number of patents or spin-offs ( Benneworth, 2015 ; Ochsner et al., 2017 ; Fecher and Hebing, 2021 ). Generally, established models for knowledge transfer do not do justice to the complexities of the diverse SSH disciplines and their many publics ( Davies et al., 2008 ).

Arguably, SSH research makes important societal contributions, but these are not well understood—at least not in the governance of science. We therefore recognize a need to better understand the societal impact of SSH disciplines in terms of a) the role they might play for societal challenges, b) the problems that might arise in interactive settings that involve SSH scholars and societal stakeholders, and c) the (possibly conflicting) quality expectations that are placed on their interaction. These objectives motivate our exploratory study, which consists of an online consultation with 125 experts (i.e., SSH researchers from different disciplines along with relevant societal stakeholders). Here, we report on the results of this consultation and reflect on the implications these might have for research evaluation.

Research Interest

The role of social sciences and humanities disciplines in response to societal problems.

There is some controversy about the role that SSH research can play in tackling societal problems: While some scholars argue that these fields should augment and emphasize their transformative potential ( Sörlin, 2018 ; Sigurðarson, 2020 ), others attribute a rather passive role to them, suggesting that they should create system knowledge (i.e., knowledge that increases understanding of a social issue) or orientation knowledge (i.e., knowledge that helps to determine possibilities for action) ( Becker, 2002 ; Jahn et al., 2012 ). One could furthermore argue that the public value of SSH research is not necessarily captured by their usefulness in solving problems but rather by their capacity to critically reflect on the problem itself and its potential solutions ( Olmos-Peñuela et al., 2015 ). In this regard, the societal impact of SSH research may also be counterintuitive if one expects clear-cut solutions to problems formulated in advance. Critics of an overly narrow conception of impact as research utilization have also pointed out how social science knowledge tends to be used in diverse ways, many of which are implicit ( Davies et al., 2008 ; Meagher et al., 2008 ; Stehr and Ruser, 2017 ). Weiss (1980) , for example, observes that expertise can “creep in” as conceptual knowledge that influences ideas and decisions. Compared to the natural and technical sciences, the impact of the SSH is thought to be more indirect and less visible. While utilization of SSH might be discreet, it can also be symbolic to the extent that it is used to justify political decisions that are already made ( Weiss, 1980 ; Albæk, 1995 ; Amara et al., 2004 ).

In summary, it is possible to identify quite different (often normative) perceptions of the societal role of SSH. Accordingly, the notion of socially relevant knowledge attributed to SSH disciplines varies: from more transformative and instrumental knowledge, to more indirect conceptual knowledge, to more counterintuitive critical knowledge. The different kinds of knowledge evoke quite different understandings of the role that the SSH should play in addressing societal challenges, which motivates our first research question (RQ1): What role is attributed to the SSH in addressing societal challenges?

Challenges for Collaborative Arrangements Involving the SSH and Societal Actors

In the sociology of science, the shift from deficit to dialogue is associated with concepts like “Mode 2,” “post-normal science,” or “triple helix” ( Funtowicz and Ravetz, 1992 ; Gibbons et al., 1994 ; Leydesdorff and Etzkowitz, 1998 ). These concepts all describe knowledge production as a mode of collaboration between scientific and societal stakeholders. According to a concept of transdisciplinarity, the main challenge for such collaborative arrangements is the integration of differences between actors on an epistemic, social-organizational, and communicative level ( Jahn et al., 2012 ). As already observed above, at the epistemic level, boundaries between subjects, investigators, and audiences have a tendency to become blurred in SSH research ( Davies et al., 2008 ; Cassidy, 2014 ). In collaborative arrangements that involve SSH researchers, questions of boundary work might therefore be of particular relevance ( Gieryn, 1983 ). Furthermore, within the diverse SSH disciplines, there is little consensus on research questions and suitable methods, which poses challenges to the robustness of findings ( Ochsner et al., 2017 ). Regarding the socio-organizational level, the structures that support societal exchange in universities are mostly centrally organized and focused on broad public communication ( Peters, 2013 ; Marcinkowski et al., 2014 ; Fecher and Hebing, 2021 ). Questions arise as to how adequate these might be for anticipating the complexities of science in general and of the SSH in particular. Furthermore, the focus on economic indicators as a means of measuring societal impact in the past might have led to structural discrimination against SSH disciplines in organizational efforts to promote societal engagement ( Benneworth and Olmos-Peñuela, 2018 ; Fecher and Hebing, 2021 ). Jacobson et al. (2004) suggest implementing an array of organizational measures that are believed to be more suitable for SSH disciplines, from increasing resources to fostering the skills of individual researchers. Regarding the communicative level, SSH researchers have frequently been accused of using overly specialized and obscure terms ( Alvesson et al., 2017 ; Healy, 2017 ). At the same time, because the social sciences—and to a lesser degree, the humanities—investigate social life, they must deal with the everyday observations and ad hoc assumptions of the individuals with whom they engage (cf. Cassidy, 2014 ).

Some researchers argue that a consensus on values is not the only necessary condition for facilitating cooperation between heterogeneous actors; more importantly the conditions and structures for cooperation must be created ( Star and Griesemer, 1989 ). For SSH disciplines, this might come with particular challenges that are not yet well understood. This motivates our second research question (RQ2): What hinders interaction between SSH researchers and societal stakeholders?

Quality Expectations Regarding the Interaction Process

If our aim is to grasp the collaborative settings of knowledge production, we will likely need to go beyond criteria that are either purely academic or targeted towards science communication through the media ( Secko et al., 2013 ; Rögener and Wormer, 2017 ). The term “socially robust,” meaning that knowledge should be scientifically robust and socially useful ( Nowotny et al., 2001 ), is now used frequently to describe quality in these settings. Rather than bridging a cognitive gap (as purely academic projects would do), these new modes of knowledge creation aim to bridge social gaps, i.e., they are geared towards potential users, political decision makers, and entrepreneurs ( Maasen and Lieven, 2006 ). The authors argue that in these settings, actors must develop social accountability procedures collaboratively. This undertaking produces social demands that differ from those made in disciplinary research because the researchers need to work outside the set of scientific norms that would otherwise guide their practice ( Merton, 1973 ; Mitroff, 1974 ). This creates new requirements vis-à-vis the outcome. These outcomes are not easily located on a disciplinary map but instead suit the context of application ( Gibbons et al., 1994 ). This will most likely be accompanied by processual requirements to bridge the above-mentioned gaps and to deal with the specific contexts that are addressed by these arrangements.

There are general preconceptions about how collaborative modes of knowledge production might consolidate the quality conceptions of all parties involved. Still, these often remain at an abstract level, which motivates our third research question (RQ3): What do scientific and societal stakeholders perceive as the conditions for good interaction?

Data and Methods

The study is exploratory in that it aims to better understand the societal impact of SSH disciplines by an empirical examination of the role ascribed to SSH research in addressing societal challenges, as well the quality expectations arising in collaborative processes involving SSH researchers. Our findings are based on an online consultation of SSH researchers, societal stakeholders, and intermediaries. We subsequently discussed the results of the consultation with SSH and science researchers in two workshops, where we further scrutinized their implications for assessing the societal impact of SSH.

The selection of participants in the consultation process was deliberate and targeted a) researchers from different SSH disciplines who had experience of knowledge transfer and b) societal stakeholders from politics, media, business, culture, civil society, and public administration who had experience in collaborating with SSH scholars. In order to ascertain that participants did indeed have experience of collaboration, we conducted preliminary interviews, researched specific collaboration projects, and, in the case of researchers, asked learned societies for nominations. The deliberate selection of participants was necessary in order to ensure that respondents could legitimately provide answers to the partly normative questions. Our final sample consists of 125 responses, of which 36 are SSH scholars, 71 societal stakeholders, and 18 intermediaries. Of the SSH scholars, four participants came from core humanities disciplines (philosophy, legal studies, history), four from economics, thirteen from other social sciences, and one each from pedagogy, linguistics, and design research. Twelve of the researchers did not indicate their disciplinary background. Further, our sample includes a group we describe as “intermediaries.” These are individuals that are involved in managing and enabling collaborations between SSH researchers, for example communications officers at universities or independent science communication consultants. We chose to include this group in the consultation because we assumed that they would be uniquely positioned to observe and thus reflect on the conditions of these interactions. Table 1 illustrates the final expert sample by group membership.

Sample of the online consultation by group membership.

Participants	No.

In universities	27
In nonuniversity research institutes	9

NGOs	19
Politics	10
Public administration	11
Private sector	11
Cultural sector	1
Media	19

The consultation consisted of an online survey that comprised both a close-ended section on sociodemographics and a set of mainly open-ended questions about individual experience in collaborative settings involving SSH researchers. Our analysis of the three research questions is based on five open questions in the survey ( Table 2 ). One of the questions refers to the Covid-19 pandemic ( Table 2 ; RQ1). We chose to include this because the pandemic is a complex societal challenge and is thus relevant to the subject of the study.

Research interest and survey questions.

Research interest	Survey question
Role of SSH researchers (RQ1)	From your perspective: For which societal issues are the SSH research particularly relevant?
Role of SSH researchers (RQ1)	How do you assess the role played by SSH disciplines in solving societal problems, for instance during the Covid-19 pandemic
Interaction challenges (RQ2)	Where have you experienced problems and challenges in communicating and applying the results of SSH research?
Interaction challenges (RQ2)	How would you assess the role of scientific institutions (universities, non-university research institutions)? Where do you recognize concrete potential for development in the relationship between science and society in these institutions?
Quality expectations (RQ3)	Please describe what constitutes good collaboration or exchange between science and society. If possible, please also address what special requirements apply to the SSH.

We conducted a structuring content analysis in order to analyze the textual data. This technique corresponds to the inductive technique of qualitative content analysis ( Mayring, 2000 ) and takes into account Kuckartz’s structuring method by using an interpretative initial processing to then iteratively form consistent categories ( Kuckartz, 2014 ). Quotations in this paper are the authors’ translations from the original German responses into English.

We encouraged the experts to publish their names and responses because we consider them relevant for further research: 103 agreed to publish their responses, 68 agreed to publish their names and institutions, 27 to publish only the name of their institutions, and 30 wished to stay anonymous. The survey instrument, the anonymized MAXQDA file, as well as the full answers of those who granted permission, can be found on the project website.

This study had limitations regarding the selection of participants in the consultation: Despite every effort being made to recruit a diverse and relevant set of participants, the selection can hardly reflect the diversity of SSH researchers and its many specialized societal stakeholders. Further research is necessary to understand the manifestations of the generic categories presented here in different contexts.

From the survey responses, we first identify topics that SSH research is associated with and the role SSH research fulfills within society. Second, we present the challenges that are mentioned when SSH researchers and societal stakeholders interact. Third, we turn to quality expectations in this interaction. In each results section, we will report on the findings by referring to the number of codes ascribed to a category in brackets and use exemplary quotes where suitable.

Role of Social Sciences and Humanities Researchers

From the responses regarding the societal issues that SSH expertise is relevant for, we were able to identify 31 societal issues that span nearly every aspect of social and natural life, as well as technical innovation. Broadly, these can be assigned to the following categories: “politics” (45), “economy” (47), “culture” (6), “education” (26), “ecology” (56), “civil society” (131), “health” (34), and “technology” (42).

The answers likely relate to the respondents’ particular interests and expertise and do not represent those areas of real-world problems that the SSH contribute to. However, the issues show that the spectrum of topics ascribed to SSH disciplines goes far beyond narrow disciplinary couplings (e.g., educational research that deals with education or economics that deal with economic growth) and includes contemporary and frequently transformative topics, such as climate change, migration, or the current pandemic. The ubiquity of potential issues for SSH engagement is expressed in this quote from a journalist:

“Every topic has a societal component—from fundamental questions of democracy and politics to questions concerning nature and technology. Basically, each question that requires social action and regulation” (Media_ID103, 10).

While these issues provide some indication of the wide topical range for potential SSH engagement, the participants’ perception of the role of SSH research in addressing these societal issues might provide a more accurate picture of how that engagement might actually unfold. We coded the answers to the question of how participants assess the role of SSH research in solving societal problems accordingly. In total, we identified six distinct societal roles that are frequently referred to by the experts: explaining, reflecting, educating, signaling, foresight, and informing ( Table 3 ).

Societal functions of SSH knowledge.

Roles	Description	Example	#Codes
Explain	To describe and contextualize an issue.	“It is always about identifying—understanding—explaining and providing contextual knowledge. That is always of importance” (Economy_ID132, 10).	77
Reflect	To discuss and interpret an issue.	“What does it mean that one part of the population can work from home in a relatively safe manner, while another part of the population cannot, and is thus potentially more exposed?” (NGO_ID85, 25).	65
Educate	To build competence in a specific area.	“[SSH] should develop intercultural competences” (Media_ID180, 15).	7
Signal	To point to an issue.	“Impulses for necessary discourses can and should also come from [SSH] research” (NGO_ID200, 10).	20
Foresee	To predict the development of an issue.	“The potential implications of current research have societal relevance—technological developments such as CRISPR Cas 9 or AI should be discussed more widely in society so that we can negotiate ethical issues raised by the introduction of such technologies early enough” (Intermediary_ID174, 10).	21
Inform	To support decision-making.	“Solid analyses of socio-political developments, numerical data, and impact assessments are needed in politics and administration. They are picked up on and incorporated into decision-making” (PublicAdmin_ID61, 16).	80

We found indications that each of these six functions correspond to different types of knowledge. For example, the “explain” category relates to system knowledge needed to understand a social issue because it contains statements from participants that are geared towards contextualizing social issues without suggesting any concrete instructions for action. By the same token, the “educate” category contains knowledge used to build competence in a specific issue area. The category “foresee” relates to knowledge needed to determine possibilities for decision-making as it contains statements from participants that refer to future developments. For example, one person working in public administration describes SSH research as an “early warning system for problems that have not yet become apparent” (PublicAdmin_ID61, 9). According to this statement, SSH disciplines should assess the societal implications of social change. These include, as several respondents state, the implications of artificial intelligence on the future of work.

The “inform” category is closely linked to what is referred to as the instrumental use of SSH knowledge, i.e., it is used directly for decision-making. Both the “reflect” and the “signal” categories resonate with what might be considered critical knowledge. Statements in the “reflect” category do not refer to the provision of expertise for problem solving but to interpreting and analyzing the problem and the solution. The “signal” category includes statements that, according to the participants in the consultation, refer to issues that receive too little attention but are considered relevant to public discourse or policymaking. Accordingly, the role of SSH disciplines is to point to these problematic aspects and to act as a critical observer. In relation to the Covid-19 pandemic, for example, the participants mentioned that SSH researchers emphasized the psychological, social, and cultural consequences of pandemic control. Some experts believe SSH expertise is not given enough attention in current political strategies, others like this intermediary describe their influence as lagged but present:

“Whereas at the beginning it was mainly the virologists who were heard, in my opinion the social sciences have now made themselves heard in many respects and have pointed out numerous important aspects of economic and socio-political relevance. For example, the fact that the daycare centers and schools have not yet been closed again is not only due to the virological assessment that children are less likely to spread the virus, but also due to the indications of the problems for working parents and for the children whose educational disadvantages have been exacerbated” (Intermediary_ID110, 24).

The statements from politicians in our sample frequently referred to the “foresee” category, but other than that there were no striking quantitative variations in the distribution of codes.

With regard to the roles attributed to the SSH in solving societal problems, we identified different levels of activity, from a rather passive, contextualizing role (e.g., “explain”) to a more active, influencing role (e.g., “inform”). This leads us to conclude that the SSH provide a diverse range of problem-relevant kinds of knowledge for societal challenges. From a solution-focused point of view, SSH knowledge is partly counterintuitive because it does not necessarily aim to contribute to a solution but seeks to question the problem and its solution. Moreover, rather than producing knowledge that might itself stimulate change or even transformation, SSH disciplines are more frequently attributed the role of producing “cohesion knowledge,” that is, knowledge that helps anticipate change. In this regard, SSH research fulfils a moderating role in complex change processes by helping to establish and maintain social order, cohesion, and equality. In our view, the multiple roles attributed to SSH disciplines could amount to a moderating role that would involve taking into account the complexity of issue formation in change processes as well as attempts to tackle these. Therefore, SSH disciplines are in a position to consider overarching issues of social cohesion and equality. The capacity of SSH research to address questions of cohesion is strongly reflected in the frequency of references to issues: the terms equality or inequality are mentioned 79 times by the respondents, democracy is mentioned 32 times, and cohesion or similar terms are mentioned 28 times.

Interaction Challenges

In order to understand where difficulties arise in the interaction between SSH scholars and societal stakeholders, the participants were asked about the problems and challenges they experienced in previous interactions and—in order to assess organizational aspects—the role of universities in supporting science-society interactions. We identified four kinds of interaction challenges in the answers: 1) translational challenges that relate to different modes and logics of interaction, 2) institutional challenges that relate to the governance and organization of science, 3) epistemic challenges that relate to knowledge creation processes of SSH disciplines, and 4) uptake challenges that relate to the use of SSH expertise by different societal stakeholders. Table 4 presents these challenges and their subdimensions.

Interaction challenges.

Challenges	Categories	Example	#Codes
Translational challenges	Language barriers	“Challenges in applying the results of social science research also lie in the different ways in which journalists and scientists work with language” (SSHscholar_ID178, 14).	27
	Conflicting system logics	“Politics has to make decisions and win majorities or, create acceptance. Science can give recommendations, but this might just result in different recommendations coexisting [...]” (Intermediary_ID110, 12).	73
Institutional challenges	Lack of resources	“The everyday routine at the university, with extensive teaching and exams obligations and increasingly also administrative tasks, which coincides with shrinking resources, already leaves little room for research. This means that the Third Mission is an additional burden” (SSHscholar_ID192, 12).	19
	Lack of organizational support	“Institutions should create structured incentive systems for scientists to raise awareness of societal challenges and to consider what they themselves can contribute to solving them” (SSHscholar_ID65, 28)	19
	Lack of rewards	“The transfer (not only the publication) of research results should be valued as an important aspect of scientific work in education but also in evaluations” (Intermediary_ID195, 13).	20
Epistemic challenges	Ambiguity of results	“But in contrast to the natural sciences, there are rarely any clear “truths” here. So it’s not easy for the media to present a comprehensive and well-balanced picture when selecting scientific contributions” (PublicAdmin_ID61, 25).	23
	Conflicting paradigms	“One challenge is the question of how issues that are scientifically controversial can be presented to the public in such a way that the reputation of science does not suffer and, ideally, this heterogeneity can even be used productively” (SSHscholar_ID179, 13).	9
Uptake challenges	Lacking appreciation of SSH expertise	“I see challenges in the general perception and appreciation of social science research being too low” (Intermediary_ID201, 13).	27
	Public attention dynamics	“Provocation is better “received” than factuality; “loud” colleagues are simply more seen and heard” (SSHscholar_ID67, 13).	13
	Risk of instrumentalization	“Politics must not misuse scientific findings for its own agendas and thereby partly discredit them” (Economy_ID96, 18).	5

Translational Challenges: Conflicting System Logics and Boundary Work

Translational challenges relate to different modes and logics of interaction between involved parties. The category comprises statements made by respondents that refer to semantic aspects and systemic differences between science and other social systems that hamper meaningful interaction. The statements in this category can be split into two categories: “language barriers” (27) and “conflicting system logics” (73).

Some participants perceive the language of SSH scholars to be complicated, as this journalist describes:

“As a journalist, it strikes me that social science researchers very often and unfortunately quite naturally use terms that are hardly used or understood by the general public” (Media_ID159, 13).

Differences, however, can be found in the assessment of language barriers. Some see the use of technical concepts as a necessity for describing social phenomena in a differentiated way, while others see it as unnecessarily complicated prose that is a hindrance to productive exchange. In general, references to language barriers are mostly made by participants working in the private sector or in the media.

A second challenge can be described as “conflicting system logics.” Statements in this category refer to three closely related aspects of incompatibility: 1) temporality of SSH research (i.e., SSH research takes time and cannot satisfy needs immediately), 2) conflicting notions of relevance (i.e., societal relevance of SSH is not based on immediate societal needs), and 3) self-referentiality of SSH research (i.e., SSH research refers to itself and not to what others consider social problems). The conflicting system logics resulting from these are well expressed in a quote from an SSH researcher, who on the one hand calls for SSH researchers to anticipate different societal contexts (here the media) but on the other hand reports that this can lead to conflicts among academic peers:

“Scholars should recognize that they move in a different system logic when they communicate with the media, for example. I experience a lot of criticism of the portrayal of science in the media, which I consider inappropriate. Of course, there is a decrease in length, but that is also completely okay.” (SSHscholar_ID138, 16–17)

In general, the participants often refer to different system logics, usually to explain why an exchange could not take place from their specific perspectives. In this quote, for example, a politician reports on the context of his decision making and the associated lack of time to deal with SSH research:

“Science is a different system than politics; there is a democracy proviso; being an elected official does not give me enough time to read or receive scientific literature.” (Politics_ID196, 17)

Different system logics explain the translational challenges between SSH researchers and members of other social subsystems, specifically with regards to language usage, the notions of relevance, and time and content-related use considerations. This explanation can be problematic when functional differentiation of social systems is used as a pretext for not engaging in interaction at all. It might be more fruitful to think of the interaction between societal stakeholders and scientists as one where boundaries between science and nonscience are contextually and continuously dissolved and redrawn.

Institutional Challenges: Mismatch Between Aspiration and Resources

Institutional challenges relate to the governance and organization of science. In this respect, we identified three types of challenges in the statements. These are “lack of resources” (19), “lack of organizational support” (19), and “lack of rewards” (20).

In most cases, references to lack of resources refer to limits concerning SSH researchers’ time and skills. One social scientist mentioned the need for training for research staff when explaining the latter:

“[We] are not trained to do this; we usually do basic research and teach basic science at universities—we need knowledge transfer” (SSHscholar_ID68, 15).

A second institutional challenge relates to the lack of organizational support. Respondents often refer to a decoupling of transfer infrastructures at universities and the researchers working there, or to necessary investment in transfer capacities at research organizations. The latter becomes clear in this statement made by a participant who works in public administration:

“In my opinion, scientific institutions should invest more in public relations—these positions are often sparsely staffed and funded [...]. The relevance of the job/intermediary function is recognized more and more, but this is (often) not yet reflected in the structures” (Intermediary_ID229, 13).

A third challenge in this category is the lack of rewards for societal engagement, which the participants link to the academic reputation and funding system. Another social scientist describes what she perceives as an undervaluation of engagement as follows:

“[There is a] lack of reputation for this activity as opposed to third-party funding and high-ranking publications. [Engagement] is only an “add on”” (SSHscholar_ID44, 13).

The notion of “engagement as an add-on” (i.e., not a main task) is mentioned frequently and especially by SSH scholars in the consultation. However, the participants discuss the matter of recognition with significant differentiation: One expert describes societal impact as an additional pathway for scholarly work, alongside scientific impact:

“Since publication excellence can hardly be mitigated, they could instead create funding lines that can only be used if the relevance to the SDGs is laid out clearly,” (SSHscholar_ID65, 28).

Lack of recognition for public engagement activities and a lack of resources to carry them out are not specific to SSH disciplines per se. However, they may be more pronounced here because knowledge transfer is even less rewarded and incentivized in a dominant framework focused on economic outcomes. If strengthening societal engagement is a science policy priority, the results here suggest that there is a perceived mismatch between this aspiration and the resources allocated to it.

Epistemic Challenges: The Illusion of Stable Social Sciences and Humanities Knowledge

The epistemic challenges category describes challenges that relate to the knowledge creation of SSH disciplines. It includes two subcategories, “ambiguous results” (23) and “conflicting paradigms” (9).

With respect to “ambiguous results,” statements often contain comparisons to the “hard” natural sciences, where results are perceived by some participants to be clear and unambiguous. In contrast, results from SSH disciplines are often described as vague. For example, for a respondent who works as a researcher and in the media, this is the main reason why results from the natural sciences are preferred:

“Questions and research designs are often too vague, the results too ambiguous. Therefore, journalists prefer communicating results from the natural sciences” (SSHscholar_ID142, 16).

The “conflicting paradigms” category contains statements that emphasize how different schools of thought within SSH disciplines result in different ways of understanding and assessing the same issue. A social scientist in the consultation interpreted the heterogeneity of SSH disciplines as an impediment to communication:

“Distinctive disciplinarity and families of methods in SSH disciplines prevent common problem-oriented communication” (SSHscholar_ID206, 22).

While the heterogeneity of SSH disciplines is often described as normal and indeed as an asset by the participants, some point to a problem, namely that this lack of consensus can also be perceived by the public as a lack of scientific rigor. This can lead to a loss of reputation and trust.

“One challenge is the question of how issues that are scientifically controversial can be presented to the public in such a way that the reputation of science does not suffer and, ideally, this heterogeneity can even be used productively” (SSHscholar_ID179, 13).

Of course, conflicting paradigms and ambiguous results are not purely SSH problems. However, they manifest in specific ways there. In general, SSH disciplines comprise very different approaches, research questions, and epistemological premises. Moreover, their results are often strongly dependent on context. These characteristics are echoed in our respondents’ view of the ambiguity of SSH results, which they describe as a challenge when interacting with societal stakeholders.

Uptake Challenges: Lacking Appreciation and Public Attention Dynamics

The category uptake challenges includes statements from participants that relate to the use of SSH expertise by societal stakeholders. We identified three types of uptake challenges. These are: “lacking public appreciation” (27), “public attention dynamics” (13), and the “risk of instrumentalization” (5).

Regarding “lacking appreciation,” SSH disciplines are, again, often contrasted with the natural sciences by participants. Many of them describe the natural sciences as having a comparatively higher public status, which becomes obvious in this statement from an SSH scholar:

“From my point of view, we offer many research topics that are of interest to a broader public, but we are not yet perceived and treated equally with the natural sciences” (Intermediary_ID229, 16)

This observation is backed up by a journalist who explains that while disciplines such as medicine, physics, or engineering are met with fascination, SSH disciplines are not:

“While the natural sciences and medicine are often met with widespread fascination for their subjects in society, this is often lacking in social science. Physics and technology are sexy, other disciplines are not” (Media_ID159, 16).

The “dynamics of public attention” subcategory subsumes statements that describe SSH research as being out of kilter with the public interest. In general, this refers to a perceived mismatch between the utilitarian perspective of societal stakeholders and the supply of knowledge that SSH disciplines can provide. Often, participants refer to the fast pace of social media, which SSH research cannot keep up with. Some participants even describe adverse effects when SSH researchers adapt their communication to the dynamics of publicity, which is made obvious in a quote from a humanities scholar, who explains how attention might trump relevance in public communication:

“Provocation is better “received” than factuality; “loud” colleagues are simply better seen and heard” (SSHscholar_ID67, 13).

The “risk of instrumentalization” category is rarely referenced. We list it nevertheless, because it is often mentioned in the literature and is distinct from the other listed challenges. The category subsumes statements that refer to the misuse of SSH expertise for political interests. For instance, a representative working in the economy and for an NGO states:

“Politicians must not misuse scientific findings for their own agendas and thereby partly discredit them” (Economy_ID96, 18).

Taken together, when SSH results are discussed by the public, they appear to not be appreciated in the same way as natural science results. Instead. they are made subject to attention dynamics and might be instrumentalized. This negative perception might be linked to the subtle nature and multiple ways in which SSH expertise reaches the public and political decision makers. If media attention factors determine whether SSH results are noted by the public, the scientific and societal relevance of SSH expertise might recede.

Quality Expectations

The third research question addresses quality expectations, i.e., conditions for a good exchange between societal stakeholders and SSH researchers. To this end, we asked the participants open questions about their expectations for a good exchange and about the specific conditions that might apply to SSH disciplines. From the answers, we are able to identify eight distinctive quality expectations that can be divided into three main categories. These are 1) process-related, b) outcome-related, and c) person-related quality expectations ( Table 5 ). Engagement with society, albeit an aspiration of many research organizations, seems to be difficult in current organizational structures according to our respondents.

Quality expectations.

Quality expectation	Categories	Example	#Codes
Process	Comprehensibility	“Summarize findings in a generally understandable, audience-oriented, and brief and concise manner” (NGO_ID60, 16).	26
	Form	“Knowledge should be transferred to the public through various and adapted transfer formats and communication channels, for example, transfer forums, workshops, lecture series as formats that can be used in a way that is appropriate to the target group and audience” (Intermediary_ID108, 16).	25
	Inclusivity	“Co-creative exchange between science and non-scientific actors is important. Each group contributes specific knowledge needed for complex problem solving” (SSHscholar_ID232, 15).	26
	Pertinence	“Knowledge and presumption must be clearly separated in the dialogue with society” (Economy_ID163, 36–37).	13
Outcome	Transparency	“It seems important to me that science communication also openly names the weaknesses of science. For example, peer review is no guarantee of quality” (SSHscholar_ID138, 30).	30
	Relevance	“At the same time, the relevance of science to the reality of life must be recognizable and tangible. This last point in particular is often missing in the social sciences” (Media_ID57, 20).	31
Person	Empathy	“Good cooperation means engaging with the other side and listening without prejudice” (SSHscholar_ID224, 16).	67
	Disinterestedness	“In my view, a good exchange is characterized above all by the fact that it is not primarily guided and inspired by the self-promotional intentions of individual scientists or scientific organizations” (SSHscholar_ID37, 16).	14

Process-Related Quality Expectations

Process-related quality expectations refer to the interaction between SSH scholars and societal stakeholders and includes the codes “comprehensibility” (26), “pertinence” (13), “inclusivity” (26), and “form” (25).

“Comprehensibility” encompasses statements that refer to the mutual understanding between actors. Typically, these statements refer to comprehensible and clear communication of results on the part of SSH scholars and the adaptation to interlocutors. Accordingly, complex contents should be conveyed in such a way that those involved in the dialogue are able to follow and respond in an informed manner. The code “pertinence” refers to statements that suggest that knowledge should be used in a problem—and solution-oriented manner. This is illustrated by a statement made by a politician:

“For the policy sphere, I would like to see more focused exchanges that bring in key research findings” (Politics_ID237, 19).

“Inclusivity” refers to the actors involved in an interaction. We distinguished between two types of inclusivity. The first is selective inclusivity, which means that appointed experts who can contribute relevant and specific expertise should be involved. The second is universal inclusivity, which implies broader participation involving those who are possibly affected by the issue. Some participants point out that diverse expertise is needed to achieve viable results. Lastly, statements coded as “form” typically refer to the existence of an interaction format that is adequate for exchange and problem-solving.

It is impossible to meet all of these expectations of the interaction process. One SSH scholar puts it in these almost utopian terms:

“The goal should be to communicate complexity, reflexivity, and provisionality simply, clearly, understandably, and plausibly” (SSHscholar_ID205, 15).

It can be assumed that the more complex a problem is and the more diverse the parties involved in the interaction process, the more difficult it will be to arrive at some form of shared meaning. In this regard, there are expected tensions between inclusivity, pertinence, and comprehensibility, while formality might imply a strategy to meet these expectations in the best possible way.

Outcome-Related Quality Expectations

Outcome-related quality expectations refer to the results of an interaction process between SSH scholars and societal stakeholders. This category comprises the codes “transparency” (30) and “relevance” (31).

The code “transparency” indicates statements that refer to two kinds of transparency: 1) method transparency and 2) motivation transparency. In this article, we use method transparency to refer exclusively to SSH disciplines and signal the requirement of communicating uncertainties and clearly describing methods as necessary for good exchange. Motivation transparency refers to the communication of motivating factors (e.g., personal interest, dependencies, client expectations) and pertains to both SSH scholars and societal stakeholders. This is made obvious in a statement from a social science scholar:

“As part of society, scientists perceive and research socially relevant topics—politics should make the use of scientific research results transparent” (SSHscholar_ID68, 18).

“Relevance” includes statements that refer to the practical implications of the interaction process. We distinguished between individual and societal relevance. Individual relevance signifies the benefits for the individuals involved and is described by some as a motivating factor for partaking in the interaction process. Societal relevance is usually viewed in a differentiated way as referring either to benefits for individual citizens or benefits for specific groups and sectors of society. In some statements, such as the following made by a politician, societal relevance is framed as a return on societal investment in publicly financed research:

“Society makes a considerable contribution to the financial security and freedom of science, not least through public budgets. It can therefore expect science to take an interest in societal issues and to make its contribution to solving societal problems [...]” (Politics_ID234, 18).

However, achieving both transparency and relevance might be difficult, as this statement from an economics scholar shows:

“The greatest challenge in communicating social science research is often to openly acknowledge the uncertainty inherent in its findings while convincing people that they nevertheless contain important information” (SSHscholar_ID157, 16).

In this case, transparency is seen as a hindrance for relevance. Further tensions might arise when personal and societal relevance do not correspond, or when transparency (in the sense of replicability) cannot be achieved. There might also be a conflict between different quality expectations in the outcome of the interaction process.

Person-Related Quality Expectations

Person-related quality expectations refer to the individuals involved in the interaction process. They subsume the codes “empathy” (67) and “disinterestedness” (14).

“Empathy” indicates statements that refer to the mutual acknowledgement of all parties involved. Most statements in this category refer to acknowledging the position of the other parties involved in the interaction process. Typically, the social position of an individual comes with certain concessions, for example, journalists are granted reporting duties, politicians have decision-making power, and SSH scholars possess research autonomy. The reciprocal nature of the expectation of empathy is made clear in this quote from a journalist in the consultation:

“When researchers recognize that the media are their partners—in discourse, in presentation, in criticism. That means being available for media inquiries, discussing issues of relevance with a journalist, and sharing material. It also means tolerating exaggerations, even if one’s own business is differentiation” (Media_ID114, 16).

Some participants state that empathy should not be blind but informed. This is made obvious in a quote from a participant who works in public administration:

“It is important that the results of SSH disciplines can be properly assessed. Excessive claims in the social sciences, in the sense of objective truths, can easily produce disappointment and lead to a deviation, which in the worst cases can then leave the impression of arbitrariness of the decisions and actions under discussion” (PublicAdmin_ID167, 15).

The code “disinterestedness” is used for statements that emphasize that actors should not pursue their own interests but act for the benefit of society. This is often combined with the expectation that personal opinions should be separated from facts and that the conversation should be devoid of emotions and self-promotional intentions. Responding to the question of what constitutes a good collaboration between science and society, one SSH scholar states:

“In my view, a good exchange is characterized above all by the fact that it is not primarily guided and inspired by the self-promotional intentions of individual scientists or scientific organizations” (SSHscholar_ID37, 16).

There are conflicts between disinterestedness and empathy, for instance when it comes to the proclaimed necessity of leaving emotions aside. In addition, there may be potential cross-category tensions between person—and outcome-related quality expectations, for instance in relation to disinterestedness and the individual relevance described above. The same holds true for informed empathy and inclusivity. Remarkably all participants, researchers as well as societal stakeholders from different fields, name the quality expectation empathy most frequently as a condition for exchange. Reflection on ones own position seems crucial for science-society-interactions.

In this article, we used an expert consultation to examine the societal impact of SSH disciplines, i.e., the role of SSH research in addressing societal issues, as well as the resulting challenges and quality expectations. The results shed light on the conundrum of addressing societal issues while being part of the subject matter.

Social Sciences and Humanities Knowledge as Cohesion Knowledge

The societal issues that SSH disciplines relate to are broad and transcend disciplinary couplings. The quasi ubiquity of SSH impact areas resonates with recent research findings (e.g., Bastow et al., 2014 ). The roles ascribed to SSH disciplines in addressing societal problems are likewise diverse and range from more instrumental tasks, such as informing a policy decision, to more contextualizing activities, such as explaining the social implications of a problem. The latter resonates with Stehr and Ruser’s (2017) description of social scientists as “meaning producers,” i.e., their knowledge does not focus on practical choices but on processes of meaning, which may give rise to decisions. In addition, we find evidence of a more counterintuitive role for SSH disciplines in addressing societal challenges, namely critiquing the definition of a problem and the envisaged solution. This finding resonates with Burchell (2009) who proposes that, from a societal perspective, the social sciences might best be interpreted as a “critical friend” (see also Davies et al., 2008 ). Participants in the consultation describe the relevance of this critical capacity, for instance, in discussing the social, cultural, and psychological implications of the Covid-19 pandemic, which some feel have not been sufficiently considered in policy decisions.

Along with these roles, we identified different types of knowledge that SSH disciplines can provide to help resolve societal challenges. These range from overview and system knowledge, as described by Becker (2002) , to instrumental knowledge ( Fähnrich and Lü ; Stehr and Ruser, 2017 ) like the kind that is used to inform political decision-making processes. This differentiation resonates with ( Weiss, 1980 ) who suggests that the contributions of SSH research to decision-making processes are much wider than a narrow idea of knowledge utilization suggests. Moreover, “critical knowledge,” i.e., knowledge that enables us to question societal decisions, appears to be an essential contribution of SSH disciplines to societal issues. This positions SSH researchers as a critical corrective in addition to its contextualizing and co-creating capacity. At a higher level of abstraction, we observe that SSH disciplines are rarely associated with “transformative knowledge” that causes change ( Becker, 2002 ) but instead with knowledge that helps us anticipate societal transformations and to deal with change (see also Sigurðarson, 2020 ). We refer to this kind of knowledge as “cohesion knowledge.”

Continuous Boundary Work

In the scholarly debate, dialogue between representatives from both science and society is understood as a condition for “socially robust” knowledge, i.e., knowledge that is both scientifically robust and socially useful ( Nowotny et al., 2001 ). Consequently, we conceptualize interaction as a prerequisite for societal impact (see also Spaapen and van Drooge, 2011 ). This motivated us to interrogate challenges in interactive and problem-oriented settings involving SSH disciplines. The challenges we identify can be categorized as translational, institutional, epistemic, and uptake challenges, and they thus correspond roughly to the framework suggested by Jahn et al. (2012) . While many of the challenges we identified point to contingent issues, some results stand out.

When it comes to translation, reducing linguistic complexity without being accused of triviality and commonplace hypotheses is a core challenge for SSH disciplines. Some of the societal stakeholders in the consultation describe SSH disciplines as self-referential and the language used as unnecessarily complicated at times. Bridging the “social gap” ( Maasen and Lieven 2006 ) between science and society thus means that SSH scholars must adapt their language (e.g., their use of terms), although at the risk of compromising their epistemic authority. A problem-oriented interaction with societal stakeholders, however, might contribute to increased “methodological efficiency” as a form of continuous external validation ( Woolgar, 2000 ). Regarding institutional challenges, we find initial evidence for a structural disadvantage of SSH disciplines. This might be explained with reference to the fact that the established entrepreneurial heuristic of societal impact carries little significance for SSH disciplines ( Benneworth and Olmos-Peñuela, 2018 ). Epistemic challenges mostly concern the heterogeneity of SSH disciplines and their approaches, intermittently conflicting paradigms, and the dynamic object of study, i.e., society as a moving target ( Dayé, 2014 ). It follows that SSH disciplines produce knowledge that is highly context-dependent, situated, and dynamic ( Gattone, 2012 ; Fähnrich and Lüthje, 2017 ). Hence, there are serious limitations regarding the extent to which objective, stable, and context-independent knowledge can be expected from SSH disciplines ( Davies et al., 2008 ). This finding is consistent with the self-conception of many SSH disciplines as critical, reflective, and contextual. When it comes to the uptake of SSH knowledge, the consulted representatives note how SSH expertise is not always fully appreciated and may explain to a certain extent the lack of appreciation for SSH research. For example, in the consultation, SSH research is often contrasted with natural science and technical disciplines, whose results are not only perceived as more stable but often as more exciting, too. This resonates with Knudsen (2017) , who found a deficit framing for the humanities in Danish print media. Cassidy (2014) explains this lack of appreciation with the close relationship of SSH disciplines to everyday life: “Unlike most natural sciences, where the specialist training, knowledge and equipment of scientists grants them largely uncontested expertise, social scientists’ expertise is often about matters of everyday experience and common-sense knowledge” (p. 190).

Taken together, these challenges suggest a twofold implication: The calls for more resources and recognition are on the one hand contingent issues that can give impulses to the governance of science. On the other hand, our results illustrate how the position of the SSH in society is a matter of ongoing negotiations. The identified challenges show how the SSH are caught up in boundary work in their interactions with extra-academic fields ( Gieryn, 1983 ). They speak of troubles of SSH researchers to claim their authority, which is linked to epistemic dynamics, that find expression in language usage, specific temporalities and context-specific results. How the SSH position themselves towards their moving target, the society, becomes even more of a challenge in collaborative formats.

Contextual Quality Configurations

Our empirical findings indicate a three-dimensional framework for ensuring quality in collaborative arrangements involving SSH researchers and societal stakeholders. The first is process-related and describes the expectations of the exchange itself. The second is person-related and describes the expectations towards the people involved. The third is outcome-oriented and includes the expectations of the outcome. In collaborative settings, there will most likely be contradictory expectations of what entitles persons to participate, how interacting partners should behave, and what constitutes relevant knowledge (see also Kropp and Wagner, 2010 ). This leads to conflicts between different expectations of quality that are difficult to avoid, for instance between disinterestedness and empathy, but also within categories, for instance, regarding different understandings of relevance (e.g., how can scientific demands for relevance be reconciled with demands for utility?). At times, the participants in the consultation offer solutions to these conflicts between quality expectations, for instance when they say that there are conditions for participation in the interaction such as having a basic understanding of the other interaction partner. This is in line with Bromme’s (2020) concept of “informed trust,” according to which it needs not only trust in public scientific statements but also knowledge on the system of science to make an informed judgement. Our findings add a nuance to this hypothesis by suggesting that informed trust must be reciprocal, i.e., researchers participating in a dialogue must also understand the societal stakeholders they engage with.

Generally, we can safely assume that the more diverse and complex the setting for a dialogue is, the more difficult it may be to document expertise and to establish transparency. If being affected by an issue legitimizes participation in a dialogue, then it may be more difficult to enforce pertinence as a premise. If expertise legitimizes participation, there is also a risk of exceeding the level of fact. It follows that there must be legitimate reasons for trade-offs between different quality expectations. These should depend on the aim of the interaction, the individuals involved, and the chosen interaction format. It follows that quality expectations in collaborative settings should not be understood universally, unilaterally, and statically. Instead, they should be considered within their specific context, reciprocally, and dynamically. Hence, we propose that quality itself must be an object of these interactions, i.e., there should ideally be deliberation about the appropriate quality configuration for the problem at hand. This could be particularly relevant for SSH disciplines, which, as discussed above, have to engage in continuous boundary work due to their position in society. The outline of a quality framework as proposed here can be a basis for deliberating on the quality of these arrangements. That said, for particularly established forms of interaction (e.g., scientific policy advice), there may already be recognized default settings from which it is possible to extrapolate.

Our results show, that the societal impact of SSH disciplines can be counterintuitive and precisely not aimed at solving a problem. Instead, they often seek to challenge both the problem and its solution. Nor does SSH research necessarily strive for transformation but instead seeks an understanding and a moderation of social change. Therefore, the impact of the SSH is often discreet, indirect, and conceptual. Thus, the quality of the societal impact of SSH disciplines can only be understood in relation to their specific context, in the sense that it is person-, problem-, and time-dependent and must take into account different field logics as it takes place in a “space between fields” ( Williams, 2020 ). For these reasons, a rigid, purely quantitative assessment of societal impact of SSH disciplines should generally be avoided, especially with regard to how assessment shapes and stabilizes underlying values ( Espeland and Sauder, 2007 ; Williams, 2020 ).

Our results provide some arguments for so-called formative evaluations of the societal impact of SSH disciplines. Formative evaluations focus on the process (e.g., an interaction, a program, or a project) while the activities are ongoing. They are geared towards learning and goal adjustment. The SIAMPI approach ( Spaapen and van Drooge, 2011 ) as well as the Agora model ( Frederiksen et al., 2003 ; Barré, 2010 ) or Public Value Mapping ( Bozeman and Sarewitz, 2011 ) are promising examples of such formative assessment concepts. Using the concept of “productive interactions,” the SIAMPI approach focuses on the individual’s contributions to an interaction rather than reactively assessing its outputs. With its emphasis on productivity however, it cannot capture the counterintuitive contributions outlined above, which do not focus on the solution to a problem but instead question the problem.

Nonetheless, this at times counterintuitive impact of SSH disciplines may not be suitable for evaluation at all. Instead, it might imply that additional measures such as capacity building are needed to support the interaction between science and society ( Sigurðarson, 2020 ). The integration of science communication, and with it the reflection on boundaries, must become an integral part of science education. This is underlined by the trend towards public legitimation of research funds and a new social contract for science not as hasty obedience to a political desire but as a basis for an informed discussion of perspectives and implications. In that sense, it seems reasonable to reflect on and gain a more nuanced understanding of the societal impact of SSH disciplines within research communities and learned societies.

Data Availability Statement

Author contributions.

All authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript. BF supervised, carried out the analysis, editing and data collection together with FK. All authors discussed the results and contributed to the final manuscript.

This study was carried out with funding from the German Federal Ministry of Education and Research (under grant numbers 01PW18008A and 01PW18008B BMBF).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Social Science Research: Meaning, Significance, Process, Examples

Social science research: overview

Introduction: A systematic and step by step search into a phenomenon is known as research. As its name itself define its meaning, that is Re-search. A new investigation into a subject that may be an existing body of knowledge, we contribute to it through a new investigation. It is termed research. It is a scientific investigation followed by various methods and techniques. “D. Slesinger and D. Stephenson define social science research as the manipulation of things, concepts, or symbols to generalize to extend, correct, or verify knowledge whether that knowledge aids in the construction of theory or the practice of an art”. We can also simply said that it is a gift to the advancement and enhancement of already known pieces of information. Social science researchers also follow scientific methods and techniques to conduct research.

Significance of social science research

Research process.

Social science research is done in various steps. These steps or actions is inevitable to carry out the entire research. The various steps that involve in an investigation are;

In the research process, this is the first and the most crucial step. All other steps are depending on this step. The topic or the research problems tells you and others what you intended to study or your destination of research. Mainly there are 2 different kinds of topics one is related to states of nature and the other is related to the relationship between variables. There are mainly two kinds of variables one is a dependant variable and the other is an independent variable. The dependant variables are variables that depend on the independent variable. For example, if we study the unemployment among youth; we can say income, family background, education qualifications; the experience can be dependent variables that depend on the unemployment among youth which is an independent variable. After you select a topic or general topic, the next thing you must consider is to narrow down the general topic into a more specific one. It is not suitable or accurate to research a general topic. Because it is will be difficult to study a wide topic. Therefore it is necessary to determine the specific topic you wish to study or research. For example, if you want to study marriage you have to narrow it down to a more specific one; you can choose to study Catholic marriage customs in some specific geographical areas. It will be easier to study rather study marriage in a specific area. By doing like this one will get the most fruitful and reliable information that will enhance the current knowledge that existing in your field of study.

The reviewing literature provides you most thoughtful ideas, discoveries and a new dimension to your study. So it is really necessary to put your best to do a literature survey. Because above all the sufferings, It will guide your research.

In short, the literature review helps you to provide;

After the literature survey, the next step is developing a hypothesis for your research. Hypotheses are tentative assumptions made to test their logical and empirical consequences. It provides a focal point for research. For example, if the topic is related to Gender we can make a hypothesis ‘Women are emotional than men’; this is an assumption made by the researcher and this assumption is tested through the research. We can test this after analyzing the data collected. The hypothesis will help the researcher to concentrate on the topic and to keep the researcher on the same route without any diversion. It also shows the researcher what kind of data is needed and what methods of data analysis should follow.

In social science research, the whole unit under the study is known as the universe or population. For example, if your research topic is the Unemployment of youth in Mexico. The youth in Mexico will be the universe or population of your study. A complete enumeration or study of the entire population or universe means census enquiry. For example, the census took place in India every ten years is an example of the census. But in research, we don’t need to enumerate the entire population under study. Or in other terms, we need to select some units from the entire population under study, that is, we need to select the samples rather than to study the entire population. There are two kinds of sampling, one is probability sampling and the other is non-probability sampling. In probability sampling, the entire population gets an equal chance to be drawn but in non-probability sampling, the entire population does not get an equal chance to be drawn. Simple random sampling, stratified random sampling, systematic sampling are among the probability sampling techniques. In non-probability sampling, the data collected from convenience sampling, judgmental sampling, quota sampling, etc. The result of your data depends on the characteristics and attributes of your selected samples. The selected samples should provide you with the necessary and accurate data. Whether you select probability sampling or non-probability sampling is depends on the topic you selected. When you select a rare and sensitive population that is hard to get, you can choose a non-probability sampling of your choice and your respondent’s confidentiality. The sampling method will eliminate unwanted costs and travelling. It will save you time.

News Releases

Studying the social sciences gives a voice to the voiceless

August 30, 2024

Contact: Jon Meerdink ( [email protected] )

ANN ARBOR — The social sciences can be summed up simply as a mission to understand why people do what they do and think what they think. This rubric works across nearly every discipline of the social sciences, from economics to health-related studies to in-depth political research.

This research alone is important, but its applications are even more critical. In fact, they could be foundational to the operation of our democracy.

Writing for the Consortium of Social Science Associations’ (COSSA) “Why Social Science?” blog, Josh Pasek, Ph.D., writes that studying the social sciences offers crucial context to the operation of elections, giving representation to people and groups in ways that elections themselves may not.

“Election results don’t tell us who made which choices or what their motivations might have been. Indeed, knowing only who won does not reveal whether voters were expressing a preference for the candidate they chose or against that candidate’s opponent. So, although representatives often begin their terms in office asserting that they have a mandate to lead, the results of elections provide little insight into what, if anything, that mandate is for.

Public opinion surveys fill this gap. They contextualize the results of elections, allowing us to discern who made which choices, what they were thinking about, and how the events and messages of a campaign cycle shaped the ways people came to their decisions.”

Pasek, a faculty associate at ISR’s Center for Political Studies, studies the effects of new media on political processes. In his COSSA piece, he argues that public opinion polling — and the proper use of polling data by media outlets — is a crucial but often overlooked part of modern American politics.

The full piece, titled “Because People Can’t Be Represented If We Don’t Know What They Think,” is available via COSSA. Pasek is the second ISR faculty member to write for COSSA this year; Narayan Sastry, Ph.D., of the Panel Study of Income Dynamics (PSID) published a piece for COSSA in July .

MSU Researchers Use XR to Study Social-Communicative Processes

Scholars in the Center for Avatar Research and Immersive Social Media Applications ( CARISMA ) Lab at Michigan State University are pioneering interdisciplinary research to study basic social-communicative processes within immersive environments.

From Theory to Innovation: How MSU’s CARISMA Lab is Leading XR Research

Nestled beneath ComArtSci, the CARISMA Lab stands at the cutting edge of extended reality (XR) research. Since opening in 2016, the lab’s interdisciplinary team, led by Professor Gary Bente , is redefining how we perceive and interact within immersive environments, pushing the boundaries of communication science.

For Bente, this methodology began long before the Oculus Rift or the Meta Quest. Bente has been blazing the XR trail since the 1980s, publishing his first article on using 3-D animation to study nonverbal communication in Behavior Research Methods, Instruments & Computers in 1989, and continuing throughout the ‘90s. He published his first book “Virtuelle Realitäten” covering virtual reality from a psychological perspective in 2002. Seventeen years later, editors S.W. Wilson and S.W. Smith published Bente’s chapter on using emergent technologies in nonverbal communication research in their book “Reflections on Interpersonal Communication” (2019). In this chapter, Bente details the experiments that inspired him to use avatars to begin with — and how, over time, technological advancements enabled him to collect even better, more precise data.

“The biggest challenge for research in natural sciences and hard science is to recreate nature, to simulate what’s going on,” Bente said. “So, if you were able to recreate a phenomenon by just numbers and getting an animation on the screen, for example — then you have understood what’s going on, I guessed.”

Bente began using his descriptive, coded data to produce those animations and simple wire frame models himself. “I was always expecting ... this will fly ,” he said. “Avatars and agents, this will be the future. Nobody believed me.”

Today, CARISMA Lab’s research spans several critical areas — including nonverbal communication, communication neuroscience and media psychology — gleaning profound insights into human behavior by using advanced technologies like motion capture, electroencephalogram (EEG) systems, VR headsets and more.

CARISMA Lab’s co-director, Associate Professor Ralf Schmälzle , is a cognitive neuroscientist using XR technologies to study things that are otherwise difficult to analyze, particularly in the realm of social interactions.

“There is one theory that has a strong history in MSU; it’s called expectancy violation theory,” Schmälzle said. This theory seeks to explain how people respond when others behave in a way that doesn’t align with their expectations or social norms, which happens regularly in social interaction. “There are these little micro disturbances, and then the brain rings kind of an alarm bell — and one can ideally study that in virtual contexts.”

Schmälzle says a benefit of using virtual reality (VR) headsets is that participants can have natural interactions with other people and the neurophysiological measurement gear is already wrapped around their head.

“We’re interested in the eye. The eye is the main information acquisition device that the brain has,” he said. “The majority of information that comes into the brain goes in either via the eye or via the ear, and those are also the two senses that VR can best already capture — because VR is basically just a cell phone in front of your eyes.”

As eye tracking has become more integrated in standard VR headsets, this tool is both accessible and invaluable to cognitive neuroscientists like Schmälzle. In one of CARISMA’s recent projects, the team used VR to track how our eyes react to media content in real-time. By observing tiny changes in pupil size, the researchers could measure audience engagement and emotional responses with a level of unprecedented accuracy. This methodology could revolutionize how we tailor media content to better connect with viewers, whether in traditional media or in emerging virtual environments.

CARISMA researchers aren’t only interested in how people react to media; they also explore how our surroundings influence what we notice and remember. The VR Billboard Paradigm study is a perfect example. By recreating a roadside environment in VR, researchers can measure where people look and what they remember when exposed to advertising — providing valuable insights into how to craft more effective visual communication strategies in the real world, as well as implications for road safety.

Sue Lim is a Ph.D. student in the Department of Communication with an interest in combining artificial intelligence (AI) and VR methods. As a laboratory assistant at CARISMA, Lim regularly works with Bente and Schmälzle. For one of her latest studies examining how interactions with AI agents can subtly influence human behavior, the CARISMA researchers built embodied conversational agents , called VR-ECAs, that can naturally converse with humans. The study revealed that when the gender of AI agents did not match that of the participants, engagement in health-related conversations and decision-making improved. It also found participants experienced greater presence while conversing with VR-embodied agents than while chatting with text-only agents, like Chat GPT. This study paves the way for new experimental research — highlighting how the way AI is presented can shape human interactions, with potential applications in education, healthcare and more.

“If you use avatars for research, the basic question is: is it the same as if you would use real people, or a video of real people?” Bente said. It’s a question he has put to the test many times with a variety of experiments. Each time, the results were nearly identical.

“Nonverbal behavior is also about using space. If you move forward in the space, you invade a little bit more of my space; the co-presence might be something that makes a difference,” Bente explained. “I wanted to see whether if I observe somebody expressing an emotion in a shared space — or the same person showing this emotion on the screen, for example — does this make a difference?”

To test that, Bente’s research on emotion perception in shared virtual environments explored how being in the same virtual space as others affects our emotional judgments. The researchers found subtle differences, but the attributions participants made, the hit rates for emotions, were still the same.

One area that can benefit from this insight, Schmälzle says, is virtual meeting platforms (like Zoom, Teams or Skype) since both spatial and social presence are key in shaping social interactions and emotional experiences. “You have a sort of spatial presence right now [in a virtual meeting]; you are a 2D face on the screen and we can have a conversation because a lot of it works via verbal information exchange,” he said. “Some social presence is also there, but I would argue it’s only about 10% compared to what the real thing is.”

Schmälzle and Bente (as well as colleagues at the SPARTIE Lab) believe that virtual meetings, held in virtual reality , will be an improvement to what we currently experience … at least, once the animations are able to translate the full range of expressive body postures and facial movements with high fidelity.

“I think in the end it will be super realistic so that you really cannot make the distinction,” Bente said.

“But I think what’s really coming — and 20 years ago, I said this will be the world: where we have augmented reality, the other is coming in as an avatar and taking a seat on my real couch — well, that’s it.”

By Jessica Mussell

CARISMA Lab Research

Basic research: CARISMA uses XR technology as a methodology to study the basics of human communication and nonverbal interaction. Motion capture, neurophysiological measures and avatar animations provide new insights into the bio-behavioral mechanisms underlying person perception, emotion inferences, conflict management and social bonding.

Applied Research: In collaboration with media industry partners, CARISMA helps to develop and evaluate practical XR applications for entertainment, training and therapy. We study user responses and outcomes of XR usage along a variety of cognitive, emotional and behavioral measures, including enjoyment, stress, learning and more.

If you are interested in our research, please contact the Department of Communication or one of our faculty.

CARISMA Research

Extended Reality at MSU

Ancient people in Taiwan yanked healthy teeth from their mouths for 'aesthetic expression' and 'tests of courage,' study finds

For thousands of years, people in Taiwan pulled out healthy teeth. Now we know why they underwent this painful procedure.

Two side-by-side skulls with missing teeth.

Archaeologists now have a better understanding of why ritual tooth removal was practiced in ancient Taiwan and other parts of Asia — and it wasn't because people had bad teeth.

While tooth ablation has been documented among groups worldwide, it was most commonly associated with the first Austronesian communities, which included people in Taiwan, Southeast Asia and Polynesia. The procedure was first introduced in this area about 4,800 years ago, during the Neolithic period, and continued until the early 20th century, according to a study published in the December 2024 issue of the journal Archaeological Research in Asia .

It involved the pulling of otherwise-healthy teeth, including the incisors and canines, without the use of anesthesia. Afterward, the cavities would be filled with ash to inhibit bleeding and inflammation.

After gathering data from more than 250 archaeological sites across Asia, researchers found that 47 contained burials from the Neolithic (4,800 to 2,400 years ago) to the Iron Age (2,400 to 400 years ago) in which the deceased had missing teeth. The practice was equally spread across males and females. However, by the 1900s, it was more common among the latter group. And it wasn't just adults who had dental work; children got it, too.

The main reason people underwent this procedure was cosmetic — for "aesthetic expression," the researchers said. They determined this based on examples given in historical literature and more modern documentation.

Related: Analysis of ancient teeth questions theory that Native Americans originated from Japan

"The first and most frequently mentioned motivation was beautification, arising from a desire to distinguish oneself from the facial features of animals, as well as to enhance personal attractiveness, in particular to the opposite sex," the authors wrote in the study. "An interesting testimony underscored the pursuit of the sight of a crimson tongue peeking through the gap of bright teeth."

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The researchers also think that having teeth extracted would have been viewed as a "test of courage" — as anyone who has had substantial dental work can attest — as well as a preventive measure.

In addition, "Local people believed that ablating the teeth could reduce pain from tattooing or alleviate difficulty in pronunciation," the authors wrote. "In many cases, the visible result was viewed as proof of bravery or a measure of maturity."

— 17th-century Frenchwoman's 'innovative' dental work was likely torturous to her teeth

— Maya sacrifice victims found with mysterious blue string in their teeth

— 9 teeth facts you probably didn't know

Another reason, taken from ethnological records from Borneo and historical descriptions from southwestern China , may be that if a person had lockjaw, a pulled tooth would have made it possible to give them nourishment and medicine.

"This most pragmatic life-saving rationale of tooth ablation may explain its persistence, despite the painful procedure," the researchers wrote in the study. "Although instances of lockjaw may have been rare, the preventative care of tooth extraction outweighed the deadly prospects."

Jennifer Nalewicki is a Salt Lake City-based journalist whose work has been featured in The New York Times, Smithsonian Magazine, Scientific American, Popular Mechanics and more. She covers several science topics from planet Earth to paleontology and archaeology to health and culture. Prior to freelancing, Jennifer held an Editor role at Time Inc. Jennifer has a bachelor's degree in Journalism from The University of Texas at Austin.

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Published: 31 August 2024

Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

Xianru Shang ORCID: orcid.org/0009-0000-8906-3216 1 ,
Zijian Liu 1 ,
Chen Gong 1 ,
Zhigang Hu 1 ,
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Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

Introduction

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

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Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

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Exploring health science students' perception of the influence of health precaution practices during the covid-19 pandemic.

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The COVID-19 Pandemic, Health Science Students, Health Precautions Practices, During the COVID-19 Pandemic

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Foster, Marquitta L., "Exploring Health Science Students' Perception of the Influence of Health Precaution Practices During the COVID-19 Pandemic" (2024). Doctoral Dissertations and Projects . 5957. https://digitalcommons.liberty.edu/doctoral/5957

The purpose of this phenomenological study was to address a lack of research on health science students’ perceptions and use of health precautions during the COVID-19 pandemic. Albert Bandura’s Social Cognitive Theory frames this study of bachelor's, master’s and doctoral level students at Liberty University, George Mason University, and Norfolk State University. Data was gathered via surveys, interviews, and observations from 35 students across the three universities, providing a diverse pool of age, gender, and ethnicity. The initial survey gathered demographic data on whether students considered themselves immunocompromised, their view on COVID-19's severity for the immunocompromised, and whether they felt COVID-19 had increased the need for medical check-ups and vaccinations. Follow-up interviews were conducted, transcribed, and coded, identifying themes related to students’ awareness of COVID-19, the influence of students’ knowledge on their behavior, attitudes toward pandemic-era restrictions and contact tracing, and their use of health precautions. Many students reported increased use of health precautions during the pandemic, and those students with experience with vulnerable populations expressed using more health precautions out of concern for others’ well-being both during and after the pandemic. Students at all educational levels mentioned the importance of sharing accurate information. The findings suggest that enhancing students’ understanding of disease transmission, and effective strategies for communicating with lay people, could be productive. Practice communicating with non-scientists should be integrated into health science classes to capitalize on health science students’ care for others and position as trusted resources. Future research could explore the impact of these changes on students’ understanding of disease transmission, communication skills, and self-efficacy.

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A qualitative investigation of financial decision-making and enabling factors among ethnic minority young adults in Hong Kong. Esther Yin-Nei Cho. Research Open Access 30 Aug 2024 Humanities and ...
The current phase of social sciences research: A thematic overview of
1. Introduction. Science, the systematic study of structure and behavior in the natural and social worlds, is among the most compelling and trustworthy ways of knowing, including authority, experience, and common sense (Gravetter & Forzano, Citation 2018; Morling, Citation 2018).Thus, it has made tremendous contributions to human existence, as manifested in all the discoveries and inventions.
Social Science Research: Principles, Methods and Practices
This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any ...
Social Science Research Council (SSRC)
Explore Our History. For 100 years the Social Science Research Council has provided the policy and philanthropic communities with access to the social and behavioral scientists working to innovate and evaluate scalable solutions to pressing societal problems. Research to solve problems. In our work we mobilize our extensive global network of ...
Social Studies of Science: Sage Journals
Since 1970, Social Studies of Science has been a central journal for the field of Science and Technology Studies, serving as a venue for the articulation and development of key ideas and findings in the field from its early years to the current day. The journal is multi-disciplinary, welcoming contributions that advance our understanding of science, technology and medicine as social and ...
2021 Top 25 Social Sciences and Human Behaviour Articles
Here, the authors show in a pilot study that features of the human infant gut microbiome are associated with non-social fear behaviours during a laboratory based assessment. Alexander L. Carlson ...
Social Science Information: Sage Journals
Social Science Information (SSI) is a major international forum for the analysis and debate of trends and approaches in social science research and teaching. Fully peer reviewed, it publishes articles in both English and French. Social Science Information presents research from a broad range of perspectives, including: anthropology; sociology; psychology; philosophy; political science; economics.
Social sciences
An analysis of ancient genomes reveals an explosive geographical and demographic spread of modern domestic horses about 4,200 years ago. The findings counter the idea that horses accompanied and ...
Research in the Social Sciences
Subjects of study in the social sciences are often interdisciplinary, so your searching will likely need to be, as well. A review of the literature for a social sciences research project not only should identify what research has been done but also compare and contrast the available information and evaluate its significance.
The Journal of Social Studies Research: Sage Journals
The Journal of Social Studies Research (JSSR) is an internationally recognized peer-reviewed journal designed to foster the dissemination of scholarly ideas and empirical research findings related to k-16 social studies education. The purpose of the journal is to share new knowledge and innovative ideas that contribute to the improvement of social studies education across the world.
Social Science Research
Social science research is a broad field of study that investigates human behavior. Social science includes the fields of psychology, sociology, anthropology, and many other areas of research.
Organizing Your Social Sciences Research Paper
I. Groups of Research Methods. There are two main groups of research methods in the social sciences: The empirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences.This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured.
Social science
social science, any branch of academic study or science that deals with human behaviour in its social and cultural aspects. Usually included within the social sciences are cultural (or social) anthropology, sociology, psychology, political science, and economics. The discipline of historiography is regarded by many as a social science, and ...
Social science
Social science is one of the branches of science, devoted to the study of societies and the relationships among individuals within those societies. The term was formerly used to refer to the field of sociology, the original "science of society", established in the 18th century.In addition to sociology, it now encompasses a wide array of academic disciplines, including anthropology, archaeology ...
The research process
Paradigms of social research. Our design and conduct of research is shaped by our mental models, or frames of reference that we use to organise our reasoning and observations. These mental models or frames (belief systems) are called paradigms. The word 'paradigm' was popularised by Thomas Kuhn (1962) [1] in his book The structure of ...
Understanding the Societal Impact of the Social Sciences and Humanities
The Role of Social Sciences and Humanities Disciplines in Response to Societal Problems. There is some controversy about the role that SSH research can play in tackling societal problems: While some scholars argue that these fields should augment and emphasize their transformative potential (Sörlin, 2018; Sigurðarson, 2020), others attribute a rather passive role to them, suggesting that ...
Unreliable social science research gets more attention than solid studies
That's far more, on average, than the papers from the project that did replicate. Now, a new study shores up the popularity of unreliable studies: Social science papers that failed to replicate racked up 153 more citations, on average, than papers that replicated successfully. This latest result is "pretty damning," says University of Maryland ...
Home :: SSRN
PHYSICAL SCIENCES are those disciplines that study natural sciences, dealing with nonliving materials. Social Sciences . SOCIAL SCIENCES are those disciplines that study (a) institutions and functioning of human society and the interpersonal relationships of individuals as members of society; (b) a particular phase or aspect of human society.
Studies in Social Science Research
Studies in Social Science Research (SSSR) is an international, peer-reviewed, open-access journal published by the Scholink.It aims to promote excellence through dissemination of high-quality research findings, specialist knowledge, and discussion of professional issues that reflect the diversity of this field.
Social Science Research: Meaning, Significance, Process, Examples
In social science research, the whole unit under the study is known as the universe or population. For example, if your research topic is the Unemployment of youth in Mexico. The youth in Mexico will be the universe or population of your study. A complete enumeration or study of the entire population or universe means census enquiry.
Studying the social sciences gives a voice to the voiceless
ANN ARBOR — The social sciences can be summed up simply as a mission to understand why people do what they do and think what they think. This rubric works across nearly every discipline of the social sciences, from economics to health-related studies to in-depth political research. This research alone is important, but its applications are ...
Social data science
Social data science is an interdisciplinary field that addresses social science problems by applying or designing computational and digital methods.As the name implies, Social Data Science is located primarily within the social science, but it relies on technical advances in fields like data science, network science, and computer science.The data in Social Data Science is always about human ...
Approaching the Social Impact of Research Through a Literature Review
Social impact was considered an inevitable consequence of the development brought about by science (Lima & Wood, 2014).Evaluation systems, which focus on scientific impact, consider that research with high academic impact generates benefits for society (Bornmann, 2013; Smith, 2001).This assumption is not always valid; there is research with high scientific impact that has not generated any ...
MSU Researchers Use XR to Study Social-Communicative Processes
From Theory to Innovation: How MSU's CARISMA Lab is Leading XR Research. Nestled beneath ComArtSci, the CARISMA Lab stands at the cutting edge of extended reality (XR) research. Since opening in 2016, the lab's interdisciplinary team, led by Professor Gary Bente, is redefining how we perceive and interact within immersive environments, pushing the boundaries of communication science.
Ancient people in Taiwan yanked healthy teeth from their ...
The procedure was first introduced in this area about 4,800 years ago, during the Neolithic period, and continued until the early 20th century, according to a study published in the December 2024 ...
Knowledge mapping and evolution of research on older adults ...
Humanities and Social Sciences Communications - Knowledge mapping and evolution of research on older adults' technology acceptance: a bibliometric study from 2013 to 2023 ... and we adhered ...
Exploring Health Science Students' Perception of the Influence of
The purpose of this phenomenological study was to address a lack of research on health science students' perceptions and use of health precautions during the COVID-19 pandemic. Albert Bandura's Social Cognitive Theory frames this study of bachelor's, master's and doctoral level students at Liberty University, George Mason University, and Norfolk State University.
Environmental and social factors impact brain aging, study shows
Countries with greater inequalities - whether economic, pollution or disease-based - exhibited older brain ages, according to a study published in Nature Science, involving the University of Surrey.