scholarly journal articles on early childhood education

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• Int J Environ Res Public Health

Early Child Development Assessments and Their Associations with Long-Term Academic and Economic Outcomes: A Systematic Review

Leah n. isquith-dicker.

1 Department of Global Health, University of Washington START Center, Seattle, WA 98195, USA; moc.liamg@wuihael (L.N.I.-D.); [email protected] (A.K.); ude.wu@bseanad (D.B.); ude.wu@sewah (S.E.H.); ude.wu@rekylsj (J.S.)

2 Department of Anthropology, School of Public Health, University of Washingto, Seattle, WA 98195, USA

Andrew Kwist

3 Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA 98195, USA

Danae Black

Stephen e. hawes, jennifer slyker, sharon bergquist.

4 Bill & Melinda Gates Foundation, 500 5th Ave N, Seattle, WA 98109, USA; [email protected]

Susanne P. Martin-Herz

5 Department of Pediatrics, University of California San Francisco, 1825 Fourth St., 6th Floor, UCSF Box 4054, San Francisco, CA 94143, USA

Associated Data

Not Applicable.

Developmental screening instruments were designed as diagnostic tools, but there is growing interest in understanding whether select tools can also be used systematically in research to examine intervention impacts on long-term outcomes. As such, this systematic review aims to examine associations between child development assessment tools and educational attainment, academic achievement, or wealth. We included studies identified in PubMed, PsycINFO, and Educational Resources Information Center if they reported an association between at least one tool from a pre-established list and one outcome of interest after age 10. Of 597 studies identified, 11 met inclusion criteria; three examined educational attainment as the outcome of interest, six examined academic achievement, one wealth, and one both educational attainment and wealth. Intelligence tests were utilized in five of the included studies, neuropsychological/executive function or behavior tools were used in five, and one study used tools across the domains. High-quality studies were identified across all three of the domains, but educational attainment and wealth had the greatest proportion of high-quality studies, as compared to academic achievement. Our review demonstrates the potential for certain child development assessment tools to adequately assess long-term outcomes of interest, but additional prospective studies using validated, culturally appropriate tools are needed. PROSPERO registration number: CRD42018092292.

1. Introduction

Recent findings from the Lancet series on early childhood development estimate that over 250 million children under five years of age in low-and middle-income countries are at risk of not achieving their full developmental potential [ 1 ]. Children in low- and middle-income countries may face a variety of adversities, including recurrent illness, malnutrition, and trauma, with long-term consequences for their health, productivity, and overall well-being [ 2 ]. It has been previously estimated that children not reaching their full developmental potential results in an average adult annual income deficit of 19.8% [ 3 ]. In addition to income loss, developmental delays have also been associated with considerable academic underachievement [ 4 , 5 , 6 ]. These factors have led to increased interest in child development assessment tools that are adequately associated with long-term academic, economic, and human capital outcomes from a young age. However, existing child development assessment tools were generally designed to assess risk or developmental status at the time of testing [ 7 , 8 , 9 , 10 ]. Limited research focused on this topic suggests that available tools may not have strong predictive potential for later outcomes [ 1 , 4 ], highlighting the need for additional investigation to determine if specific tools or developmental domains may be useful for both prediction of outcome without intervention or in evaluation of intervention programs.

This systematic review was conducted to identify child development assessment tools that are associated with the long-term outcomes of educational attainment, academic achievement, and wealth. Given that an assessment of study quality is also included in this review, this synthesis provides information to aid researchers in the selection and prioritization of tools or domains for further research in this area.

2. Materials and Methods

2.1. data sources.

A literature search was conducted in PubMed, PsycINFO, and Educational Resources Information Center (ERIC) on March 30, 2018. Publication date was restricted to manuscripts published in 1990 or later, due to differences in assessment tools and publication standards in comparison to more recent literature ( Document S1 ). A search template was created that was applied to all 3 databases with minimal tailoring ( Document S2 ). The search yielded 597 unique results that were exported into the Covidence (Melbourne, Australia) systematic review software [ 11 ]. This systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and preregistered at PROSPERO: CRD42018092292.

2.2. Development Tool Selection

The search template contained a list of 104 child development assessment tools ( Table S1 ). An initial list of 1398 tools was generated from a search of the PsycTEST database, a repository of assessment tools indexed from articles in peer-reviewed journals and books by experts at the American Psychological Association [ 12 ]. The PsycTEST search utilized the search terms, “child development, executive function, school, education, academic, readiness, reading, literacy” and excluded the terms “sexual behaviors and divorce.” As many tools were not relevant to study objectives, one of the authors (SMH) manually filtered the list and added additional relevant assessment tools absent from PsycTEST database to assemble the final list. Tools were retained in the final list if they measured at least one of the five most common domains of development (gross motor, fine motor, language, cognitive, and social emotional), or examined reading/pre-reading skills or executive function. Tools were required to show some indication of psychometric properties, since it was felt that at least some evidence of reliability and validity were prerequisites to adequate association between the tools and future educational and economic outcomes, even if this was obtained from cross-sectional as opposed to longitudinal research. Tools were excluded if they examined only sublevels of developmental domains, were specific to second language learning, were designed explicitly to evaluate gender differences, were specific to health or mental health diagnoses, were specific to a particular study context, examined child or caregiver attitudes toward a developmental domain or skill set rather than the child’s development (e.g., child reading attitude), or focused specifically on theory of the mind, math achievement, or home literacy environment.

2.3. Study Inclusion and Exclusion Criteria

Studies were included in this review on the basis of the following criteria: (1) the study was conducted using an experimental or observational design; (2) the study used at least one of the assessment tools in the list with children under the age of 18; (3) the study reported at least one outcome related to educational attainment, academic achievement, or wealth and assessed this outcome after the age of 10 years; educational attainment was defined by the highest-grade level completed at the time of data collection, while academic achievement was defined as performance in one or more subject areas; (4) articles were published in English or French; French-language articles were included in an attempt to ensure inclusion of articles that were conducted in Francophone Africa.

Cross-sectional studies were excluded because the study objective was to identify tools that were associated with long-term academic and socioeconomic outcomes. Studies conducted with children who were hospitalized or had severe neurologic injuries, genetic conditions, or autism spectrum disorder were excluded, because the use of a tool in such a sample could not easily be generalizable to the larger pediatric population. The age of 10 was chosen as a lower bound for long-term outcomes due to concern that children in some low-and middle-income countries may terminate formal schooling near this age. There were no exclusion criteria related to the length of time between tool assessment and outcome evaluation or the specific geographic location. Detailed inclusion and exclusion criteria can be found in the study’s PROPSERO preregistration.

2.4. Research Processes

Title and abstract screening were completed for all identified studies independently by two reviewers (LNID and AK), and discordance was resolved by a third reviewer (JS). Full text screening was also completed by two reviewers (LNID and AK), with discordance resolved by a third reviewer (DB). For studies excluded by full-text review, reviewers selected one primary reason for exclusion, and discordance in study exclusion rationale was resolved by a third reviewer (JS). The exclusion hierarchy was as follows, in order of priority: outcome not of interest, cross-sectional study design, outcome assessed at younger than 10 years of age, population with medical/developmental condition, assessment tool not on list. A PRISMA flowchart is provided in Figure 1 .

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart of the selection process of published studies.

In addition to this structured search, targeted searching was conducted in two ways. First, publications identified from a list of cohort studies recommended by subject matter experts (SMH and SB) were evaluated for their adherence to study inclusion criteria [ 13 , 14 , 15 , 16 ]. Second, an additional search using cohort studies identified during the initial stages of the title and abstract screening process was undertaken, and three potentially relevant studies were added to the total pool for title and abstract screening (additional studies identified through other sources in Figure 1 ). These additional steps were taken in an effort to broaden the scope of the review in the event that the search terms missed relevant studies.

2.5. Data Abstraction

The following information was abstracted from the articles identified in the full-text review: author, publication year, sample size, sampling method, time between assessment tool and outcome, assessment tool(s) used, age at which assessment tool was used, outcome(s), age at which outcome was evaluated, and measure(s) of association. For studies that used an assessment tool at multiple time points without separate effect measures, we only reported the greater duration from child development assessment to outcome (e.g., for tool applied at age 11 and age 16 and outcome measured at age 19, we only reported association between age 11 to age 19). In some studies, more than one assessment tool was used, including some child development assessment tools that were not on our pre-specified list. In these cases, only the associations between the tools on the list and our outcomes of interest were reported. Effect measures are presented adjusted for standard sociodemographic factors (i.e., parent education, sex, and wealth) unless otherwise stated. Regression coefficients and odds ratios are presented with statistical significance, and confidence intervals when measures of statistical significance were unavailable.

2.6. Data Synthesis

We used a narrative approach to data synthesis, which is the preferred method when empirical approaches and variables are highly varied across studies [ 17 ]. Tools were then categorized by the domain or construct area they assessed. This classification was initially made by a developmental-behavioral pediatrician (SMH) and then independently by 3 volunteer neuropsychologists. We used outcome, tool domain, and a study quality assessment as the classification schemes for synthesizing data.

2.7. Quality Assessment

A quality assessment was conducted to determine the rigor of study methods and relevance of the effect measures reported, in the context of the objectives of our study. For the quality assessment, five criteria were evaluated by the two authors (DB and LID) who completed the data extraction. These criteria were adapted from the Cochrane Collaboration Risk of Bias Tool, usually applied to evaluations of quantitative evidence from systematic reviews [ 18 ]. The authors of this tool recommended the assessment of five specific categories of bias and one category for other types of bias as needed in accordance with study objectives. Detail on bias categories is provided below; other categories were not considered given the sufficient coverage provided by those applied. The authors evaluated the criteria on these categories independently by maintaining separate data sheets that were shared only when evaluations were complete. Discordance was discussed and resolved by a third reviewer (JS). Each criterion is defined below and was assigned a designation of, low, high, or unclear quality with point values of −1, 1, and 0, respectively. Criteria were weighted equally because each category of bias was deemed of equal importance to study quality. An overall assessment of study quality was ascertained by the sum of the point values, termed the "cumulative quality assessment", which was used to categorize studies as of high, low, or neutral quality. The unclear designation was assigned when information regarding a criterion were not provided in the article itself and was not possible to ascertain from supplemental materials or earlier publications describing study methods. Quality assessment criteria were as follows:

• (1) Selection: Evaluated how participants were selected for inclusion in the study. A study with a random sample or an attempted census was designated high quality and a convenience sample was designated as low quality.
• (2) Sample size: Examined the adequacy of the sample size. A total sample size of >100 participants was designated high quality for the current review, as smaller studies may have very limited statistical power.
• (3) Attrition: Assessed loss to follow up, withdrawal, or exclusion from analysis. Studies with a rate of attrition of < 25% were designated high quality.
• (4) Duration: Evaluated the length of time between child development assessment and outcome. Studies with durations >5 years were considered to be high quality.
• (5) Outcome reporting: Evaluated the extent to which authors provided information on how outcomes were measured. Standardized tests, registries, or assessment tools and those reported by teachers or trained experts (e.g., psychologist) were designated high quality, and self-report (child or parent) was designated low quality.
• (6) Cumulative quality assessment: Sum of point values for criterion 1–5.

3.1. Overview of Studies

Of 597 unique articles identified, 500 were excluded during the title and abstract screening phase, largely due to being cross-sectional in nature, not assessing an outcome of interest, or having the outcome of interest but assessing it prior to 10 years of age. During this phase, none of the publications identified by subject matter experts for targeted searching met criteria for full-text review. Of the 97 articles included in the full text review phase, 11 met study criteria for inclusion ( Table S2 ); the number of articles excluded for each criterion is documented in Figure 1 . All included studies were observational cohort studies, with a follow-up duration range from 2 years to greater than 20 years. Six studies were sampled from a school setting [ 19 , 20 , 21 , 22 , 23 , 24 ], two from birth cohorts [ 25 , 26 ], one via an adoption agency [ 27 ], and two through larger population-based studies [ 28 , 29 ]. Sample sizes varied widely, with smaller cohorts (<50) among special populations (e.g., low-income families) and larger population-based cohorts (>6000).

3.2. Assessment Tool Domains of Studies Included for Review

The child development assessment tools utilized in the 11 included studies were classified into three categories: neuropsychological/executive function and behavior, intelligence, and general development and achievement ( Table 1 ). Figure 2 displays the distribution of studies by the domain of the tool used. Neuropsychological/executive function and behavior tools were employed in five studies; intelligence tests in five studies, and multiple tools from both the general development/achievement and intelligence domains were used in one study (see Figure 2 notes for details). Studies that analyzed multiple tools independently were counted separately for each tool.

Included studies by domain of child development assessment tool. The total number of studies listed exceeds the number of studies included in this review because [ 27 ] included 2 child development assessment tools of interest in 2 domains (Development/achievement and Intelligence). A detailed explanation for the high/neutral/low quality designation is provided in Section 3.4 below.

Child development assessment tools utilized in included studies, by domain.

3.3. Outcomes

The association between a child development assessment tool of interest and educational attainment was measured by four of the 11 selected studies, as shown in Figure 3 [ 25 , 27 , 28 , 29 ]. Educational attainment was determined either by self-report of the number of school years completed or national registries that included school completion information. Six studies reported associations between a tool of interest and academic achievement [ 19 , 20 , 21 , 22 , 23 , 24 ]. There was more heterogeneity in the measurement of academic achievement, including standardized tests that were named (e.g., Iowa Test of Basic Skills, Metropolitan Achievement Test, and General Certificate of Secondary Education) or unnamed, as well as school grade point averages, either from school records or by self-report. Only two studies assessed outcomes related to wealth, income, or socioeconomic status [ 25 , 26 ].

Included studies by outcome of interest. NOTES: The total number of studies listed exceeds the number of studies included in this review because [ 25 ] assessed both educational attainment and wealth. A detailed explanation for the high/neutral/low quality designation is provided in Section 3.4 below.

3.4. Quality Assessment

Table 2 displays the results of the quality assessment, which identified two low quality studies, four neutral quality studies, and five high quality studies. The low-quality studies were published in 1995 and 2017 and represented small samples of children attending a residential school in Canada (N = 20) and an elementary school in Switzerland (N = 103), respectively [ 20 , 21 ]. These studies reported non-significant effect estimates for outcomes and had short duration of follow-up (≤3 years). The high-quality studies were published between 2001 and 2014, included large cohorts (>1000) from New Zealand, Norway, and The Netherlands, and a smaller cohort from the United States [ 22 , 25 , 26 , 28 , 29 ]. The effect measures for the high-quality studies were almost all significant (except one effect measure from a study that used the Youth Self Report & Child Behavior Checklist [ 29 ] and had greater length of follow up (range 5 to 29 years). The five high quality studies are summarized below:

• Moffitt, 2011 [ 26 ]

Study quality assessment.

Each criterion was evaluated with the following numerical values: high quality = 1; low quality = −1, unclear quality = 0. Each study could receive up to a cumulative assessment value of 5. Studies with values > 1 were designated high quality studies, values of 1, 0 and −1 neutral quality, and < −1 low quality studies. See Section 2.7 (Materials and Methods: Quality Assessment) for additional detail.

A prospective cohort study from the participants in the Dunedin Multidisciplinary Health and Development Study Cohort in New Zealand assessed childhood self-control, socioeconomic factors, and IQ using the Wechsler Intelligence Scales for Children, Revised (WISC-R; repeat measures at ages 3, 5, 7, 9, and 11), and the association with wealth at age 32. Statistical models included adjustment for socioeconomic factors and fixed-effects modeling applied to dizygotic same-gender twins to compare outcomes of siblings with differential self-control levels and thus isolate the effect of self-control. The study found that the intelligence assessment was significantly associated with four measures of wealth: socioeconomic status, income, financial planfulness, and financial issues (regression estimates −0.400, −0.291, −0.160, and 0.029, respectively; all p < 0.05).

• Sagatun, 2014 [ 28 ]

A retrospective cohort study that utilized data from a Norwegian registry to assess the association between the Strengths and Difficulties Questionnaire administered to 15- to 16-year-olds and academic attainment as recorded in the national registry of school completion at age 20–21. Statistical models included adjustments for children’s ethnic background, county of residence, parents’ education, income, and marital status. The study found that this tool was significantly associated with odds of non-completion of school (ORs 1.11–1.48, all p < 0.001).

• Lamp, 2001 [ 22 ]

A prospective cohort study among families enrolled in the Head Start Program in the United States assessed intelligence using the Stanford Binet Intelligence scale at age 4 and its correlation with academic achievement at ages 5 to 10 years, measured by the Metropolitan Achievement Test. No information regarding the factors used for adjustment in statistical models was provided. The study found that intelligence as measured by this tool was significantly correlated with academic achievement (correlation coefficients 0.39–0.62, all p < 0.01).

• Fergusson, 2005 [ 25 ]

A retrospective cohort study involving participants from the Christchurch Child Development Study in New Zealand assessed intelligence using the WISC-R in 8 to 9-year-olds and analyzed its association with wealth, educational outcomes, and obtaining a university degree between the ages of 18 and 25 years. Statistical models included adjustment for a series of covariate factors including measures of childhood social and family disadvantage and behavior. The study found that intelligence was significantly associated with gross income (regression coefficient 1.595, p < 0.05) and gaining school or university qualifications (regression coefficients 0.67–0.82, p < 0.01).

• Veldman, 2014 [ 29 ]

A prospective cohort study to determine likelihood of educational attainment (measured by number of years of schooling completed) by age 19, using data from the Tracking Adolescent’s Individual Lives Survey in The Netherlands, assessed 11 year-olds using the Child Behavior Checklist and its Youth Self Report. Statistical models included adjustment for children’s sex, age, IQ, parental educational status, and physical health status. The study found that externalizing, internalizing, and attention problems, as assessed by these combined tools, were associated with higher odds of low (primary, lower vocational and lower secondary education) vs. medium (intermediate vocational and intermediate secondary) educational attainment at age 19 (OR 1.25–1.78; statistical significance varied—see Table S3 for details).

4. Discussion

4.1. overview of key findings.

This study sought to examine the evidence base for the association between child development assessment tools and longer-term outcome. After applying a rigorous set of inclusion criteria on 597 studies identified from our initial search, we retained 11 observational cohort studies in this systematic review that investigated the association between a child development assessment tool of interest and a long-term outcome of interest. Although the studies were distributed across all three outcomes of interest, and three development tool domains, the majority of these studies investigated the outcome of academic achievement and used intelligence or neuropsychological/executive function and behavioral tools as predictors. Five of the eleven studies were determined to be high quality and reported measures of association that were almost all significant; given that these studies had at least 100 participants, and a minimum of 5 years duration of follow-up, these would have more statistical power to show a significant effect size. These findings suggest that child development assessment tools across a range of development domains may have predictive potential for various types of outcomes later in life, but several limitations of the available literature and limitations of our study suggest that further research is needed as described below.

4.2. Limitations of the Available Literature

The evidence base supporting the ability of child development assessment tools to predict long-term outcomes remains limited to remarkably few studies, with a need for more high-quality studies that are adequately powered and have follow-up sufficient to reveal associations with adult-life outcomes. Figure 2 and Figure 3 illustrate that there are high quality studies distributed across the three outcomes of interest and all three assessment tool domains. However, the included studies were heterogeneous with respect to study design, assessment tools, outcome measures, and statistical models. This heterogeneity precludes direct comparison, even between studies that used the same tool (e.g., WISC-R) to determine whether these associations are repeatable, and the effect sizes are consistent across populations. Our quality assessment suggests that issues related to attrition remain a challenge in longitudinal studies; continuing to engage and track study participants over decades is a common challenge in longitudinal studies, so this finding is not all together surprising. However, it is notable that two studies did not clearly describe attrition, which threatens both evaluation of sample size and effect measures [ 20 , 24 ].

All included studies in this review were observational cohort studies, which are susceptible to several limitations. Cohort studies are prone to differential loss to follow-up of participants with medical or financial challenges, which can bias findings. While many studies accounted for confounding with adjusted effect estimates, additional sources of residual confounding likely remained, including family and community contextual factors, the impact of developmental interventions, and children’s physical health. Longitudinal studies that document and control for these contextual factors are needed.

Additionally, the use of multiple or composite assessment tools was framed as a “best fit” approach by some authors. However, the utilization of multiple predictors can diminish the statistical validity of significant results due to the increased probability of a significant result due solely to chance, given the large number of hypothesis tests. A priori assertions grounded in theoretical rationale for the utility of composite or multiple domain assessment tools can help to mitigate this issue and provide better evidence as to whether composite assessments improve prediction of outcomes; alternatively, the assessment of predictors separately would help to isolate the effect of individual tools.

Finally, the generalizability of findings from this review is limited by the fact that all of the studies took place in high-income countries among relatively homogenous racial and ethnic groups. Few of the tools assessed in this review have been validated for use in African, Asian, and South American populations. The absence of studies from low-and middle-income countries may be a reflection of the small number of tools validated for use in these populations, and limits generalizability of findings to populations from low-income countries, and populations with high rates of malnutrition or limited access to education.

4.3. Limitations of Present Study

There are several limitations to this review. First, the study was designed with a specific purpose to identify developmental assessment tools that predict long term outcomes related to academic and economic potential of individuals and communities and did not include research assessing other long-term outcomes with high relevance for health and quality of life. Despite efforts to be comprehensive in its inclusion of tools by completing a broad search of the PsycTESTS database and reviewing almost 1400 tools, some studies were excluded at full-text review because they did not include an assessment tool from the original search list (e.g., a study that examined educational attainment among three large cohorts from Finland, the UK, and the Philippines and found significant positive associations between cognitive development scores at early ages and attainment in adulthood [ 30 ]). Despite a thorough search of three robust databases, there is likely additional relevant research that was not captured. In particular, grey literature, such as non-peer reviewed organizational reports, and economics literature (e.g., EconLit database) were not considered and may be a source of additional information regarding the socioeconomic outcome of interest. Additionally, only English and French literature was reviewed due to the linguistic capacity of the research team, and thus there may be additional literature in other languages that may be particularly relevant to address the issue mentioned above related to generalizability of findings to the low-and middle-income country context.

Next, this review was completed in 2018; to remediate the concern of additional published literature not being reflected in this review, in January 2021 we conducted post-hoc abstract screening of articles published in 2018–2021 in all three databases (PubMed, Educational Resources Information Center (ERIC), and PsycINFO), using the same search terms. Of 158 results across the three databases, five articles passed abstract screening and were full-text reviewed, and only two additional studies met inclusion criteria [ 31 , 32 ]. First, Samuels et al., 2019 found that the Behavior Rating Inventory of Executive Function (BRIEF) and BRIEF Self-Report (BRIEF-SR) were significantly associated with the upcoming cumulative grade point average in a diverse population of 259 New York middle and high school students, independent of gender, free/reduced lunch, and special education status [ 31 ]. However, it is unclear whether this instrument predicts longer-term academic performance because the time interval between tool assessment and outcome assessment was notably short. Second, Kosik et al., 2018 found in a U.S based birth cohort that the WISC at age seven was significantly associated with educational attainment, employment, and wealth in adulthood [ 32 ]. Despite the identification of these two additional studies, of which likely only Kosik et al., 2018 would be considered high-quality, we are confident that the findings reported in our main review remain relevant and continue to fill a needed gap in the literature. These studies’ findings do not conflict with findings of the five high-quality studies in the main review, and in fact only further support our review’s overall conclusions.

Finally, all of the high-quality studies reviewed reported positive associations, suggesting publication bias and potential underreporting of null findings. Coupled with the small sample sizes and shorter follow-up of the low and neutral quality studies reviewed, additional research is needed to support the associations identified between tools and outcomes studied herein.

4.4. Recommendations for Future Research

Additional research evaluating regionally-validated tools, conducted in large and diverse study populations with adequate follow-up, including low-and middle-income countries, are needed to understand whether these tools can be used to predict long term outcomes and assess the impact of interventions. Existing data from large cohort studies in these low-and middle-income countries, either ongoing or already completed, could also be leveraged to contribute to this field of work. Many of the tools evaluated in our review were proprietary, and there is growing interest in developing tools that are valid across multiple populations and that can be administered by medical staff or community health workers [ 33 ]. Additionally, to address the limitation of the inability to capture all potentially relevant development tools of interest, researchers conducting future research on this topic could consider not restricting their search to specific tools, but instead develop a detailed search string on keywords related developmental domains.

5. Conclusions

Our review identified 11 studies investigating associations between early childhood assessment tools and long-term economic and academic outcomes of interest. Five of these studies were determined to be high-quality and reported mostly statistically significant associations, suggesting that certain child development assessment tools are associated with the long-term outcomes of interest. Given that child development assessment tools were designed to identify children with developmental delay at the time of assessment, our study addresses a key need to characterize the potential for these tools to be sensitive to intervention effects and to potentially predict longer-term outcomes. The high-quality literature reviewed was primarily conducted in high-resource contexts and was relatively sparse; as such, additional prospective studies, engaging large, diverse populations in both high-income and low-and middle-income countries are needed to adequately address remaining gaps in this evidence base.

Acknowledgments

We appreciate the three volunteer neuropsychologists who assisted in domain classification of the childhood development assessment tools of interest: Shannon Lundy, Stephany Cox, and Gina Pfeifle. The majority of the content of this paper was included in some form in a report for the Bill & Melinda Gates Foundation; further refinement of the quality assessment methodology and Discussion section was conducted after the report was delivered.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/18/4/1538/s1 , Document S1, Document S2: PubMed, PyscINFO, and ERIC database search strings, Table S1: Child development assessment tools included in search string, Table S2. Details of studies included in the review.

Author Contributions

S.P.M.-H. and S.B. conceptualized and designed the study, reviewed, and revised the manuscript. L.N.I.-D., A.K., D.B. and J.S. designed the study, collected the data, carried out the analyses, drafted the initial manuscript, and reviewed and revised the manuscript. S.E.H. critically reviewed the manuscript for important intellectual content and reviewed and revised the manuscript. All authors have read and agreed to the published version of the manuscript.

This research was funded by the Bill & Melinda Gates Foundation through a grant with the University of Washington Strategic Analysis, Research and Training (START) Center.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

Sharon Bergquist was employed by and Susanne Martin-Herz was a consultant to the Bill & Melinda Gates Foundation during the course of the review. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Bill & Melinda Gates Foundation. All other authors have no conflict of interest to declare.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Introduction
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• Article Information

eAppendix 1. CLS Background

eAppendix 2 . CPC Program Description

eAppendix 3. SDH Definitions and Justification

eTable 1. Index of Structural Equality and Support (I-SES) as Operationalized in Chicago Longitudinal Study

eAppendix 4. Covariates in Model Specification

eAppendix 5. Inverse Probability Weighting

eAppendix 6. Educational Attainment Mediator

eTable 2. Group Equivalence at Age 35 Follow Up and for Original Chicago Longitudinal Study Cohort (N=1,124)

eFigure. Standardized Mean Differences for 2 Child-Parent Center (CPC) Program Contrasts for Low (0-3), Middle (4-6), and Top (7-9) Scores on the I-SES [Index of Structural Equality and Support] for the Total Sample and by Neighborhood Poverty Status (40% or More vs. Less in Poverty by Child’s Age 3 years) as Assessed at Midlife

eAppendix 7. Alternative Model Estimates

eTable 3. Alternative Models for CPC Preschool Participation and Index of Structural Equality and Support (I-SES) at Midlife

eReferences.

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Morency MM , Reynolds AJ , Loveman-Brown M , Kritzik R , Ou S. Structural Equality and Support Index in Early Childhood Education. JAMA Netw Open. 2024;7(8):e2432050. doi:10.1001/jamanetworkopen.2024.32050

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Structural Equality and Support Index in Early Childhood Education

• 1 Institute of Child Development, University of Minnesota, Minneapolis
• 2 Human Capital Research Collaborative, University of Minnesota, Minneapolis

Question   Does a comprehensive early childhood education program promote engagement in more supportive and resource-rich communities in adulthood?

Findings   This cohort study that followed-up 1124 individuals from preschool age to adulthood found that participation in the Child-Parent Center early education program was associated with higher scores on the Index of Structural Equality and Support at midlife.

Meaning   These findings suggest that early childhood programs can strengthen sociostructural and community supports well into adulthood.

Importance   Whether early childhood education is associated with a wide range of adult outcomes above and beyond individual- and family-level outcomes is unknown. As a consequence of improving educational and career success, it is postulated that participation in high quality, comprehensive programs can promote residence in more supportive community contexts in adulthood.

Objective   To investigate whether participation in high-quality early childhood programs (ECP) in high-poverty neighborhoods is associated with neighborhood-level social determinants of health (SDH) at midlife.

Design, Setting, and Participants   This cohort study analyzed data from the Chicago Longitudinal Study, a prospective cohort investigation following-up 989 children aged 3 to 4 years attending the Child-Parent Center (CPC) preschool program between 1983 and 1985 and a comparison group of 550 children using a nonrandomized trial design. Participants from the original sample who completed a telephone interview on health and well-being between ages 32 and 37 years were included in this analysis. Data analysis was conducted from April to June 2024.

Exposure   Participation in a CPC program, which includes preschool (ages 3 to 4 years) and school-age (kindergarten through third grade), vs usual early education programs.

Main Outcomes and Measures   The study used a new SDH measure (Index of Structural Equality and Support [I-SES]) based on the Healthy People 2030 framework. This 9-item index score included neighborhood-level assessment, measurement of the quality of education and health services, and assessment of racial discrimination in social and community contexts. Years of education by age 34 years was assessed as the key mediator of influence.

Results   A total of 1124 individuals (mean [SD] age at survey completion, 34.9 [1.4] years; 614 women [54.6%]; 1054 non-Hispanic Black [93.8%]; 69 Hispanic [6.2%]; 1 non-Hispanic White [<0.1%]) were included in the study, of whom 740 were in the CPC cohort and 384 were in the comparison cohort. After adjustment for baseline attributes and attrition, compared with no CPC preschool, CPC preschool was associated with significantly higher mean (SD) I-SES scores (5.93 vs 5.53; mean difference, 0.40; 95% CI, 0.16-0.65; standardized mean difference = 0.22). Compared with CPC participation for 0 to 3 years, CPC participation for 4 to 6 years showed a similar pattern of positive associations (adjusted mean I-SES score, 5.97 vs 5.69; mean difference, 0.28; 95% CI, 0.06-0.50; P  = .01; SMD = 0.15). CPC participation had a larger-magnitude association with I-SES in married vs single-parent households. Years of education partially mediated the association of CPC with I-SES (up to 41%), especially among those growing up in the highest-poverty neighborhoods.

Conclusions and Relevance   This cohort study found that early childhood programming is associated with SDH in adulthood. These findings reinforce the importance of early childhood education in addressing health disparities and contributing to healthier, more equitable communities and suggest that educational attainment is a key mechanism for health promotion.

Among early life experiences, participation in high-quality early childhood programs (ECP) is associated with a wide range of adult outcomes that include greater economic well-being, better cardiovascular and mental health, and reduced involvement in the criminal justice system. 1 , 2 Due to the breadth of outcomes affected and the major role of educational success in creating cumulative advantages over time, 1 , 3 ECPs that engage families intensively at multiple ecological levels may have carryover benefits to community-level social determinants of health (SDH). 4 Whether it is neighborhood poverty or discrimination, these environmental stressors and other sociostructural factors have pervasive influences on health and well-being across the life course. 4 Living in economically disadvantaged areas can limit access to essential resources such as quality health care and safe housing. Finally, despite the detrimental role of systemic racism and discrimination in areas such as health care, housing, and employment, studies show that Black communities greatly value education and view it as an avenue to social mobility, reflecting the importance of drawing value and satisfaction from one’s education as an SDH. 5

One of the 5 overarching goals for Healthy People 2030 4 is to create social, physical, and economic environments that promote attaining the full potential for health and well-being for all. Emerging research continues to explore the fundamental contributors underlying SDH as well as the health-related sequelae of these conditions, typically delineating the underlying modifiable determinants of health and grouping them according to categories like health behaviors, economic stability, physical environment, community safety, and clinical care. 6 , 7 It is critical to adopt a holistic, upstream approach in SDH research to address risk and protective factors and behaviors, rather than disease outcomes, enabling the development of prevention and interventions to mitigate compounding health issues. Early childhood education is intertwined with SDH through its influence on educational attainment, nutrition, parental employment, and access to support services. 1 Investing in high-quality programs can have far-reaching outcomes for individuals’ health and well-being, playing a vital role in addressing health disparities and promoting overall population health, which indicates the importance of investigating the association of ECPs with composite measures of SDH.

In this study, we assess, to our knowledge, for the first time whether an evidence-based, comprehensive ECP in high-poverty neighborhoods is associated with a new SDH index at midlife based on the 5-component framework of Healthy People 2030. The SDH variables proposed for this index have strong empirical bases that associate educational attainment with social mobility, which motivated us to also assess whether educational attainment mediates this association. 2 - 5

This cohort study was approved by the University of Minnesota institutional review board. Participants provided written and oral informed consent upon survey initiation. The reporting of the study follows the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. 8

Data were analyzed from the Chicago Longitudinal Study (CLS), a prospective cohort investigation following 989 children aged 3 to 4 years attending the Child-Parent Center (CPC) preschool program between 1983 and 1985 and a comparison group of 550 children using a nonrandomized trial design. 9 , 10 The comparison group participants attended the usual early education programs primarily in randomly selected schools matched to CPC locations based on poverty and neighborhood characteristics. A subset of participants from the original cohort completed a telephone interview on health and well-being between ages 32 and 37 years, which constituted our study sample. Some participants mailed in surveys. Questions concerned education, employment, health behavior, community resources, safety, and experiences of discrimination. Previous data from participants has been collected at ages 10 years, 15 to 18 years, 18 to 24 years, and 26 to 28 years. 10 , 11 Participant sociodemographic data was collected from various sources, such as children, parents, teachers, and school administrative records. Race and ethnicity of participants were ascertained through self-report. Race and ethnicity categories included non-Hispanic Black, Hispanic, and non-Hispanic White. Race and ethnicity were included because it is an important attribute of the study sample for description, life circumstances, and influences.

The CLS design (eAppendix 1 in Supplement 1 ) is methodologically strong in that the CPC group included all children enrolled in these centers (none were excluded) and that they resided in the highest poverty-level neighborhoods. 10 , 11 Any comparison group would by necessity be more advantaged in sociostructural attributes. These attributes minimize any potential selection bias. Moreover, all comparison group participants enrolled in alternative, usual treatment services (other preschool or kindergarten programs). Continuing school-age program enrollment was a combination of family and administrative selection and choice because children who moved from CPC schools left the program by definition, but schools also varied by number of years of school-age services offered (2 years vs 3 years). Assessment of key covariates and baseline attributes showed equivalence on nearly all factors, and this finding has been confirmed in many previous reports. 10 - 13 This included achievement growth prior to enrollment in school-age services for program and comparison groups, suggesting equal performance between groups and no positive selection that would confound estimates of outcomes for program duration. 13 , 14

CPC provides comprehensive education and family support services aimed at mitigating the impacts of poverty (eAppendix 2 in Supplement 1 ). 3 , 9 Enrichment experiences emphasize engagement at family, school, and community levels. After a half-day preschool program (3 hours, 5 days per week) at ages 3 and/or 4 years in small classes with child-teacher ratios of 17:2, CPC components in kindergarten through third grade include reduced class sizes (maximum of 25 students), teacher aides for each class, health services, continued parent involvement opportunities, and enriched classroom environments for enhancing holistic well-being, including physical health. Following 1 to 2 years of half-day preschool, services extend to third grade for a total of up to 6 years. The overarching goal is to promote school success, ultimately leading to better health and well-being over the life course. Many prior studies have documented program structures, impacts, and validity of program estimates. Findings have corroborated this goal with the hypothesis that benefits carryover to SDH. 3 , 5 , 11

The Healthy People 2030 SDH framework is comprised of the following components: economic stability, neighborhood and built environment, health care access and quality, education access and quality, and social and community context. 4 It is unique among sociostructural indexes in its focus on neighborhood-level assessment, measurement of the quality of services and experiences in community settings, and assessment of racial discrimination as part of social and community context. We created an overall measure using 9 dichotomous indicators for the 5 components called the Index of Structural Equality and Support (I-SES). The survey items make the index and were completed by both CPC and comparison participants. See eAppendix 3 and eTable 1 in Supplement 1 for detailed information on variable definitions. As a positive measure of supports at midlife, scores range from 0 to 9, with higher scores meaning greater endorsement of positive environment structures at midlife.

The family risk index comprised of 8 sociodemographic indicators measured by age 3 years (eg, high school dropout or income near the federal poverty level) and its squared term were also included to assess cumulative risk. Receipt of c hild welfare services and adverse child experiences from birth to age 5 years, whether the mother attended college, neighborhood poverty status by age 3 years, single-parent family status by age 3 years (from birth records), and self-reported chronic health conditions as assessed in the age 35-year survey were also included. Models with CPC preschool included school-age participation to adjust for the influence of later intervention.

Linear regressions were analyzed with inverse probability weighting (IPW) to adjust for attrition bias and 12 covariates, including baseline family socioeconomic status and neighborhood poverty (eAppendix 4 and eAppendix 5 in Supplement 1 ). SPSS software version 29 (IBM) was used to calculate 95% CIs, with a 2-tailed P  < .05 set as the level of significance. Standardized mean differences (SMDs) of 0.20 denote practical significance. They are equivalent to a 15% to 20% change near the midpoint of the outcome distribution. CPC preschool and CPC preschool plus school-age participation were analyzed separately along with 3 subgroups: household structure (married vs single-parent status), multiple family risk status, and neighborhood poverty at preschool entry. The mediator was years of education completed by age 34 years . It was taken from administrative records (eg, National Student Clearinghouse) and supplemented with survey reports over time (eAppendix 6 in Supplement 1 ).

We also examined the distribution of scores in three categories: low (0-3), middle (4-6), and top (7-9). This reveals if group differences were similar across the full range of structural supports. SMDs were calculated at each of these levels for the model adjusted for baseline covariates and attrition.

Mediation was assessed by the difference-in-difference method (or percentage reduction). This is the mean difference in program estimates between groups without the mediator and estimates between groups with the mediator included in the model, and then divided by the unmediated program coefficient. This proportion is multiplied by 100 to denote the percentage reduction in the program group difference associated with the mediator, which is years of education completed. This approach to mediation provides conservative estimates by definition because complex indirect effects through paths of intervening mediators are not considered. However, our estimates are readily interpretable as direct contributors to understanding long-term associations. Data analysis was completed from April to June 2024.

A total of 1124 individuals (mean [SD] age at survey completion, 34.9 [1.4] years; 614 women [54.6%]; 1054 non-Hispanic Black [93.8%]; 69 Hispanic [6.2%]; 1 White [<.01%]) were included in the study, of whom 740 were in the CPC cohort and 384 were in the comparison cohort ( Table 1 ). Of all participants, 560 (49.8%) resided in low-income neighborhoods. Participants had completed a mean (SD [range]) 12.90 (2.13 [7-22]) years of education by age 34 years, with 161 (14.3%) having received a bachelor’s degree or higher. The mean (SD) I-SES score for the entire cohort was 5.77 (1.84), with 281 cases (25.0%) with a score less than or equal to 4 and 414 cases (36.8%) with a score of 7 or greater. The unadjusted mean (SD) I-SES scores for the CPC preschool and comparison groups were 5.91 (1.84) and 5.53 (1.82), respectively, with values for continuing program group following a similar pattern. Study participants growing up in high poverty neighborhoods (>40% of residents below federal poverty level) had lower mean (SD) I-SES scores than the lower poverty group (5.73 [1.87] vs 5.82 [1.80]). At midlife, however, the differential was accentuated (mean [SD] score, 5.01 [1.87] vs 6.03 [1.76]). Table 2 shows that I-SES indicators were positively associated with educational attainment (years of education), the preeminent individual-level SDH in Healthy People 2030. The total index score had a correlation of with educational attainment ( r  = 0.21). Correlations with overall life satisfaction ( r  = 0.41) and self-rated health ( r  = 0.17) followed a similar pattern. See eTable 2 in Supplement 1 for group equivalence at age 35 years for the original CLC cohort.

Table 3 shows that after adjusting for baseline characteristics including early family and social environments, compared with no CPC, CPC preschool was associated with a significantly higher mean I-SES score (5.93 vs 5.53; mean difference, 0.40; 95% CI, 0.16-0.65; P  = .03; SMD = 0.22). A similar pattern of differences was found for adjusted mean I-SES scores for CPC preschool plus school-age participation (4 to 6 years) compared with 0 to 3 years of participation (5.97 vs 5.69; mean difference, 0.28; 95% CI, 0.06-0.50; P  = .01; SMD = 0.15).

The eFigure in Supplement 1 shows the pattern of adjusted program group differences (SMDs) at low, middle, and top categories of the I-SES distribution. For the total sample, X participants (12.4%) were in the low category, X (50.8%) in the middle category, and X (37.X%) in the top category. For the CPC preschool vs none contrast, program participants were more likely to be in the top group of I-SES scores of 7 to 9 of 9 points (SMD = 0.25). They were less likely to be in the lower 2 groups (CPC preschool, SMD  = −0.12; no CPC, SMD = −0.23). The pattern was similar for the dosage groups (4-6 years vs 0-3 years). When separated by neighborhood poverty status at the time of program participation, children in CPC growing up in relatively lower poverty settings (<40% of residents below poverty) experienced the largest benefits in I-SES. For the top score group, SMDs were 0.33 and 0.25, respectively, for CPC preschool vs none and higher vs lower dosage groups (eFigure in Supplement 1 ).

Subgroup findings overall showed similar associations across groups, but there were larger-magnitude associations among more advantaged groups. One significant subgroup interaction was identified. CPC preschool was had a larger-magnitude association with I-SES in married households (adjusted mean score, 6.36 vs 5.42; mean difference, 0.94; 95% CI, 0.46 to 1.44; P  < .001; SMD = 0.51) than in single-parent households (adjusted mean score, 5.65 vs 5.56; mean difference, 0.09; 95% CI, −0.06 to 0.62; P  = .67; SMD = 0.05). This pattern was also found for the dosage groups of 4 to 6 years vs fewer years ( Table 3 ). Similarly, the lower neighborhood poverty group had significantly higher adjusted mean I-SES scores, including both the preschool vs comparison contrast (6.07 vs 5.58; mean difference, 0.49; 95% CI, 0.14 to 0.84; P  = .02; SMD = 0.27) and preschool plus school age vs comparison contrast (6.07 vs 5.73; mean difference, 0.34; 95% CI, 0.03 to 0.65; P  = 0.1; SMD = 0.18). The lone comparison favoring higher risk groups was for family risk status, which was found in both the preschool vs comparison contrast (adjusted mean I-SES score, 5.91 vs 5.47; mean difference, 0.44; 95% CI, 0.13 to 0.71; SMD = 0.24) and preschool plus school age vs comparison contrast (adjusted mean I-SES score, 5.90 vs 5.65; mean difference, 0.25; 95% CI, −0.06 to 0.76; P  = X.X; SMD = 0.14). No differences for the full program groups were detected ( Table 3 ).

Alternative estimates support robustness (eAppendix 7 and eTable 3 in Supplement 1 ). Estimated program outcomes were similar between IPW and non-IPW models, suggesting that attrition occurred at random and was not associated with baseline characteristics (eAppendix 6 in Supplement 1 ).

For the mediation results for the total sample, years of education accounted for 16% to 18% of the association of CPC with I-SES. Mediation increased with economic disadvantage. Among those growing up in the highest poverty neighborhoods, 31% to 41% of the association was mediated by years of education ( Table 3 ). These values are above and beyond the influence of baseline characteristics and program participation. These results reflect only the direct association with educational attainment. More complex associations are possible. Robustness testing using different model specifications did not alter the pattern of findings and was consistent with results reported here (eTable 3 in Supplement 1 ).

The findings of this cohort study provide evidence suggesting that a multilevel, comprehensive-service ECP is associated with SDH in adulthood. To our knowledge, this is the first study to find such an association. Findings also document that this new index measure of SDH comprised of impactful neighborhood indicators can discriminate between the early life experiences of children who do or do not participate in intensive educational enrichment. The findings also establish that the benefits of ECPs extend beyond individual-level education and occupational success to the broader sociostructural environment. Although in general CPC participation had similar positive associations with I-SES across subgroups, the SMD for children growing up in married households exceeded those in single-parent households and in other subgroups by a factor of 2 or higher. This finding suggests that economic and family resources available in the early years of life create cumulative advantages that are unlikely to be overcome by social intervention alone, even comprehensive programs like CPC. Concerted efforts at multiple levels over extended periods of time, however, can improve well-being.

The finding that educational attainment, a leading individual-level SDH, accounted for a sizable share of observed differences for the most economically disadvantaged groups suggests that educational success is one mechanism for reducing disparities in supportive social environments. This finding is consistent with a large body of research demonstrating that ECPs have compensatory and protective effects for children and families growing up in the most economically disadvantaged communities. 1 , 2 , 9 However, only programs high in quality have these benefits, and the barriers to such quality have increased in recent years.

Nevertheless, the developmental origins of educational attainment are complex and involve socioeconomic position, home and school environments, motivational and socioemotional influences, and achievement behaviors. 3 , 11 , 15 Investigation of these and related influences were beyond the scope of the present study. Previous findings in the CLS and related studies show that the cumulative advantages initiated by ECPs are complex and circuitous, including individual and personal, family, school, and community processes. 3 , 11 The early cognitive and scholastic advantages of CPC, for example, carryover to strengthened parental involvement in school, enrollment in higher quality schools, avoidance of delinquent behaviors, and ultimately higher educational attainment. 3 , 11 This process and others warrant further investigation and confirmation, especially in comprehensive frameworks such as the 5-Hypothesis Model. 3

This study has limitations. The main limitation is that our SDH measure, although broad and based on a well-documented framework, may not fully represent community and structural influences. Moreover, results are correlational and warrant replication.

This cohort study found that ECP was associated with SDH in adulthood. These findings suggest that CPC and similar programs can contribute to broader efforts to mitigate health disparities and create healthier, more equitable communities. Educational attainment appears to be a key transmitter of observed benefits, which reinforces its importance as a major goal of ECPs.

Accepted for Publication: July 11, 2024.

Published: August 30, 2024. doi:10.1001/jamanetworkopen.2024.32050

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Morency MM et al. JAMA Network Open .

Corresponding Author: Arthur J. Reynolds, PhD, Human Capital Research Collaborative, University of Minnesota, 51 E River Rd, Minneapolis, MN 55455 ( [email protected] ).

Author Contributions: Ms Morency and Dr Reynolds had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Reynolds, Morency, Loveman-Brown, Kritzik.

Acquisition, analysis, or interpretation of data: Reynolds, Morency, Loveman-Brown, Ou.

Drafting of the manuscript: Reynolds, Morency, Loveman-Brown, Kritzik.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Reynolds, Morency, Ou.

Obtained funding: Reynolds.

Administrative, technical, or material support: Reynolds, Ou.

Supervision: Reynolds, Ou.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by the National Institute of Child Health and Human Development (grant No. HD034294) and the Bill & Melinda Gates Foundation of Education (grant No OPP1173152).

Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We thank the Chicago Public School District and participating schools for cooperation in data collection and collaboration in this study. Finally, we are especially grateful to the children and families who have participated over many years and have been supremely generous with their time and input about their lives and for providing so many valuable insights.

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• FIRE: Forum of International Research in Education This open access, peer reviewed journal promotes "interdisciplinary scholarship on the use of internationally comparative data for evidence-based and innovative change in educational systems, schools, and classrooms worldwide."
• Frontline Learning Research An official journal of EARLI, European Association for Research on Learning and Instruction. Open Access.
• Future of Children Articles on policy topics relevant to children and youth. An open access journal from the Woodrow Wilson School of Public and International Affairs at Princeton University and the Brookings Institution.
• Harvard Educational Review "a scholarly journal of opinion and research in education. It provides an interdisciplinary forum for discussion and debate about the field's most vital issues."
• High School Journal "The High School Journal publishes research, scholarship, essays, and reviews that critically examine the broad and complex field of secondary education."
• IDEA Papers A national forum for the publication of peer-reviewed articles pertaining to the general areas of teaching and learning, faculty evaluation, curriculum design, assessment, and administration in higher education.
• Impact: A Journal of Community and Cultural Inquiry in Education A peer-reviewed, open-access journal devoted to the examination and analysis of education in a variety of local, regional, national, and transnational contexts.
• Instructional Science "Instructional Science promotes a deeper understanding of the nature, theory, and practice of the instructional process and resultant learning. Published papers represent a variety of perspectives from the learning sciences and cover learning by people of all ages, in all areas of the curriculum, and in informal and formal learning contexts." Peer reviewed.
• Interdisciplinary Journal of Problem-based Learning - IJPBL This open access, peer reviewed journal "publishes relevant, interesting, and challenging articles of research, analysis, or promising practice related to all aspects of implementing problem-based learning (PBL) in K–12 and post-secondary classrooms."
• International Journal of Computer-Supported Collaborative Learning An Official Publication of the International Society of the Learning Sciences
• International Journal of Educational Leadership Preparation - IJELP An open access journal from the National Council of Professors of Educational Administration. Articles undergo a double-blind peer review process.
• Internet and Higher Education Publishes peer reviewed articles "devoted to addressing contemporary issues and future developments related to online learning, teaching, and administration on the Internet in post-secondary settings."
• Journal for Research in Mathematics Education An official journal of the National Council of Teachers of Mathematics (NCTM), JRME publishes peer reviewed research articles and literature reviews, as well as commentaries and book reviews. Concerned with mathematics education at both the K-12 and college level.
• Journal of Applied Research on Children - JARC Published by the CHILDREN AT RISK Institute, this open access. peer reviewed journal publishes "interdisciplinary research that is linked to practical, evidenced-based policy solutions for children’s issues."
• Journal of Computer Assisted Learning JCAL "is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange."
• Journal of Education A scholarly peer-reviewed journal focusing on K-12 education. This long-standing journal is sponsored by the Boston University School of Education.
• Journal of Educational Psychology This blind peer reviewed journal from the American Psychological Association publishes "original, primary psychological research pertaining to education across all ages and educational levels," as well as "exceptionally important theoretical and review articles that are pertinent to educational psychology."
• Journal of Educational Research "publishes manuscripts that describe or synthesize research of direct relevance to educational practice in elementary and secondary schools, pre-K–12."
• Journal of Interactive Media in Education - JIME This long-standing peer reviewed open access journal publishes research on the theories, practices and experiences in the field of educational technology.
• Journal of Research in Science Teaching - JRST This blind peer reviewed journal is the official journal of NARST: A Worldwide Organization for Improving Science Teaching and Learning Through Research, which "publishes reports for science education researchers and practitioners on issues of science teaching and learning and science education policy."
• Journal of Teacher Education The flagship journal of the American Association of Colleges for Teacher Education (AACTE) publishes peer reviewed articles on teacher education and continued support for teachers.
• Journal of the Learning Sciences "JLS provides a multidisciplinary forum for research on education and learning as theoretical and design sciences." This official journal of the International Society of the Learning Sciences uses a double blind review process.
• Journal of Vocational Behavior "The Journal of Vocational Behavior publishes empirical and theoretical articles that expand knowledge of vocational behavior and career development across the life span. " Peer reviewed.
• Learning and Instruction This peer reviewed journal from the European Association for Research on Learning and Instruction (EARLI) publishes "advanced scientific research in the areas of learning, development, instruction and teaching."
• Mentoring & Tutoring: Partnership in Learning - National Council of Professors of Educational Administration (NCPEA) Publishes "papers on all aspects of mentoring, tutoring and partnership in education, other academic disciplines and the professions."
• Michigan Journal of Community Service Learning MJCSL is an open-access journal focusing on research, theory, pedagogy, and other matters related to academic service-learning, campus-community partnerships, and engaged/public scholarship in higher education. Published by the University of Michigan. All articles are free online --don't worry about the "Buy a copy" messages.
• Michigan Reading Journal Open access journal from the Michigan Reading Association.
• NACADA Journal - National Academic Advising Association "The NACADA Journal is the biannual refereed journal of the National Academic Advising Association. It exists to advance scholarly discourse about the research, theory and practice of academic advising in higher education."
• Numeracy Published by the National Numeracy Network, this open access and peer reviewed journal "supports education at all levels that integrates quantitative skills across disciplines."
• Policy and Society A highly ranked open access journal that publishes peer-reviewed research on critical issues in policy theory and practice at the local, national and international levels. Includes articles on Education policy.
• Reading Research Quarterly RRQ publishes peer reviewed scholarship on literacy, including original research, theoretical and methodological essays, review articles, scholarly analysis of trends and issues, as well as reports and viewpoints. Published by the International Literacy Association.
• Review of Educational Research RER "publishes critical, integrative reviews of research literature bearing on education." A blind peer reviewed journal from the American Educational Research Association.
• Review of Higher Education Published by the Association for the Study of Higher Education this journal provides peer-reviewed research studies, scholarly essays, and theoretically-driven reviews on higher education issues.
• Review of Research in Education RRE "provides an annual overview and descriptive analysis of selected topics of relevant research literature through critical and synthesizing essays."
• Science Education "Science Education publishes original articles on the latest issues and trends occurring internationally in science curriculum, instruction, learning, policy and preparation of science teachers with the aim to advance our knowledge of science education theory and practice."
• Scientific Studies of Reading The official Journal of the Society for the Scientific Study of Reading "publishes original empirical investigations dealing with all aspects of reading and its related areas, and occasionally, scholarly reviews of the literature and papers focused on theory development. " Uses blind peer review.
• Sociology of Education "SOE publishes research that examines how social institutions and individuals' experiences within these institutions affect educational processes and social development." A blind peer reviewed journal from the American Sociological Association.
• Studies in Science Education This blind peer reviewed journal publishes review articles that offer "analytical syntheses of research into key topics and issues in science education."
• Teachers College Record "The Teachers College Record is a journal of research, analysis, and commentary in the field of education. It has been published continuously since 1900 by Teachers College, Columbia University."
• Theory into Practice "TIP publishes articles covering all levels and areas of education, including learning and teaching; assessment; educational psychology; teacher education and professional development; classroom management; counseling; administration and supervision; curriculum; policy; and technology." Peer reviewed.
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Education Librarian

• Last Updated: Aug 30, 2024 10:51 AM
• URL: https://guides.emich.edu/early

Journal article

Is the availability and quality of local early childhood education and care services associated with young children's mental health at school entry?

Amanda Alderton, Lucy Gunn, Karen Villanueva, Meredith O'Connor, Claire Boulangé, Hannah Badland

Health Place | Published : 2024

DOI: 10.1016/j.healthplace.2024.103327

PURPOSE: This study investigated the relationship between geographic availability (and quality) of local early childhood education and care services and children's early mental health outcomes for all children entering their first year of full-time school in Melbourne, Australia. METHODS: We capitalise on a unique population linked dataset, the Australian Early Development Census - Built Environment, which combines geospatial measures of children's neighbourhoods with demographic information and child mental health outcomes for all school entrants in Australia's 21 most populous cities and towns. Objective early childhood education and care service location and quality exposures were develop..

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