The influences of child, family, and socioeconomic factors on children's early academic development are best understood within the context of one another. Yet, most existing studies have focused primarily on either family- or child-level factors, such as parental influences or child executive functions, in explaining socioeconomic inequalities in children's academic achievement. In an attempt to integrate these two lines of research, the current investigation simultaneously examined the specific contextual and cognitive pathways that underlie associations between socioeconomic factors and children's early academic achievement using data from a prospective longitudinal study conducted at 10 sites across the United States (N = 1,364). Findings revealed that after controlling for a host of potentially confounding influences, parent education, but not family income-to-needs, was linked to children's math achievement indirectly via sequential paths that included both parenting factors-maternal sensitivity and cognitive stimulation-and children's working memory skills. Likewise, parent education was predictive of children's reading achievement indirectly via paths that included cognitive stimulation and working memory. Finally, independent of child executive functions, parent education was also indirectly related to children's reading achievement via cognitive stimulation and to children's math achievement via maternal sensitivity. Together, these findings shed light on the specific contextual and cognitive mechanisms that underlie socioeconomic-related differences in children's early academic skills and provide potential insights for policies and interventions aimed at closing the achievement gap.

Over the past decade, there has been a growing appreciation of metascience issues in psychological science. Using data collected from 2615 posters presented at the 2021 biennial meeting of the Society for Research in Child Development, this article examines the use of transparent research practices to increase rigor and reproducibility as well as generalizability through greater inclusivity of diverse samples. Research presented through poster presentations was heavily skewed toward quantitative studies featuring American researchers using Western hemisphere samples. Sharing of data/materials, preregistrations, and replications were uncommon. During a time when governments are increasingly requiring more open practices and access, this research provides an important baseline by which developmental science can benchmark progress toward the goals of greater inclusivity and openness.

The relation between mathematical achievement in early childhood and future academic success is well established. However, our knowledge about the effect of instruction on mathematical performance is often reliant upon self-report or videotaped instruction measures and standardized achievement assessments.The current study uses teacher audio recordings to examine the role of classroom mathematics instruction in the growth of adaptive early mathematical skills.Kindergarten children (N = 98, M(age) = 5.55 years, 53% male) were followed across the school year.Findings suggested children with the lowest levels of adaptive mathematics skills grew the most across the school year, suggesting that basic skills continue to be the focus in early elementary years. Further, no aspects of mathematics instruction predicted growth in children's addition or counting skills.These results highlight the need for more robust and ecologically valid measurement in assessing classroom mathematics instruction in future research.

Importance Child physical and emotional abuse and neglect may affect epigenetic signatures of accelerated aging several years after the exposure. Objective To examine the longitudinal outcomes of early-childhood and midchildhood exposures to maltreatment on later childhood and adolescent profiles of epigenetic accelerated aging. Design, Setting, and Participants This cohort study used data from the Future of Families and Child Wellbeing Study (enrolled 1998-2000), a US birth cohort study with available DNA methylation (DNAm) data at ages 9 and 15 years (assayed between 2017 and 2020) and phenotypic data at birth (wave 1), and ages 3 (wave 3), 5 (wave 4), 9 (wave 5), and 15 (wave 6) years. Data were analyzed between June 18 and December 10, 2023. Exposures Emotional aggression, physical assault, emotional neglect, and physical neglect via the Parent-Child Conflict Tactics Scale at ages 3 and 5 years. Main Outcomes and Measures Epigenetic accelerated aging (DNAmAA) was measured using 3 machine learning-derived surrogates of aging (GrimAge, PhenoAge, and DunedinPACE) and 2 machine learning-derived surrogates of age (Horvath and PedBE), residualized for age in months. Results A total of 1971 children (992 [50.3%] male) representative of births in large US cities between 1998 and 2000 were included. Physical assault at age 3 years was positively associated with DNAmAA for PhenoAge (beta = 0.073; 95% CI, 0.019-0.127), and emotional aggression at age 3 years was negatively associated with PhenoAge DNAmAA (beta = -0.107; 95% CI, -0.162 to -0.052). Emotional neglect at age 5 years was positively associated with PhenoAge DNAmAA (beta = 0.051; 95% CI, 0.006-0.097). Cumulative exposure to physical assault between ages 3 and 5 years was positively associated with PhenoAge DNAmAA (beta = 0.063; 95% CI, 0.003-0.123); emotional aggression was negatively associated with PhenoAge DNAmAA (beta = -0.104; 95% CI, -0.165 to -0.043). The association of these measures with age 15 years PhenoAge DNAmAA was almost fully mediated by age 9 years PhenoAge DNAm age acceleration. Similar patterns were found for GrimAge, DunedinPACE, and PhenoAge, but only those for PhenoAge remained after adjustments for multiple comparisons. Conclusions and Relevance In this cohort study, altered patterns of DNAmAA were sensitive to the type and timing of child maltreatment exposure and appeared to be associated with more proximate biological embedding of stress.

Children in low- and middle-income countries (LMICs) are disproportionately at risk of not meeting their developmental potential. Parental discipline can promote and hinder child outcomes; however, little research examines how discipline interacts with contextual factors to predict child outcomes in LMICs. Using data from 208,156 households with children between 36 and 59 months (50.5% male) across 63 countries, this study examined whether interactions between gender inequality and discipline (shouting, spanking, beating, and verbal reasoning) predicted child aggression. Results showed aggression was higher in countries with high gender inequality, and associations between discipline and child aggression were weaker in countries where gender inequality was higher. Improvements in country-level gender parity, in addition to parenting, will be necessary to promote positive child outcomes in LMICs.

A common challenge in developmental research is the amount of incomplete and missing data that occurs from respondents failing to complete tasks or questionnaires, as well as from disengaging from the study (i.e., attrition). This missingness can lead to biases in parameter estimates and, hence, in the interpretation of findings. These biases can be addressed through statistical techniques that adjust for missing data, such as multiple imputation. Although this technique is highly effective, it has not been widely adopted by developmental scientists given barriers such as lack of training or misconceptions about imputation methods and instead utilizing default methods within software like listwise deletion. This manuscript is intended to provide practical guidelines for developmental researchers to follow when examining their data for missingness, making decisions about how to handle that missingness, and reporting the extent of missing data biases and specific multiple imputation procedures in publications.

Adolescence, the second decade of life, bridges childhood and adulthood, but also represents a host of unique experiences that impact health and well-being. Lifespan theories often emphasize the continuity of individual characteristics and their contexts from childhood to adolescence, underscoring the distal influence of childhood experiences. Yet, adolescence is marked by transitions that may provoke discontinuities, particularly within individuals, their contexts, and their interactions within those contexts. These discontinuities occur at varied times, orders, and intensities for individual youth, suggesting that adolescence may be a developmental turning point where earlier life experiences may be mediated, reversed, or transformed by proximal events. This perspective piece emphasizes the importance of considering transitions, discontinuities, and developmental turning points in adolescence as well as their potential to explain heterogeneity in adolescent and adult outcomes. We explore one biological and one contextual transition in adolescence and highlight innovative theories and methods for investigating continuity and discontinuity dynamics across development, which could lead to new insights related to the adolescent period and its importance in shaping future life trajectories.

Child physical and emotional abuse and neglect may affect epigenetic signatures of accelerated aging several years after the exposure. To examine the longitudinal outcomes of early-childhood and midchildhood exposures to maltreatment on later childhood and adolescent profiles of epigenetic accelerated aging. This cohort study used data from the Future of Families and Child Wellbeing Study (enrolled 1998-2000), a US birth cohort study with available DNA methylation (DNAm) data at ages 9 and 15 years (assayed between 2017 and 2020) and phenotypic data at birth (wave 1), and ages 3 (wave 3), 5 (wave 4), 9 (wave 5), and 15 (wave 6) years. Data were analyzed between June 18 and December 10, 2023. Emotional aggression, physical assault, emotional neglect, and physical neglect via the Parent-Child Conflict Tactics Scale at ages 3 and 5 years. Epigenetic accelerated aging (DNAmAA) was measured using 3 machine learning–derived surrogates of aging (GrimAge, PhenoAge, and DunedinPACE) and 2 machine learning–derived surrogates of age (Horvath and PedBE), residualized for age in months. A total of 1971 children (992 [50.3%] male) representative of births in large US cities between 1998 and 2000 were included. Physical assault at age 3 years was positively associated with DNAmAA for PhenoAge (β = 0.073; 95% CI, 0.019-0.127), and emotional aggression at age 3 years was negatively associated with PhenoAge DNAmAA (β = −0.107; 95% CI, −0.162 to −0.052). Emotional neglect at age 5 years was positively associated with PhenoAge DNAmAA (β = 0.051; 95% CI, 0.006-0.097). Cumulative exposure to physical assault between ages 3 and 5 years was positively associated with PhenoAge DNAmAA (β = 0.063; 95% CI, 0.003-0.123); emotional aggression was negatively associated with PhenoAge DNAmAA (β = −0.104; 95% CI, −0.165 to −0.043). The association of these measures with age 15 years PhenoAge DNAmAA was almost fully mediated by age 9 years PhenoAge DNAm age acceleration. Similar patterns were found for GrimAge, DunedinPACE, and PhenoAge, but only those for PhenoAge remained after adjustments for multiple comparisons. In this cohort study, altered patterns of DNAmAA were sensitive to the type and timing of child maltreatment exposure and appeared to be associated with more proximate biological embedding of stress.

Objective: This study examined the longitudinal trajectories of economic hardship for low-income families with a college education.Background: The relation between parental education and family income to parenting behaviors and children's achievement is well documented. Less is known on how high education and low income interact within families, particularly over time.Method: The sample consisted of 537 families who were low-income and college-educated when their child was in kindergarten. We used latent growth curve analyses to classify families into different trajectory classes based on economic hardship over several years. We then examined predictors and outcomes of each class.Results: Within this sample of low-income, college-educated families, there were two economic hardship trajectories: Transient (i.e., short-term) and Chronic (i.e., long term). Parents in the transient class were more likely to work an occupation requiring a postsecondary degree and had higher educational expectations than the chronic class. We conducted additional analyses to test for generalizability and comparison to other family types.Conclusion: Parental education attainment may provide a protective buffer for parents and children when facing short- or long-term economic hardship.Implications: This study highlights the sustained importance of educational attainment and the need for policy and program solutions to address families' diverse needs.

Events of the past decade have revealed substantial limitations in our standard approach to evaluating manuscripts for publication. Preference for 'positive results' and findings that are surprising or novel has led to a substantial publication bias that casts doubt on large portions of the existing literature (Davis-Kean & Ellis, 2019; Scheel et al., 2021). Registered Reports represent a major initiative to combat these problems, as they shift the focus of evaluation from the nature of the findings to the strength of the conceptualization, research design and analytic plan (Chambers, 2013). Contrary to the standard review process, with Registered Reports the process is split into two distinct stages. Authors initially submit a Stage 1 proposal consisting of the Introduction, Method and Planned Analysis sections prior to conducting the study. The Stage 1 proposal is sent for peer review, with an ultimate positive outcome of an 'in principle acceptance,' which is a guarantee that the journal will publish the full article, regardless of the results, providing the authors conduct the study as planned and do so competently. Following the in principle acceptance authors collect the data and/or conduct the analysis and then submit the Stage 2 report for final review. For more information, and answers to frequently asked questions about Registered Reports, see https://cos.io/rr/. Registered Reports have been increasingly adopted in journals across the sciences in general, and psychology in particular. Although uptake had initially been slow amongst developmental journals, this has changed considerably in recent years (see Syed et al., 2023, for Registered Reports specifically and Silverstein et al., 2024, for open science and metascience more generally). Nevertheless, there remain many questions about how the format works for complex longitudinal designs and secondary data (van den Akker et al., 2021), both of which are common in developmental research (see also Syed & Donnellan, 2020). The purpose of this Special Issue was to feature Registered Reports using secondary (pre-existing) data pertaining to developmental issues from the prenatal period through early adulthood. Secondary datasets refer to data collected by someone other than the primary user. Datasets used in the eight articles featured in the special issue covered wide ground. Two of the articles relied on the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development, one to investigate how early caregiver interactions are related to educational attainment, income and employment (Duncan et al., 2024), and the other to compare relations between parental sensitivity and two different methods for assessing attachment (Nivison et al., 2024). Examining parenting from a different perspective, Wright and Jackson (2024) drew from the German Socioeconomic Panel study to test the independent predictive power of parent and child personality traits on a variety of adolescent outcomes (e.g., health, education, family and civic engagement). Several studies focused on the schooling context: Spiegler et al. (2024) used the Children of Immigrants Longitudinal Survey in Four European Countries to examine how peer victimisation was related to classroom ethnic diversity and teacher interactions; Kim and Sidney (2024) used the Trends in International Mathematics and Science Study to examine sources of influences for individual differences in students' academic self-concept; and Zimmermann et al. (2024) used the Early Childhood Longitudinal Study Kindergarten class of 2011 to understand how pre-Kindergarten enrollment was related to indicators of social development across the transition into and out of Kindergarten. Finally, two studies examined physiological aspects of development: Chaku and Barry (2024) used the Adolescent Brain Cognitive Development study to understand how hormonal profiles were associated with cognitive development, and Woods et al. (2024) drew from the Future of Families and Child Wellbeing Study to test whether indicators of sleep were longitudinally associated with cognitive and behavioural development. Taken together, the articles in the current Special Issue highlight both the feasibility and utility of Registered Reports with secondary developmental data. It is abundantly clear from the papers published for this special issue that Registered Reports are a viable option for those who are using existing or secondary datasets, and that they only scratch the surface of available datasets that could be put to good use with Registered Reports. Some other examples of secondary datasets include but are not limited to Monitoring the Future, Panel Study of Income Dynamics, National Longitudinal Surveys, British Cohort Studies, Growing Up in Scotland and many more (see Davis-Kean & Ellis, 2019, for a review, and Davis-Kean et al., 2015, for more details on how to access these and other datasets). All of these datasets, and many more, are potentially suitable for Registered Reports but are underused with the format. We do, however, want to highlight a few important issues that were noted during the review process. First, reviewers sometimes struggle with how to review papers that do not contain data, but only the 'proposal' of the idea and methods. For secondary data in particular, reviewers struggled with the limitation of existing data already having been collected and not being able to advise on new primary data collection. Often, as has been noted by Davis-Kean et al. (2015), there are limitations on what questions can be answered with secondary data. There is no option to add data to the existing data or change the methods of the study. Reviewers would often suggest such changes for these papers that were not possible. Thus, a recommendation for future secondary data Registered Reports is that very clear reviewer information be provided on the role of the reviewer but also the limitations of what can be requested by the reviewer to the authors. Basically, the methodology and data structure are generally already known for the study, the reviewers' job is to determine if the questions are of interest to the field of study and if the methods and the data set being used are suitable to answer the questions being asked. A challenge that exists in the interaction between the reviewers and authors, evident for both preregistrations and Registered Reports, is the frequent need for robustness checks that may not have been previously registered, but are important for validating the findings. These are often seen as exploratory analyses but often are reasonable requests for checking the validity of a finding when a reviewer notes an alternative hypothesis that is both plausible and testable in the data set. Unlike primary data collection which may be restricted in the breadth of variables available to do the robustness check, secondary data will often have the available constructs that could be tested. We recommend authors and reviewers think through the addition of alternative specifications or hypotheses that could be tested with the existing data at the Stage 1 proposal phase. Sometimes, however, such realisations occur after the fact and thus must be added as exploratory analyses to the Stage 2 manuscript. Authors are encouraged to do this, and editors and reviewers are encouraged to facilitate it, so long as the additions are transparently reported, as we always want to be sure we are conducting the most rigorous tests in our studies. Finally, on the initial submission for review for this special issue, it was sometimes the case that the actual questions being submitted were not major questions of the field, or could not adequately be tested with the proposed dataset. Any analysis of secondary data could be done, but it is important for us to all consider whether it should be done. One of the primary goals of Registered Reports is to ensure that a study is informative of its research questions regardless of the results. This design feature demands high-quality studies and is particularly well-suited for the most complex, controversial and transformative research because it provides the clearest constraints on the questionable research practices and publication bias that often plague developmental research (Davis-Kean & Ellis, 2019). Elevating this format to being one where having authorship on a Registered Report denotes that extreme care and careful planning were done to obtain the finding will help to increase the confidence in the research that is done on infant and child development.

This study is a conceptual replication of a widely cited study by Moffitt et al. (2011) which found that attention and behavior problems in childhood (a composite of impulsive hyperactive, inattentive, and impulsive-aggressive behaviors labeled "self-control") predicted adult financial status, health, and criminal activity. Using data from longitudinal cohort studies in the United States (n = 1,168) and the United Kingdom (n = 16,506), we largely reproduced their pattern of findings that attention and behavior problems measured across the course of childhood predicted a range of adult outcomes including educational attainment (βU.S. = -0.22, βU.K. = -0.13) and spending time in jail (ORU.S. = 1.74, ORU.K. = 1.48). We found that associations with outcomes in education, work, and finances diminished in the presence of additional covariates for children's home environment and achievement but associations for other outcomes were more robust. We also found that attention and behavior problems across distinct periods of childhood were associated with adult outcomes. Specific attention and behavior problems showed some differences in predicting outcomes in the U.S. cohort, with attention problems predicting lower educational attainment and hyperactivity/impulsivity predicting ever spending time in jail. Together with the findings from Moffitt et al., our study makes clear that childhood attention and behavior problems are associated with a range of outcomes in adulthood for cohorts born in the 1950s, 1970s, and 1990s across three countries. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Over the past decade, there has been a growing appreciation of issues around metascience—how research is conducted—in psychological science. In addition to enhancing rigor and reproducibility through open and transparent research practices, greater inclusivity through diverse samples can enhance research relevance and applicability for historically marginalized and understudied populations. The present study reports on a comprehensive analysis of 2,615 posters presented at the 2021 biennial meeting of the Society for Research in Child Development. Results revealed that research that was presented is heavily skewed towards quantitative studies featuring American researchers and Western hemisphere samples. Sharing of data/materials, preregistrations, and replications are extremely uncommon. Data provide a much-needed baseline by which developmental science can benchmark progress towards greater inclusivity and openness.

This study investigated the content of parenting information shared on social media by identifying the range and frequency of topics shared by parenting-focused accounts on Twitter. Using the Twitter API, a universe of 675,069 tweets were gathered from 74 of the most-followed parenting-focused accounts, or ‘hubs’, from January 2016 to June 2018. Using a custom, semi-automated topic modeling approach, we identified the topics – and subtopics within topics – parenting hubs shared with their followers and investigated whether any meaningful differences in topical focus existed between accounts targeting mothers versus fathers. Results indicate that over one third of tweets were about Parenting Behavior and nearly one quarter about Health, with Entertainment, School and Motherhood and Fatherhood generally as less tweeted topics. Mother-focused accounts tweeted more about Health than father-focused accounts, which tweeted more than others about Entertainment. Implications for future parenting and social media research are discussed.

We leveraged nationally representative data from the Panel Study of Income Dynamics-Child Development Supplement (N = 3,562) and the Early Childhood Longitudinal Study (N = 18,174), to chart the development of working memory, indexed via verbal forward and backward digit span task performance, from 3 to 19 years of age. Results revealed non-linear growth patterns for forward and backward digit span tasks, with the most rapid growth occurring during childhood followed by a brief accelerated period of growth during early adolescence. We also found similar developmental trajectories on digit span task performance for males and females across the U.S. population. Together, this study highlights the relative importance of the childhood period for working memory development and provides researchers with a reference against which to compare the developmental changes of working memory in individual studies. From a practical perspective, clinicians and educators can also use this information to understand important periods of working memory growth using national developmental trends.

Using data from 12 studies, we meta-analyze correlations between parent number talk during interactions with their young children (mean sample age ranging from 22 to 79 months) and two aspects of family socioeconomics, parent education, and family income. Potential variations in correlation sizes as a function of study characteristics were explored. Statistically significant positive correlations were found between the amount of number talk in parent-child interactions and both parent education and family income (i.e., r = 0.12 for education and 0.14 for income). Exploratory moderator analyses provided some preliminary evidence that child age, as well as the average level of and variability in socioeconomic status, may moderate effect sizes. The implications of these findings are discussed with special attention to interpreting the practical importance of the effect sizes in light of family strengths and debate surrounding "word gaps".

Using data from the Applied Problems subtest of the Woodcock-Johnson Tests of Achievement (Woodcock & Johnson, 1989/1990, Woodcock-Johnson psycho-educational battery-revised. Allen, TX: DLM Teaching Resources) administered to 1,364 children from the National Institute of Child Health and Human Development (NICHD) Study of Early Childcare and Youth Development (SECCYD), this study measures children's mastery of three numeric competencies (counting, concrete representational arithmetic and abstract arithmetic operations) at 54 months of age. We find that, even after controlling for key demographic characteristics, the numeric competency that children master prior to school entry relates to important educational transitions in secondary and post-secondary education. Those children who showed low numeric competency prior to school entry enrolled in lower math track classes in high school and were less likely to enrol in college. Important numeracy competency differences at age 54 months related to socioeconomic inequalities were also found. These findings suggest that important indicators of long-term schooling success (i.e., advanced math courses, college enrollment) are evident prior to schooling based on the levels of numeracy mastery.

Researchers using social media data want to understand the discussions occurring in and about their respective fields. These domain experts often turn to topic models to help them see the entire landscape of the conversation, but unsupervised topic models often produce topic sets that miss topics experts expect or want to see. To solve this problem, we propose Guided Topic-Noise Model (GTM), a semi-supervised topic model designed with large domain-specific social media data sets in mind. The input to GTM is a set of topics that are of interest to the user and a small number of words or phrases that belong to those topics. These seed topics are used to guide the topic generation process, and can be augmented interactively, expanding the seed word list as the model provides new relevant words for different topics. GTM uses a novel initialization and a new sampling algorithm called Generalized Polya Urn (GPU) seed word sampling to produce a topic set that includes expanded seed topics, as well as new unsupervised topics. We demonstrate the robustness of GTM on open-ended responses from a public opinion survey and four domain-specific Twitter data sets.

Developmental cascades describe how systems of development interact and influence one another to shape human development across the lifespan. Despite its popularity, developmental cascades are commonly used to understand the developmental course of psychopathology, typically in the context of risk and resilience. Whether this framework can be useful for studying children's educational outcomes remains underexplored. Therefore, in this chapter, we provide an overview of how developmental cascades can be used to study children's academic development, with a particular focus on the biological, cognitive, and contextual pathways to educational attainment. We also provide a summary of contemporary statistical methods and highlight existing data sets that can be used to test developmental cascade models of educational attainment from birth through adulthood. We conclude the chapter by discussing the challenges of this research and explore important future directions of using developmental cascades to understand educational attainment.

Research in developmental psychology often contains samples where education and income are highly related. This study examines characteristics of low-income families who have at least one parent with a college education and how their children’s achievement and parenting practices compare to other types of families. Using the Early Childhood Longitudinal Study ‘98, 768 families were identified as low-income and college-educated. The majority of parents were White, working, and married, with high educational expectations. Children from low-income, college-educated families scored higher on achievement tests compared to children from low-income, less-educated and high-income, less-educated families. Compared to these same two types of families, low-income, college-educated parents were more involved in school and home activities, such as taking their child to libraries. The present findings extend understanding of, and confront common stereotypes about, families living in or near poverty. Even when lacking financial resources, education may provide a protective buffer for low-income families.

Large-scale organic data generated from newspapers, social media, television, and radio require an expertise in infrastructure management, data collection, and data processing in order to gain research value from them. We have developed text analytic research portals to help social science researchers who do not have the resources necessary to collect, store, and process these large-scale data sets. Our portals allow researchers to use an intuitive point and click interface to generate variables from large, dynamic data sets using state of the art text mining and learning methods. These timely variables constructed from noisy text can then be used to advance social science research in areas such as political science, economics, public health, and psychology research.