Answering Developmental Questions Using Secondary Data

A metascience investigation of inclusive, open, and reproducible science practices in research posters at the 2021 SRCD biennial meeting

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.

Growing up amid conflict: Implications of the Developmental Peacebuilding Model

Worldwide, 420 million children are affected by conflict and over half of all children experience violence every year. Thus, youth are unarguably affected by war and settings of persisting societal violence. Despite often being conceptualized as either powerless victims or violent perpetrators, recent advances in research and international policy recognize young people as key change agents in transforming adverse settings into positive environments. Framed by the Developmental Peacebuilding Model, this paper focuses on predictors, outcomes and intervention points within the family for youth peacebuilding. Recent advances of family-based interventions in diverse, non-WEIRD samples will be highlighted. Rooted in existing knowledge, we conclude with concrete suggestions on how to use secondary data to investigate youth peacebuilding across the globe.

Using A Thin Slice Coding Approach to Assess Preschool Overweight and Obesity

Obesity is a major public health problem and cause of significant burden across the lifespan. Longitudinal samples, beginning in early childhood offer an advantageous approach to studying obesity, given the potential to observe within-individual changes over time. Yet among the many available longitudinal studies of children, particularly those studying psychological disorders, do not assess for overweight/obesity status or related constructs necessary to compute BMI. We offer a unique thin slice approach for assessing obesity/overweight status using previously collected video data. The current study observationally coded overweight/obesity status in a clinically enriched sample of preschoolers oversampled for depression (N=299). Preschoolers (ages 3-6 years) completed 1-8 structured observational tasks with an experimenter. Overweight/obesity was coded using a "thin slice" technique with 7,820 unique ratings available for analysis. Parent-reported physical health problems were assessed throughout the study and BMI percentiles were available from ages 8-19 years. Thin-slice ratings of overweight/obesity were reliably observed in preschoolers' ages 3-6 years. Thin-slice ratings of overweight/obesity during preschool significantly predicted adolescent BMI percentiles at six separate assessments spanning ages 8-19 years. Further, preschool overweight/obese thin-slice ratings were associated with more physical health problems over time and less sport/activity participation during preschool. Overweight/obesity can be observationally identified in preschool-age children and offers a reliable estimate of future BMI percentile. Study findings highlight how previously collected data could be utilized to study the developmental trajectories of overweight/obesity to inform this critical public health problem.

Determinants of comprehensive knowledge on mother-to-child transmission of HIV and its prevention among childbearing women in Rwanda: insights from the 2020 Rwandan Demographic and Health Survey

BACKGROUND

Maternal knowledge on mother-to-child transmission (MTCT) and its prevention has been identified to enhance maternal testing and adherence to antiretroviral therapy (ART) regimen. Examining prevalence and associated factors on MTCT and its prevention among women provides empirical evidence for design and implementation of health strategies aimed at increasing MTCT knowledge and its elimination. This study therefore examined women's comprehensive knowledge and associated factors on MTCT and its prevention among childbearing women in Rwanda.

METHODS

Analysis was conducted on a weighted sample of 14,634 women from the 2020 Rwanda Demographic and Health Survey (RDHS). Dataset cleaning and missing value analysis was conducted. Chi square, bivariate and multivariable regression was then conducted in complex samples in SPSS. Alpha level set at p < 0.05 and at 95% Confidence Interval (95% CI). All analysis were adjusted for unequal probability sampling using survey weights. Bivariate and multivariable results were reported with crude and adjusted odds ratios.

RESULTS

The mean age was 29.2 years, SD-9.1. Prevalence of HIV testing and comprehensive knowledge on MTCT and its prevention among women in Rwanda was 79.6% and 65.1% respectively. Findings from this study showed that married women have higher odds (aOR = 1.18, 95% CI = 1.04-1.35) of comprehensive knowledge on MTCT and its prevention compared to those unmarried. Women who were living in southern (aOR = 1.23, 95%CI = 1.02-1.48) and eastern (aOR = 1.37, 95% CI = 1.13-1.66) parts of Rwanda were more likely to have adequate knowledge on MTCT of HIV and its prevention than those in Kigali. Also, women who received post-test counselling (aOR = 1.26, 95% CI = 1.01-2.11) have increased knowledge on MTCT than those who did not. Women with access to radio (aOR = 1.18, 95% CI = 1.06-1.32) and television (aOR = 1.25, 95% CI = 1.07-1.45) at least once a week were more likely to have adequate knowledge on MTCT and its prevention compared to those who do not in Rwanda.

CONCLUSION

There is inadequate knowledge on MTCT and its elimination among women of reproductive age in Rwanda. Strategies to enhance knowledge on MTCT and its prevention among childbearing women should be adopted through rigorous educational sensitization campaigns using local media such as radio and television. Health services that focus on prevention of MTCT must emphasize post-test counselling.

The reciprocal interplay of physical activity and health‐related quality of life in children and adolescents: Evidence for both upward and downward spirals

OBJECTIVE

This study examines the bidirectional effect between physical activity (PA) and health-related quality of life in children and adolescents, focusing on within-person effects.

METHODS

PA and health-related quality of life were assessed in children and adolescents (N = 685, age: M = 10.29 years, SD = 1.35, range = 8-14), via self-report across four waves, each 6 months apart, and a random-intercept cross-lagged panel model with time-invariant cross-lagged effects was calculated.

RESULTS

Positive cross-lagged effects between prior PA and health-related quality of life 6 months later ( γ y  = 0.536, 95% CI [0.016, 1.055], p = .043, d = 0.11) and vice versa ( γ x  = 0.015, 95% CI [0.001, 0.030], p = .039, d = 0.12) were found. Furthermore, the random intercept correlation was significant ( T xy  = 3.622, 95% CI [2.204, 5.041], p < .001, d = 0.27).

CONCLUSIONS

The findings confirm known correlations between PA and health-related quality of life and extends them by indicating both an upward and downward spiral of PA and health-related quality of life in children and adolescents.

Trajectories of adolescent life satisfaction

Increasing global policy interest in measuring and improving population wellbeing has prompted academic investigations into the dynamics of lifespan life satisfaction. Yet little research has assessed the complete adolescent age range, although it harbours developmental changes that could affect wellbeing far into adulthood. This study investigates how life satisfaction develops throughout the whole of adolescence, and compares this development to that in adulthood, by applying exploratory and confirmatory latent growth curve modelling to UK and German data, respectively (37 076 participants, 10-24 years). We find a near universal decrease in life satisfaction during adolescence. This decrease is steeper than at any other point across adulthood. Further, our findings suggest that adolescent girls' life satisfaction is lower than boys', but that this difference does not extend into adulthood. The study highlights the importance of studying adolescent subjective wellbeing trajectories to inform research, policy and practice.

Trajectories of adolescent life satisfaction

Increasing global policy interest in measuring and improving population wellbeing has prompted academic investigations into the dynamics of lifespan life satisfaction. Yet little research has assessed the complete adolescent age range, although it harbours developmental changes that could affect wellbeing far into adulthood. This study investigates how life satisfaction develops throughout the whole of adolescence, and compares this development to that in adulthood, by applying exploratory and confirmatory latent growth curve modelling to UK and German data, respectively (37 076 participants, 10-24 years). We find a near universal decrease in life satisfaction during adolescence. This decrease is steeper than at any other point across adulthood. Further, our findings suggest that adolescent girls' life satisfaction is lower than boys', but that this difference does not extend into adulthood. The study highlights the importance of studying adolescent subjective wellbeing trajectories to inform research, policy and practice.

Factors Associated with HIV Testing among Reproductive Women Aged 15-49 Years in the Gambia: Analysis of the 2019-2020 Gambian Demographic and Health Survey

Voluntary counselling and testing for Human Immunodeficiency Virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS) has always been one of the key policy interventions in the management and control of HIV/AIDS transmission. However, the prevalence of HIV testing among reproductive women in the Gambia remains low despite near universal information about HIV and Sexually Transmitted Infections (STIs) in the Gambia. Understanding factors influencing HIV testing uptake provides empirical data for the development of targeted evidenced-based strategies aimed at enhancing HIV testing uptake. Therefore, this study examined the factors associated with HIV testing among reproductive women aged 15−49 years in the Gambia. Data on weighted sample of 11,865 women from the 2019−2020 Gambia Demographic and Health Survey were analyzed in this study. Chi square, bivariate and multivariate logistic regression models were fitted and analysis conducted through Complex Samples Analysis in Statistical Package for Social Sciences (SPSS). Level of significance was set at p < 0.05 and 95% CI. Further analysis was conducted to determine the variability in HIV testing among women stratified by rural and urban centers. Prevalence of HIV testing among reproductive women was 42.1% (95% CI = 40.1−44.2%) in the Gambia. Women aged 20−24 years and 25−29 years (aOR = 3.10, 95% CI = 2.51−3.83) and (aOR = 4.52, 95% CI = 3.61−5.54) were more likely to test for HIV than those aged 15−19 years, respectively. Married women (aOR = 5.90, 95% CI = 4.84−7.02) were more likely to test for HIV compared to those who were not in any union. Respondents with higher education in urban centers (aOR = 2.65, 95% CI = 2.08−3.86) were likely to test for HIV compared to those in rural areas. HIV testing in the Gambia among reproductive women is low. Age, marital status, wealth index, place of residence, educational level, recent sexual activity, previous history of risky sexual behaviors, and history of an STI were associated with HIV testing. Health interventions targeted at increasing HIV testing uptake should factor in these.

Developmental cascades and educational attainment

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.

Secondary Analysis of Existing Data Sets for Developmental Behavioral Pediatrics

ABSTRACT

Secondary analysis of existing large, national data sets is a powerful method to address many of the complex, key research questions in developmental behavioral pediatrics (DBP). Major advantages include decreasing the time needed to complete a study and reducing expenses associated with research by eliminating the need to collect primary data. It can also increase the generalizability of research and, with some data sets, provide national estimates that may form the basis for developing policy. However, few resources are available to direct researchers who seek to develop expertise in this area. This study aims to guide investigators with limited experience in this area who wish to improve their skills in performing secondary analysis of existing large data sets. This study provides direction on the steps to perform secondary analysis of existing data sets. It describes where and how data sets can be identified to answer questions of interest to DBP. Finally, it offers an overview of a number of data sets relevant to DBP.

Secondary data analysis of British population cohort studies: A practical guide for education researchers

BACKGROUND

Britain is rich in longitudinal population cohort studies that posit valuable data resources for social science. However, education researchers currently underutilize these resources.

AIMS

The current paper (1) outlines the power and benefits of secondary data analyses for educational science and (2) provides a practical guide for education researchers on the characteristics, data, and accessibility of British population cohort studies.

METHODS

We identified eight British population cohort studies from the past 40 years that collected scholastic performance data during primary and secondary schooling, including (1) Avon Longitudinal Study of Parents And Children (ALSPAC), (2) Twins Early Development Study (TEDS), (3) Effective Pre-School, Primary and Secondary Education Project (EPPSE), (4) Millennium Cohort Study (MCS), (5) Born in Bradford (BiB), (6) Next Steps (LYSPE1), (7) Understanding Society (US), and (8) Our Future (LYSPE2). Participants across these studies were born between 1989 and 2010, and followed up at least once and up to 68 times, over periods of 7 to 29 years. For each study, we summarize here the context and aims, review the assessed variables, and describe the process for accessing the data.

CONCLUSIONS

We hope this article will encourage and support education researchers to widely utilize existing population cohort studies to further advance education science in Britain and elsewhere.

Methodological Issues With Coding Participants in Anonymous Psychological Longitudinal Studies

Longitudinal studies are commonly used in the social and behavioral sciences to answer a wide variety of research questions. Longitudinal researchers often collect data anonymously from participants when studying sensitive topics to ensure that accurate information is provided. One difficulty gathering longitudinal anonymous data is that of correctly matching participants across waves of data collection. A number of methods have been proposed for using nonidentifying codes to match anonymous participants; however, currently there is no consensus on the most effective method. This article reviews and analyzes the literature on nonidentifying codes and provides recommendations for researchers interested in using these types of codes in conducting anonymous longitudinal studies.

Scientific Data Management in the Age of Big Data: An Approach Supporting a Resilience Index Development Effort

The increased availability of publicly available data is, in many ways, changing our approach to conducting research. Not only are cloud-based information resources providing supplementary data to bolster traditional scientific activities (e.g., field studies, laboratory experiments), they also serve as the foundation for secondary data research projects such as indicator development. Indicators and indices are a convenient way to synthesize disparate information to address complex scientific questions that are difficult to measure directly (e.g., resilience, sustainability, well-being). In the current literature, there is no shortage of indicator or index examples derived from secondary data with a growing number that are scientifically focused. However, little information is provided describing the management approaches and best practices used to govern the data underpinnings supporting these efforts. From acquisition to storage and maintenance, secondary data research products rely on the availability of relevant, high-quality data, repeatable data handling methods and a multi-faceted data flow process to promote and sustain research transparency and integrity. The U.S. Environmental Protection Agency recently published a report describing the development of a climate resilience screening index which used over one million data points to calculate the final index. The pool of data was derived exclusively from secondary sources such as the U.S. Census Bureau, Bureau of Labor Statistics, Postal Service, Housing and Urban Development, Forestry Services and others. Available data were presented in various forms including portable document format (PDF), delimited ASCII and proprietary format (e.g., Microsoft Excel, ESRI ArcGIS). The strategy employed for managing these data in an indicator research and development effort represented a blend of business practices, information science, and the scientific method. This paper describes the approach, highlighting key points unique for managing the data assets of a smaller scale research project in an era of "big data."

Sampling and Sampling Frames in Big Data Epidemiology

Purpose of Review

The 'big data' revolution affords the opportunity to reuse administrative datasets for public health research. While such datasets offer dramatically increased statistical power compared with conventional primary data collection, typically at much lower cost, their use also raises substantial inferential challenges. In particular, it can be difficult to make population inferences because the sampling frames for many administrative datasets are undefined. We reviewed options for accounting for sampling in big data epidemiology.

Recent Findings

We identified three common strategies for accounting for sampling when the data available were not collected from a deliberately constructed sample: 1) explicitly reconstruct the sampling frame, 2) test the potential impacts of sampling using sensitivity analyses, and 3) limit inference to sample.

Summary

Inference from big data can be challenging because the impacts of sampling are unclear. Attention to sampling frames can minimize risks of bias.

Enabling Confirmatory Secondary Data Analysis by Logging Data Checkout

As more researchers make their data sets openly available, the potential of secondary data analysis to address new questions increases. However, the distinction between primary and secondary data analysis is unnecessarily confounded with the distinction between confirmatory and exploratory research. We propose a framework, akin to library-book checkout records, for logging access to data sets in order to support confirmatory analysis when appropriate. This system would support a standard form of preregistration for secondary data analysis, allowing authors to demonstrate that their plans were registered prior to data access. We discuss the critical elements of such a system, its strengths and limitations, and potential extensions.

Longitudinal modeling in developmental neuroimaging research: Common challenges, and solutions from developmental psychology

Hypotheses about change over time are central to informing our understanding of development. Developmental neuroscience is at critical juncture: although the majority of longitudinal imaging studies have observations with two time points, researchers are increasingly obtaining three or more observations of the same individuals. The goals of the proposed manuscript are to draw upon the long history of methodological and applied literature on longitudinal statistical models to summarize common problems and issues that arise in their use. We also provide suggestions and solutions to improve the design, analysis and interpretation of longitudinal data, and discuss the importance of matching the theory of change with the appropriate statistical model used to test the theory. Researchers should articulate a clear theory of change and to design studies to capture that change and use appropriately sensitive measures to assess that change during development. Simulated data are used to demonstrate several common analytic approaches to longitudinal analyses. We provide the code for our simulations and figures in an online supplement to aid researchers in exploring and plotting their data. We provide brief examples of best practices for reporting such models. Finally, we clarify common misunderstandings in the application and interpretation of these analytic approaches.