Barry Forer

Toward a Social Care Program of Research: A Population-Level Study of Neighborhood Effects on Child Development.

The article reports results from a Human Early Learning Partnership initiative that aims to address limitations within the literature concerning neighborhood effects on child development. Problems include the tendency for studies to (a) rely on small samples of children, (b) focus on high-risk populations, (c) define neighborhood by Census boundaries, (d) attend only to 1 or 2 developmental domains, and (e) adhere to a narrow understanding of socioeconomic status. By collecting data from a near-census of kindergarten children in British Columbia, Canada, using the Early Development Instrument, our research addresses all 5 problems. Findings reported in this article lay the groundwork for the Human Early Learning Partnerships much more ambitious program of social care research that aims to measure directly the processes by which physical and social settings influence human development in the formative early years, rather than to infer them from data routinely collected for other purposes. The article concludes by inviting international colleagues to critically evaluate our program of research in its early days of implementation.

Testing and measurement from a multilevel view: Psychometrics and validation.

A growing number of testing and assessment programs gather individual student or child measures, but by design, they do not make inferences or decisions about individual students or children but rather for an aggregate such as a school, school district, neighborhood, or state. We call such measurement practices multilevel measurement. In striking contrast to multilevel measurement, however, the widely used measurement and testing models (including our psychometric and validation models) are, by historical precedent, geared toward individual differences, as are the constructs they measure and related construct validation work. Our purposes herein are to (a) introduce multilevel measurement; (b) contrast it with conventional views of measurement; and (c) discuss its implications for how one defines constructs, considers high stakes, and conducts theoretical and day-to-day work such as evaluating the measurement properties and

The use of population‐level data to advance interdisciplinary methodology: a cell‐through‐society sampling framework for child development research

The authors argue that population‐level data should be used to advance interdisciplinary research about community effects on early development. These data permit the identification of neighborhoods in which development patterns deviate from predictions based on local socioeconomic status (SES). So‐called ‘off‐diagonal’ places signal where researchers are likely to discover processes that either deflect the risks of low SES or dampen the salutary impact of favorable SES. Since such neighborhoods will be best understood relative to nearby ‘on‐diagonal’ neighborhoods where macro‐economic and/or public policy factors are constant, the authors present a methodology for illuminating these regional clusters. The method is deployed in British Columbia, Canada, where a team has collected developmental observations from two censuses of kindergarten children (n = 82,632). The article discusses how these clusters can be used to coordinate sampling decisions among academics representing the range of disciplines needed to study child development from cell‐through‐society, as is recommended in the literature.

Examining the social determinants of children's developmental health: protocol for building a pan-Canadian population-based monitoring system for early childhood development

Introduction Early childhood is a key period to establish policies and practices that optimise childrens health and development, but Canada lacks nationally representative data on social indicators of childrens well-being. To address this gap, the Early Development Instrument (EDI), a teacher-administered questionnaire completed for kindergarten-age children, has been implemented across most Canadian provinces over the past 10 years. The purpose of this protocol is to describe the Canadian Neighbourhoods and Early Child Development (CanNECD) Study, the aims of which are to create a pan-Canadian EDI database to monitor trends over time in childrens developmental health and to advance research examining the social determinants of health. Methods and analysis Canada-wide EDI records from 2004 to 2014 (representing over 700 000 children) will be linked to Canada Census and Income Taxfiler data. Variables of socioeconomic status derived from these databases will be used to predict neighbourhood-level EDI vulnerability rates by conducting a series of regression analyses and latent variable models at provincial/territorial and national levels. Where data are available, we will measure the neighbourhood-level change in developmental vulnerability rates over time and model the socioeconomic factors associated with those trends. Ethics and dissemination Ethics approval for this study was granted by the Behavioural Research Ethics Board at the University of British Columbia. Study findings will be disseminated to key partners, including provincial and federal ministries, schools and school districts, collaborative community groups and the early childhood development research community. The database created as part of this longitudinal population-level monitoring system will allow researchers to associate practices, programmes and policies at school and community levels with trends in developmental health outcomes. The CanNECD Study will guide future early childhood development action and policies, using the database as a tool for formative programme and policy evaluation.

Selection of area-level variables from administrative data: an intersectional approach to the study of place and child development.

Given data limitations, neighborhood effects scholarship relies heavily on administrative data to measure area-level constructs. We provide new evidence to guide the selection of indicators from routinely collected sources, focusing on effects on early child development. Informed by an analytic paradigm attuned to the intersection of race, class, and sex, along with population-level data in British Columbia, Canada, our findings signal the need for greater precision when choosing variables in place of the now dominant approaches for measuring constructs like income/wealth, employment, family structure and race/ethnicity. We also provide new evidence about which area-level variables associate with the different domains of child development, as well as how area-level associations vary across urban and rural contexts.

Neighbourhood socioeconomic status indices and early childhood development

The developmental health of young children is highly influenced by the socioeconomic conditions in which they are raised. How to accurately measure these conditions is a point of debate in the current literature on child development, health, and social determinants. We have evaluated four existing indices of socioeconomic status (SES) to determine the most relevant for the analysis of early childhood development (ECD) in Canada. Following a literature review of published SES indices which used 2006 Canadian Census data, four indices were chosen based on their relevance to ECD and the number of citations in subsequent articles. These were: the Canadian Deprivation Index, the Socioeconomic Factor Index, the Canadian Marginalization Index and an index created by the Early Childhood Mapping Project in Alberta, Canada. The indices were replicated using SES data for 2038 customized geographic neighbourhoods encompassing 99.9% of the Canadian population, and the relationship of the indices to ECD was investigated by linking to aggregated data from the Early Development Instrument (EDI), a teacher-completed questionnaire used to assess kindergarten childrens physical, social, emotional, and cognitive development, and communication skills. The derived SES indices were compared based on four criteria: the input variables used, the index structure, the interpretability of the index and the variance they explained (R2) in the different EDI outcome measures. In terms of variance explained, material components of the SES indices (e.g., income, education) consistently showed the strongest association with childrens language and cognitive development. The patterns of association for the non-material SES components and the other developmental domains of the EDI were more complex. We discuss the findings in regard to current developments in the field, and the need for refining empirical and theoretical approaches to examine associations between different facets of SES contextual factors and different aspects of ECD outcomes.

Establishing a protocol for building a pan-Canadian population-based monitoring system for early childhood development for children with health disorders: Canadian Children’s Health in Context Study (CCHICS)

Introduction Health disorders early in life have tremendous impact on children’s developmental trajectories. Almost 80% of children with health disorders lack the developmental skills to take full advantage of school-based education relative to 27% of children without a health disorder. In Canada, there is currently a dearth of nationally representative data on the social determinants of early childhood development for children with health disorders. Evidence from Canada and other countries indicate that poorer developmental outcomes in typically developing children are associated with lower socioeconomic status (SES). However, to date, it is not known whether this relationship is stronger among children with health disorders. The study’s objectives are to estimate the prevalence and to investigate social determinants of developmental outcomes for young children with health disorders, using the Early Development Instrument (EDI). Methods and analysis Study objectives will be achieved through three steps. First, using existing EDI data for 10 provinces and 2 territories collected from 2004 to 2015, we will investigate differences in developmental health outcomes among children with identified health disorders. Second, population-level EDI data will be linked with neighbourhood sociodemographic census data to explore associations between socioeconomic characteristics and rates of specific diagnoses among children aged 5–6 years, including trends over time. Third, for 3 of these 12 regions, additional health and/or education databases will be linked at an individual level. These data will be used to establish differences in EDI outcomes in relation to the age-of-onset of diagnosis, and presence of intervention or treatment. Ethics and dissemination Study methodologies have been approved by the Hamilton Integrated Research Ethics Board. The results of the analyses of developmental health outcomes for children with health disorders combined with SES will have implications for both health service delivery and school-based intervention strategies. Results will contribute to a framework for public policy.

A Pan-Canadian Data Resource for Monitoring Child Developmental Health: The Canadian Neighbourhoods Early Child Development (CanNECD) Database

The Canadian Neighbourhoods and Early Child Development (CanNECD) database is a unique resource for research on child developmental health and well-being within the socioeconomic and cultural context of Canadian neighbourhoods. This paper describes the CanNECD database and highlights its potential for advancing research at the intersection of child development, social determinants of health, and neighbourhood effects. The CanNECD database contains cross-sectional population-level child developmental health data from all across Canada collected through regional implementation of the Early Development Instrument (EDI), geo-coded information on residential neighbourhoods covering all of Canada, and socioeconomic and demographic variables from the Canada Census and Income Taxfiler database. Individuals are not identified in the database, as no identifying information, such as names and addresses, is attached to the EDI record. At data collection, each individual child is given a unique number which is a combination of site, school, and position on a class list. Each neighbourhood receives a unique identifier which then is linkable across datasets. The nearly 800,000 EDI records spanning 2003-2014 and representing all Canadian provinces and territories (with the exception of Nunavut) are compiled in a secure electronic collection system at the Offord Centre for Child Studies, McMaster University in Hamilton, Canada. Early studies using the EDI demonstrated its utility as a tool for assessing child developmental health at a population level, and its potential for both community-level and large-scale monitoring of child populations. Research using the CanNECD database is now examining to what extent social determinants and the steepness of the social gradients of developmental health differ between geographical jurisdictions and between different sub-populations. We are also working to identify outlier neighbourhoods in which EDI scores are substantially higher or lower than predicted by a neighbourhood’s demographic and socioeconomic characteristics, and exploring other potentially important determinants of children’s developmental health. Finally, we are examining the extent to which change-over-time in aggregate EDI scores varies geographically, and how well it coincides with changes in socioeconomic factors. Thus, the CanNECD database offers the opportunity for research that will inform national policies and strategies on child developmental health.

National and International Educational Achievement Testing: A Case of Multi-level Validation Framed by the Ecological Model of Item Responding

The results of large-scale student assessments are increasingly being used to rank nations, states, and schools and to inform policy decisions. These uses often rely on aggregated student test score data, and imply inferences about multilevel constructs. Validating uses and interpretations about these multilevel constructs requires appropriate multilevel validation techniques. This chapter combines multilevel data analysis techniques with an explanatory view of validity to develop explanations of score variation that can be used to evaluate multilevel measurement inferences. We use country-level mathematics scores from the Trends in International Mathematics and Science Study (TIMSS) to illustrate the integration of these techniques. The explanation focused view of validity accompanied by the ecological model of item responding situates conventional response process research in a multilevel construct setting and moves response process studies beyond the traditional focus on individual test-takers’ behaviors.

The Ages and Stages Questionnaire: Latent factor structure and growth of latent mean scores over time

BACKGROUND Very little research exists that looks at the Ages and Stages Questionnaire simultaneously from a modern latent variable point of view and by looking at its psychometric properties over time. AIMS To explore the latent factor structure of the ASQ using Exploratory Structural Equation Modeling techniques for ordinal data and investigate its change over time using the method of vertical scaling from multidimensional Item Response Theory. STUDY DESIGN Longitudinal, with the same children being assessed at multiple timepoints. SUBJECTS Children measured using the 12, 14, 16, 18, 20, 22, 24, 27, 30, 33, 36, 42, 48month questionnaires of the ASQ. Initial sample (12months) consisted of 2219 children and final sample (48months), 892 children due to drop-out. OUTCOME MEASURES Ages and Stages Questionnaire, 3rd version (ASQ-3). RESULTS Results indicate that all ASQ-3 age questionnaires examined showed the proposed 5-factor structure (except the 12-month version) but with different patterns over time. The Gross Motor domain had the fewest misfitting items, from 12months onwards. The Personal-Social domain and the Problem Solving domain had larger numbers of misfitting items. Results from the vertical scaling analysis showed that both the Problem-Solving and Personal-Social dimensions also exhibited the most complex patterns of change over time. CONCLUSIONS The psychometric properties of the ASQ-3 seem to be both time-dependent and domain-dependent. Earlier questionnaires reflect a latent structure that was not as well-defined as for later versions. Also, domains such as Communication and Gross Motor appear to be much more reliably measured than others, such as Problem-Solving and Personal-Social.