|Title:||Risk Factors and Services for Vocabulary Delays in Early Childhood: Population-based Estimates|
|Principal Investigator:||Morgan, Paul||Grantee:||Pennsylvania State University|
|Program:||Early Intervention and Early Learning in Special Education [Program Details]|
|Award Period:||3/1/2012–2/28/2014||Award Amount:||$699,658|
Co-Principal Investigators: George Farkas (University of California, Irvine), Carol Hammer (Temple University), and Marianne Hillemeier (The Pennsylvania State University)
Purpose: Little is currently known about early precursors of academic and behavioral school readiness for children, particularly those with or at risk for disabilities. Evidence indicates that vocabulary knowledge constitutes a potentially malleable factor that, if increased, may improve children's reading, mathematics, and behavioral readiness for kindergarten. Yet these relations have not been convincingly established. It is also critical to better understand the onset of vocabulary delays during at-risk children's infant, toddler, and preschool years, and how these delays are affected by the receipt of early intervention services. The primary aim of this study is to determine whether and to what extent vocabulary knowledge, as well as parenting and child care quality and early intervention services, constitute potentially malleable and educationally relevant factors that may increase at-risk children's reading, mathematical, and behavioral readiness for schooling. This study will also seek to identify moderators of the relation between earlier vocabulary knowledge and children's school readiness.
Project Activities: The researchers will analyze the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B) to determine: (1) factors that most strongly predict children's vocabulary knowledge at 24 months of age; (2) which children are most likely to receive early intervention or early childhood special education when they are 24–48 and 48–60 months of age; (3) which children are most likely to display vocabulary delays at 48 months of age; (4) factors that strongly predict children's general cognitive and behavioral functioning at 24 months, as well as their pre-academic and behavioral functioning at 48 months of age; and (5) which children are most likely to display lower academic and/or behavioral readiness at 60 months of age.
Products: The expected products from this study include publications and presentations on research activities and findings that may serve as a basis for developing interventions for infants, toddlers, and preschoolers at risk for disabilities.
Setting: The ECLS-B is a dataset with a nationally-representative sample of children born in the United States in 2001.
Sample: The ECLS-B includes data on children born in the United States in 2001 (sampled from birth certificate files) who were then assessed up to kindergarten, at 9, 24, 48, and 60 months of age. ECLS-B oversampled for low birth weight children and racial and ethnic minorities. Parents of 550 24-month-olds reported that their children received early intervention services. At both the 48- and 60-month assessments, 850 parents reported that their children received early intervention services.
Intervention: There is no intervention.
Research Design and Methods: This study involves secondary data analyses of standardized direct measures and questionnaire data collected in the ECLS-B.
Control Condition: Due to the nature of the research design, there is no control condition.
Key Measures: Measures included in the analysis of the ECLS-B data include individually administered and parental reports of children's vocabulary knowledge, cognitive functioning, reading and mathematics achievement, and direct observation and teacher ratings of learning-related, externalizing, and internalizing problem behaviors. Measures also include direct observation of parent-child interactions, direct observation of child care quality, birth certificate data on socio-demographic, gestational, and birth characteristics, and parent interviews. Outcomes include children's vocabulary knowledge, cognitive functioning, reading and mathematics achievement, and learning-related, externalizing, and internalizing problem behaviors.
Data Analytic Strategy: The researchers will use regression analyses to address the research questions in this study. These will include cross-lagged regression models with extensive statistical control for likely confounds and weighted adjustments to account for sample clustering, multiple imputation to account for missing data, and propensity score matching methods to better identify the predicted effects of natural variation in receipt of specific early intervention services on the school readiness of children with identified delays or disabilities.