|Title:||Meta-Analytic Structural Equation Modeling of Family Capacity-Building Early Intervention Practices|
|Principal Investigator:||Dunst, Carl||Awardee:||Orelena Hawks Puckett Institute|
|Program:||Early Intervention and Early Learning [Program Details]|
|Award Period:||3/1/11–2/28/13||Award Amount:||$474,822|
Purpose: A major premise of the Individuals with Disabilities Education Act (IDEA) Part C program is that early intervention builds and strengthens family capacity. This, in turn, has positive effects on parent and child outcomes. The aim of this study is to examine this premise by identifying the relationships between certain intervention characteristics and parent and child outcomes. These characteristics include program variables, such as service intensity and frequency of parent contacts, as well as process variables, such as the types of family-centered help provided.
Project Activities: Meta-analytic structural equation modeling will be used to identify causal and mediating influences of the early intervention program and process variables on parenting and child outcomes. The extent to which the two sets of variables individually or in combination are related to parenting self-efficacy, parent-child interactions, and child behavior and development will be explored.
Products: Products from this study include publications and presentations on research activities and findings related to the relationships between early intervention service characteristics and parent and child outcomes.
Setting: Studies included in the analyses are those in which families received early intervention services.
Population: The target population is families who have received early intervention services.
Intervention: This study does not involve a predetermined intervention. Instead, it will suggest possible characteristics of early intervention programs and processes as they are currently practiced that are found to correlate with parent and child outcomes.
Research Design and Methods: Meta-analytic structural equation modeling will be used. Relevant studies will be identified through an extensive review of published and unpublished research. Included studies will involve children birth to three years of age in home-based early intervention programs or parent involvement programs. The studies will also include measures in at least three of the variables of interest (i.e., program variables, process variables, parenting self-efficacy, parent-child interactions, and child outcomes). Studies will also be included if correlations among measures are reported or are available. Studies will be coded and include variables of interest, constructs within the variables of interest, and other relevant variables such as background or demographic information. Meta-analytic structural equation modeling of studies will be used to identify causal and mediating influences of early intervention program and process variables on parenting and child outcomes.
Control Condition: There is no control condition.
Key Measures: Five types of variables will be included in this research. They include measures of program delivery, program processes, parent self-efficacy, parent-child interactions, and child developmental outcomes, including social, emotional, motor, communication, adaptive and cognitive development.
Data Analytic Strategy: Meta-analytic structural equation modeling of studies will be used to discern direct and indirect relationships between the program and process variables and family and child outcomes. The analyses will determine the relations between program variables and parenting and child outcomes; the relations between process variables and parenting and child outcomes; and the relations between the combined program and process variables and parent-child interactions and child outcomes. The researchers will also examine the extent to which parenting self-efficacy beliefs mediate the relationship between early intervention program and process variables and parent-child interactions, parent outcomes, and child behavior and development. The models will also include parent and family background variables and child disability diagnosis.