Bridging Disciplinary Boundaries (January 11 - 14, 2007) |
To answer question one and two, we utilize survival analysis to describe the risk of initial placement in special education during elementary school. Preliminary analyses include life table analysis and sample survivor/hazard functions by socio-demographic characteristics. To answer question three, we explore a model of special education placement by investigating the effects of socio-demographic characteristics, child cognition, behavior, and early child care/family experience. We used logistic regression analysis for the dichotomous outcome of any special education from K-6 grades.
Data in this study come from phases I, II and III of the NICHD Study of Early Child Care and Youth Development (SECCYD), a longitudinal study of child development of more than 1,300 children and their families. The sample was recruited from 10 sites across the United States beginning in 1991. The NICHD SECCYD is a comprehensive study of children in context, specifically in the home, childcare, and primary school contexts. The present study draws from approximately 1,000 children who had received at least one teacher report of special education placement through sixth grade.
While a majority of children in the NICHD SECCYD did not get placed in special education, approximately 1/3rd of all children had at least one low or high placement from Kindergarten through sixth grade. Children in first grade were at greater risk of being placed into special education. Over time in school, the risk declined. During each grade, boys were significantly more likely to experience a first placement than girls. Similarly, African-American and low-income children were at greater risk for a first placement during each grade than other children. Predictors of any special education included the chronicity of low-income, lower maternal education, lower scores on the Bayley MDI, later-born children, and the chronicity of center-based child care. These prediction findings were statistically significant above and beyond the covariate specification, which included a range of socio-demographic characteristics and program sites.
These findings provide a foundation for future social work research, policy, and practice. Future research will focus on the predictors of multiple special education placements to identify the children most at risk for special education tracking. Future research will also expand the survival analysis by adding additional predictors to the model. Study findings have implications for targeted early childhood and preschool aged prevention and intervention programs for children at risk of single or repeated special education placements.