Improving the Delivery of Early Intervention to Children
with Disabilities from High Poverty Background

OSERS, USDE, Directed Research Project

ABSTRACT

Children from high poverty backgrounds are at greater risk for mental retardation than children in the general population. Nonetheless, early intervention programs aimed at improving the outcomes of children and their families in poverty are typically not as effective as they are with more advantaged groups. While much work has been completed examining the impact of environmental risks on children’s outcomes, little work has been directed at identifying the mechanisms responsible for these adverse outcomes. While some poor outcomes may be attributable to the compounding and interactive effects of risk factors, others may be due to the moderating effect of risks on implementation quality. Children from high-risk environments are likely to receive programs that are implemented less well, less often, and for shorter duration. For example, in an analysis of the national data from the Infant Health and Development Program (IHDP), serving low birth weight infants and families (Liaw, Meisels, & Brooks-Gunn, 1995), investigators studied the relationships among program participation, child outcomes, and other family variables. The measures of program participation included a measure of exposure (i.e., numbers of home visits, days child participated in the centers, support group participation), rate of participation (numbers of intervention activities and numbers of activity episodes used by a child in center activities), and a measure of active experience, which included staff ratings of parental interest and child mastery of activities. The authors found first, that the degree of active experience in the intervention accounted for a greater degree of variance in children's IQ scores. Second, they found that parents and children who were more actively involved were more advantaged (i.e., they were most likely to have mothers who were white, older, more highly educated, and of higher cognitive ability). They were also the least likely to live below the poverty line. These findings support the hypothesis that families from high poverty backgrounds experience a variety of barriers that impede the family's ability to actively engage in and sustain intervention. Families facing multiple challenges of poverty, substance abuse, and violence, tend to be in chronic states of crisis, experience a sense of alienation from service providers, and exhibit a sense of learned helplessness and low self-esteem (Summers, McMann, & Fuger, 1997). Multiple and chronic crises place the family in a constant state of disruption with little sense of routine, stability or structure (Kagan & Schlosberg,1989). These factors each present barriers to early intervention participation. The goal of this project is to test hypotheses concerning how risk factors associated with families from high poverty backgrounds interact with service practices to moderate the effects of early intervention, and to develop alternative practices to enhance effectiveness of early intervention practices with these children and families. Aim 1: To identify risk and protective factors of children with disabilities and their families in poverty who are receiving early intervention services and describe the relationship of those factors to effectiveness of early intervention. Aim 2: To examine the effectiveness of a Family-Guided Routines-Based Intervention and to examine the moderating effect of implementation quality in promoting growth in children with disabilities as well as promoting positive change in their families’ outcomes. Aim 3: To identify barriers to the implementation of effective interventions for children with disabilities in poverty and strategies for overcoming these barriers. Aim 4: To develop, implement, and evaluate enhanced interventions that incorporate the identified characteristics of effective early intervention for children with disabilities and their families from high poverty backgrounds. Aim 5: To disseminate enhanced interventions and research findings about factors that increase effectiveness of early intervention for children with disabilities and their families from high poverty backgrounds.Experimental Approach

Design. The effectiveness of a set of family-guided approaches to early intervention are being studied as a function of two types of factors (1) risk factors experienced by families and (2) the quality of intervention services received. This project employs three separate but interrelated quantitative studies. In Year 1, we will run an experimental study investigating the effects of family-guided activities-based intervention delivered based on bi-weekly visits to families by home visitors (N = 20, 10 Experimental, 10 Control randomly assigned to treatment). We will examine the effects of the intervention on children's cognitive, language, and social outcomes, on parent-child-interaction, and on family outcomes of engagement and satisfaction (N = 100, 5 per home visitor). We will also examine barriers to effectiveness in the form of less than adequate fidelity, intensity or duration of intervention and identify threats to quality of implementation. In Year 2, we will employ qualitative research methods using focus groups, unstructured interviews, and participant observation of both staff and families to explore factors related to differing levels of implementation quality and to generate potential solutions to these problems. In Year 3, we will run a second experimental study with a sample size identical to Study 1 (N = 20 home visitors and 100 children and their families) investigating an enhanced intervention that incorporates family-centered solutions to barriers identified in Study 2.
Participants. Participants will be early intervention home visitors from the Wyandottee County Infant-Toddler Program who have at least seven children under the age of two years in their caseloads. For Studies 1 and 3, we will employ the following sampling procedure. From this pool of volunteer home visitors, 20 home visitors will be selected using a stratified random sampling procedure to approximate racial representation of the school system (i.e., 45% African-American). This same stratified random approach will be used to assign home visitors to intervention or comparison groups in Studies 1 and 3.
For both Studies 1 and 3, we will recruit 5 family/child participants for children who qualify as being from the caseloads of the 20 participating home visitors. Recruitment criteria for the families will include: an income level below the relative poverty threshold (Hernandez, 1997) and living in the eastern section of Wyandottee County. Children in these families will be not any older than 24 months and will have been identified as having a significant developmental delay of at least 1.5 SD in at least two developmental domains. Because of the difficulties in obtaining accurate determinations of level and type of disability before the age of 3 years, we will not stratify the sample on these variables but include developmental status in analysis of children’s and family’s outcomes. For the qualitative study (Study 2), we will select case study and focus group participants using a “purposive sampling” method (Rubin & Rubin, 1995) which involves deliberately selecting participants based on predetermined characteristics. Those characteristics will be identified based on results from Study 1, as we are able to see which family risk and protective factors appear to be highly related to successful outcomes of early intervention, and/or as we are able to recognize family variables that appear to most influence program fidelity and sustainability. Methods. Multiple measures selected for their theoretical and technical relevance will be used. These include: sociodemographic indicators, cognitive, language, and developmental tests/inventories, in home observations, and measures of intervention fidelity. The statistical analytic needs of this project range from simple descriptive and correlation statistics with graphical displays to techniques for testing hypotheses concerning differential rates of growth over time between intervention and traditional intervention (control) groups. To serve these needs, the SPSS 9.0 statistical package, MS-EXCEL 2000 spreadsheet software, and the HLM 5.0, hierarchical linear modeling tools of Bryk & Raudenbusch (1992) will be used. Together these tools enable preparation of data files, exploratory analyses needed for planning more complex analyses and testing hypotheses, testing differences between groups in linear growth parameters (slope and intercept), and preparation of graphical displays of the fitted linear trajectories.