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Demographic variables associated with eligibility for preschool special education services

Posted on:2013-11-11Degree:Psy.DType:Dissertation
University:St. John's University (New York)Candidate:Ferro, Pamela MFull Text:PDF
GTID:1457390008988603Subject:Education
Abstract/Summary:
Many preschool children are affected by disabilities requiring intervention through Early Childhood Special Education (ECSE; Camilli, Vargas, Ryan, & Barnett, 2010). Such interventions can include speech therapy, occupational therapy, physical therapy, counseling, and special education. Earlier delivery of these special education services tends to lead to better outcomes (Costa & Witten, 2009). While ECSE has been shown to help alleviate symptoms of disabilities (Martin, 2010; Conyers, Reynolds, & Ou, 2003), the Individuals with Disabilities Education Act (IDEA, 2004) is criticized for a lack of specificity of eligibility requirements for these services (Daley & Carlson, 2009). Researchers have argued that district recommendation for preschool special education services may not only depend on child functioning (e.g., scores on assessment batteries, diagnosis), but also on extraneous district variables (e.g., socio-economic status; Daley & Carlson, 2009). The present study investigated the degree to which specific variables predict recommendations for preschool special education services. Demographic characteristics of child, prior services received in Early Intervention (EI), child functioning, and variables external to the child (i.e., district variables) were examined to determine their predictive weight of a recommendation to receive services. Chi-square tests of independence, correlation analyses, logistic regressions, and multiple regressions were conducted to examine which specific variables predict services received. Archival data was gathered from 296 children's files located at a certified preschool evaluation site in New York. Demographic information of each child, including age, gender, language(s), medical condition/primary diagnosis, as well as educational information, including reason for referral and prior/current services received in ET was gathered from the files. Forty-two districts were included in analyses. Districts were coded by percentage of reduced/free lunches, spending per student/special education student, and average household income, in order to represent socio-economic status (SES). Results indicated that while some child variables were strongly related to a recommendation of services (i.e., diagnosis), others inconsistently predicted a recommendation of services (i.e., scores on standardized assessments). Additionally, the relationship between district SES and whether services were recommended was not significant. Future directions and implications for school psychologists were discussed.
Keywords/Search Tags:Special education, Services, Variables, Child, Demographic, District
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