School-Level Predictors of Speech-Language Therapy Enrollment.
Purpose: There are extensive concerns about the size of speech-language caseloads in schools. However, little empirical data exist regarding the patterns of speech-language services enrollment. We reviewed data from several hundred schools in a large state to explore the role of school-level factors...
| Published in: | Perspectives of the ASHA Special Interest Groups Vol. 7; no. 3; pp. 938 - 947 |
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| Main Authors: | , |
| Format: | research tables/charts Journal Article |
| Published: |
American Speech-Language-Hearing Association
Jun2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157435145&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157435145 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2381473X KTSD jtl: Perspectives of the ASHA Special Interest Groups issn: 2381473X maglogo: N pubinfo: dt: Jun2022 vid: 7 iid: 3 pid: 42 pub: American Speech-Language-Hearing Association place: Rockville, Maryland artinfo: ui: 157435145 157435145 157435145 10.1044/2022_PERSP-21-00329 157435145 ppf: 938 ppct: 9 formats: fmt: @attributes: type: P tig: atl: School-Level Predictors of Speech-Language Therapy Enrollment. aug: au: Shanks, Lauryn Hall-Mills, Shannon affil: School of Communication Science & Disorders, Florida State University, Tallahassee sug: subj: Speech Therapy Language Therapy School Health Services Human Empirical Research Florida Schools Descriptive Statistics Regression Socioeconomic Factors Poverty Reading English as a Second Language Data Analysis Software Post Hoc Analysis Correlational Studies Intraclass Correlation Coefficient Bivariate Statistics Multiple Regression ab: Purpose: There are extensive concerns about the size of speech-language caseloads in schools. However, little empirical data exist regarding the patterns of speech-language services enrollment. We reviewed data from several hundred schools in a large state to explore the role of school-level factors in speech-language case enrollment. Method: Child count and enrollment data reports from a stratified sample of schools located within 12 Florida school districts (N = 808) were drawn from the Florida Department of Education portal for the 2018-2019 school year. Three school districts were selected from each of several population sizes. To control for school population size, the raw numbers for each variable were converted into proportions. To examine the relations among variables, multiple correlational and regression analyses were conducted. Results: The results indicated that two school-level factors significantly predicted the total speech-language services enrollment and language therapy enrollment (e.g., proportion of students of low socioeconomic status [SES], passing the state reading assessment), whereas three school factors significantly predicted the speech therapy enrollment (e.g., proportion of low-SES students, passing the reading assessment, and enrolled in English as a second or other language services). Conclusions: The outcomes of this study suggested that school factors can predict speech-language service enrollment, which offers important implications for decision makers in schools. Implications for educational practices and further research are presented. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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