Examining Student Assistance Program Data in a Rural Public School to Determine Which Factors Predict Access to Student Assistance Program Team Recommended Services

Oliver, Jill

Oliver, J. (2025). Examining Student Assistance Program Data in a Rural Public School to Determine Which Factors Predict Access to Student Assistance Program Team Recommended Services.

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Title	Examining Student Assistance Program Data in a Rural Public School to Determine Which Factors Predict Access to Student Assistance Program Team Recommended Services
Abstract	Mental health and substance use are major concerns for youth across the nation, particularly with poor mental health on the rise. Student Assistance Programs (SAPs) have been put in place so that students in need of services can be referred to these programs and get appropriate services recommended to them. However, there has been a lack of specific data analysis on SAPs. The purpose of this study was to find predictive factors that impact which students access services that are recommended through the SAP program. Spearman’s correlations, binary logistic regressions, and a binomial test were utilized to see if there were predictive factors for receiving written permission, accessing school services, and accessing community services. One predictive factor that was found in this study was that as grade level increased, the likelihood of receiving parent permission to proceed with the SAP process (and thus getting recommended services) decreased. The study also found that students who are recommended for school services are highly likely to access those services. However, the data showed that academic supports had the lowest rate of being accessed. Another major finding that was uncovered was that receiving parent permission to proceed with the SAP process was a major barrier to accessing services. Analyses from this study indicate a need to further investigate the obstacles that prevent parents from giving permission to proceed with the SAP process.
Date	2025

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Title: Examining Student Assistance Program Data in a Rural Public School to Determine Which Factors Predict Access to Student Assistance Program Team Recommended Services
Author: Oliver, Jill
Abstract: Mental health and substance use are major concerns for youth across the nation, particularly with poor mental health on the rise. Student Assistance Programs (SAPs) have been put in place so that students in need of services can be referred to these programs and get appropriate services recommended to them. However, there has been a lack of specific data analysis on SAPs. The purpose of this study was to find predictive factors that impact which students access services that are recommended through the SAP program. Spearman’s correlations, binary logistic regressions, and a binomial test were utilized to see if there were predictive factors for receiving written permission, accessing school services, and accessing community services. One predictive factor that was found in this study was that as grade level increased, the likelihood of receiving parent permission to proceed with the SAP process (and thus getting recommended services) decreased. The study also found that students who are recommended for school services are highly likely to access those services. However, the data showed that academic supports had the lowest rate of being accessed. Another major finding that was uncovered was that receiving parent permission to proceed with the SAP process was a major barrier to accessing services. Analyses from this study indicate a need to further investigate the obstacles that prevent parents from giving permission to proceed with the SAP process.
Advisor: Hall-Wirth, Jessica
Committee Members: Tarr, Christopher
Larwin, Karen
Date Issued: 2025
Degree Granting Institution: Slippery Rock University of Pennsylvania
College of Education
Special Education
Degree Name: Degree of Doctor of Education (Ed. D.)
Degree Level: Doctorate Degree
Degree Discipline: Special Education
Genre: Dissertation/Thesis
Copyright Statement: The copyright to this item is owned by the author and falls under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License. (https://creativecommons.org/licenses/by-nc-nd/4.0/)