Associations Between School-Based Mental Health and Education Outcomes: Analyzing Public Data With Multilevel Modeling

Abstract

This case study describes how multilevel modelling was applied using online public data to determine the impact of mental health treatment in school settings. School-based mental health (SBMH) is increasingly available to help young people succeed and to bridge gaps in mental health care for racially minoritized youth. However, there is only a limited understanding of how well SBMH bridges gaps in highly segregated school systems. This case study discusses the research methodology and design decisions from a study titled “Associations Between School Demographics, School-Based Mental Health, and School Outcomes in New York City Public Schools” completed as a graduate thesis at the Graduate Center (CUNY). This case study uses examples to discuss challenges with research conceptualization using secondary data, the process of collecting multi-informant online data, and statistical analyses with hierarchical data. Practical applications for advanced undergraduates using similar methods are discussed.

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