Case
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.