Date of Award

January 2026

Document Type

Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

John E. Pachankis

Second Advisor

Danielle M. Chiaramonte

Abstract

LGBTQ-affirmative cognitive behavioral therapy (CBT) is an evidence-based practice intended to improve LGBTQ people’s mental health. Several randomized controlled trials have found the treatment to be efficacious at reducing anxiety, depression, and substance use problems in LGBTQ individuals. In real-world clinical contexts, providers deliver and adapt evidence-based practices to best meet their own and client needs. Further, arts-based therapeutic approaches have been utilized among LGBTQ populations to increase self-awareness, strengthen relationships, and develop resilience, but the ways in which they are integrated with evidence-based practices remains unknown. The current study explores how and why providers deliver LGBTQ-affirmative CBT with arts-based adaptations. Data for this study derive from a hybrid type III effectiveness-implementation trial that trained mental health providers in LGBTQ-affirmative CBT. A subsample of providers (N = 12) completed semi-structured, qualitative interviews about their experiences delivering LGBTQ-affirmative CBT with arts-based adaptations. Through a manifest content analysis, we found that arts-based adaptations spanned nine media. Using thematic analysis, we found that providers transformed LGBTQ-affirmative CBT into arts-based approaches, supplemented LGBTQ-affirmative CBT with arts-based approaches, and delivered LGBTQ-affirmative CBT with arts-based approaches as a background activity. Providers delivered LGBTQ-affirmative CBT with arts-based adaptations to address client-related therapeutic barriers, increase acceptability for themselves and clients, and because of its perceived effectiveness on client outcomes. Future research should examine the effectiveness of these arts-based adaptations on LGBTQ clients’ mental health.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 09/16/2027

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