Honors Theses

Date of Award

Spring 5-8-2026

Document Type

Undergraduate Thesis

Department

Psychology

First Advisor

John Young

Second Advisor

Todd Smitterman

Third Advisor

Kate Kellum

Relational Format

Dissertation/Thesis

Abstract

This study explores ways to bridge the research-practice gap in psychology by examining how role-play, structured self-reflections, and AI-generated feedback support the development of Unified Protocol (UP) clinical skills. Using a single-subject design, the researcher simulated therapy sessions with a volunteer acting as the patient, implementing UP modules in sequence, while collecting both quantitative and qualitative data. Each session included preparation using the UP, role-play, and pre- and post-session reflection. Performance was evaluated using Lyssn, an AI-based platform that generated Cognitive Therapy Rating Scale (CTRS; Young & Beck, 1980) scores and detailed feedback on CBT techniques. This was interpreted and applied by the therapist to improve facilitation of subsequent sessions. Results showed consistently high therapist competence across sessions, with improvements in agenda adherence, pacing, and structured application of UP modules over time. Challenges emerged in balancing therapist talk-time, facilitating guided discovery, and clearly communicating. These findings suggest that combining AI feedback and structured self-reflections may be useful to enhance evidence-based psychological treatments by increasing fidelity and supporting the development of practical clinical skills in a way that translates to real-world therapeutic practice.

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