Presented By: Marissa Zhu, Wayne State University School of Medicine

Purpose
This study aims to evaluate the perceived efficacy and utility of various feedback models - ATA (Ask-Tell-Ask), SFED (Set, Feedback, Explain, Direct), R2C2 (Relationship, Reaction, Content, Coaching), and ARCH (Ask/allow for self-assessment, Reinforce things done well, Confirm areas needing correction, and Help with an improvement plan) - within a students-as-teachers course for M4 medical students. It explores these models across diverse teaching sessions, including Case-Based Learning (CBL), Clinical Skills Labs, Small Group Discussions, and Lectures, to identify the most effective models for specific contexts and purposes.

Methods
The study employs a mixed-methods approach, combining quantitative data from surveys with qualitative data from course assignments and focus group interviews. Upon completing their teaching session, M4 students will complete a Feedback Model Comparison Log to document their reflections and experiences with the effectiveness of a specific feedback model for their teaching session. Quantitative ratings gathered from these reflection logs will quantitatively assess M4 students' perceptions of each feedback model's efficacy and utility. Additionally, content analyses of course assignments will provide qualitative insights into students' experiences, attitudes, and perspectives regarding the feedback models.

Results
Preliminary findings indicate varying levels of perceived effectiveness and utility among the feedback models across different teaching contexts. Initial data suggests that the SFED model appears to be the most adaptable and effective in clinical settings, significantly influencing the improvement of feedback skills among M4 students.

Conclusions
Initial findings from this research contribute to understanding the role and impact of different feedback models within an mSAT course. Lessons learned so far underscore the importance of contextually appropriate feedback mechanisms in teaching settings and enrich the literature on feedback models in medical education.