AI provides congruent and prescriptive feedback for squat form: qualitative assessment of coaching provided by AI and
Alessandro Luna1, Michael W Denham1
1Columbia University Vagelos College of Physicians & Surgeons, New York, NY 10032, USA.
Abstract:
Objectives: To assess style and themes of feedback provided by artificial intelligence (AI) mobile application and physical therapist (PT) to participants during bodyweight squat exercise. Methods: Research population was age 20-35, without any pre-existing condition that precluded participation in bodyweight exercise. Qualitative methodology followed directed content analysis. Cohen's kappa coefficient verified consistency between coders. Results: Both AI and PT groups had seven female and eight male participants. Three themes emerged: affirmation schema, correction paradigms and physical assessments. Average kappa coefficient calculated for all codes was 0.96, a value that indicates almost perfect agreement. Conclusion: Themes generated highlight the AI focus on congruent, descriptive and prescriptive feedback, while the PT demonstrated multipoint improvement capabilities. Further research should establish feedback comparisons with multiple PTs and correlate qualitative data with additional quantitative data on performance outcomes based on feedback.
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