Generative Artificial Intelligence Use in United States Doctor of Physical Therapy Programs

Clicks: 27
ID: 329870
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #39 of 103 articles by views in Physical Therapy

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract Importance Generative Artificial Intelligence (AI) in education is poised to significantly impact the field of physical therapy. Research on generative AI use in physical therapist education remains limited. Objective The objective was to examine generative AI use in physical therapist education among students and faculty. Design This was a cross-sectional, online survey. Setting The survey was conducted among accredited Doctor of Physical Therapy (DPT) programs in the United States (US). Participants Students and faculty were recruited from US DPT programs as of January 2025. Intervention(s) or Exposure(s) Generative AI use within DPT programs was measured by participant self-report. Main Outcomes and Measures A novel 32-item survey comprising closed- and open-ended questions assessed generative AI use, patterns and purposes of use; platforms, training and comfort levels, views on generative AI’s role in physical therapist practice, student preparedness and academic integrity, adoption facilitators/barriers, and demographics. Factors associated with generative AI use were examined using multivariable logistic regression. Results Among 1067 respondents (873 students, 194 faculty), 853 (79.9%) reported using generative AI, including 687 students (78.7%) and 166 faculty (85.6%). ChatGPT was the most common used platform (662 students, 96.4%; 153 faculty, 92.2%). Common reasons for use included creating study guide/sample questions (482 students, 70.2%; 74 faculty, 44.6%) and creating patient cases (370 students, 53.9%; 102 faculty, 61.5%). Barriers to use included concerns about reliability and scientific rigor (student users: 411, 59.8%; non-users: 133, 71.5%; faculty users: 90, 54.2%; non-users: 14, 50.0%) and lack of trust in the technology and/or companies behind it (student users: 287, 41.8%; non-users: 112, 60.2%; faculty users: 63, 38.0%; non-users: 13, 46.4%). Generative AI use was associated with higher self-reported comfort with the technology (students: OR = 11.6, 95% CI = 7.9–17.1; faculty: OR = 14.3, 95% CI = 5.1–40.0). Conclusion Generative AI is widely used among DPT students and faculty, yet substantial variability exists in its use and formal instruction within DPT programs. Relevance As its integration into health care accelerates, incorporating education on generative AI within DPT programs is crucial to ensure students are prepared to use these tools competently and responsibly.
Reference Key
openalex_W7214487691 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Craig P. Hensley, Christa M. Nelson, Benjamin Price, Allison Dennemann, Benjamin Knoll, Carolyn Oh, Jungwha Julia Lee, Carole A. Tucker, Alison H. Chang
Journal Physical Therapy
Year 2026
DOI
10.1093/ptj/pzag102
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.