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Self-Reported AI Competency and Educational Needs for Integrated AI and Digital Rehabilitation Education Among Occupational Therapy Students: A Cross-Sectional Survey

Year: 2026

Type: article

Abstract: Background and Aim: The growing use of generative artificial intelligence (AI) in healthcare calls for occupational therapy education that combines critical appraisal, clinical reasoning, and digital rehabilitation. This study aimed to examine students' interest in AI, perceived AI competency, and needs for integrated AI and digital rehabilitation education, and identified factors associated with educational content needs. Participants and Methods: An exploratory cross-sectional survey using convenience sampling and five researcher-developed scales without full psychometric validation was conducted among occupational therapy students from three universities. A total of 250 questionnaires were submitted, and 230 complete responses were analyzed. Descriptive statistics, reliability tests, Welch group comparisons, Pearson correlations, and hierarchical multiple regression with sensitivity analyses were used. Results: Mean scores were 3.64±0.77 for AI interest, 3.42±0.67 for self-reported AI competency, 3.93±0.68 for educational content needs, 3.95±0.63 for educational priority, and 3.82±0.64 for instructional method preference. All five domains were positively correlated. Educational priority and instructional method preference showed the strongest correlation (r=0.701). AI interest (β=0.490, p<0.001) and self-reported AI competency (β=0.154, p=0.015) were associated with educational content needs in the conventional regression; the final model explained 34.3% of the variance. The competency association was sensitive to robust inference (HC3 p=0.0504). Conclusion: Students expressed preferences for integrated, practice-oriented education addressing AI use, occupational therapy clinical reasoning, client-appropriate tool selection, assessment, and intervention planning.

Source: Journal of Multidisciplinary Healthcare

DOI: 10.2147/jmdh.s650490

Authors: Yun-Hee Park, Deok-Ju Kim

Institutions: Choonhae College of Health Sciences, Cheongju University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Quality education, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,836