Attitude and Readiness Towards Artificial Intelligence Among Rehman College of Rehabilitation Sciences: A Cross-Sectional Study

Background: Artificial intelligence applications are becoming increasingly prevalent across a wide range of fields, with healthcare being one of the most significantly impacted sectors. Objective: To assess the attitudes and readiness of physical therapy students at Rehman College of Rehabilitation Sciences toward artificial intelligence and to identify factors influencing their preparedness for integrating it into clinical practice and education. Methodology: A descriptive cross-sectional study was conducted at Rehman College of Rehabilitation Sciences for six months from June 2024 to November 2024. After the approval from the graduate study committee of Rehman College of Rehabilitation Sciences, 141 participants were screened, and informed consent was taken. The data collection tools used in this study were the Medical Artificial Intelligence Readiness Scale for Medical Students and the Artificial Intelligence Attitude Scale. Frequencies and percentages were reported for categorical data such as age, gender, year of study, and two general questions about AI. The Shapiro-Wilk test was used to check the normality of the data. An independent T-test was used to investigate the association between attitude towards artificial intelligence and gender, and a one-way ANOVA was used to examine the association between study year and readiness. Pearson’s correlation test was used to find out the correlation between readiness and attitude towards artificial intelligence. Results: About 53.2% participants demonstrated a positive attitude towards artificial intelligence, while 46.8% exhibited a negative attitude. On the readiness scale, students scored an average of 15/40 for cognition, 38/40 for ability, 9/15 for vision, and 11/15 for ethics, yielding an overall mean readiness score of 74±18.8 out of a possible 110. Readiness levels were found to be significantly associated with students’ year of study and were positively correlated with their attitudes towards artificial intelligence. Conclusion: The findings suggest that physical therapy students generally possess positive attitudes and strong technical abilities regarding artificial intelligence. However, gaps remain in cognitive understanding and ethical awareness. While gender differences were not significant, lower readiness levels were noted among third- and fifth-year students. Strengthening educational efforts in artificial intelligence, cognition, and ethics is recommended for more effective integration into physical therapy education.