Knowledge, Attitude, and Practices of Artificial Intelligence in Undergraduate and Postgraduate Physical Therapy Students

Muqadas Attiqe; Fajar Arif; Wajida Perveen; Suneeq Ahmad Bin Shahzad; Yasha Sajjad; Umer Ilyas

doi:10.55735/tg4rxc70

Authors

Muqadas Attiqe Department of Physical Therapy, School of Allied Health Sciences, CMH Lahore Medical College & IOD (NUMS), Lahore, Pakistan https://orcid.org/0009-0006-8694-2454
Fajar Arif Department of Physical Therapy, School of Allied Health Sciences, CMH Lahore Medical College & IOD (NUMS), Lahore, Pakistan https://orcid.org/0009-0004-1854-5452
Wajida Perveen Department of Physical Therapy, School of Allied Health Sciences, CMH Lahore Medical College & IOD (NUMS), Lahore, Pakistan https://orcid.org/0000-0002-4833-0928
Suneeq Ahmad Bin Shahzad Rehab Sage Physiotherapy, Lahore, Pakistan https://orcid.org/0009-0001-8186-2299
Yasha Sajjad Department of Physical Therapy, School of Allied Health Sciences, CMH Lahore Medical College & IOD (NUMS), Lahore, Pakistan https://orcid.org/0000-0001-6084-3761
Umer Ilyas Department of Physical Therapy, School of Allied Health Sciences, CMH Lahore Medical College & IOD (NUMS), Lahore, Pakistan https://orcid.org/0000-0001-9950-7829

DOI:

https://doi.org/10.55735/tg4rxc70

Keywords:

Artificial intelligence , Attitude , Knowledge , Practice , Physiotherapy students

Abstract

Background: Artificial intelligence has grown in prominence over the last few decades, and its use in medicine is spreading throughout the world. The adoption of AI-based healthcare solutions is lagging in Pakistan and other developing countries. Objective: To analyze the knowledge, attitudes, and practices of Pakistani undergraduate and graduate physiotherapy students about artificial intelligence. Methodology: This multicentre analytical cross-sectional study was conducted six months after ethical approval, including participants from CMH Lahore Medical College & Institute of Dentistry, Lahore, University of Lahore, University of South Asia, University of Management and Technology, Lahore, and Riphah International University, Lahore. Non-probability convenience sampling was used to include both male and female undergraduate, graduate, and postgraduate physiotherapy students aged 18 to 45 years, from 1^st to 5^th year undergraduate and 1st and 2nd year postgraduate physiotherapy students. While students enrolled in other medical and allied health sciences programs, MBBS and BDS students were excluded from this study. Data collection commenced after obtaining ethical approval, and informed consent was obtained from every participant. Data were collected by online survey and by distributing the questionnaires to physiotherapy students wherever possible. Frequencies and percentages are used to express descriptive statistics. Frequencies and percentages are used for categorical values. Results: Approximately 92% of physiotherapists were aware of artificial intelligence. Of these, 45.6% believed that it should be taught in medical schools, as it is essential to the medical field. Almost 31.4% of respondents think artificial intelligence can enhance the therapeutic relationship between patients and therapists. About 58.6% reported that using AI technologies in their employment had made their jobs easier. However, just 14.5% of students claimed that using AI was simple. Conclusion: Most students had some knowledge of artificial intelligence, and many respondents expressed interest in working on AI-related projects in the future. These findings demonstrate the high level of interest, optimistic outlook, and potential of integrating artificial intelligence in the physiotherapy sector.

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