PERCEPTION OF ARTIFICIAL INTELLIGENCE AMONG PHYSICAL THERAPISTS OF PAKISTAN ALONG WITH ITS ETHICAL IMPLICATION

Authors

  • Rahila Anis University of Management and Technology, Lahore, Pakistan. Author
  • Ubaidullah khan University of Management and Technology, Lahore, Pakistan. Author
  • Sania Akram University of Management and Technology, Lahore, Pakistan. Author
  • Maida Mushtaq University of Management and Technology, Lahore, Pakistan. Author
  • Mahnoor Liaqat University of Management and Technology, Lahore, Pakistan. Author
  • Nadia Talib University of Management and Technology, Lahore, Pakistan. Author
  • Fatima Nasir University of Management and Technology, Lahore, Pakistan. Author

DOI:

https://doi.org/10.71000/ntbnmk15

Keywords:

Artificial Intelligence, Attitude of Health Personnel, Knowledge, Pakistan, Perception, Physical Therapists, Rehabilitation

Abstract

Background: Artificial intelligence (AI) is increasingly transforming rehabilitation practices by enhancing diagnostic accuracy, optimizing treatment planning, and reducing the workload of physiotherapists (PTs). In Pakistan, limited research has explored PTs’ awareness and perceptions of AI applications in rehabilitation. Understanding these perspectives is crucial for guiding integration strategies and addressing educational gaps in this evolving field.

Objective:  To evaluate the knowledge, attitudes, and perceptions of physiotherapists in Pakistan regarding the use of AI in rehabilitation, and to identify associated factors influencing awareness and acceptance.

Methods: A cross-sectional study was conducted between June and September 2023 using a validated four-part questionnaire (content validity index: 0.8) distributed via Google Forms and in paper format. The minimum sample size of 213 was calculated using G*Power (version 3.1.9.7), with a logistic regression model assuming an odds ratio of 1.5, α = 0.05, and 80% power. Inclusion criteria were licensed physiotherapists with ≥6 months of clinical or academic experience in Pakistan. Chiropractors, other healthcare professionals, and those unwilling to participate were excluded. Purposive sampling yielded 259 respondents. Data were analyzed using IBM SPSS version 25.0, applying descriptive statistics (frequency, percentage, mean ± SD) with p ≤ 0.05 considered significant.

Results: Among respondents, 65% were female and 35% male, with a mean age of 26.61 ± 3.56 years. Awareness of AI in rehabilitation was reported by 62.2%, with higher knowledge in those with <5 years of experience (72%) compared to >5 years (58%). Only 22% had used AI tools in clinical practice, while 78% had only heard of them. Most agreed AI could reduce workload (64%) and improve patient care (70%), yet 29% cited difficulty understanding its complexity. Importantly, 89.6% expressed willingness to learn more about AI, and 64% supported its inclusion in rehabilitation curricula.

Conclusion: Physiotherapists in Pakistan generally demonstrated positive perceptions toward AI in rehabilitation, though practical exposure and understanding remain limited. Targeted training and curriculum integration are recommended to enhance readiness for AI adoption.

Author Biographies

  • Rahila Anis, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Ubaidullah khan, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Sania Akram, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Maida Mushtaq, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Mahnoor Liaqat, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Nadia Talib, University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

  • Fatima Nasir , University of Management and Technology, Lahore, Pakistan.

    University of Management and Technology, Lahore, Pakistan.

References

Vélez-Guerrero MA, Callejas-Cuervo M, Mazzoleni S. Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review. Sensors (Basel). 2021;21(6).

Soin A, Hirschbeck M, Verdon M, Manchikanti L. A Pilot Study Implementing a Machine Learning Algorithm to Use Artificial Intelligence to Diagnose Spinal Conditions. Pain Physician. 2022;25(2):171-8.

Lee D, Yoon SN. Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. Int J Environ Res Public Health. 2021;18(1).

Lewandrowski KU, Elfar JC, Li ZM, Burkhardt BW, Lorio MP, Winkler PA, et al. The Changing Environment in Postgraduate Education in Orthopedic Surgery and Neurosurgery and Its Impact on Technology-Driven Targeted Interventional and Surgical Pain Management: Perspectives from Europe, Latin America, Asia, and The United States. J Pers Med. 2023;13(5):852.

Laï M-C, Brian M, Mamzer M-FJJotm. Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France. 2020;18(1):1-13.

Lewandrowski K-U, Elfar JC, Li Z-M, Burkhardt BW, Lorio MP, Winkler PA, et al. The Changing Environment in Postgraduate Education in Orthopedic Surgery and Neurosurgery and Its Impact on Technology-Driven Targeted Interventional and Surgical Pain Management: Perspectives from Europe, Latin America, Asia, and The United States. 2023;13(5):852.

Alsobhi M, Khan F, Chevidikunnan MF, Basuodan R, Shawli L, Neamatallah Z. Physical Therapists’ Knowledge and Attitudes Regarding Artificial Intelligence Applications in Health Care and Rehabilitation: Cross-sectional Study. J Med Internet Res. 2022;24(10):e39565.

Elshami W, Hegazy F, Aboelnasr E, Tekin H. The Impact of Artificial Intelligence (AI) in Physiotherapy Practice: A Study of Physiotherapist Willingness and Readiness. Journal of Hunan University Natural Sciences. 2022;49:196-201.

Abdullah R, Fakieh B. Health Care Employees’ Perceptions of the Use of Artificial Intelligence Applications: Survey Study. J Med Internet Res. 2020;22(5):e17620.

Alsobhi M, Sachdev HS, Chevidikunnan MF, Basuodan R, K UD, Khan F. Facilitators and Barriers of Artificial Intelligence Applications in Rehabilitation: A Mixed-Method Approach. Int J Environ Res Public Health. 2022;19(23).

Scheetz J, Rothschild P, McGuinness M, Hadoux X, Soyer HP, Janda M, et al. A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology. 2021;11(1):5193.

Shi M, Peng H, Lin Y, Ma Y, Qi Y. Perception Research of Artificial Intelligence in Environmental Public Health Physiotherapy Nursing for the Elderly. J Environ Public Health. 2022;2022:2124710.

Ali N, Abdrazaq A, Shah Z, Househ M. Artificial Intelligence-Based Mobile Application for Emotion Sensing for Children Through Art. Stud Health Technol Inform. 2022;290:1130-1.

Piette JD, Newman S, Krein SL, Marinec N, Chen J, Williams DA, et al. Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: A Randomized Comparative Effectiveness Trial. JAMA Intern Med. 2022;182(9):975-83.

Mahmoud H, Aljaldi F, El-Fiky A, Battecha K, Thabet A, Alayat M, et al. Artificial Intelligence machine learning and conventional physical therapy for upper limb outcome in patients with stroke: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2023;27(11):4812-27.

Gouverneur P, Li F, Shirahama K, Luebke L, Adamczyk WM, Szikszay TM, et al. Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition. Sensors. 2023;23(4):1959.

Luna A, Casertano L, Timmerberg J, O'Neil M, Machowsky J, Leu CS, et al. Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial. Sci Rep. 2021;11(1):18109.

Abuzaid MM, Elshami W, Hegazy F, Aboelnasr EA, Tekin HOJJoHUNS. The Impact of Artificial Intelligence (AI) in Physiotherapy Practice: A Study of Physiotherapist Willingness and Readiness. 2022;49(3).

Vourganas I, Stankovic V, Stankovic L. Individualised Responsible Artificial Intelligence for Home-Based Rehabilitation. Sensors (Basel). 2020;21(1).

Shahzad SAB, Shahid I, Nouman M, Anis R, Asif S, Khan MU. A COMPARATIVE STUDY REGARDING THE PERCEPTION OF PHYSICAL THERAPIST AND PHYSICAL THERAPY STUDENTS ABOUT USABILITY OF ARTIFICIAL INTELLIGENCE CHATBOT I.E, OPENAI-CHATGPT FOR THE RETRIEVAL OF INFORMATION IN ACADEMIC AND CLINICAL SETTINGS. Biological and Clinical Sciences Research Journal. 2024;2024(1):973.

Alsobhi M, Khan F, Chevidikunnan MF, Basuodan R, Shawli L, Neamatallah Z. Physical Therapists' Knowledge and Attitudes Regarding Artificial Intelligence Applications in Health Care and Rehabilitation: Cross-sectional Study. J Med Internet Res. 2022;24(10):e39565.

Abdullah R, Fakieh B. Health Care Employees' Perceptions of the Use of Artificial Intelligence Applications: Survey Study. J Med Internet Res. 2020;22(5):e17620.

Fernandes LG, Oliveira RFF, Barros PM, Fagundes FRC, Soares RJ, Saragiotto BT. Physical therapists and public perceptions of telerehabilitation: An online open survey on acceptability, preferences, and needs. Braz J Phys Ther. 2022;26(6):100464.

Kang H, Huh S. Sample size determination and power analysis using the G*Power software. jeehp. 2021;18(0):17-0.

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Published

2025-08-06

How to Cite

1.
Rahila Anis, Ubaidullah khan, Sania Akram, Maida Mushtaq, Mahnoor Liaqat, Nadia Talib, et al. PERCEPTION OF ARTIFICIAL INTELLIGENCE AMONG PHYSICAL THERAPISTS OF PAKISTAN ALONG WITH ITS ETHICAL IMPLICATION. IJHR [Internet]. 2025 Aug. 6 [cited 2025 Aug. 28];3(4 (Health and Rehabilitation):474-81. Available from: https://insightsjhr.com/index.php/home/article/view/1221