Perceptions for Utilization of Artificial Intelligence among Early Pediatric Rehabilitation Practitioners: A Survey in Pakistan: Utilization of Artificial Intelligence among Early Pediatric Rehabilitation Practitioners

Samreen Sadiq; Shazia Rizwan; Syed Asadullah Arslan; . Rabeya; Sobia Qamar; Sobia Shahalam

doi:10.54393/pjhs.v5i09.1973

Authors

Samreen Sadiq Faculty of Rehabilitation Sciences, University of Biological and Applied Sciences, Lahore, Pakistan
Shazia Rizwan Department of Pediatric Medicine, Lahore Medical and Dental College, Ghurki Trust Teaching Hospital, Lahore, Pakistan
Syed Asadullah Arslan Faculty of Rehabilitation Sciences, University of Biological and Applied Sciences, Lahore, Pakistan
. Rabeya Department of Pediatrics, Sargodha Medical College, Sargodha, Pakistan
Sobia Qamar Department of Pediatric Medicine, University of Child Health Sciences, Children Hospital, Lahore, Pakistan
Sobia Shahalam Department of Pediatric Medicine, Lahore Medical and Dental College, Ghurki Trust Teaching Hospital, Lahore, Pakistan

DOI:

https://doi.org/10.54393/pjhs.v5i09.1973

Keywords:

Artificial Intelligence, Benefits, Knowledge, Rehabilitation

Abstract

Integration of Artificial Intelligence in clinical medicine is rapidly expanding, driven by advancements in computing and extensive datasets. Artificial Intelligence is primarily utilized to design diagnostic tools for numerous medical conditions. Objective: To assess perceptions of using Artificial Intelligence among early pediatric rehabilitation practitioners in Pakistan. Methods: A cross-sectional online survey was conducted from November 2023 to April 2024, targeting young Masters students of Physical Therapy specializing in Pediatric Care and early pediatric therapists across Pakistan. Nonprobability convenience sampling was utilized. Participants were recruited through mailing lists and social media platforms. The anonymous survey collected demographic data and explored participants' knowledge, expected benefits, fears, and practices regarding Artificial Intelligence using a structured questionnaire. Descriptive statistics were employed for data analysis. Results: A total of 120 participants, with a mean age of 26 years and 70% female representation, completed the survey. Approximately 39.1% had received Artificial Intelligence training during their medical education, and 48.3% had utilized Artificial Intelligence tools during their learning. Key findings included 93.3% believing that Artificial Intelligence will enhance medical training and 60.8% agreeing that Artificial Intelligence will improve healthcare access. Despite positive attitudes towards AI, 54.1% had not utilized AI in their practice, indicating a need for further professional education. Conclusion: It was concluded that the study highlights a generally positive perception of Artificial Intelligence among novice pediatric rehabilitation practitioners in Pakistan but underscores the need for comprehensive AI education and training.

References

Sheikh H, Prins C, Schrijvers E. Artificial intelligence: Definition and Background. In mission AI: The New System Technology. Cham: Springer International Publishing. 2023 Jan: 15-41. doi: 10.1007/978-3-031-21448-6_2.

Topol EJ. High-Performance Medicine: The Convergence of Human and Artificial Intelligence. Nature Medicine. 2019 Jan; 25(1): 44-56. doi: 10.1038/s41591-018-0300-7.

Hoodbhoy Z, Masroor Jeelani S, Aziz A, Habib MI, Iqbal B, Akmal W et al. Machine Learning for Child and Adolescent Health: A Systematic Review. Pediatrics. 2021 Jan: 147(1). doi: 10.1542/peds.2020-011833.

Butt SA, Sadaqat AS, Rana AR, Khan TK, Nabi MS, Afzal RA et al. Knowledge of Artificial Intelligence and Its Applications in Health Care Workers. Journal of Akhtar Saeed Medical and Dental College. 2024 Jul: 6(01).

Khalid UB, Naeem M, Stasolla F, Syed MH, Abbas M, Coronato A. Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends. International Journal of General Medicine. 2024 Dec; 7: 943-69. doi: 10.2147/IJGM.S453903.

Zavrsnik J, Kokol P, Zlahtic B, Blazun Vosner H. Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis. Electronics. 2024 Jan; 13(3): 512. doi: 10.3390/electronics13030512.

Dias R and Torkamani A. Artificial Intelligence in Clinical and Genomic Diagnostics. Genome Medicine. 2019 Nov; 11(1): 70. doi: 10.1186/s13073-019-0689-8.

Levy S, Duda M, Haber N, Wall DP. Sparsifying Machine Learning Models Identify Stable Subsets of Predictive Features for Behavioral Detection of Autism. Molecular Autism. 2017 Dec: 8:1-7. doi: 10.1186/s13229-017-0180-6.

Gülşen M and Yalçın SS. Fostering Tomorrow: Uniting Artificial Intelligence and Social Pediatrics for Comprehensive Child Well-being. Turkish Archives of Pediatrics. 2024 Jul: 59(4). doi: 10.5152/TurkArchPediatr.2024.24076.

Liang H, Tsui BY, Ni H, Valentim CC, Baxter SL, Liu G et al. Evaluation and Accurate Diagnoses of Pediatric Diseases Using Artificial Intelligence. Nature Medicine. 2019 Mar; 25(3): 433-8. doi:10.1038/s41591-018-0335-9.

Wolf RM, Channa R, Liu TA, Zehra A, Bromberger L, Patel D et al. Autonomous Artificial Intelligence Increases Screening and Follow-Up For Diabetic Retinopathy in Youth: The ACCESS Randomized Control Trial. Nature Communications. 2024 Jan; 15(1): 421. doi: 10.1038/s41467-023-44676-z.

Shu LQ, Sun YK, Tan LH, Shu Q, Chang AC. Application of Artificial Intelligence in Pediatrics: Past, Present and Future. World Journal of Pediatrics. 2019 Apr; 15: 105-8. doi: 10.1007/s12519-019-00255-1.

Sit C, Srinivasan R, Amlani A, Muthuswamy K, Azam A, Monzon L et al. Attitudes and Perceptions of UK Medical Students Towards Artificial Intelligence and Radiology: A Multicentre Survey. Insights into Imaging. 2020 Dec; 11: 1-6. doi: 10.1186/s13244-019-0830-7.

Dwivedi YK, Hughes L, Ismagilova E, Aarts G, Coombs C, Crick T et al. Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy. International Journal of Information Management. 2021 Apr; 57: 101994. doi: 10.1016/j.ijinfomgt.2019.08.002.

Konopik J and Blunck D. Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review. Journal of Medical Internet Research. 2023 Jun; 25: e41512. doi: 10.2196/41512.

Ahmed Z, Bhinder KK, Tariq A, Tahir MJ, Mehmood Q, Tabassum MS et al. Knowledge, Attitude, and Practice of Artificial Intelligence Among Doctors and Medical Students in Pakistan: A Cross-Sectional Online Survey. Annals of Medicine and Surgery. 2022 Apr; 76: 103493. doi: 10.1016/j.amsu.2022.103493.

Zawacki-Richter O, Bai JY, Lee K, Slagter van Tryon PJ, Prinsloo P. New Advances in Artificial Intelligence Applications in Higher Education? International Journal of Educational Technology in Higher Education. 2024 May; 21(1): 32. doi: 10.1186/s41239-024-00464-3.

Wen Z and Huang H. The Potential for Artificial Intelligence in Healthcare. Journal of Commercial Biotechnology. 2022 Dec: 27(4). doi: 10.5912/jcb1327.

Richardson JP, Smith C, Curtis S, Watson S, Zhu X, Barry B et al. Patient Apprehensions About the Use of Artificial Intelligence in Healthcare. Nature Partner Journal Digital Medicine. 2021 Sep; 4(1): 140. doi: 10.1038/s41746-021-00509-1.

Abbasi N, Nizamullah FN, Zeb S. AI in Healthcare: Integrating Advanced Technologies with Traditional Practices for Enhanced Patient Care. BULLET: Jurnal Multidisiplin Ilmu. 2023 Jun; 2(3): 546-56.