Geleceğe Hazır mıyız? Fizyoterapi ve Rehabilitasyon Öğrencilerinin Yapay Zekâya Yönelik Tutumları ve Yapay Zekâ Okuryazarlığı

Abstract

Amaç: Bu araştırma, fizyoterapi ve rehabilitasyon öğrencilerinin yapay zekâya (YZ) yönelik tutumlarını, YZ okuryazarlık düzeylerini ve bunlarla ilişkili faktörleri incelemeyi amaçlamıştır. Gereç ve Yöntem: Araştırma 431 fizyoterapi ve rehabilitasyon öğrencisi (yaş ortalaması, 20,97±2,52 yıl) ile yürütülmüştür. Öğrencilerin, YZ farkındalık ve görüşleri, literatür taranarak hazırlanan sorularla, YZ tutumları Yapay Zekaya Yönelik Genel Tutum Ölçeği ile, YZ okuryazarlığı Yapay Zekâ Okuryazarlık Ölçeği ile değerlendirilmiştir. İki grup arasındaki ölçüm değerlerinin karşılaştırılmasında bağımsız gruplarda t testi, ikiden fazla grupta ölçüm değerlerinin karşılaştırılmasında tek yönlü varyans analizi kullanılmıştır. Bulgular: Öğrencilerin %70’i sağlık ve sağlık sisteminde YZ teknolojilerinden haberdar olup %80’i ChatGPT/Gemini gibi YZ teknolojilerini kullanmaktadır. Öğrencilerin çoğu YZ’yi ödev, sınav, sunum hazırlama için, hız ve kolaylık sağlaması nedeni ile tercih etmektedir. YZ’ye yönelik pozitif tutum ve negatif tutumun (ortalama puan sırasıyla: 41,35±6.83, 24,22±5,21) ve YZ okuryazarlık (ortalama puan, 45,25±7,98) düzeyinin sınıf ve günlük internet kullanım süresine göre değişmediği bulunmuştur (p>0,05). Cinsiyete göre YZ okuryazarlık düzeyinde anlamlı bir fark yoktur. YZ’ye yönelik tutum cinsiyete göre değişmektedir, erkek öğrencilerin YZ’ye yönelik pozitif tutumu daha yüksektir (p=0,001). Öğrencilerin %85’i YZ gibi teknolojik gelişmeleri öğrenmeye ve kullanmaya istekli olduğunu belirtmiştir. Diğer yandan, öğrencilerin %40’ı YZ’nin yaygınlaşmasıyla mesleklerinin yok olacağı, %42’si ise YZ’nin gelecekte iş bulmalarını tehlikeye sokacağı konusunda kararsızdır. Öğrencilerin %83’ü YZ’nin ders müfredatına eklenmesi gerektiğini düşünmektedir. Sonuç: Çalışmamız, fizyoterapi ve rehabilitasyon öğrencilerinin YZ’nin sağlık alanındaki potansiyelini fark ettiğini ve bu teknolojiye yönelik olumlu bir tutum sergilediğini ortaya koymuştur. Ancak, öğrencilerin YZ okuryazarlık düzeyleri orta seviyede olup, öğrenciler YZ’nin meslek hayatları üzerindeki etkileri konusunda belirsizlikler yaşamaktadır. Fizyoterapi ve rehabilitasyon öğrencilerinin YZ okuryazarlığını geliştirmek için, fizyoterapi ve rehabilitasyon eğitimi müfredatlarına temel YZ kavramlarını, veri analizi yöntemlerini ve rehabilitasyonda YZ destekli araçların kullanımını içeren dersler eklenebilir. Anahtar Kelimeler: Fizyoterapi, okuryazarlık, öğrenci, sağlık, tutum, yapay zekâ

Keywords

• fizyoterapi
• yapay zeka
• okuryazarlık
• öğrenci
• sağlık
• tutum

Are We Ready for the Future? Physiotherapy and Rehabilitation Students' Attitudes Towards Artificial Intelligence and Artificial Intelligence Literacy

Abstract

Objective: This study aimed to investigate the attitudes of physical therapy and rehabilitation students towards artificial intelligence (AI), their AI literacy levels, and the factors associated with these. Material and Method: The study was conducted with 431 physical therapy ve rehabilitation students (mean age, 20.97 ± 2.52 years). Students' AI awareness and opinions were assessed with questions prepared by reviewing the literature, their attitudes towards AI were assessed with the General Attitude Towards Artificial Intelligence Scale, and their AI literacy was assessed with the Artificial Intelligence Literacy Scale. Independent samples t-test was used to compare the measurement values between two groups, and one-way analysis of variance was used to compare the measurement values between more than two groups. Results: 70% of the students were aware of AI technologies in health and the healthcare system, and 80% of them used AI technologies such as ChatGPT/Gemini. Most students prefer AI for assignments, exams, etc., because it provides speed and convenience. It was found that positive and negative attitudes towards AI (mean scores: 41.35 ± 6.83, 24.22 ± 5.21, respectively) and AI literacy level (mean score, 45.25 ± 7.98) did not differ according to class and daily internet usage (p>0.05). Attitude towards AI differed according to gender (p=0.001). 85% of the students stated that they were willing to learn and use technological developments such as AI. On the other hand, 40% of the students are undecided about whether their profession will disappear with the widespread use of AI, and 42% are undecided about whether AI will jeopardize their future job prospects. 83% of the students think that AI should be added to the curriculum. Conclusion: Our study revealed that physical therapy students are aware of the potential of AI in the health field and have a positive attitude towards this technology. However, the students' AI literacy levels are at an intermediate level, and students have uncertainties about the effects of AI on their professional lives. To improve the AI literacy of physical therapy students, basic AI concepts, data analysis methods, and the use of AI-supported tools in rehabilitation can be added to the physical therapy curriculum. Keywords: Physical therapy, literacy, student, health, attitude, artificial intelligence.

Keywords

• physical therapy
• literacy
• student
• health
• attitude
• artificial intelligence

References

1. 1. Panch T, Szolovits P, Atun R. Artificial intelligence, machine learning and health systems. J Glob Health. 2018 Oct; 8(2): 020303.
2. 2. Huang J, Saleh S ,Liu Y. A review on artificial intelligence in education. Acad J Interdiscip Stud. 2021 May; 10(3): 206-217.
3. 3. Luan H, Geczy P, Lai H, Gobert J, Yang S J, Ogata H, et al. Challenges and future directions of big data and artificial intelligence in education. Front Psychol. 2020 Oct; 11: 580820.
4. 4. Chen L, Chen P ,Lin Z. Artificial intelligence in education: A review. IEEE Access. 2020 Apr; 8: 75264-75278.
5. 5. Yuskovych-Zhukovska V, Poplavska T, Diachenko O, Mishenina T, Topolnyk Y, Gurevych R. Application of artificial intelligence in education. Problems and opportunities for sustainable development. Broad Res Artif Intell Neurosci. 2022 Feb; 13(1): 339-356.
6. 6. Yu H. Reflection on whether Chat GPT should be banned by academia from the perspective of education and teaching. Front Psychol. 2023 Jun; 14: 1181712.
7. 7. Shidiq M. The use of artificial intelligence-based chat-gpt and itschallenges for the world of education; from the viewpoint of the development of creative writing skills. ICHES. 2023 May; 1(1):353-357.
8. 8. Laupichler M C, Aster A, Schirch J ,Raupach T. Artificial intelligence literacy in higher and adult education: A scoping literature review. Comput Educ Artif Intell. 2022 Sep; 3: 100101.

9. 9. Hornberger M, Bewersdorff A ,Nerdel C. What do university students know about Artificial Intelligence? Development and validation of an AI literacy test. Comput Educ Artif Intell. 2023 Sep; 5: 100165.
10. 10. Ramanandi V H. Role and scope of artificial intelligence in physiotherapy: A scientific review of literature. Int J Adv Sci Res. 2021 Oct; 6(1): 11-14.
11. 11. Davids J, Lidströmer N ,Ashrafian H. Artificial ıntelligence for physiotherapy and rehabilitation. In: Lidströmer N, Ashrafian H, editors. Artificial Intelligence in Medicine. Cham: Springer; 2022. p. 1789-1807.
12. 12. Oakden-Rayner L. Reply to 'Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists' by Haenssle et al. Ann Oncol. 2019 May; 30(5): 854.
13. 13. Lau A Y ,Staccini P. Artificial intelligence in health: new opportunities, challenges, and practical implications. Yearb Med Inform. 2019 Aug; 28(01): 174-178.
14. 14. Mohapatra A, Mohanty P, Pattnaik M ,Padhan S. Physiotherapy in the digital age: A narrative review of the paradigm shift driven by the integration of artificial intelligence and machine learning. Physiotherapy (J Indian Assoc Physiotherapists). 2024 Dec: 18 (2): 63-71
15. 15. Stewart J, Lu J, Gahungu N, Goudie A, Fegan P G, Bennamoun M, et al. Western Australian medical students’ attitudes towards artificial intelligence in healthcare. PLoS One. 2023 Aug; 18(8): e0290642.
16. 16. Sapci A H ,Sapci H A. Artificial intelligence education and tools for medical and health informatics students: systematic review. JMIR Med Educ. 2020 Apr; 6(1): e19285.
17. 17. Teng M, Singla R, Yau O, Lamoureux D, Gupta A, Hu Z, et al. Health care students’ perspectives on artificial intelligence: countrywide survey in Canada. JMIR Med Educ. 2022 Sep; 8(1): e33390.
18. 18. Elçiçek M. Öğrencilerin yapay zekâ okuryazarlığı üzerine bir inceleme. BİTED. 2024 Haz; 6(1): 24-35.
19. 19. Gömleksiza M N ,Uğraşa H. Öğretim elemanlarinin teknostres düzeylerinin belirlenmesi. ERPA 2022 Sep: 176-182.
20. 20. Szolovits P. Artificial intelligence and medicine. New York: Routledge; c2019. 242 p.
21. 21. Haug C J ,Drazen J M. Artificial intelligence and machine learning in clinical medicine, 2023. NEJM. 2023 Mar; 388(13): 1201-1208.
22. 22. Pinto dos Santos D, Giese D, Brodehl S, Chon S-H, Staab W, Kleinert R, et al. Medical students' attitude towards artificial intelligence: a multicentre survey. Eur Radiol. 2019 Jul; 29: 1640-1646.
23. 23. Park C J, Paul H Y ,Siegel E L. Medical student perspectives on the impact of artificial intelligence on the practice of medicine. Curr Probl Diagn Radiol. 2021 Oct; 50(5): 614-619.
24. 24. Syed W ,Basil A. Al-Rawi M. Assessment of awareness, perceptions, and opinions towards artificial intelligence among healthcare students in Riyadh, Saudi Arabia. Medicina. 2023 Apr; 59(5): 828.
25. 25. Truong N M, Vo T Q, Tran H T B ,Nguyen H T. Healthcare students’ knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam. Heliyon. 2023 Dec; 9(12).
26. 26. Mart M ,Kaya G. Okul öncesi öğretmen adaylarının yapay zekâya yönelik tutumları ve yapay zekâ okur yazarlığı arasındaki ilişkinin incelenmesi. Edutech Res. 2024 Jun; 2(1): 91-109.
27. 27. Ronquillo C E, Peltonen L M, Pruinelli L, Chu C H, Bakken S, Beduschi A, et al. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021 May; 77(9): 3707-3717.
28. 28. Swan B A. Assessing the knowledge and attitudes of registered nurses about artificial ıntelligence in nursing and health care. Nurs Econ. 2021; 39(3): 139-143.
29. 29. Ahmed Z, Bhinder K K, Tariq A, Tahir M J, Mehmood Q, Tabassum M S, et al. Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: A cross-sectional online survey. Ann Med Surg. 2022 Apr; 76: 103493.
30. 30. Liu D S, Sawyer J, Luna A, Aoun J, Wang J, Boachie L, et al. Perceptions of US medical students on artificial intelligence in medicine: mixed methods survey study. JMIR Med Educ. 2022 Oct; 8(4): e38325.
31. 31. Özel Ş ,Büyükçavuş M H. Diş hekimliği öğrencilerinin diş hekimliğinde yapay zekâ uygulamaları ile ilgili düşüncelerinin incelenmesi. Yeditepe J Dent. 2022 Apr; 18(2): 55-60.
32. 32. Alsobhi M, Khan F, Chevidikunnan M F, 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 Oct; 24(10): e39565.
33. 33. Yüzbaşıoğlu E. Attitudes and perceptions of dental students towards artificial intelligence. J Dent Educ. 2021 Aug; 85(1): 60-68.
34. 34. Rowe M, Nicholls D A ,Shaw J. How to replace a physiotherapist: artificial intelligence and the redistribution of expertise. Physiother. Theory Pract. 2022 Jun; 38(13): 2275-2283.
35. 35. Tubaishat A. An investigation into the attitudes of nursing students toward technology. J Nurs Res. 2014 Jun; 22(2): 119-125.
36. 36. Kandemir F ,Azizoğlu F. Hemşirelerin yapay zekaya yönelik genel tutumlarının incelenmesi. Yoğun Bakım Hemş Derg. 2024 Jul; 28(2): 113-125.
37. 37. Gong B, Nugent J P, Guest W, Parker W, Chang P J, Khosa F, et al. Influence of Artificial ıntelligence on canadian medical students' preference for radiology specialty: anational survey study. Acad Radiol. 2019 Apr; 26(4): 566-577.
38. 38. 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 Imaging. 2020 Feb; 11(1): 14.
39. 39. Mehta N, Harish V, Bilimoria K, Morgado F, Ginsburg S, Law M, et al. Knowledge of and attitudes on artificial intelligence in healthcare: a provincial survey study of medical students. Medrxiv. 2021 Jan; 2021-01.
40. 40. Laï M C, Brian M, Mamzer M F. Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France. J Transl Med. 2020 Jan; 18(1): 14.
41. 41. Thompson R F, Valdes G, Fuller C D, Carpenter C M, Morin O, Aneja S, et al. Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation?. Radiother Oncol. 2018 Dec; 129(3): 421-426.