Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design, Setting, and Population
2.2. Designing of the Questionnaires
2.3. Statistical Analysis
3. Results
3.1. Sociodemographic Characteristics
3.2. Awareness of Students about Artificial Intelligence (AI)
3.3. Perceptions of Students about AI
3.4. Opinions about Artificial Intelligence (AI)
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Webster, C.S. Artificial intelligence and the adoption of new technology in medical education. Med. Educ. 2021, 55, 6–7. [Google Scholar] [CrossRef]
- Arel, I.; Rose, D.C.; Karnowski, T.P. Deep machine learning-a new frontier in artificial intelligence research [research frontier]. IEEE Comput. Intell. Mag. 2010, 5, 13–18. [Google Scholar] [CrossRef]
- Miotto, R.; Wang, F.; Wang, S.; Jiang, X.; Dudley, J.T. Deep learning for healthcare: Review, opportunities, and challenges. Brief Bioinf. 2018, 19, 1236–1246. [Google Scholar] [CrossRef] [PubMed]
- OED Oxford English Dictionary. Artificial Intelligence. Available online: https://www.oed.com/viewdictionaryentry/Entry/271625 (accessed on 27 December 2022).
- Mirza, A.A.; Wazgar, O.M.; Almaghrabi, A.A.; Ghandour, R.M.; Alenizi, S.A.; Mirza, A.A.; Alraddadi, K.S.; Al-Adwani, F.H.; Alsakkaf, M.A.; Aljuaid, S.M. The Use of Artificial Intelligence in Medical Imaging: A Nationwide Pilot Survey of Trainees in Saudi Arabia. Clin. Pract. 2022, 12, 852–866. [Google Scholar] [CrossRef] [PubMed]
- Ting, D.S.W.; Pasquale, L.R.; Peng, L.; Campbell, J.P.; Lee, A.Y.; Raman, R.; Tan, G.S.W.; Schmetterer, L.; Keane, P.A.; Wong, T.Y. Artificial intelligence and deep learning in ophthalmology. Br. J. Ophthalmol. 2019, 103, 167–175. [Google Scholar] [CrossRef]
- Edubirdie. Essay on Artificial Intelligence: Critical Analysis of the Chinese Room. (14 July 2022). Retrieved 14 April 2023. Available online: https://edubirdie.com/examples/essay-on-artificial-intelligence-critical-analysis-of-the-chinese-room/ (accessed on 23 April 2023).
- Esteva, A.; Robicquet, A.; Ramsundar, B.; Kuleshov, V.; DePristo, M.; Chou, K.; Cui, C.; Corrado, G.; Thrun, S.; Dean, J. A guide to deep learning in healthcare. Nat. Med. 2019, 25, 24–29. [Google Scholar] [CrossRef]
- Kermany, D.S.; Goldbaum, M.; Cai, W.; Valentim, C.C.S.; Liang, H.; Baxter, S.L.; McKeown, A.; Yang, G.; Wu, X.; Yan, F.; et al. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning. Cell 2018, 172, 1122–1131.e9. [Google Scholar] [CrossRef]
- Reznick, R.K.; Harris, K.; Horsley, T. Task Force Report on Artificial Intelligence and Emerging Digital Technologies. 2020. Available online: https://www.royalcollege.ca/rcsite/health-policy/initiatives/ai-task-force-e (accessed on 21 February 2022).
- Tang, A.; Tam, R.; Cadrin-Chênevert, A.; Guest, W.; Chong, J.; Barfett, J.; Chepelev, L.; Cairns, R.; Mitchell, J.R.; Cicero, M.D.; et al. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology. Can. Assoc. Radiol. J. 2018, 69, 120–135. [Google Scholar] [CrossRef]
- Eltorai, A.E.M.; Bratt, A.K.; Guo, H.H. Thoracic Radiologists’ Versus Computer Scientists’ Perspectives on the Future of Artificial Intelligence in Radiology. J. Thorac. Imaging 2020, 35, 255–259. [Google Scholar] [CrossRef]
- Qurashi, A.A.; Alanazi, R.K.; Alhazmi, Y.M.; Almohammadi, A.S.; Alsharif, W.M.; Alshamrani, K.M. Saudi Radiology Personnel’s Perceptions of Artificial Intelligence Implementation: A Cross-Sectional Study. J. Multidiscip. Healthc. 2021, 14, 3225–3231. [Google Scholar] [CrossRef]
- Abuzaid, M.M.; Elshami, W.; McConnell, J.; Tekin, H.O. An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice. Health Technol. 2021, 11, 1045–1050. [Google Scholar] [CrossRef] [PubMed]
- Tajaldeen, A.; Alghamdi, S. Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: A survey-based study. Acta Radiol. Open 2020, 9, 20–58. [Google Scholar] [CrossRef] [PubMed]
- Ooi, S.K.G.; Makmur, A.; Soon, A.Y.Q.; Fook-Chong, S.; Liew, C.; Sia, S.Y.; Ting, Y.H.; Lim, C.Y. Attitudes toward artificial intelligence in radiology with learner needs assessment within radiology residency programs: A national multi-program survey. Singap. Med. J. 2021, 62, 126–134. [Google Scholar] [CrossRef] [PubMed]
- Abuzaid, M.M.; Elshami, W.; Tekin, H.; Issa, B. Assessment of the Willingness of Radiologists and Radiographers to Accept the Integration of Artificial Intelligence into Radiology Practice. Acad. Radiol. 2022, 29, 87–94. [Google Scholar] [CrossRef]
- Coppola, F.; Faggioni, L.; Regge, D.; Giovagnoni, A.; Golfieri, R.; Bibbolino, C.; Miele, V.; Neri, E.; Grassi, R. Artificial intelligence: Radiologists’ expectations and opinions gleaned from a nationwide online survey. Radiol. Med. 2021, 126, 63–71. [Google Scholar] [CrossRef] [PubMed]
- Collado-Mesa, F.; Alvarez, E.; Arheart, K. The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program. J. Am. Coll. Radiol. 2018, 15, 1753–1757. [Google Scholar] [CrossRef]
- Chen, M.; Zhang, B.; Cai, Z.; Seery, S.; Gonzalez, M.J.; Ali, N.M.; Ren, R.; Qiao, Y.; Xue, P.; Jiang, Y. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Front. Med. 2022, 9, 990604. [Google Scholar] [CrossRef]
- Global Australia. Artificial Intelligence (AI). Available online: https://www.globalaustralia.gov.au/industries/digitech/artificial-intelligence (accessed on 18 April 2023).
- Kassam, A.; Kassam, N. Artificial intelligence in healthcare: A Canadian context. In Healthcare Management Forum; SAGE Publications: Sage, CA, USA; Los Angeles, CA, USA, 2020; Volume 33, pp. 5–9, No. 1. [Google Scholar]
- Teng, M.; Singla, R.; Yau, O.; Lamoureux, D.; Gupta, A.; Hu, Z.; Hu, R.; Aissiou, A.; Eaton, S.; Hamm, C.; et al. Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada. JMIR Med. Educ. 2022, 8, e33390. [Google Scholar] [CrossRef]
- Li, R.; Yang, Y.; Wu, S.; Huang, K.; Chen, W.; Liu, Y.; Lin, H. Using artificial intelligence to improve medical services in China. Ann. Transl. Med. 2020, 8, 711. [Google Scholar] [CrossRef]
- Syed, W.; Samarkandi, O.A.; Alsadoun, A.; Harbi, M.K.A.; Al-Rawi, M.B.A. Evaluation of clinical knowledge and perceptions about the development of thyroid cancer-An observational study of healthcare undergraduates in Saudi Arabia. Front. Public Health 2022, 10, 912424. [Google Scholar] [CrossRef]
- Kolachalama, V.B.; Garg, P.S. Machine learning and medical education. NPJ Digit. Med. 2018, 1, 54. [Google Scholar] [CrossRef]
- Singh, R.P.; Hom, G.L.; Abramoff, M.D.; Campbell, J.P.; Chiang, M.F. Current challenges and barriers to real-world artificial intelligence adoption for the healthcare system, provider, and the patient. Transl. Vis. Sci. Technol. 2020, 9, 45. [Google Scholar] [CrossRef] [PubMed]
- Khanagar, S.; Alkathiri, M.; Alhamlan, R.; Alyami, K.; Alhejazi, M.; Alghamdi, A. Knowledge, attitudes, and perceptions of dental students towards artificial intelligence in Riyadh, Saudi Arabia. Med. Sci. 2021, 25, 1857–1867. [Google Scholar]
- Jha, N.; Shankar, P.R.; Al-Betar, M.A.; Mukhia, R.; Hada, K.; Palaian, S. Undergraduate Medical Students’ and Interns’ Knowledge and Perception of Artificial Intelligence in Medicine. Adv. Med. Educ. Pract. 2022, 13, 927–937. [Google Scholar] [CrossRef] [PubMed]
- Ahmed, Z.; Bhinder, K.K.; Tariq, A.; Tahir, M.J.; Mehmood, Q.; Tabassum, M.S.; Malik, M.; Aslam, S.; Asghar, M.S.; Yousaf, Z. Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: A cross-sectional online survey. Ann. Med. Surg. 2022, 76, 103493. [Google Scholar] [CrossRef]
- Liu, D.S.; Sawyer, J.; Luna, A.; Aoun, J.; Wang, J.; Boachie, L.; Halabi, S.; Joe, B. Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study. JMIR Med. Educ. 2022, 8, e38325. [Google Scholar] [CrossRef]
- Bhattamisra, S.K.; Banerjee, P.; Gupta, P.; Mayuren, J.; Patra, S.; Candasamy, M. Artificial Intelligence in Pharmaceutical and Healthcare Research. Big Data Cogn. Comput. 2023, 7, 10. [Google Scholar] [CrossRef]
- Henstock, P.V. Artificial intelligence for pharma: Time for internal investment. Trends Pharmacol. Sci. 2019, 40, 543–546. [Google Scholar] [CrossRef]
- Momattin, H.; Arafa, S.; Momattin, S.; Rahal, R.; Waterson, J. Robotic Pharmacy Implementation and Outcomes in Saudi Arabia: A 21-Month Usability Study. JMIR Hum. Factors 2021, 8, e28381. [Google Scholar] [CrossRef]
- Raza, M.A.; Aziz, S.; Noreen, M.; Saeed, A.; Anjum, I.; Ahmed, M.; Raza, S.M. Artificial Intelligence (AI) in Pharmacy: An Overview of Innovations. Innov. Pharm. 2022, 13, 13. [Google Scholar] [CrossRef]
Variables | Frequency (n) | Percentage (%) |
---|---|---|
Gender | ||
Male | 118 | 75.2% |
Female | 39 | 24.8% |
Age | ||
18–22 | 101 | 64.3% |
23–25 | 52 | 33.1% |
26–30 | 4 | 2.5% |
Nationality | ||
Saudi | 153 | 97.5% |
Non-Saudi | 4 | 2.5% |
Level/year of study | ||
Fourth-year | 65 | 41.45 |
Fifth year | 36 | 22.9% |
Internship | 56 | 35.7% |
Variables | Frequency | Percentage |
---|---|---|
Do you think that Artificial intelligence will replace the physician, pharmacist, or nurse in the healthcare system? | ||
Agree | 28 | 17.8% |
Disagree | 20 | 12.7% |
It is a tool that helps healthcare professionals | 109 | 69.4% |
What is your opinion, if artificial intelligence is widespread in Saudi Arabia? | ||
Risk of losing jobs with the introduction of robots (Artificial intelligence) with the decrease in the need for employees | 39 | 24.8% |
Healthcare professionals will be better with the widespread use of artificial intelligence. | 90 | 57.3% |
The choice of specialization Field will be influenced by how artificial intelligence is used in that Field | 16 | 10.2% |
I don’t know | 12 | 7.6% |
Have you received any formal education about artificial intelligence? | ||
Yes | 16 | 10.2% |
No | 126 | 80.3% |
Received training over the internet | 4 | 2.5% |
Through seminars and presentations | 11 | 7.0% |
Variables | Strongly Agree n (%) | Agree n (%) | Neutral n (%) | Disagree n (%) | Strongly Disagree n (%) |
---|---|---|---|---|---|
Artificial intelligence (AI) devalues the medical profession | 24 (15.3%) | 12 (7.6%) | 48 (30.6%) | 52 (33.1%) | 21 (13.4%) |
Artificial intelligence (AI) reduces errors in medical practice | 41 (26.1%) | 77 (49.0%) | 24 (15.3%) | 8 (5.1%) | 7 (4.5%) |
Artificial intelligence (AI) facilitates patients’ access to the service | 39 (24.8%) | 60 (38.2%) | 46 (29.3%) | 8 (5.1%) | 4 (2.5%) |
Artificial intelligence (AI) facilitates healthcare professionals’ access to information | 66 (42.0%) | 56 (35.7%) | 35 (22.3%) | 0 (0%) | 0 (0%) |
Artificial intelligence (AI) enables healthcare professionals to make more accurate decisions | 60 (38.2%) | 70 (44.6%) | 27 (17.2%) | 0 (0%) | 0 (0%) |
Artificial intelligence increases patients’ confidence in medicine | 16 (10.2%) | 41 (26.1%) | 80 (51%) | 15 (9.6)% | 5 (3.2%) |
Artificial intelligence facilitates patient education | 17 (10.8%) | 72 (45.9%) | 48 (30.6%) | 11 (7.0%) | 9 (5.7%) |
Artificial intelligence negatively affects the relationship between healthcare professionals the patient | 22 (14%) | 23 (14.6%) | 72 (45.9%) | 28 (17.8%) | 12 (7.6%) |
Artificial intelligence damages the trust which is the basis of the patient-healthcare professional’s relationship | 25 (15.9%) | 27 (17.2%) | 63 (40.1%) | 30 (19.1%) | 12 (7.6%) |
Artificial intelligence reduces the humanistic aspect of the medical profession. | 33 (21%) | 46 (29.3%) | 33 (21%) | 29 (18.5%) | 16 (10.2%) |
Artificial intelligence violations of professional confidentiality may occur more | 12 (7.6%) | 32 (20.4%) | 56 (35.7%) | 36 (22.9%) | 21 (13.4%) |
Artificial intelligence allows the patient to increase his control over his health | 13 (8.3%) | 32 (20.4%) | 77 (49%) | 27 (17.2%) | 8 (5.1%) |
Variables | Should Be Included n (%) | Not Sure n (%) | I Don’t Know n (%) |
---|---|---|---|
Knowledge and skills in Artificial intelligence (AI) | 89 (56.7%) | 52 (33.1%) | 16 (10.2%) |
Artificial intelligence (AI) as an application for reducing medication errors | 97 (61.8%) | 40 (25.5%) | 20 (12.7%) |
Training to prevent and solve ethical problems that may arise with Artificial intelligence (AI) applications | 110 (70.1%) | 24 (15.3%) | 23 (14.6%) |
A simplified lecture on Artificial intelligence, Computer use, Coding, Python language | 97 (61.8%) | 36 (22.9%) | 24 (15.3%) |
Artificial intelligence (AI) applications that will increase patients’ control over their health | 104 (66.2%) | 45 (28.7%) | 8 (5.1%) |
Artificial intelligence (AI) in scientific research | 94 (59.9%) | 48 (30.6%) | 15 (9.6%) |
Artificial intelligence (AI) assisted emergency responses | 77 (49%) | 73 (46.5%) | 7 (4.5%) |
Participants Characteristics | Mean | Std. Deviation (Std) | F-Value | t-Value | p-Value |
---|---|---|---|---|---|
Gender | |||||
Male | 8.69 | 1.42 | - | 0.011 | 0.916 * |
Female | 8.92 | 1.54 | |||
Age | |||||
18–22 | 8.71 | 1.46 | |||
23–25 | 8.96 | 1.39 | |||
26–30 | 7.00 | 0.00 | 3.602 | - | 0.030 |
Level/year of study | |||||
Third year | 8.46 | 1.45 | |||
Fourth-year | 9.22 | 1.33 | 3.293 | ||
Internship | 8.78 | 1.46 | - | 0.040 | |
Nationality | |||||
Saudi | 8.77 | 0.00 | - | ||
Non-Saudi | 8.00 | 1.46 | 6.265 | 0.013 * | |
Are you aware of artificial intelligence (AI)? | |||||
Yes | 8.68 | 1.36 | |||
No | 8.95 | 1.67 | - | 2.640 | 0.106 * |
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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, 59, 828. https://doi.org/10.3390/medicina59050828
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; 59(5):828. https://doi.org/10.3390/medicina59050828
Chicago/Turabian StyleSyed, Wajid, and Mahmood Basil A. Al-Rawi. 2023. "Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia" Medicina 59, no. 5: 828. https://doi.org/10.3390/medicina59050828