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Jackson P, Ponath Sukumaran G, Babu C, Tony MC, Jack DS, Reshma VR, Davis D, Kurian N, John A. Artificial intelligence in medical education - perception among medical students. BMC MEDICAL EDUCATION 2024; 24:804. [PMID: 39068482 PMCID: PMC11283685 DOI: 10.1186/s12909-024-05760-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 07/09/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND As Artificial Intelligence (AI) becomes pervasive in healthcare, including applications like robotic surgery and image analysis, the World Medical Association emphasises integrating AI education into medical curricula. This study evaluates medical students' perceptions of 'AI in medicine', their preferences for AI training in education, and their grasp of AI's ethical implications in healthcare. MATERIALS & METHODS A cross-sectional study was conducted among 325 medical students in Kerala using a pre-validated, semi structured questionnaire. The survey collected demographic data, any past educational experience about AI, participants' self-evaluation of their knowledge and evaluated self-perceived understanding of applications of AI in medicine. Participants responded to twelve Likert-scale questions targeting perceptions and ethical aspects and their opinions on suggested topics on AI to be included in their curriculum. RESULTS & DISCUSSION AI was viewed as an assistive technology for reducing medical errors by 57.2% students and 54.2% believed AI could enhance medical decision accuracy. About 49% agreed that AI could potentially improve accessibility to healthcare. Concerns about AI replacing physicians were reported by 37.6% and 69.2% feared a reduction in the humanistic aspect of medicine. Students were worried about challenges to trust (52.9%), patient-physician relationships (54.5%) and breach of professional confidentiality (53.5%). Only 3.7% felttotally competent in informing patients about features and risks associated with AI applications. Strong demand for structured AI training was expressed, particularly on reducing medical errors (76.9%) and ethical issues (79.4%). CONCLUSION This study highlights medical students' demand for structured AI training in undergraduate curricula, emphasising its importance in addressing evolving healthcare needs and ethical considerations. Despite widespread ethical concerns, the majority perceive AI as an assistive technology in healthcare. These findings provide valuable insights for curriculum development and defining learning outcomes in AI education for medical students.
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Affiliation(s)
| | | | - Chikku Babu
- Pushpagiri Medical College, Tiruvalla, Kerala, India
| | | | | | - V R Reshma
- Pushpagiri Medical College, Tiruvalla, Kerala, India
| | - Dency Davis
- Pushpagiri Medical College, Tiruvalla, Kerala, India
| | - Nisha Kurian
- Pushpagiri Medical College, Tiruvalla, Kerala, India
| | - Anjum John
- Pushpagiri Medical College, Tiruvalla, Kerala, India.
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Jarab AS, Al-Qerem W, Al-Hajjeh DM, Abu Heshmeh S, Mukattash TL, Naser AY, Alwafi H, Al Hamarneh YN. Artificial intelligence utilization in the healthcare setting: perceptions of the public in the UAE. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-9. [PMID: 38832887 DOI: 10.1080/09603123.2024.2363472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/29/2024] [Indexed: 06/06/2024]
Abstract
Understanding the use of AI in healthcare is essential for the successful implementation of AI-driven healthcare solutions. The aim of this study was to evaluate public perception of AI utilization in healthcare settings. A validated questionnaire assessed general perceptions towards AI utilization, the use of AI by physician , and the use of AI by pharmacists . The study included 770 participants. The median perception score indicated an unfavorable attitude. Participants who had lower education level and those with no employment had a significantly lower perception scores than their counterpart. Participants who reported low income and those who visited the pharmacy five to ten times on average had a higher perception than their counterparts did. The reported negative perception necessitates the implementation of education campaigns to improve AI literacy and dispel any misconceptions and concerns, particularly among individuals with low education, high income, unemployment, and frequent pharmacy visits.
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Affiliation(s)
- Anan S Jarab
- College of Pharmacy, Al Ain University, Abu Dhabi, United Arab Emirates
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan
| | - Walid Al-Qerem
- Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, Amman, Jordan
| | - Dua'a M Al-Hajjeh
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan
| | - Shrouq Abu Heshmeh
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan
| | - Tareq L Mukattash
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan
| | - Abdallah Y Naser
- Department of Applied Pharmaceutical Sciences and Clinical Pharmacy, Faculty of Pharmacy, Isra University, Amman, Jordan
| | - Hassan Alwafi
- Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Yazid N Al Hamarneh
- Department of Pharmacology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada
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Serbaya SH, Khan AA, Surbaya SH, Alzahrani SM. Knowledge, Attitude and Practice Toward Artificial Intelligence Among Healthcare Workers in Private Polyclinics in Jeddah, Saudi Arabia. ADVANCES IN MEDICAL EDUCATION AND PRACTICE 2024; 15:269-280. [PMID: 38596622 PMCID: PMC11001543 DOI: 10.2147/amep.s448422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 03/27/2024] [Indexed: 04/11/2024]
Abstract
Purpose The objective of our study was to assess awareness, attitudes, and practices regarding artificial intelligence (AI) among healthcare workers in private polyclinics in Jeddah, Saudi Arabia. Methods We conducted cross-sectional study among healthcare workers in private clinics in Jeddah. Data was collected using a structured, validated questionnaire in Arabic and English on awareness, attitudes, and behaviors regarding AI. Cronbach's alpha for the questionnaire ranged from 0.6 to 0.8. Descriptive and bivariate analysis was done to assess the scores and their association of various sociodemographic variables with awareness, attitudes, and behaviors regarding AI. Multiple linear regression was performed to predict the scores of awareness, attitudes, and behaviors based on the sociodemographic variables. Results We recruited 361 participants for this study. Approximately, 62% of the healthcare workers were female. The majority (36%) of healthcare workers were nurses, while 25% were physicians. The median awareness, attitude, and behavioral scores were 5/6 (IQR 3-6), 5/8 (IQR 4-7), and 0/3 (IQR 0), respectively. Approximately three-fourths (74%) of the healthcare workers believed that they understood the basic computational principles of AI. Only half of the participants were willing to use AI when making future medical decisions. We found that male healthcare workers had better knowledge scores regarding AI as compared to female healthcare workers (Beta = 0.555, 95%, p value = 0.010), while for attitude scores, being administrative employee as compared to other employees was found to have negative attitude towards AI (Beta = 0.049, 95%, p value = 0.03). Conclusion We found that healthcare workers had an overall good awareness and optimistic attitude toward AI. Despite this, the majority is worried about the potential consequences of replacing their jobs with AI in the future. There is a dire need to educate and sensitize healthcare workers regarding the potential impact of AI on healthcare.
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Affiliation(s)
- Suhail Hasan Serbaya
- Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
| | - Adeel Ahmed Khan
- Saudi Board Program of Preventive Medicine, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
| | - Saud Hasan Surbaya
- Inter-Professional Training Director Administration, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
| | - Safar Majhood Alzahrani
- Inter-professional Training Administration, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
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Ahmed S, Kapadia A, Ahmed Siddiqui I, Shaukat A, Khan MD, Alam Khan MQ, Iqbal S, Abbas G, Zubairi AM, Nawaz Naqvi SH, Sadiqa A, Jafri L, Siddiqui I. Artificial Intelligence - Perception of Clinical Laboratories' Technical Staff a Nationwide Multicentre Survey in Pakistan. EJIFCC 2024; 35:23-30. [PMID: 38706736 PMCID: PMC11063789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
Introduction As Artificial Intelligence (AI) technology continues to assimilate into various industries, there is a huge scope in the healthcare industry specifically in clinical laboratories. The perspective of the laboratory professionals can give valuable insight on the ideal path to take for AI implementation. Methods The study utilized a cross-sectional survey design and was conducted at the section of Chemical Pathology, Department of Pathology and Laboratory Medicine, the Aga Khan University (AKU), Karachi, Pakistan in collaboration with Consultant Pathologists of 9 clinical laboratories associated with teaching hospitals across Pakistan from October-November 2023. The survey was for a duration of 2 weeks and was circulated to all working laboratory technical staff after informed consent. Results A total of 351 responses were received, of which 342 (male=146, female=196) responses were recorded after exclusion. Respondents ranged from technologists, faculty, residents, and coordinators, and were from different sections (chemical pathology, microbiology, haematology, histopathology, POCT). Out of the total 312 (91.2%) of respondents stated that they were at least somewhat familiar with AI technology. Experts in AI were only 2.0% (n=7) of all respondents, but 90% (n=6) of these were < 30 years old. 76.3% (n=261) of the respondents felt the need to implement more AI technology in the laboratories, with time saving (26.1%) and improving performances of tests (17.7%) cited to be the greatest benefits of AI. Security concerns (n=144) and a fear of decreasing personal touch (n=143) were the main concerns of the respondents while the younger employees had an increased fear of losing their jobs. 76.3% were in favour of an increase in AI usage in the laboratories. Conclusion This study highlights a favourable perspective among laboratory professionals, acknowledging the potential of AI to enhance both the efficiency and quality of laboratory practices. However, it underscores the importance of addressing their concerns in the thoughtful implementation of this emerging technology.
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Affiliation(s)
- Sibtain Ahmed
- Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Aqueel Kapadia
- Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Imran Ahmed Siddiqui
- Department of Pathology, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan
| | - Asma Shaukat
- Department of Chemical Pathology, Quaid-e-Azam Medical College, Bahawalpur, Pakistan
| | | | - Muhammad Qaiser Alam Khan
- Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan
| | - Sahar Iqbal
- Department of Pathology, Dow International Medical College, Dow University of Health Sciences, Karachi, Pakistan
| | - Ghazanfar Abbas
- Department of Chemical Pathology, Shifa International Hospital, Islamabad, Pakistan
| | - Adnan Mustafa Zubairi
- Clinical Laboratories - Outreach: Indus Hospital & Health Network, Karachi, Pakistan
| | - Syed Haider Nawaz Naqvi
- Department of Chemical Pathology, Sindh Institute of Urology and Transplantation, Karachi, Pakistan
| | - Ayesha Sadiqa
- Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Lena Jafri
- Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
| | - Imran Siddiqui
- Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan
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Daher OA, Dabbousi AA, Chamroukh R, Saab AY, Al Ayoubi AR, Salameh P. Artificial Intelligence: Knowledge and Attitude Among Lebanese Medical Students. Cureus 2024; 16:e51466. [PMID: 38298326 PMCID: PMC10829838 DOI: 10.7759/cureus.51466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/01/2024] [Indexed: 02/02/2024] Open
Abstract
Background Artificial intelligence (AI) has taken on a variety of functions in the medical field, and research has proven that it can address complicated issues in various applications. It is unknown whether Lebanese medical students and residents have a detailed understanding of this concept, and little is known about their attitudes toward AI. Aim This study fills a critical gap by revealing the knowledge and attitude of Lebanese medical students toward AI. Methods A multi-centric survey targeting 365 medical students from seven medical schools across Lebanon was conducted to assess their knowledge of and attitudes toward AI in medicine. The survey consists of five sections: the first part includes socio-demographic variables, while the second comprises the 'Medical Artificial Intelligence Readiness Scale' for medical students. The third part focuses on attitudes toward AI in medicine, the fourth assesses understanding of deep learning, and the fifth targets considerations of radiology as a specialization. Results There is a notable awareness of AI among students who are eager to learn about it. Despite this interest, there exists a gap in knowledge regarding deep learning, albeit alongside a positive attitude towards it. Students who are more open to embracing AI technology tend to have a better understanding of AI concepts (p=0.001). Additionally, a higher percentage of students from Mount Lebanon (71.6%) showed an inclination towards using AI compared to Beirut (63.2%) (p=0.03). Noteworthy are the Lebanese University and Saint Joseph University, where the highest proportions of students are willing to integrate AI into the medical field (79.4% and 76.7%, respectively; p=0.001). Conclusion It was concluded that most Lebanese medical students might not necessarily comprehend the core technological ideas of AI and deep learning. This lack of understanding was evident from the substantial amount of misinformation among the students. Consequently, there appears to be a significant demand for the inclusion of AI technologies in Lebanese medical school courses.
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Affiliation(s)
- Omar A Daher
- Faculty of Medicine, Beirut Arab University, Beirut, LBN
| | | | | | | | - Amir Rabih Al Ayoubi
- Department of General Medicine, Faculty of Medical Sciences, Lebanese University, Beirut, LBN
| | - Pascale Salameh
- Department of Primary Care and Population Health, University of Nicosia Medical School, Nicosia, CYP
- Department of Public Health, Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie (INSPECT-LB), Beirut, LBN
- Department of Pharmacy Practice, Lebanese University, Beirut, LBN
- School of Medicine, Lebanese American University, Beirut, LBN
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