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Hoti K, Weidmann AE. Encouraging dissemination of research on the use of artificial intelligence and related innovative technologies in clinical pharmacy practice and education: call for papers. Int J Clin Pharm 2024:10.1007/s11096-024-01777-z. [PMID: 39046690 DOI: 10.1007/s11096-024-01777-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 07/05/2024] [Indexed: 07/25/2024]
Affiliation(s)
- Kreshnik Hoti
- Division of Pharmacy, Department of Pharmacy Practice and Pharmaceutical Care, Faculty of Medicine, University of Pristina, Prishtina, Kosovo
| | - Anita Elaine Weidmann
- Innsbruck University, Innsbruck, Austria.
- International Journal of Clinical Pharmacy and Research Committee, European Society of Clinical Pharmacy, Chaam, The Netherlands.
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Lim AS, Ling YL, Wilby KJ, Mak V. What's been trending with OSCEs in pharmacy education over the last 20 years? A bibliometric review and content analysis. CURRENTS IN PHARMACY TEACHING & LEARNING 2024; 16:212-220. [PMID: 38171979 DOI: 10.1016/j.cptl.2023.12.028] [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: 07/18/2023] [Revised: 12/01/2023] [Accepted: 12/22/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Objective structured clinical examinations (OSCEs) remain an integral part of pharmacy education. This study aimed to characterize key researchers, areas, and themes in pharmacy education OSCEs using a bibliometric review with content analysis. METHODS A bibliometric review was conducted on literature from over 23 years from January 2000 to May 2023. Articles focusing on any type of OSCE research in pharmacy education in both undergraduate and postgraduate sectors were included. Articles were excluded if they were not original articles or not published in English. A summative content analysis was also conducted to identify key topics. RESULTS A total of 192 articles were included in the analysis. There were 242 institutions that contributed to the OSCE literature in pharmacy education, with the leading country being Canada. Most OSCE research came from developed countries and were descriptive studies based on single institution data. The top themes emerging from content analysis were student perceptions on OSCE station styles (n = 98), staff perception (n = 19), grade assessment of OSCEs (n = 145), interprofessional education (n = 11), standardized patients (n = 12), and rubric development and standard setting (n = 8). IMPLICATIONS There has been a growth in virtual OSCEs, interprofessional OSCEs, and artificial intelligence OSCEs. Communication rubrics and minimizing assessor variability are still trending research areas. There is scope to conduct more research on evaluating specific types of OSCEs, when best to hold an OSCE, and comparing OSCEs to other assessments.
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Affiliation(s)
- Angelina S Lim
- Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville 3052, VIC, Australia.
| | - Yeap Li Ling
- School of Pharmacy, Monash University Malaysia, 47500 Subang Jaya, Selangor, Malaysia.
| | - Kyle J Wilby
- College of Pharmacy, Faculty of Health, Dalhousie University, PO Box 15000, 5968 College Street, Halifax, Nova Scotia B3H 4R2, Canada.
| | - Vivienne Mak
- Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville 3052, VIC, Australia.
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Benítez TM, Xu Y, Boudreau JD, Kow AWC, Bello F, Van Phuoc L, Wang X, Sun X, Leung GKK, Lan Y, Wang Y, Cheng D, Tham YC, Wong TY, Chung KC. Harnessing the potential of large language models in medical education: promise and pitfalls. J Am Med Inform Assoc 2024; 31:776-783. [PMID: 38269644 PMCID: PMC10873781 DOI: 10.1093/jamia/ocad252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 12/09/2023] [Accepted: 12/17/2023] [Indexed: 01/26/2024] Open
Abstract
OBJECTIVES To provide balanced consideration of the opportunities and challenges associated with integrating Large Language Models (LLMs) throughout the medical school continuum. PROCESS Narrative review of published literature contextualized by current reports of LLM application in medical education. CONCLUSIONS LLMs like OpenAI's ChatGPT can potentially revolutionize traditional teaching methodologies. LLMs offer several potential advantages to students, including direct access to vast information, facilitation of personalized learning experiences, and enhancement of clinical skills development. For faculty and instructors, LLMs can facilitate innovative approaches to teaching complex medical concepts and fostering student engagement. Notable challenges of LLMs integration include the risk of fostering academic misconduct, inadvertent overreliance on AI, potential dilution of critical thinking skills, concerns regarding the accuracy and reliability of LLM-generated content, and the possible implications on teaching staff.
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Affiliation(s)
- Trista M Benítez
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, United States
| | - Yueyuan Xu
- Tsinghua Medicine, Tsinghua University, Beijing, 100084, China
| | - J Donald Boudreau
- Institute of Health Sciences Education, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC H3A 0G4, Canada
| | - Alfred Wei Chieh Kow
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Fernando Bello
- Technology Enhanced Learning and Innovation Department, Duke-NUS Medical School, National University of Singapore, 169857, Singapore
| | - Le Van Phuoc
- College of Health Sciences, VinUniversity, Hanoi, 100000, Vietnam
| | - Xiaofei Wang
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, 200240, China
| | - Gilberto Ka-Kit Leung
- Department of Surgery, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong, 999077, China
| | - Yanyan Lan
- Institute of AI Industrial Research, Tsinghua University, Beijing, 100084, China
| | - Yaxing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Beijing Ophthalmology and Visual Sciences Key Laboratory, Capital University of Medical Science, Beijing, 100730, China
| | - Davy Cheng
- School of Medicine, The Chinese University of Hong Kong (Shenzhen), Shenzhen, 518172, China
| | - Yih-Chung Tham
- Centre for Innovation and Precision Eye Health; and Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, 169857, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, 168751, Singapore
| | - Tien Yin Wong
- Tsinghua Medicine, Tsinghua University, Beijing, 100084, China
- Singapore Eye Research Institute, Singapore National Eye Centre, 168751, Singapore
- School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Beijing, 100084, China
| | - Kevin C Chung
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, United States
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Abdel Aziz MH, Rowe C, Southwood R, Nogid A, Berman S, Gustafson K. A scoping review of artificial intelligence within pharmacy education. AMERICAN JOURNAL OF PHARMACEUTICAL EDUCATION 2024; 88:100615. [PMID: 37914030 DOI: 10.1016/j.ajpe.2023.100615] [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: 07/25/2023] [Revised: 10/19/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
OBJECTIVES This scoping review aimed to summarize the available literature on the use of artificial intelligence (AI) in pharmacy education and identify gaps where additional research is needed. FINDINGS Seven studies specifically addressing the use of AI in pharmacy education were identified. Of these 7 studies, 5 focused on AI use in the context of teaching and learning, 1 on the prediction of academic performance for admissions, and the final study focused on using AI text generation to elucidate the benefits and limitations of ChatGPT use in pharmacy education. SUMMARY There are currently a limited number of available publications that describe AI use in pharmacy education. Several challenges exist regarding the use of AI in pharmacy education, including the need for faculty expertise and time, limited generalizability of tools, limited outcomes data, and several legal and ethical concerns. As AI use increases and implementation becomes more standardized, opportunities will be created for the inclusion of AI in pharmacy education.
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Affiliation(s)
- May H Abdel Aziz
- University of Texas at Tyler, Ben and Maytee Fisch College of Pharmacy, Department of Pharmaceutical Sciences and Health Outcomes, Tyler, TX, USA.
| | - Casey Rowe
- University of Florida College of Pharmacy, Department of Pharmacotherapy and Translational Research, Orlando, FL, USA
| | - Robin Southwood
- University of Georgia, College of Pharmacy, Department of Clinical and Administrative Pharmacy, Athens, GA, USA
| | - Anna Nogid
- Fairleigh Dickinson University, School of Pharmacy and Health Sciences, Department of Pharmacy Practice, Florham Park, NJ, USA
| | - Sarah Berman
- University of the Incarnate Word, Feik School of Pharmacy, Department of Pharmacy Practice, San Antonio, TX, USA
| | - Kyle Gustafson
- Northeast Ohio Medical University, Department of Pharmacy Practice, Rootstown, OH, USA
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