ArticleExploratory research in clinical and social pharmacy2024
Generative artificial intelligence (Gen-AI) in pharmacy education: Utilization and implications for academic integrity: A scoping review.
Article in Exploratory research in clinical and social pharmacy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Designing equitable and inclusive assessments in pharmacology: Insights from education practices in medical sciences.British journal of clinical pharmacology · 2026Review
- Artificial Intelligence Integration in U.S. Healthcare Professional Degree Programs: A Rapid Scoping Review.Research square · 2026Article
- Adoption of artificial intelligence tools among pharmacy students in Syria: patterns of use, educational perceptions, and institutional barriers.BMC medical education · 2026Article
- Mixed-methods study on GenAI Usage, dependence behaviors, and standardized application paths among Chinese medical students.NPJ digital medicine · 2026Article
- The Impact of Generative Artificial Intelligence Use on Perceived English Learning Achievement: The Roles of Use Behavior and Task-Technology Fit.Behavioral sciences (Basel, Switzerland) · 2026Article
- Perceptions of Professional Behavior in a Midwestern College of Pharmacy Community: A Mixed-Methods Study.American journal of pharmaceutical education · 2026Article
- A scoping review of the use of generative artificial intelligence tools in health profession education.BMC medical education · 2026Article
- Applications, attitudes and ethical considerations of Generative Artificial Intelligence (Gen AI) in nursing education: a scoping review.BMC nursing · 2026Article
- Emerging advancements and expanding technological scope of education and practices in pharmacy and pharmaceutical sciences.BioImpacts : BI · 2026Review
- Understanding university students' AI ethical decision-making in academic contexts: a SOR - social cognitive perspective.Frontiers in psychology · 2026Article
- Guiding student use of generative AI in undergraduate pharmacology: a narrative review and proposed source-checking process framework.Frontiers in medicine · 2026Review
- Article
- Survey of Guidance for Authors on the Use of Generative Artificial Intelligence in Pharmaceutical Journals.The Canadian journal of hospital pharmacy · 2026Article
- Pharmacy Students' Perspectives on Integrating Generative AI into Pharmacy Education.Pharmacy (Basel, Switzerland) · 2025Article
- Attitudes and usage of ChatGPT among pharmacy students in a Sub-Saharan African country, Zambia: findings and implications on the education system.BMC medical education · 2025Article
- Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.BMC medical education · 2025Article
- [Digital learning methods in pharmacy].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Generative artificial intelligence (Gen-AI), exemplified by the widely adopted ChatGPT, has garnered significant attention in recent years. Its application spans various health education domains, including pharmacy, where its potential benefits and drawbacks have become increasingly apparent. Despite the growing adoption of Gen-AIsuch as ChatGPT in pharmacy education, there remains a critical need to assess and mitigate associated risks. This review exploresthe literature and potential strategies for mitigating risks associated with the integration of Gen-AI in pharmacy education. Aim: To conduct a scoping review to identify implications of Gen-AI in pharmacy education, identify its use and emerging evidence, with a particular focus on strategies which mitigate potential risks to academic integrity. Methods: A scoping review strategy was employed in accordance with the PRISMA-ScR guidelines. Databases searched includedPubMed, ERIC [Education Resources Information Center], Scopus and ProQuestfrom August 2023 to 20 February 2024 and included all relevant records from 1 January 2000 to 20 February 2024 relating specifically to LLM use within pharmacy education. A grey literature search was also conducted due to the emerging nature of this topic. Policies, procedures, and documents from institutions such as universities and colleges, including standards, guidelines, and policy documents, were hand searched and reviewed in their most updated form. These documents were not published in the scientific literature or indexed in academic search engines. Results: Articles ( Conclusion: Drawing upon existing literature, this review highlights the importance of evidence-based approaches to address the challenges posed by Gen-AI such as ChatGPT in pharmacy education settings. Additionally, whilst mitigation strategies are suggested, primarily drawn from the grey literature, there is a paucity of traditionally published scientific literature outlining strategies for the practical and ethical implementation of Gen-AI within pharmacy education. Further research related to the responsible and ethical use of Gen-AIin pharmacy curricula; and studies related to strategies adopted to mitigate risks to academic integrity would be beneficial.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.