ArticleAmerican journal of pharmaceutical education2024
Student Pharmacists' Perceptions of Artificial Intelligence and Machine Learning in Pharmacy Practice and Pharmacy Education.
Article in American journal of pharmaceutical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
13 citing papers in PubMed.
- Translation, cultural adaptation, and validation of the perceived Artificial Intelligence Literacy Questionnaire-6 (PAILQ-6) in Arabic-speaking pharmacists: A cross-sectional methodological study.Exploratory research in clinical and social pharmacy · 2026Article
- Distilling AI Workforce-Readiness Competencies for U.S. Pharmacists from Job Advertisements: Implications for Pharmacy Education.Pharmacy (Basel, Switzerland) · 2026Article
- Mapping Current Use of Artificial Intelligence in Pharmacology Education via a Scoping Review.Pharmacology research & perspectives · 2026Article
- The use and methodological reporting of large language models in qualitative research: a scoping review.BMC medical research methodology · 2026Article
- Guiding student use of generative AI in undergraduate pharmacology: a narrative review and proposed source-checking process framework.Frontiers in medicine · 2026Review
- Article
- Pharmacy Students' Perspectives on Integrating Generative AI into Pharmacy Education.Pharmacy (Basel, Switzerland) · 2025Article
- Comparative evaluation of artificial intelligence platforms and drug interaction screening databases using real-world patient data.Exploratory research in clinical and social pharmacy · 2025Article
- Pharmacy Students' Perceptions and Use of Artificial Intelligence Tools in Oman: A Cross-Sectional Survey.Cureus · 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
- Accuracy and teachability of artificial intelligence chatbots in solving pharmaceutical calculations: a descriptive study.International journal of clinical pharmacy · 2025Article
- Article
- Pharmacists' propensity to trust automated technologies: A demographic analysis.Journal of the American Pharmacists Association : JAPhAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
objectiveThis study explored student pharmacists' perceptions and attitudes regarding artificial intelligence (AI) and machine learning (ML) in pharmacy practice. Due to AI/ML's promising prospects, understanding students' current awareness, comprehension, and hopes for their use in this field is essential.
methodsIn April 2024, a Zoom focus group discussion was conducted with 6 student pharmacists using a self-developed interview guide. The guide included questions about the benefits, challenges, and ethical considerations of implementing AI/ML in pharmacy practice and education. The participants' demographic information was collected through a questionnaire. The research team conducted a thematic analysis of the discussion transcript. The results generated by a team member using NVivo were compared with those generated by ChatGPT, and all discrepancies were addressed.
resultsStudent pharmacists displayed a generally positive attitude toward the implementation of AI/ML in pharmacy practice but lacked knowledge about AI/ML applications. Participants recognized several advantages of AI/ML implementation in pharmacy practice, including improved accuracy and time-saving for pharmacists. Some identified challenges were alert fatigue, AI/ML-generated errors, and the potential obstacle to person-centered care. The study participants expressed their interest in learning about AI/ML and their desire to integrate these technologies into pharmacy education.
conclusionThe demand for integrating AI/ML into pharmacy practice is increasing. Student and professional pharmacists need additional AI/ML training to equip them with knowledge and practical skills. Collaboration between pharmacists, institutions, and AI/ML companies is essential to address barriers and advance AI/ML implementation in the pharmacy field.
Indexed as
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What Socratic holds
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 Socratic graph.