ArticleMedEdPublish (2016)2025
Applied insights for using Generative Artificial Intelligence in Faculty Development in Health Professions Education.
Article in MedEdPublish (2016), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- AI-Generated Versus Human Supervisor Feedback on Medical Students' Clinical Clerkship Logs: Cross-Sectional Convergent Mixed Methods Study.JMIR medical education · 2026Article
- Learning ophthalmic anatomy with AI-generated visual resource: the moderating role of educational background.Frontiers in medicine · 2026Article
- A primer on artificial intelligence for palliative care educators.Palliative care and social practice · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Generative artificial intelligence (GenAI) has rapidly become accessible to health professions educators and learners, creating both opportunities and new responsibilities for faculty development (FD). GenAI can help draft, adapt, and translate educational materials, and can assist faculty developers as a "co-developer." However, GenAI outputs require human oversight, and FD leaders must actively manage accuracy, privacy/confidentiality, equity/fairness, and sustainability concerns. This article offers a perspective on how GenAI can be leveraged as a co-developer in FD by drawing on emerging literature and discussion points from a workshop at the Applied insights: We provide eight applied insights, organised across key phases of FD work (planning, content creation, delivery, and evaluation). These insights highlight how faculty developers can: Conclusions: When used responsibly, GenAI can augment FD and help educators work more efficiently without reducing the central role of human judgment, ethics, and contextual expertise. Faculty developers can increase benefits and reduce harms by making their governance explicit, modelling prompt literacy, and embedding quality assurance/quality improvement cycles.
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Identifiers
What OpenQuestion 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 OpenQuestion graph.