ArticleHealth science reports2026
Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development.
Article in Health science reports, 2026. 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.
- Artificial Intelligence as a Core Public Health Competency: Proposal and Perspectives in Education and Research.JMIR medical education · 2026Article
- Understanding Time Availability and Format Preferences for AI Professional Development in Health Professions Education.Journal of CME · 2026Article
- AI competency misalignment in preventive medicine: a multi-stakeholder survey with latent profile analysis in Sichuan and Chongqing.International journal of public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) has catalyzed profound shifts in public health education, compelling institutions to explore innovative methods to prepare a digitally competent and resilient workforce. AI has emerged as a transformative tool, enabling adaptive, personalized, and scalable learning experiences. However, the long-term implications and equity considerations of AI integration in education remain underexplored. Aim: This scoping review aimed to map the existing literature on the role of AI in public health education, focusing on its impact on workforce competency development and associated challenges. Methods: Following Arksey and O'Malley's framework with enhancements from Levac et al., a comprehensive literature search was conducted across major databases, including PubMed, Scopus, and IEEE Xplore. Eligible studies, published from January 2015 to May 2025, were screened using PRISMA-ScR guidelines. Data were extracted and thematically analyzed to identify patterns, competencies addressed, and ethical or institutional considerations. Results: A total of 26 studies were included. Key themes included the transformation of pedagogical practices through AI-powered simulations and adaptive platforms, the rise of AI-specific and digital literacy training, institutional disparities in readiness, and significant ethical concerns around algorithmic bias and equitable access. Interdisciplinary collaboration and curriculum reform were identified as pivotal in sustaining AI integration. Conclusion: AI holds great promise in enhancing public health education, but its integration should be approached with attention to equity, institutional capacity, and ethical responsibility. Strategic policy, curriculum reform, and ongoing research are critical to fostering a workforce equipped for future public health challenges.
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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.