Integrating Task-Technology Fit and Community of Practice Theories to Enhance Medical Educator Skill Confidence in Generative AI: Design, Implementation, and Pilot Outcomes.

Abstract read

In one paragraph

Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Impact of a Practical, Hands-On, Continuing Professional Development Course About AI in Health Care Professions Education on the Perceptions and Behaviors of Health Care Educators: Qualitative Case Study.JMIR medical education · 2026
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Youngjin ChoDepartment of Medical Education, Geisinger College of Health Sciences School of Medicine, 525 Pine Street, Scranton, PA 18509 USA.ORCID 0009-0005-0819-6778

John L SzarekDepartment of Medical Education, Geisinger College of Health Sciences School of Medicine, 525 Pine Street, Scranton, PA 18509 USA.ORCID 0000-0003-2635-5881

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faculty need sustainable generative AI (genAI) development approaches beyond one-off workshops or resource-intensive formal programs. We piloted a community of practice (CoP) integrating task-technology fit (TTF) principles with social learning. Two volunteer facilitators delivered six sessions to medical education faculty, focusing on authentic micro-tasks with demonstrated AI-task alignment. Thirteen participants completed post-series surveys. Self-rated knowledge increased significantly (1.3 points, Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-025-02520-7.

Indexed as

Community of practiceFaculty developmentGenerative AIMedical educatorsTask-technology fit

Identifiers

PMID41798335

DOI10.1007/s40670-025-02520-7

PMCPMC12960897

What OpenQuestion holds

Textmetadata

LicenceCC BY

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Registered trials

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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.