Evidence map›Paper›PMID 41854702›Full record

ArticleFamily medicine2025

Digital Learning Tools in Postgraduate Family Medicine Training: A Scoping Review.

Lina Shoppoff, Doug Archibald, Lindsay Bradley, Kunal Dalsania, Tracy Deyell, Ramtin Hakimjavadi, Emily Hum, Kheïra Jolin-Dahel, Sathya Karunananthan, Arya Ragozar and 4 more

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Family medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Lina ShoppoffDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Doug ArchibaldDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Lindsay BradleyDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Kunal DalsaniaInterdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
Tracy DeyellBruyère Research Institute, Ottawa, ON, Canada.
Ramtin HakimjavadiDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Emily HumInterdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
Kheïra Jolin-DahelDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Sathya KarunananthanBruyère Research Institute, Ottawa, ON, Canada.
Arya RagozarOttawa Hospital Research Institute, Ottawa, ON, Canada.
Parisa RezaiefarDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Claire SethuramDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Hui YanDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.
Clare LiddyDepartment of Family Medicine, University of Ottawa, Ottawa, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesMedical education is undergoing a digital revolution, yet few studies have examined digital learning tools in postgraduate family medicine training. This scoping review aims to identify existing tools, describe their use, and suggest future research directions.

methodsWe conducted a search of six academic databases and gray literature in 2021 and updated it in 2022. We mapped full-text English or French publications from 2010 onward that featured digital learning tools for family medicine trainees based on tool types, learning outcomes, core competencies, and educational outcomes.

resultsOut of 2058 records, 39 studies met inclusion criteria. Twenty-six studies (66.6%) described online computer-based tools. Simulations, including virtual and augmented reality, were featured in seven studies (17.9%) and mobile applications in three studies (7.7%). The tools were designed to facilitate skills and knowledge in examination and procedures (36%), pathology (33%), pharmacology (23%), and communication (18%). The majority targeted competencies relevant to the practice of primary care in the community or office setting (82%), with fewer addressing maternal care (8%) and scholarship (8%). None addressed home/long-term care, hospital care, or leadership/advocacy. In terms of educational outcomes, most studies assessed knowledge/skills (72%), learning experience (59%), and attitudes (46%), while few evaluated behavioral change (5%), organizational impact (3%), or patient care (0%).

conclusionsWe identified very few articles on digital learning tools in postgraduate family medicine education. Our findings reveal critical gaps, including limited integration of innovative technologies, unaddressed core competencies, and insufficient evaluation of the outcomes of digital learning tools.

Indexed as

Computer-Assisted InstructionEducation, Medical, GraduateFamily PracticeClinical CompetenceDigital HealthDigital MediaHumansLearning

Identifiers

PMID41854702
PMCPMC12972192

What OpenQuestion holds

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Registered trials

None linked

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.