Evidence map›Paper›PMID 42247555›Full record

ArticleJMIR medical education2026

Adoption and Use of Social Media in Health Care Among Medical Residents: Cross-Sectional Study.

Zineb Zouakia, Aurélia Manns, Thomas Meyre, Anita Burgun, Natacha Kadlub, Rosy Tsopra

Abstract read
In one paragraph

Article in JMIR medical education, 2026. 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

6 authors.

Zineb ZouakiaClinical Bioinformatics Laboratory, Imagine Institute, Université Paris Cité, INSERM UMR1163, 24 Boulevard du Montparnasse, Paris, F-75006, France, 33 668169844.ORCID 0009-0008-4955-6911
Aurélia MannsClinical Bioinformatics Laboratory, Imagine Institute, Université Paris Cité, INSERM UMR1163, 24 Boulevard du Montparnasse, Paris, F-75006, France, 33 668169844.ORCID 0009-0007-9298-6135
Thomas MeyreClinical Bioinformatics Laboratory, Imagine Institute, Université Paris Cité, INSERM UMR1163, 24 Boulevard du Montparnasse, Paris, F-75006, France, 33 668169844.ORCID 0009-0000-1496-0377
Anita BurgunClinical Bioinformatics Laboratory, Imagine Institute, Université Paris Cité, INSERM UMR1163, 24 Boulevard du Montparnasse, Paris, F-75006, France, 33 668169844.ORCID 0000-0001-6855-4366
Natacha KadlubDepartment of Maxillofacial Surgery and Plastic Surgery, MAFACE Rare Diseases Reference Centre, Faculty of Medicine, Hôpital Necker Enfants Malades, APHP, Université Paris Cité, Paris, France.ORCID 0000-0001-5961-4064
Rosy TsopraClinical Bioinformatics Laboratory, Imagine Institute, Université Paris Cité, INSERM UMR1163, 24 Boulevard du Montparnasse, Paris, F-75006, France, 33 668169844.ORCID 0000-0002-9406-5547

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Social media apps are widely used by health care professionals despite security and regulatory risks. Identifying factors associated with this use is important for developing effective risk-reduction strategies. Objective: This study aimed to investigate how medical residents use 6 popular social media apps in professional tasks and to identify factors influencing their adoption in health care, using the validated Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. Methods: An anonymous web-based survey was conducted between June 2024 and November 2024 among medical residents in France. Participants reported demographic characteristics, frequency, and professional contexts of use for 6 apps (Facebook, Instagram, LinkedIn, Messenger, TikTok, and WhatsApp) and completed UTAUT2-based items. The model was adapted by adding a technology trust construct. Descriptive analyses were performed for all apps. With a sufficient sample size, partial least squares structural equation modeling was conducted for WhatsApp to identify factors associated with behavioral intention and use behavior. Results: A total of 137 residents (n=87, 63.5% female participants) across 40 specialties completed the survey. WhatsApp was the most widely and professionally used app (n=127, 92.7%), with 75.9% (n=104) using it at least many times per week. It was primarily used for patient care, including written transmissions (n=86, 62.8%), case discussions (n=76, 55.5%), and specialist advice (n=86, 62.8%), as well as for professional networking (n=62, 45.3%). Messenger was used by 46.7% (n=64) of participants for similar purposes. Facebook (n=35, 25.6%) and LinkedIn (n=20, 14.6%) were mainly used for education and networking, whereas Instagram (n=11, 8%) was rarely used, and TikTok was not used for professional purposes. Regarding adoption factors, WhatsApp had the highest overall scores, including the highest performance expectancy (mean 5.4, SD 1.12), behavioral intention (mean 5.28, SD 1.15), and use behavior (mean 5.91, SD 1.30), with high effort expectancy (mean 6.82, SD 0.55) and facilitating conditions (mean 6.07, SD 0.85). LinkedIn showed the highest social influence (mean 5.05, SD 1.06), whereas Instagram showed the highest hedonic motivation (mean 6.61, SD 0.51). Technology trust scores were low across all apps, ranging from a mean of 2.23 (SD 1.16) for Facebook to a mean of 3.72 (SD 1.39) for LinkedIn. In the partial least squares structural equation modeling analysis for WhatsApp, habit was the only significant predictor of behavioral intention (β=.53; P<.001) and use behavior (β=.45; P<.001). Conclusions: WhatsApp dominates professional use among residents despite low trust in its security, and its use is mainly driven by habit. Secure alternatives with features similar to popular social media apps, supported by institutional policies and digital professionalism training, are needed to encourage physicians to better consider safety when using social media.

Indexed as

Internship and ResidencySocial MediaAdultCross-Sectional StudiesDigital HealthFemaleFranceHumansMaleMobile ApplicationsSurveys and Questionnairesclinical practicedigital healthFacebookhealth care professionalshealth communicationmedical residencymessagingphysicianssocial mediatechnology acceptanceUnified Theory of Acceptance and Use of Technology 2UTAUT2WhatsApp

Identifiers

PMID42247555
PMCPMC13240641

What OpenQuestion holds

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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.