Evidence map›Paper›PMID 39865568›Full record

ArticleJMIR medical education2025

Medical Students' Acceptance of Tailored e-Mental Health Apps to Foster Their Mental Health: Cross-Sectional Study.

Catharina Grüneberg, Alexander Bäuerle, Sophia Karunakaran, Dogus Darici, Nora Dörrie, Martin Teufel, Sven Benson, Anita Robitzsch

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Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

8 authors.

Catharina GrünebergClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0009-0002-0918-5905
Alexander BäuerleClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0000-0003-1488-8592
Sophia KarunakaranClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0009-0000-1202-2950
Dogus DariciInstitute of Anatomy and Neurobiology, University of Münster, Münster, Germany.ORCID 0000-0002-2375-8792
Nora DörrieClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0000-0002-9760-9167
Martin TeufelClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0000-0003-2120-1840
Sven BensonCenter for Translational Neuro- and Behavioral Sciences, University of Duisburg-Essen, Essen, Germany.ORCID 0000-0002-4487-4258
Anita RobitzschClinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital, University of Duisburg-Essen, Virchowstraße 174, Essen, 45147, Germany, 49 201438755212.ORCID 0009-0005-2941-1123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Despite the high prevalence of mental health problems among medical students and physicians, help-seeking remains low. Digital mental health approaches offer beneficial opportunities to increase well-being, for example, via mobile apps. Objective: This study aimed to assess the acceptance, and its underlying predictors, of tailored e-mental health apps among medical students by focusing on stress management and the promotion of personal skills. Methods: From November 2022 to July 2023, a cross-sectional study was conducted with 245 medical students at the University of Duisburg-Essen, Germany. Sociodemographic, mental health, and eHealth-related data were assessed. The Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. Differences in acceptance were examined and a multiple hierarchical regression analysis was conducted. Results: The general acceptance of tailored e-mental health apps among medical students was high (mean 3.72, SD 0.92). Students with a job besides medical school reported higher acceptance (t107.3=-2.16; P=.03; Padj=.027; Cohen d=4.13) as well as students with higher loads of anxiety symptoms (t92.4=2.36; P=.02; Padj=.03; Cohen d=0.35). The t values were estimated using a 2-tailed t test. Regression analysis revealed that acceptance was significantly predicted by anxiety symptoms (β=.11; P=.045), depressive symptoms (β=-.11; P=.05), internet anxiety (β=-.12; P=.01), digital overload (β=.1; P=.03), and the 3 UTAUT core predictors-performance expectancy (β=.24; P<.001), effort expectancy (β=.26; P<.001), and social influence (β=.43; P<.001). Conclusions: The high acceptance of e-mental health apps among medical students and its predictors lay a valuable basis for the development and implementation of tailored e-mental health apps within medical education to foster their mental health. More research using validated measures is needed to replicate our findings and to further investigate medical students' specific needs and demands regarding the framework of tailored e-mental health apps.

Indexed as

Mental HealthMobile ApplicationsStudents, MedicalAdultCross-Sectional StudiesFemaleGermanyHumansMaleSurveys and QuestionnairesTelemedicineYoung Adultacceptanceappassessmentcross-sectional studyeHealthe–mental health appsfosterintention to usemedical educationmedical studentsmental health appsmental health problemsmobile appsphysiciantailored interventionsUTAUTwell-being

Identifiers

PMID39865568
PMCPMC11785350

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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.