JMIR Publications

ABSTRACT

Background:

Despite the high prevalence of mental health disorders among medical students and physicians, help-seeking remains low. Digital mental health approaches offer beneficial opportunities to increase well-being e.g., via mobile apps.

Objective:

This study aims to assess the acceptance, and its underlying predictors, of tailored electronic mental health app (e-mental health) among medical students.

Methods:

From November 2022 to July 2023, a cross-sectional study was conducted with N=245 medical students at the University of Duisburg-Essen. 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; d=4.13) as well as students with higher loads of anxiety symptoms (t92.40=2.36; P=.02; Padj=.03; d=0.35). 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=.10; P=.03) and the three UTAUT core predictor’s 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.