Determining the acceptance of e-mental health interventions in elite athletes using the unified theory of acceptance and use of technology

Sheila Geiger; Julia Aufderlandwehr; Anna Julia Esser; Theresa Schadendorf; Thomas Muehlbauer; Eva-Maria Skoda; Martin Teufel; Alexander Bäuerle

doi:10.3389/fspor.2024.1416045

Determining the acceptance of e-mental health interventions in elite athletes using the unified theory of acceptance and use of technology

Front Sports Act Living. 2024 Oct 1:6:1416045. doi: 10.3389/fspor.2024.1416045. eCollection 2024.

Authors

Sheila Geiger^{1

2}, Julia Aufderlandwehr^{1

2}, Anna Julia Esser^{1

2}, Theresa Schadendorf^{1

2}, Thomas Muehlbauer³, Eva-Maria Skoda^{1

2}, Martin Teufel^{1

2}, Alexander Bäuerle^{1

2}

Affiliations

¹ Clinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
² Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University of Duisburg-Essen, Essen, Germany.
³ Division of Movement and Training Sciences/Biomechanics of Sport, University of Duisburg-Essen, Essen, Germany.

Abstract

Background: Elite athletes are exposed to many different sport-specific stressors that may put them at particular risk for mental health symptoms and disorders. E-mental health interventions could be a feasible option to support elite athletes in need. The aim of the present study was to assess the acceptance of e-mental health interventions among elite athletes and explore its underlying drivers and barriers.

Materials and methods: A cross-sectional study was conducted with N = 382 elite athletes. Of these, N = 275 (71.99%, 167 females) were included in the statistical analyses. The impact of various sociodemographic, sport-related and medical characteristics on acceptance was assessed. EHealth-related data and acceptance of e-mental health interventions were examined using a modified assessment based on the Unified Theory of Acceptance and Use of Technology (UTAUT).

Results: Overall, the acceptance of e-mental health interventions in elite athletes can be classified as high (M = 3.69 SD = 0.97). In the UTAUT regression model sex, financial situation, depression symptoms, digital confidence, digital overload as well as the UTAUT predictors performance expectancy, effort expectancy, and social influence predicted acceptance significantly.

Conclusions: The UTAUT model has proven to be a valuable instrument in predicting of acceptance of e-mental health interventions in elite athletes. Given the strong association between acceptance and future use, new interventions should focus on the explored factors to establish effective e-mental health interventions for elite athletes.

Keywords: UTAUT; eHealth; internet; sports; survey.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. We thank the Open Access Fund of the University of Duisburg-Essen for supporting the publication of the manuscript.