Acceptance, needs and demands of e-mental health interventions in adolescent elite athletes

AI Summary

Moderate overall acceptance of e-mental health interventions among adolescent elite athletes, with higher acceptance in females and individual-sport athletes.
Performance expectancy, effort expectancy, and social influence significantly predicted acceptance; gender also contributed, while mental health symptoms and digital variables did not.
Preferred interventions are user-centred, smartphone-delivered, customisable, and modular with 10-20 minute sessions to support sustained engagement and prevention.

AI Summary

BACKGROUND: Elite sports place high psychological and physical demands on adolescent elite athletes, increasing the risk for mental health problems.

This study investigated adolescent elite athletes' acceptance of e-mental health interventions, identified predictors of acceptance, and explored their specific needs and demands.

Gender (β = 0.097, p =.017), the UTAUT predictors performance expectancy (β = 0.458, p <.001), effort expectancy (β = 0.309, p <.001), and social influence (β = 0.152, p =.015) significantly explained variance in acceptance in adolescent elite athletes, whereas sport type, depression-, anxiety-, and distress symptoms, internet anxiety, digital confidence, and -overload were not significant predictors.

Basic summary

Discov Ment Health. 2026 Jun 11;6(1):108. doi: 10.1007/s44192-026-00474-9.

ABSTRACT

BACKGROUND: Elite sports place high psychological and physical demands on adolescent elite athletes, increasing the risk for mental health problems. E-mental health interventions may offer flexible and low-threshold support. This study investigated adolescent elite athletes’ acceptance of e-mental health interventions, identified predictors of acceptance, and explored their specific needs and demands.

METHODS: Data from N = 217 adolescent elite athletes (age range: 14-17 years) participating in a web-based survey (March 2022-March 2023) were analyzed. Frequencies for preferred program features and delivery modes were calculated. Acceptance and its predictors were examined using an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. Group comparisons (t-tests, ANOVAs) and hierarchical regression analyses were conducted.

RESULTS: Overall acceptance of e-mental health interventions was moderate. Female athletes and those in individual sports indicated higher acceptance than male and team-sport athletes. Gender (β = 0.097, p = .017), the UTAUT predictors performance expectancy (β = 0.458, p < .001), effort expectancy (β = 0.309, p < .001), and social influence (β = 0.152, p = .015) significantly explained variance in acceptance in adolescent elite athletes, whereas sport type, depression-, anxiety-, and distress symptoms, internet anxiety, digital confidence, and -overload were not significant predictors. Preferred interventions were customizable, delivered via smartphone app, and completed in 10-20-minutes sessions.

CONCLUSIONS: Findings highlight the need for user-centered, flexible e-mental health interventions tailored to adolescent elite athletes. Targeting key acceptance drivers and preferred design features may support sustained engagement and inform indicated prevention strategies in this population.

PMID:42274845 | DOI:10.1007/s44192-026-00474-9

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