AUTHOR=Malik Ishaq , Mushquash Aislin R. 

TITLE=Acceptance of a mental health app (JoyPopTM) for postsecondary students: a prospective evaluation using the UTAUT2

JOURNAL=Frontiers in Digital Health

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2025.1503428

DOI=10.3389/fdgth.2025.1503428

ISSN=2673-253X

ABSTRACT=IntroductionMental health (MH) smartphone applications (MH apps) can support the increasing MH needs of postsecondary students and mitigate barriers to accessing support. Evaluating MH app acceptance using technology acceptance models is recommended to improve student engagement with MH apps. The JoyPopTM app was designed to improve youth resilience and emotion regulation. The JoyPopTM app is associated with improved student MH, but its acceptance has yet to be evaluated quantitatively. The present study used the Unified Theory of Acceptance and Use of Technology (UTAUT2) to evaluate and examine constructs and moderators influencing the acceptance (i.e., behavioural intention) and use of the JoyPopTM app.MethodParticipants were 183 postsecondary students attending a Canadian University who used the app for one week and completed measures before and after using the app. Relationships posited by the UTAUT2 were tested using partial least squares structural equation modelling (PLS-SEM).ResultsMost participants accepted the JoyPopTM app. The UTAUT2 model explained substantial variance in behavioural intention and app use. Performance expectancy, hedonic motivation, and facilitating conditions predicted behavioural intention, and behavioural intention and facilitating conditions predicted app use. Age moderated the association between facilitating conditions and behavioural intention. Experience moderated the relationship between performance expectancy, hedonic motivation, and social influence on behavioural intention.DiscussionResults provide insight into factors influencing the acceptance of the JoyPopTM app and its ability to engage students. Results also provide valuable insights for evaluating and optimally designing MH apps.