Decision-making processes underlying digital mental health intervention adoption among adolescents and young adults with common mental health issues: An integrated DEMATEL-ISM approach
Yongyi Wang, Junjie Liu, Shimin ZhuObjective
Despite their potential, digital mental health interventions (DMHIs) are underutilized among adolescents and young adults (AYAs) with common mental health issues. While prior work has synthesized facilitators and barriers to DMHI adoption, the decision-making processes across heterogeneous AYA remain insufficiently understood. This study aimed to understand DMHI adoption decisions by examining the relative importance and underlying pathways of identified factors within AYA subgroups.
Methods
Participants in this cross-sectional study were recruited from secondary schools and universities in Hong Kong. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) was applied to reveal factor importance and cause-effect relationships, while the Interpretive Structural Modelling (ISM) approach was used to map hierarchical structures.
Results
Based on 14 facilitators and 13 barriers to DMHI adoption, the DEMATEL results suggested that, for adolescents, endorsements and motivational challenges emerged as the most central factors, while the supportive environment and technical issues were the most influential. Among young adults, universality and retention issues were the most central, with content engagement and technical issues exerting the greatest influence. Notable differences were observed regarding the driving mechanisms behind adoption decisions: adolescents emphasised both intervention-specific and individual-level drivers, whereas young adults primarily focused on intervention-related concerns, including high quality and effect and design limitations.
Conclusion
This exploratory study offers a systematic, user-centred perspective on DMHI adoption processes, with developmental contrasts highlighting the need for more age-sensitive guidance in intervention design and implementation. These insights may provide a preliminary basis for future research on resource allocation and policy development, with further evidence from larger and more demographically balanced samples needed to support broader policy implications.