Application of user profiling in mental health management: a scoping review

Mental health disorders affect 970 million people globally, yet treatment access remains limited by stigma and resource constraints. User profiling technology leverages AI and multi-source data to enable personalized mental healthcare.

This scoping review synthesizes evidence on user profiling applications in patient mental health management to inform evidence-based practice.

Following established scoping review methodology, we systematically searched seven databases (Wanfang, CNKI, PubMed, Embase, Web of Science, Scopus, Cochrane Library) from 1 January 1964 to 28 May 2025. Two researchers independently screened records against eligibility criteria and extracted data.

Eighteen studies were included. User profiling construction encompassed three core phases: multidimensional data acquisition, feature extraction, and visualization. Applications spanned diverse populations including adolescents, young adults, and psychiatric patients, facilitating personalized intervention planning, resource allocation, and crisis management. Implementation demonstrated enhanced service accessibility, intervention precision, user experience optimization, and remote intervention efficacy.

User profiling technology delivers personalised mental health services through the integration of multidimensional data. This approach demonstrates significant advantages in enhancing intervention effectiveness, reducing healthcare costs, and improving user satisfaction, positioning it as a promising technology within the field of digital psychological interventions. However, its practical application still faces numerous challenges, including the long-term validation of current intervention outcomes and limitations in technological universality.