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BACKGROUND There is an increasing number of online support groups providing advice and information on topics related to mental health. OBJECTIVE The study aimed to investigate the needs that Internet users meet through peer-to-peer interactions. METHODS A search of 4 databases was performed until July 24, 2021. Qualitative or mixed methods (i.e., qualitative and quantitative) studies investigating interactions among Internet users with mental disorders were included. The φ coefficient was used and machine-learning (ML) techniques were applied to investigate associations between the type of mental disorders and online interactions linked to seeking help or support. RESULTS Of the 11,316 identified records, 38 studies that assessed a total of 79,735 users and 218,156 posts were included. The most frequent interactions were noted for people with eating disorders (19%), depression (19%), and psychoactive substance use (17%). We grouped interactions between users into 42 codes, with the “network” code being the most common (7%). The most frequently coexisting codes were “request for information” and “sharing self-disclosure” (34 times, φ = 0.57, P CONCLUSIONS People with mental disorders mostly use Internet to seek support, find answers to their questions, and to chat. The results of this analysis should be interpreted as a proof of concept. More data about online interactions between these people might help apply ML methods to develop a tool that might facilitate screening or even support mental health assessment. CLINICALTRIAL Our protocol was registered in the Open Science Framework (osf.io/j3azv). |
