In JMIR mental health
BACKGROUND : An increasing number of online support groups are providing advice and information on topics related to mental health.
OBJECTIVE : This study aimed to investigate the needs that internet users meet through peer-to-peer interactions.
METHODS : A search of 4 databases was performed until August 15, 2022. Qualitative or mixed methods (ie, qualitative and quantitative) studies investigating interactions among internet users with mental disorders were included. The φ coefficient was used and machine learning techniques were applied to investigate the associations between the type of mental disorders and web-based interactions linked to seeking help or support.
RESULTS : Of the 13,098 identified records, 44 studies (analyzed in 54 study-disorder pairs) that assessed 82,091 users and 293,103 posts were included. The most frequent interactions were noted for people with eating disorders (14/54, 26%), depression (12/54, 22%), and psychoactive substance use disorders (9/54, 17%). We grouped interactions between users into 42 codes, with the empathy or compassion code being the most common (41/54, 76%). The most frequently coexisting codes were request for information and network (35 times; φ=0.5; P<.001). The algorithms that provided the best accuracy in classifying disorders by interactions were decision trees (44/54, 81%) and logistic regression (40/54, 74%). The included studies were of moderate quality.
CONCLUSIONS : People with mental disorders mostly use the internet to seek support, find answers to their questions, and chat. The results of this analysis should be interpreted as a proof of concept. More data on web-based interactions among these people might help apply machine learning methods to develop a tool that might facilitate screening or even support mental health assessment.
Storman Dawid, Jemioło Paweł, Swierz Mateusz Jan, Sawiec Zuzanna, Antonowicz Ewa, Prokop-Dorner Anna, Gotfryd-Burzyńska Marcelina, Bala Malgorzata M
2022-Dec-05
mental disorders, peer-to-peer interactions, scoping review, web-based interactions
