ArticleJMIR mental health2022
Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions.
Article in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Enhancing care in alcohol-associated liver disease through peer support for alcohol use disorder.Hepatology communications · 2026Review
- Nursing students' attitudes and intentions towards seeking professional psychological help: the mediating role of emotional intelligence.BMC psychology · 2025Article
- Technologies for Interoperable Internet of Medical Things Platforms to Manage Medical Emergencies in Home and Prehospital Care: Scoping Review.Journal of medical Internet research · 2025Article
- Needs Expressed in Peer-to-Peer Web-Based Interactions Among People With Depression and Anxiety Disorders Hospitalized in a Mental Health Facility: Mixed Methods Study.Journal of medical Internet research · 2024Article
- Understanding the Impacts of Online Mental Health Peer Support Forums: Realist Synthesis.JMIR mental health · 2024Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn increasing number of online support groups are providing advice and information on topics related to mental health.
objectiveThis study aimed to investigate the needs that internet users meet through peer-to-peer interactions.
methodsA 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.
resultsOf 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.
conclusionsPeople 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.