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Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions
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 Aug...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788841/ https://www.ncbi.nlm.nih.gov/pubmed/36469366 http://dx.doi.org/10.2196/36056 |
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author | Storman, Dawid Jemioło, Paweł Swierz, Mateusz Jan Sawiec, Zuzanna Antonowicz, Ewa Prokop-Dorner, Anna Gotfryd-Burzyńska, Marcelina Bala, Malgorzata M |
author_facet | Storman, Dawid Jemioło, Paweł Swierz, Mateusz Jan Sawiec, Zuzanna Antonowicz, Ewa Prokop-Dorner, Anna Gotfryd-Burzyńska, Marcelina Bala, Malgorzata M |
author_sort | Storman, Dawid |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9788841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-97888412022-12-24 Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions Storman, Dawid Jemioło, Paweł Swierz, Mateusz Jan Sawiec, Zuzanna Antonowicz, Ewa Prokop-Dorner, Anna Gotfryd-Burzyńska, Marcelina Bala, Malgorzata M JMIR Ment Health Review 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. JMIR Publications 2022-12-05 /pmc/articles/PMC9788841/ /pubmed/36469366 http://dx.doi.org/10.2196/36056 Text en ©Dawid Storman, Paweł Jemioło, Mateusz Jan Swierz, Zuzanna Sawiec, Ewa Antonowicz, Anna Prokop-Dorner, Marcelina Gotfryd-Burzyńska, Malgorzata M Bala. Originally published in JMIR Mental Health (https://mental.jmir.org), 05.12.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Review Storman, Dawid Jemioło, Paweł Swierz, Mateusz Jan Sawiec, Zuzanna Antonowicz, Ewa Prokop-Dorner, Anna Gotfryd-Burzyńska, Marcelina Bala, Malgorzata M Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title | Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title_full | Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title_fullStr | Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title_full_unstemmed | Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title_short | Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions |
title_sort | meeting the unmet needs of individuals with mental disorders: scoping review on peer-to-peer web-based interactions |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788841/ https://www.ncbi.nlm.nih.gov/pubmed/36469366 http://dx.doi.org/10.2196/36056 |
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