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The quality of informational social support in online health communities: A content analysis of cancer-related discussions

OBJECTIVE: Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this...

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Autores principales: Petrič, Gregor, Cugmas, Marjan, Petrič, Rok, Atanasova, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941603/
https://www.ncbi.nlm.nih.gov/pubmed/36825079
http://dx.doi.org/10.1177/20552076231155681
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author Petrič, Gregor
Cugmas, Marjan
Petrič, Rok
Atanasova, Sara
author_facet Petrič, Gregor
Cugmas, Marjan
Petrič, Rok
Atanasova, Sara
author_sort Petrič, Gregor
collection PubMed
description OBJECTIVE: Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums. METHODS: A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS. RESULTS: The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, P < .001), trustworthiness (M = 4.65, P < .001), relevance (M = 3.59, P < .001), and justification (M = 3.81, P = .05) in messages providing informational social support regarding cancer-related issues. CONCLUSIONS: This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors.
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spelling pubmed-99416032023-02-22 The quality of informational social support in online health communities: A content analysis of cancer-related discussions Petrič, Gregor Cugmas, Marjan Petrič, Rok Atanasova, Sara Digit Health Original Research OBJECTIVE: Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums. METHODS: A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS. RESULTS: The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, P < .001), trustworthiness (M = 4.65, P < .001), relevance (M = 3.59, P < .001), and justification (M = 3.81, P = .05) in messages providing informational social support regarding cancer-related issues. CONCLUSIONS: This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors. SAGE Publications 2023-02-20 /pmc/articles/PMC9941603/ /pubmed/36825079 http://dx.doi.org/10.1177/20552076231155681 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Petrič, Gregor
Cugmas, Marjan
Petrič, Rok
Atanasova, Sara
The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title_full The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title_fullStr The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title_full_unstemmed The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title_short The quality of informational social support in online health communities: A content analysis of cancer-related discussions
title_sort quality of informational social support in online health communities: a content analysis of cancer-related discussions
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941603/
https://www.ncbi.nlm.nih.gov/pubmed/36825079
http://dx.doi.org/10.1177/20552076231155681
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