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Social Support in a Diabetes Online Community: Mixed Methods Content Analysis

BACKGROUND: Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories t...

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Detalles Bibliográficos
Autores principales: Da Moura Semedo, Cidila, Bath, Peter A, Zhang, Ziqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945924/
https://www.ncbi.nlm.nih.gov/pubmed/36607714
http://dx.doi.org/10.2196/41320
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author Da Moura Semedo, Cidila
Bath, Peter A
Zhang, Ziqi
author_facet Da Moura Semedo, Cidila
Bath, Peter A
Zhang, Ziqi
author_sort Da Moura Semedo, Cidila
collection PubMed
description BACKGROUND: Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories that may be more important for different diabetes stages may help diabetes online communities (DOCs) provide more tailored support to web-based users. OBJECTIVE: This study aimed to explore and quantify the categorical patterns of social support observed in a DOC, taking into consideration users’ different diabetes stages, including prediabetes, type 2 diabetes (T2D), T2D with insulin treatment, and T2D remission. METHODS: Data were collected from one of the largest DOCs in Europe: Diabetes.co.uk. Drawing on a mixed methods content analysis, a qualitative content analysis was conducted to explore what social support categories could be identified in users’ posts. A total of 1841 posts were coded by 5 human annotators according to a modified version of the Social Support Behavior Code, including 7 different social support categories: achievement, congratulations, network support, seeking emotional support, seeking informational support, providing emotional support, and providing informational support. Subsequently, quantitative content analysis was conducted using chi-square post hoc analysis to compare the most prominent social support categories across different stages of diabetes. RESULTS: Seeking informational support (605/1841, 32.86%) and providing informational support (597/1841, 32.42%) were the most frequent categories exchanged among users. The overall distribution of social support categories was significantly different across the diabetes stages (χ(2)(18)=287.2; P<.001). Users with prediabetes sought more informational support than those in other stages (P<.001), whereas there were no significant differences in categories posted by users with T2D (P>.001). Users with T2D under insulin treatment provided more informational and emotional support (P<.001), and users with T2D in remission exchanged more achievement (P<.001) and network support (P<.001) than those in other stages. CONCLUSIONS: This is the first study to highlight what, how, and when different types of social support may be beneficial at different stages of diabetes. Multiple stakeholders may benefit from these findings that may provide novel insights into how these categories can be strategically used and leveraged to support diabetes management.
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spelling pubmed-99459242023-02-23 Social Support in a Diabetes Online Community: Mixed Methods Content Analysis Da Moura Semedo, Cidila Bath, Peter A Zhang, Ziqi JMIR Diabetes Original Paper BACKGROUND: Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories that may be more important for different diabetes stages may help diabetes online communities (DOCs) provide more tailored support to web-based users. OBJECTIVE: This study aimed to explore and quantify the categorical patterns of social support observed in a DOC, taking into consideration users’ different diabetes stages, including prediabetes, type 2 diabetes (T2D), T2D with insulin treatment, and T2D remission. METHODS: Data were collected from one of the largest DOCs in Europe: Diabetes.co.uk. Drawing on a mixed methods content analysis, a qualitative content analysis was conducted to explore what social support categories could be identified in users’ posts. A total of 1841 posts were coded by 5 human annotators according to a modified version of the Social Support Behavior Code, including 7 different social support categories: achievement, congratulations, network support, seeking emotional support, seeking informational support, providing emotional support, and providing informational support. Subsequently, quantitative content analysis was conducted using chi-square post hoc analysis to compare the most prominent social support categories across different stages of diabetes. RESULTS: Seeking informational support (605/1841, 32.86%) and providing informational support (597/1841, 32.42%) were the most frequent categories exchanged among users. The overall distribution of social support categories was significantly different across the diabetes stages (χ(2)(18)=287.2; P<.001). Users with prediabetes sought more informational support than those in other stages (P<.001), whereas there were no significant differences in categories posted by users with T2D (P>.001). Users with T2D under insulin treatment provided more informational and emotional support (P<.001), and users with T2D in remission exchanged more achievement (P<.001) and network support (P<.001) than those in other stages. CONCLUSIONS: This is the first study to highlight what, how, and when different types of social support may be beneficial at different stages of diabetes. Multiple stakeholders may benefit from these findings that may provide novel insights into how these categories can be strategically used and leveraged to support diabetes management. JMIR Publications 2023-01-06 /pmc/articles/PMC9945924/ /pubmed/36607714 http://dx.doi.org/10.2196/41320 Text en ©Cidila Da Moura Semedo, Peter A Bath, Ziqi Zhang. Originally published in JMIR Diabetes (https://diabetes.jmir.org), 06.01.2023. 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 Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on https://diabetes.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Da Moura Semedo, Cidila
Bath, Peter A
Zhang, Ziqi
Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title_full Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title_fullStr Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title_full_unstemmed Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title_short Social Support in a Diabetes Online Community: Mixed Methods Content Analysis
title_sort social support in a diabetes online community: mixed methods content analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945924/
https://www.ncbi.nlm.nih.gov/pubmed/36607714
http://dx.doi.org/10.2196/41320
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