糖尿病在线社区的社会支持:混合方法内容分析。

Q2 Medicine JMIR Diabetes Pub Date : 2023-01-06 DOI:10.2196/41320
Cidila Da Moura Semedo, Peter A Bath, Ziqi Zhang
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摘要

背景:糖尿病患者根据糖尿病的分期可能会有不同的需求。这些需求可以通过在线健康社区得到满足,个人在其中寻求与健康有关的信息并交换不同类型的社会支持。了解对不同糖尿病阶段可能更重要的社会支持类别可能有助于糖尿病在线社区(DOCs)为网络用户提供更有针对性的支持。目的:本研究旨在探讨和量化DOC中观察到的社会支持的分类模式,考虑用户的不同糖尿病阶段,包括糖尿病前期、2型糖尿病(T2D)、胰岛素治疗的T2D和T2D缓解。方法:数据收集自欧洲最大的DOCs之一:Diabetes.co.uk。利用混合方法内容分析,进行定性内容分析,以探索在用户的帖子中可以识别哪些社会支持类别。5名人工注释员根据修改后的《社会支持行为规范》对帖子进行编码,共1841篇,包括成就、祝贺、网络支持、寻求情感支持、寻求信息支持、提供情感支持和提供信息支持7个不同的社会支持类别。随后,采用卡方事后分析进行定量内容分析,比较不同阶段糖尿病患者最突出的社会支持类别。结果:寻求信息支持(605/1841,32.86%)和提供信息支持(597/1841,32.42%)是用户交流频率最高的类别。社会支持类别在糖尿病各阶段的总体分布差异有统计学意义(χ218=287.2;P.001)。胰岛素治疗下的t2dm患者提供了更多的信息和情感支持(结论:这是第一个强调不同类型的社会支持在糖尿病不同阶段可能有益的研究。多个利益相关者可能从这些发现中受益,这些发现可能为如何战略性地使用和利用这些类别来支持糖尿病管理提供新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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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 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 (χ218=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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来源期刊
JMIR Diabetes
JMIR Diabetes Computer Science-Computer Science Applications
CiteScore
4.00
自引率
0.00%
发文量
35
审稿时长
16 weeks
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