网络社区中糖尿病的多病模式和早期信号。

IF 2.5 Q2 HEALTH CARE SCIENCES & SERVICES
JAMIA Open Pub Date : 2025-05-30 eCollection Date: 2025-06-01 DOI:10.1093/jamiaopen/ooaf049
Ching Jin, Zhen Zhu
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引用次数: 0

摘要

目的:本研究旨在通过分析在线糖尿病支持社区的用户参与度及其与其他疾病相关社区的互动,探索与糖尿病相关的多发病模式。此外,它还试图评估是否可以通过在线参与数据检测到糖尿病的早期信号。材料和方法:我们从2008年到2024年收集了Reddit上3个与糖尿病相关的主要子版块(“diabetes”、“diabetes_t1”和“diabetes_t2”)和88个其他疾病相关的子版块的数据。构建了用户与子reddit之间的二部网络,并将其转化为加权多病态网络。使用统计阈值确定重要链接,以确保子reddit之间有意义的连接。此外,我们还分析了用户参与时间线,以识别潜在的糖尿病早期信号。结果:糖尿病与心理健康状况(如抑郁、焦虑和多动症)和体重管理讨论密切相关。其他值得注意的关联包括自身免疫性疾病、慢性疼痛、胃肠道疾病和生殖健康问题。在心理健康、肥胖和怀孕状况中发现了2型糖尿病的早期信号,但在1型糖尿病中没有发现明显的早期信号。讨论:本研究首次大规模实证分析了网络社区中糖尿病的多发病模式和早期信号。这些发现强化了已知的糖尿病的多病性,特别是它与心理健康和肥胖的关系。早期信号的存在表明,社交媒体数据可以帮助在诊断之前识别有风险的个体,为早期干预提供机会。结论:我们的研究结果表明,社交媒体数据可以揭示糖尿病的多病模式和早期信号,提供了传统健康记录之外的见解。随着数字健康数据的持续增长,有效利用这些资源对于推进糖尿病预防和管理将变得越来越重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimorbidity patterns and early signals of diabetes in online communities.

Objectives: This study aims to explore multimorbidity patterns associated with diabetes by analyzing user engagement in online diabetes support communities and their interactions with other disease-related communities. Additionally, it seeks to assess whether early signals of diabetes can be detected through online engagement data.

Materials and methods: We collected Reddit data for 3 primary diabetes-related subreddits ("diabetes," "diabetes_t1," and "diabetes_t2") and 88 other disease-related subreddits from 2008 to 2024. A bipartite network was constructed linking users to subreddits, which was then transformed into a weighted multimorbidity network. Significant links were identified using a statistical threshold to ensure meaningful connections between subreddits. Additionally, we analyzed user engagement timelines to identify potential early signals of diabetes.

Results: Diabetes is strongly linked to mental health conditions (such as depression, anxiety, and ADHD) and weight management discussions. Other notable associations include autoimmune diseases, chronic pain, gastrointestinal disorders, and reproductive health issues. Early signals of type 2 diabetes were detected in mental health, obesity, and pregnancy conditions, but no significant early indicators were found for type 1 diabetes.

Discussion: This study is the first large-scale empirical analysis of multimorbidity patterns and early signals of diabetes in online communities. The findings reinforce the known multimorbidity of diabetes, particularly its ties to mental health and obesity. The presence of early signals suggests that social media data could help identify individuals at risk before diagnosis, offering opportunities for early intervention.

Conclusion: Our findings demonstrate that social media data can reveal both multimorbidity patterns and early signals of diabetes, offering insights beyond traditional health records. As digital health data continue to grow, effectively leveraging these resources will become increasingly important for advancing diabetes prevention and management.

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来源期刊
JAMIA Open
JAMIA Open Medicine-Health Informatics
CiteScore
4.10
自引率
4.80%
发文量
102
审稿时长
16 weeks
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