ArticleJMIR diabetes2023
Social Support in a Diabetes Online Community: Mixed Methods Content Analysis.
Article in JMIR diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Social Support Mechanisms in an Online Type 1 Diabetes Community: Social Network Analysis of Stakeholder Diversity and Disease Duration.Journal of medical Internet research · 2026Observational
- Investigating Social Media Use by Young People to Self-Manage Type 1 Diabetes Mellitus: Large-Scale Analysis of Social Media Discussions Using Topic Modeling.Journal of medical Internet research · 2025Article
- Analysis of the Behavioral Performance and Social Support of Patients in Online Health Communities From User Profile Perspectives: Comparative Study.Journal of medical Internet research · 2025Article
- Toward Personalized Digital Experiences to Promote Diabetes Self-Management: Mixed Methods Social Computing Approach.JMIR diabetes · 2025Article
- Online Health Information Seeking: Implications for Self-Management in Hypertension.Risk management and healthcare policy · 2025Article
- Factors Influencing Psychological Insulin Resistance Among Patients with Type 2 Diabetes in China: A Structural Equation Model Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- How Does an Online Mental Health Community on Twitter Empower Diverse Population Levels and Groups? A Qualitative Analysis of #BipolarClub.Journal of medical Internet research · 2024Article
- Preferences for Peer Support Amongst Families Engaged in Paediatric Screening Programmes: The Perspectives of Parents Involved in Screening for Type 1 Diabetes in Children Aged 3-13.Health expectations : an international journal of public participation in health care and health policy · 2024Article
- Review
- Article
- Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India.Frontiers in artificial intelligence · 2024Article
- Online Health Information Seeking Behaviors Among People With Diabetes: A Scoping Review.SAGE open nursingReview
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Authors and funding
3 authors.
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Abstract
backgroundPatients 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.
objectiveThis 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.
methodsData 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.
resultsSeeking 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
conclusionsThis 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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