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Overcoming Health Fears: How do online peers help patients with chronic pain?

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  • Rueger, Jasmina
  • Dolfsma, Wilfred
  • Aalbers, Rick

Abstract

This study investigates how online interactions influence anxiety levels in patients with chronic musculoskeletal pain by examining the impact of social interactions within online health communities. We used actor-oriented modelling to analyse the online interactions of 200 users with musculoskeletal pain in an English-speaking online health community over three years. This method focuses on how people make decisions and interact within a network. We examined the behaviours and network dynamics of influential users with different anxiety levels to see how they engage socially online and if they adopt (non-)anxious attitudes from their peers. The findings suggest that although online social interactions could benefit anxious patients, more anxious individuals tend to experience more social isolation online. Moreover, individuals tend to adopt anxious attitudes from online peers, highlighting the influence of social interactions on emotional well-being. Contrary to homophily assumptions, we observed an “opposites anxiety attract” phenomenon—users frequently formed ties with others whose anxiety levels differed from their own. This dynamic indicates both encouraging and concerning aspects of virtual peer influence. While online health communities can reduce anxiety in patients with musculoskeletal pain, the effectiveness of social support depends on individuals’ anxiety levels and their online interactions. Understanding these nuances is important for optimising digital platforms to support those struggling with anxiety and depression related to chronic pain.

Suggested Citation

  • Rueger, Jasmina & Dolfsma, Wilfred & Aalbers, Rick, 2025. "Overcoming Health Fears: How do online peers help patients with chronic pain?," Social Science & Medicine, Elsevier, vol. 382(C).
    • Handle: RePEc:eee:socmed:v:382:y:2025:i:c:s0277953625006288
    DOI: 10.1016/j.socscimed.2025.118297
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    1. Shi, Runyu & Petrakaki, Dimitra, 2026. "User-AI intimacy in digital health," Social Science & Medicine, Elsevier, vol. 389(C).

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