Peer Support for Chronic Pain in Online Health Communities: Quantitative Study on the Dynamics of Social Interactions in a Chronic Pain Forum

• Published in: Journal of medical Internet research Vol. 26; no. 10289; p. e45858
• Main Authors: Necaise, Aaron, Amon, Mary Jean
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 05.09.2024; JMIR Publications
• Subjects: Care and treatment; Chronic pain; Chronic Pain - psychology; Health aspects; Health attitudes; Humans; Interpersonal communication; Online Social Networking; Online social networks; Pain; Peer Group; Psychological aspects; Social aspects; Social Interaction; Social Media; Social Networking; Social networks; Social Support; United States; growth curve modeling; chronic pain; sentiment analysis; wavelet analysis; online health communities; affective synchrony; nonlinear dynamics; social media; peer support
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/45858

Peer support for chronic pain is increasingly taking place on social media via social networking communities. Several theories on the development and maintenance of chronic pain highlight how rumination, catastrophizing, and negative social interactions can contribute to poor health outcomes. However, little is known regarding the role web-based health discussions play in the development of negative versus positive health attitudes relevant to chronic pain. This study aims to investigate how participation in online peer-to-peer support communities influenced pain expressions by examining how the sentiment of user language evolved in response to peer interactions. We collected the comment histories of 199 randomly sampled Reddit (Reddit, Inc) users who were active in a popular peer-to-peer chronic pain support community over 10 years. A total of 2 separate natural language processing methods were compared to calculate the sentiment of user comments on the forum (N=73,876). We then modeled the trajectories of users' language sentiment using mixed-effects growth curve modeling and measured the degree to which users affectively synchronized with their peers using bivariate wavelet analysis. In comparison to a shuffled baseline, we found evidence that users entrained their language sentiment to match the language of community members they interacted with (t =4.02; P<.001; Cohen d=0.40). This synchrony was most apparent in low-frequency sentiment changes unfolding over hundreds of interactions as opposed to reactionary changes occurring from comment to comment (F =17.70; P<.001). We also observed a significant trend in sentiment across all users (β=-.02; P=.003), with users increasingly using more negative language as they continued to interact with the community. Notably, there was a significant interaction between affective synchrony and community tenure (β=.02; P=.02), such that greater affective synchrony was associated with negative sentiment trajectories among short-term users and positive sentiment trajectories among long-term users. Our results are consistent with the social communication model of pain, which describes how social interactions can influence the expression of pain symptoms. The difference in long-term versus short-term affective synchrony observed between community members suggests a process of emotional coregulation and social learning. Participating in health discussions on Reddit appears to be associated with both negative and positive changes in sentiment depending on how individual users interacted with their peers. Thus, in addition to characterizing the sentiment dynamics existing within online chronic pain communities, our work provides insight into the potential benefits and drawbacks of relying on support communities organized on social media platforms.