School of Modeling, Simulation, and Training, University of Central Florida, Orlando, FL, United States.
Department of Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States.
J Med Internet Res. 2024 Sep 5;26:e45858. 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.
通过社交网络社区，同伴支持在社交媒体上越来越多地用于慢性疼痛。关于慢性疼痛的发展和维持的几个理论强调了沉思、灾难化和消极的社会互动如何导致不良的健康结果。然而，对于网络健康讨论在慢性疼痛相关的消极和积极健康态度的发展中所起的作用，人们知之甚少。
本研究旨在通过研究参与者如何响应同伴互动来改变用户语言的情绪，从而探讨参与在线同伴支持社区如何影响疼痛表达。
我们收集了 199 名随机抽样的 Reddit（Reddit，Inc）用户的评论历史，这些用户在一个流行的同行慢性疼痛支持社区中活跃了 10 年。比较了 2 种不同的自然语言处理方法来计算论坛上用户评论的情绪（N=73876）。然后，我们使用混合效应增长曲线模型来模拟用户语言情绪的轨迹，并使用双变量小波分析来衡量用户与同伴情感同步的程度。
与随机基线相比，我们发现有证据表明，用户的语言情绪与他们与之互动的社区成员的语言相匹配（t=4.02；P<.001；Cohen d=0.40）。这种同步性在数百次互动中展开的低频情绪变化中最为明显，而不是在评论之间发生的反应性变化（F=17.70；P<.001）。我们还观察到所有用户的情绪都有显著的趋势（β=-.02；P=.003），随着用户继续与社区互动，他们越来越多地使用更消极的语言。值得注意的是，情感同步和社区任期之间存在显著的相互作用（β=.02；P=.02），即短期用户的情感同步程度较高与负面情绪轨迹相关，而长期用户的情感同步程度较高与正面情绪轨迹相关。
我们的结果与疼痛的社会沟通模型一致，该模型描述了社会互动如何影响疼痛症状的表达。在社区成员中观察到的长期与短期情感同步之间的差异表明存在情绪调节和社会学习的过程。在 Reddit 上参与健康讨论似乎与情绪的积极和消极变化都有关，具体取决于个体用户与他们的同伴的互动方式。因此，除了描述在线慢性疼痛社区中存在的情绪动态外，我们的工作还提供了对依赖于社交媒体平台组织的支持社区的潜在好处和缺点的见解。
