JMIR Publications

ABSTRACT

Background:

Peer support among patients with chronic pain is increasingly taking place in social media communities. Several theories on the development and maintenance of chronic pain highlight how negative rumination, catastrophizing, and social interactions can facilitate poor health outcomes. However, little is known regarding the role medical discussions on social media play in the development of negative versus positive health attitudes that are highly relevant to chronic pain progression.

Objective:

The aim of the current study was to understand how participation in social media health communities influenced patient pain expressions based on changes in language sentiment and affective synchrony with other community members.

Methods:

We collected the complete comment histories of 200 randomly sampled social media users who were active in a popular chronic pain community (/r/ChronicPain) over a span of ten years. Two 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 of affective synchrony during their interactions with bivariate wavelet analysis.

Results:

In comparison to a shuffled baseline, we found evidence that users entrained their language sentiment to more closely match the language of community members they interacted with (t(198) = 4.02, P < .001, d = .40). This synchrony was most apparent in low-frequency sentiment changes unfolding over hundreds of interactions as opposed to reactionary changes occurring comment-to-comment (F(2,198) = 17.70, P < .001). We also observed a significant trend in sentiment across all users (β = -.02, P = .003), with users utilizing increasingly more negative language as they continued to post comments in the community. Notably, there was a significant interaction between affective synchrony and community tenure (β = .02, P = .02), such that affective synchrony was associated with negative sentiment trajectories among short-term users and positive sentiment trajectories among long-term users.

Conclusions:

Our results are consistent with the social communication model of pain, which describes how social interactions can influence the interpretation and expression of pain symptoms. The long-term affective synchrony observed between community members suggests a process of emotional coregulation and social learning. Although overly pessimistic pain attitudes have negative health implications, caution should be taken when interpreting our results. Notably, we found that social media usage was associated with both negative and positive changes in sentiment depending on how individual users interacted with the community. Thus, in addition to characterizing the sentiment dynamics existing within online chronic pain communities, our work provides insight into how social media health communities can be utilized as a productive outlet for pain patients.