Feeling Blue? Go Online: An Empirical Study of Social Support among Patients

Abstract

In this paper, we investigate whether social support exchanged in an online healthcare community benefits patients’ mental health. We propose an inhomogeneous Partially Observed Markov Decision Process (POMDP) model to examine the latent health outcomes of online health community members. The transition between different health states is modeled as a probability function that incorporates different forms of social support that patients exchange via discussion board posts. We find that patients gain benefits from learning from others and that their participation in the online community helps them to improve their health and to better engage in their disease self-management process. Our results also reveal differences in the influence of various forms of social support exchanged on the evolution of patients’ health conditions. We find evidence that informational support is the most prevalent type of support in the online healthcare community. Nevertheless, emotional support plays the most significant role in helping patients move to a healthier state. Overall, the influence of social support is found to vary by patients’ health conditions. Finally, we demonstrate that our proposed POMDP model can provide accurate predictions for patients’ health states and can be used to recover missing or unavailable information on patients’ health conditions.

Keywords: healthcare, social networks, online media, user generated content, Observed Markov Decision Process

JEL Classification: C51, C31, C32, C50, C52, C53, I10, I18