The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Feeling Blue? Go Online: An Empirical Study of Social Support Among Patients
Open accessAbstract
In this paper, we investigate whether social support exchanged in an online healthcare community benefits patients’ mental health. We propose a nonhomogeneous Partially Observed Markov Decision Process (POMDP) model to examine the latent health outcomes for 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 benefit 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 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 depending on 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.
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Cited by
Hansen, J. M., Saridakis, G., & Benson, V. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.010 · Cited by 527
Zhang, X., Liu, S., Deng, Z., & Chen, X. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.06.028 · Cited by 355
Internet’s Dirty Secret: Assessing the Impact of Online Intermediaries on HIV Transmission1
Chan, J., & Ghose, A. (2014) · MIS Quarterly · doi:10.25300/misq/2014/38.4.01 · Cited by 178
Engaging Voluntary Contributions in Online Communities: A Hidden Markov Model1
Chen, W., Wei, X., & Zhu, K. X. (2018) · MIS Quarterly · doi:10.25300/misq/2018/14196 · Cited by 173
Exploring the inhibitors of online health service use intention: A status quo bias perspective
Zhang, X., Guo, X., Wu, Y., Lai, K.-H., & Vogel, D. (2017) · Information & Management · doi:10.1016/j.im.2017.02.001 · Cited by 126
Metadata
- Authors
- Yan, L., & Tan, Y.
- Venue
- Information Systems Research
- Published
- 2014-12
- Volume
- 25
- Issue
- 4
- Pages
- 690-709
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2119453837
- Cited by
- 447
- References
- 69
- FWCI
- 30.20
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.