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Online peer support is increasingly important to encourage patients with chronic diseases to engage in successful self-management. However, studies mainly focus on individual-level participation and have not fully explored how to maximize the impact of online peer support through group identification. In this study, we aim to build an online social identity-based group to examine the impact of group identity on peer support. Twenty-five participants who completed the first phase of a larger study were randomly assigned either to the treatment group (identity-based group level, n = 15, three subgroups, five members in each subgroup) or to the control group (individual-level, n = 10). All participants in both treatment and control groups received the same tasks and incentives. Peer support behavior (informational support and emotional support), task completion (knowledge learning, self-tracking behavior), and health-related outcomes (self-efficacy [SE] and HbA1c) were collected for qualitative and quantitative analysis. Results from a 3-month pilot experiment showed that the treatment group offered substantial enhancement in peer support compared to the control group. It also significantly promoted improvement in SE. However, there was no significant difference in task completion or changes in HbA1c between the two groups. The results of the content analysis suggest that having a team leader, timely responsiveness, and intergroup competition played important roles in building social identity-based online groups and subsequently generating peer support. We provide some encouraging results that indicate how online groups may be effectively designed to promote peer support. © Society of Behavioral Medicine 2022. All rights reserved. For permissions, please e-mail:


Jingyuan Su, Michelle Dugas, Xitong Guo, Guodong Gao. Building social identity-based groups to enhance online peer support for patients with chronic disease: a pilot study using mixed-methods evaluation. Translational behavioral medicine. 2022 May 26;12(5):702-712

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PMID: 35312778

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