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The effect of peer support networks in alleviating anxiety and enhancing perceived social support

She, W.-J.; Yip, B.; Covaci, A.; Yu, S.; Ang, C. S.; Nakajima, S.; Siriaraya, P.

2026-03-26 health systems and quality improvement
10.64898/2026.03.22.26349028 medRxiv
Show abstract

Support from peers has long been considered an alternative support resource than professional healthcare ones. Despite the inconclusive findings of previous studies regarding the effects of peer support, the integration of Peer Support Networks (PSNs) for youth and adolescents appears to offer promising outcomes. However, many existing digital peer support systems operate as proprietary platforms, lacking transparency in monitoring the efficacy of support and in understanding how personality traits influence outcomes. However, many existing digital peer support systems operate as proprietary platforms lacking transparency in monitoring the effect of peer support and understand the influence of personality traits on its outcomes. To address these limitations, we utilized our research platform, Peer2S, a digital PSN designed to facilitate connections based on shared lived experiences while simultaneously monitoring users mental well-being and personality traits. We conducted a four-week within-subjects experiment with 28 Japanese university students to examine the PSN systems impact on anxiety and perceived social support. Following a two-week baseline control period, participants interacted with the system for two weeks. Pre- and post-intervention assessments utilized generalized anxiety and multidimensional social support measures, alongside personality evaluations. The results indicated that participants experienced a significant reduction in anxiety after using the system, whereas no significant changes occurred during the control period. Perceived general social support showed a borderline significant increase, though specific college-context support dimensions remained unchanged. Furthermore, multiple regression analysis revealed that personality traits moderated anxiety outcomes. Contrary to typical protective associations, higher agreeableness significantly predicted increased anxiety during the intervention, which may reflect cultural tendencies toward conflict avoidance and over-accommodation in Japan. Conscientiousness demonstrated a marginally significant protective effect against anxiety, while personality traits did not predict changes in perceived social support. These findings suggest that short-term, algorithmically mediated peer support can yield measurable improvements in mental well-being, particularly in reducing anxiety. Moreover, the varying impacts of personality traits highlight the necessity of considering sociocultural contexts when designing and deploying digital mental health interventions. Authors summaryThe formation of social bonds is often selective, established through shared values, cultural interests, or significant life experiences among "peers." In some populations such as adolescents and young adults, peer support is regarded as a promising source of empathy, understanding, and psychological support. We report a study conducted using our customized digital peer matchmaking system with Japanese university students to examine if this novel approach to peer support impacts mental well-being. We found that after just two weeks of using the system, participants experienced a significant reduction in their anxiety levels. We also dove deeper to look at if individual personality traits influence their use outcomes. Interestingly, our results revealed that highly agreeable individuals actually experienced increased anxiety while using the system. In a Japanese cultural context, this may occur because agreeable users tend to avoid conflict and over-accommodate others at their own expense. Ultimately, our research demonstrates that matchmaking algorithms can effectively facilitate digital peer support to improve mental well-being, provided we carefully consider how different personality traits and cultural backgrounds shape user experiences.

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