Evaluating the Communication of Online Social Support: A Mixed-Methods Analysis of Structure and Content

Jesse W.C. Yip*

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    15 Citations (Scopus)

    Abstract

    Social support in online self-help groups has been found to benefit participants with emotional instability or mental illness. Many studies have employed content analysis to reveal categories of social support, claiming the prevalence of emotional and informational support can aid support seekers. In the studies, optimal matching theory is used to explain the helpfulness of these types of support. This article argues that content analysis is unpersuasive in its claim that support seekers benefit from social support; participants’ communicative behaviors should also be considered to evaluate the potential advantages and drawbacks of such groups. Drawing on a mixed-method approach of conversation analysis and content analysis, this study investigates the sequential structure and content of social support in communication in six online self-help groups for anxiety and depression (OSGADs). The main findings show that optimal matching theory may not be suitable for elucidating how support seekers receive help due to the immediate provision of social support and little interaction otherwise. In addition, results identify expressed understanding/empathy and advice as prominent support categories in OSGADs, with most thread openers requesting support indirectly.

    Original languageEnglish
    Pages (from-to)1210-1218
    Number of pages9
    JournalHealth Communication
    Volume35
    Issue number10
    Early online date3 Jun 2019
    DOIs
    Publication statusPublished - 23 Aug 2020

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