Abstract

Online mental health communities have become a major platform where individuals can talk about their mental health problems and obtain social support. This study aims to understand the antecedents of perceived usefulness among members in an online mental health community, while providing reference for the managers and users of online mental health communities. We obtained a total of 143,190 posts from ReachOut.com released by the CLPsych2017 shared task. Then, we used text mining to derive the independent and dependent variables. Next, a structural equation model observing the perceived usefulness of online mental health community members was constructed from the perspective of an information adoption model. The informativeness of help-seeking posts had a significant positive relationship with the information quality of reply posts; the information quality of reply posts was a significant positive predictor of perceived usefulness, with the information quality of reply posts partially mediating the relationship between the informativeness of help-seeking posts and perceived usefulness. The information provided by online mental health community members' help-seeking posts and the quality of replies were found to be the factors that influenced perceived usefulness. This study highlights the importance of the information quality of reply posts and provides useful insights for administrators who can help users to improve their response quality and obtain the support they need.

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