Empirical study of factors that influence the perceived usefulness of online mental health community members

Author:

Li Jing12ORCID,Liu Dexi1,Wan Changxuan1,Liang Zifang1,Zhu Tingshao3ORCID

Affiliation:

1. Jiangxi University of Finance and Economics Nanchang China

2. Institute for Data Analysis and Intelligent Decision Making Fujian Jiangxia University Fuzhou China

3. Institute of Psychology Chinese Academy of Sciences Beijing China

Abstract

AbstractOnline 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.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Psychology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3