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Effects of members' response styles in an online depression community based on text mining and empirical analysis
Information Processing and Management ; 60(2), 2023.
Article in English | Scopus | ID: covidwho-2246550
ABSTRACT
The online depression community (ODC) has become a popular resource for people with depression to manage their mental health during the COVID-19 pandemic. This study proposed a novel perspective based on response style theory to investigate whether depression individuals' distractive and ruminative behaviors in ODC were related to social support received and co-rumination. Furthermore, we explored the influences of social support and co-rumination on suicidal behaviors using panel data set. We collected text data from 22,286 depressed users of a large ODC in China from March 2020 to July 2021, and conducted text mining and econometrics analyses to test our research questions. The results showed that depression users' online ruminative behaviors had a positive relationship with the co-rumination and had a negative relationship with social support received. Besides, constructive distractive behaviors (i.e., providing social support to others) increased the support users received from others but had a negative relationship with co-rumination. Depression users' future suicidal behaviors are influenced by past received social support and co-rumination. The received social supports and co-rumination have a negative and positive influence on depression users' future suicidal behaviors, respectively. Our results enrich the application of response style theory in online medicine. They provide meaningful insights into behaviors that influence the acquisition of online social support and the incidence of online co-rumination in ODCs. This study helps relevant institutions to conduct more targeted online suicide interventions for depression patients. © 2022 Elsevier Ltd
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: Information Processing and Management Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: Information Processing and Management Year: 2023 Document Type: Article