Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 16, 2023
Open Peer Review Period: Jan 16, 2023 - Mar 13, 2023
Date Accepted: Mar 8, 2023
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Analysis of public attitudes towards anxiety disorder in social media
ABSTRACT
Background:
Anxiety disorder has become a major clinical and public health problem, which causes a significant economic burden in worldwide. Public attitudes towards anxiety can impact the psychological state, help seeking and social activities of people with anxiety.
Objective:
The purpose of this study was to explore public attitudes towards anxiety disorders and the changing trends of these attitudes by analyzing the posts related to anxiety disorders in social media (e.g., Sina Weibo), as well as psycholinguistic and topical features of the text content of posts.
Methods:
A total of 325,807 Sina Weibo posts with the keyword term “anxiety disorder” from April 2018 to March 2022 were collected and analyzed. First, it analyzed the changing trends of the number and total length of posts every month. Second, a Chinese Linguistic Psychological Text Analysis System (TextMind) was used to analyze the changing trends of language features of posts. Third, we used a topic model for semantic content analysis to identify specific themes in Weibo users' attitudes toward anxiety.
Results:
The changing trends of the number and the total length of posts indicated that anxiety related posts significantly increased from April 2018 to March 2022, and were greatly impacted by the beginning of the new terms. The analysis of linguistic features showed that the frequency of cognitive process, affective process, biological process words and assent words increased significantly over time, while the frequency of social process words decreased significantly, and the public anxiety was greatly impacted by the COVID-19 pandemic. Feature correlation analysis showed that the frequencies of words related to work and family are almost negatively correlated with the ones of other psychological words. Semantic content analysis identified five common topics: discrimination and stigma, symptoms and physical health, treatment and support, work and social, and family and life. The results illustrated that the area of topic "family and life" decreased significantly over time, while the other four areas of topics all increased.
Conclusions:
The findings of this study indicate that pubic discrimination and stigma against anxiety disorder remain high, particularly in the aspects of self-denial and negative emotions. People with anxiety disorders should receive more social support to reduce the impact of discrimination and stigma.
Citation
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Copyright
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