» Articles » PMID: 36231878

Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach

Overview
Publisher MDPI
Date 2022 Oct 14
PMID 36231878
Authors
Affiliations
Soon will be listed here.
Abstract

Mental health attitude has huge impacts on the improvement of mental health. In response to the ongoing damage the COVID-19 pandemic caused to the mental health of the Chinese people, this study aims to explore the factors associated with mental health attitude in China. To this end, we extract the key topics in mental health-related microblogs on Weibo, the Chinese equivalent of Twitter, using the structural topic modeling (STM) approach. An interaction term of sentiment polarity and time is put into the STM model to track the evolution of public sentiment towards the key topics over time. Through an in-depth analysis of 146,625 Weibo posts, this study captures 12 topics that are, in turn, classified into four factors as stigma ( = 54,559, 37.21%), mental health literacy ( = 32,199, 21.96%), public promotion ( = 30,747, 20.97%), and social support ( = 29,120, 19.86%). The results show that stigma is the primary factor inducing negative mental health attitudes in China as none of the topics related to this factor are considered positive. Mental health literacy, public promotion, and social support are the factors that could enhance positive attitudes towards mental health, since most of the topics related to these factors are identified as positive ones. The provision of tailored strategies for each of these factors could potentially improve the mental health attitudes of the Chinese people.

Citing Articles

Knowledge, attitudes, and practices regarding whole-course management among patients with gastrointestinal cancers: a cross-sectional study.

Huang M, Feng L, Ren H, Yuan Z, Liu C, Liu Y World J Surg Oncol. 2025; 23(1):45.

PMID: 39924482 PMC: 11809093. DOI: 10.1186/s12957-025-03668-7.


Exploring sources of patient dissatisfaction in mobile health communication: A text analysis based on structural topic model.

Liu J, Ding P, Jiang H Digit Health. 2024; 10:20552076241287890.

PMID: 39381814 PMC: 11459492. DOI: 10.1177/20552076241287890.


Mental health status among non-medical college students returning to school during the COVID-19 pandemic in Zhanjiang city: A cross-sectional study.

Deng X, Zhang H Front Psychol. 2023; 13:1035458.

PMID: 36710795 PMC: 9874120. DOI: 10.3389/fpsyg.2022.1035458.


Topic modeling and sentiment analysis of Chinese people's attitudes toward volunteerism amid the COVID-19 pandemic.

Yin R, Wu J, Tian R, Gan F Front Psychol. 2022; 13:1064372.

PMID: 36405177 PMC: 9672683. DOI: 10.3389/fpsyg.2022.1064372.

References
1.
Woodward A, Taylor R, Bullard K, Neighbors H, Chatters L, Jackson J . Use of professional and informal support by African Americans and Caribbean blacks with mental disorders. Psychiatr Serv. 2008; 59(11):1292-8. PMC: 2955359. DOI: 10.1176/ps.2008.59.11.1292. View

2.
Shi L, Lu Z, Que J, Huang X, Lu Q, Liu L . Long-Term Impact of COVID-19 on Mental Health among the General Public: A Nationwide Longitudinal Study in China. Int J Environ Res Public Health. 2021; 18(16). PMC: 8393580. DOI: 10.3390/ijerph18168790. View

3.
Lee H, Hwang J, Ball J, Lee J, Yu Y, Albright D . Mental Health Literacy Affects Mental Health Attitude: Is There a Gender Difference?. Am J Health Behav. 2020; 44(3):282-291. DOI: 10.5993/AJHB.44.3.1. View

4.
Bradbury A . Mental Health Stigma: The Impact of Age and Gender on Attitudes. Community Ment Health J. 2020; 56(5):933-938. DOI: 10.1007/s10597-020-00559-x. View

5.
Reavley N, Jorm A . Recognition of mental disorders and beliefs about treatment and outcome: findings from an Australian national survey of mental health literacy and stigma. Aust N Z J Psychiatry. 2011; 45(11):947-56. DOI: 10.3109/00048674.2011.621060. View