Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Oct 1;19(19):12579.
doi: 10.3390/ijerph191912579.

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

Ruheng Yin  1 , Rui Tian  1 , Jing Wu  2 , Feng Gan  1
Affiliations

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

Ruheng Yin et al. Int J Environ Res Public Health. .

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 (n = 54,559, 37.21%), mental health literacy (n = 32,199, 21.96%), public promotion (n = 30,747, 20.97%), and social support (n = 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.

Keywords: COVID-19; China; Weibo; mental health attitude; social media; structural topic modeling; text analysis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Framework of the data analysis process.
Figure 2
Figure 2
Plate diagram of structural topic model (STM).
Figure 3
Figure 3
Total number of Weibo posts for 12 months from August 2021 to June 2022.
Figure 4
Figure 4
Topic prevalence based on sentiment polarity (positive vs. negative).
Figure 5
Figure 5
Change in topic prevalence based on sentiment polarity over time. (a) Information seeking (topic 1); (b) advice and sharing (topic 2); (c) media promotion (topic 3); (d) celebrity effect (topic 4); (e) community effect (topic 5); (f) encouragement (topic 10); (g) World Mental Health Day (topic 11); (h) public stigma (topic 6); (i) self-stigma (topic 7); (j) mental health service (topic 8); (k) patient stories (topic 9); (l) symptoms description (topic 12).
Figure 5
Figure 5
Change in topic prevalence based on sentiment polarity over time. (a) Information seeking (topic 1); (b) advice and sharing (topic 2); (c) media promotion (topic 3); (d) celebrity effect (topic 4); (e) community effect (topic 5); (f) encouragement (topic 10); (g) World Mental Health Day (topic 11); (h) public stigma (topic 6); (i) self-stigma (topic 7); (j) mental health service (topic 8); (k) patient stories (topic 9); (l) symptoms description (topic 12).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Huang Y., Wang Y., Wang H., Liu Z., Yu X., Yan J., Wu Y. Prevalence of mental disorders in China: A cross-sectional epidemiological study. Lancet Psychiatry. 2019;6:211–224. doi: 10.1016/S2215-0366(18)30511-X. - DOI - PubMed
    1. Ren Y., Qian W., Li Z., Liu Z., Zhou Y., Wang R., Qi L., Yang J., Song X., Zeng L. Public mental health under the long-term influence of COVID-19 in China: Geographical and temporal distribution. J. Affect. Disord. 2020;277:893–900. doi: 10.1016/j.jad.2020.08.045. - DOI - PMC - PubMed
    1. Liu T., Li S., Qiao X., Song X. Longitudinal change of mental health among active social media users in China during the COVID-19 outbreak. Healthcare. 2021;9:833. doi: 10.3390/healthcare9070833. - DOI - PMC - PubMed
    1. Zhao N., Wang Y., Li S., Liu X., Wu P., Zhu T. Impact of Wuhan city lockdowns on psychology and behavior among general population. Bull. Chin. Acad. Sci. 2020;035:264–272.
    1. Zhang W.R., Wang K., Yin L., Zhao W.F., Xue Q., Peng M., Min B.Q., Tian Q., Leng H.X., Du J.L., et al. Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychother. Psychosomr. 2020;89:242–250. doi: 10.1159/000507639. - DOI - PMC - PubMed

Publication types