The Latent Class Structure of Chinese Mental Health Literacy and its Association With Mental Health

Zhai Hongkun; Li Qiang; Wei Xiaowei

doi:10.16719/j.cnki.1671-6981.20250304

PDF(2219 KB)

Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (3) : 544-555. DOI: 10.16719/j.cnki.1671-6981.20250304

Clinical Psychology & Consulting

The Latent Class Structure of Chinese Mental Health Literacy and its Association With Mental Health

Zhai Hongkun¹, Li Qiang², Wei Xiaowei³

Author information +

History +

Abstract

Given the escalating prominence of public mental health issues, numerous researchers are focusing on enhancing mental health literacy among the public. While some studies affirm that improved mental health literacy can bolster an individual’s help-seeking behavior and mental health, others contradict this notion. They argue that mental health literacy, particularly the knowledge aspect, has minimal influence on resolving personal psychological issues and could potentially stigmatize patients, thereby adversely impacting their help-seeking behavior. This study posits that the primary cause of this discrepancy lies in the tendency of previous research to treat mental health literacy as a monolithic entity, thereby overlooking the possibility of intricate structural patterns within public mental health literacy. Indeed, established research points out that there is not always a positive correlation between the variables within mental health literacy, and that the relationship between knowledge, attitudes, and behaviors needs further investigation. Therefore, the present study used latent class analysis to identify the existence of different structural patterns of mental health literacy, so as to clarify the relationship among knowledge, attitude, and behavior in mental health literacy. On this basis, this study further examined the correlation between different structural patterns of mental health literacy and mental health.
This research was conducted through two studies. Study 1 involved 1050 Chinese citizens, aged between 18 and 59 years, who participated in a mental health literacy assessment using the Mental Health Literacy Questionnaire (MHLQ). A categorical model of mental health literacy was developed using latent class analysis, and its generalizability was evaluated using 10-fold cross-validation. The results show that the 4-category model is the best overall performer among all the tested models. On the one hand, the 4-category model fits the data well, with optimal performance on BIC and CAIC, and suboptimal performance on AIC and sample size-adjusted BIC, and the bootstrap likelihood ratio test results show that when the model reaches the 4-category level, the addition of new categories is no longer significant for the improvement of the model fit. On the other hand, the 10-fold cross-validation results show that the 4-category model exhibits superior performance in fitting the dataset compared to other models, implying that the 4-category model has excellent generalization ability. The latent classes identified by the 4-category model can be named based on the participants' response performance as “high knowledge, attitude and behavior type”, “low knowledge, attitude and behavior type”, “low knowledge, attitude and high behavior type”, and “high knowledge, attitude and low behavior type”.
Study 2 was conducted with the aim of exploring the relationship between the latent classes of mental health literacy and mental health, as well as the explanatory power and gain of these categories on mental health. A total of 728 Chinese citizens, aged between 18 and 55 years, were recruited as participants. This study used the MHLQ to measure the level of mental health literacy of the participants and the Chinese Psychological Health Inventory (CPHI) and the Brief Symptom Inventory-18 (BSI-18) to measure the level of mental health of the participants. ANCOVA was utilized to analyze the differences in mental health among individuals belonging to different latent classes of mental health literacy. Furthermore, regression and specification curve analysis were used to examine the explanatory power and gain of these latent classes on individuals’ mental health in various situations. The findings revealed significant differences in the mental health of individuals across different latent classes of mental health literacy. Additionally, the latent classes of mental health literacy demonstrated unique effects in explaining individuals’ mental health.
In summary, this study used latent category analysis to validate the category model for mental health literacy within the Chinese public. The research identifies four distinct categories of mental health literacy. Significant disparities were observed in the mental health of individuals across these different categories. Moreover, the latent classes of mental health literacy were found to exert a unique explanatory effect on individual mental health.

Key words

mental health literacy / heterogeneity / latent class analysis / mental health

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Zhai Hongkun, Li Qiang, Wei Xiaowei. The Latent Class Structure of Chinese Mental Health Literacy and its Association With Mental Health[J]. Journal of Psychological Science. 2025, 48(3): 544-555 https://doi.org/10.16719/j.cnki.1671-6981.20250304

References

[1] 陈祉妍, 王雅芯, 郭菲, 章婕, 江兰. (2019). 国民心理健康素养调查. 见傅小兰, 张侃, 陈雪峰, 陈祉妍(编), 中国国民心理健康发展报告(2017~2018). (pp. 220-263). 社会科学文献出版社.
[2] 陈祉妍, 吴振云, 方格. (2008). 中国心理健康量表(成人版)使用手册[Unpublished manuscript]. 中国科学院心理研究所.
[3] 胡号应, 颜瑜章, 陈力鸣, 蒲文杰, 廖伟, 李洁. (2012). 广州市城乡居民的心理健康知识知晓率及对精神疾病的态度. 中国心理卫生杂志, 26(1), 30-35.
[4] 贾丽媛, 黄雪雪, 薛艳妮, 胡婕, 张至贤, 李丹琳, .., 张诗晨. (2022). 中学生心理健康素养及童年期虐待与饮酒行为的关联. 中国学校卫生, 43(5), 648-652.
[5] 江光荣, 李丹阳, 任志洪, 闫玉朋, 伍新春, 朱旭, .., 张琳. (2021). 中国国民心理健康素养的现状与特点. 心理学报, 53(2), 182-201.
[6] 江光荣, 赵春晓, 韦辉, 于丽霞, 李丹阳, 林秀彬, 任志洪. (2020). 心理健康素养: 内涵、测量与新概念框架. 心理科学, 43(1), 232-238.
[7] 李强, 魏晓薇, 翟宏堃. (2020). 健康中国视角下优化国民心理健康素养研究: 意义与取径. 西南交通大学学报(社会科学版), 21(4), 61-68.
[8] 明志君, 陈祉妍. (2020). 心理健康素养: 概念、评估、干预与作用. 心理科学进展, 28(1), 1-12.
[9] 魏晓薇. (2022). 心理疾病知识暴露对心理疾病污名的影响: 权力的作用机制[博士学位论文]. 南开大学, 天津.
[10] 温忠麟, 谢晋艳, 王惠惠. (2023). 潜在类别模型的原理、步骤及程序. 华东师范大学学报(教育科学版), 41(1), 1-15.
[11] 尹奎, 彭坚, 张君. (2020). 潜在剖面分析在组织行为领域中的应用. 心理科学进展, 28(7), 1056-1070.
[12] 钟晓钰, 李铭尧, 李凌艳. (2021). 问卷调查中被试不认真作答的控制与识别. 心理科学进展, 29(2), 225-237.
[13] Aghukwa, C. N. (2010). Medical students' beliefs and attitudes toward mental illness: effects of a psychiatric education. Academic Psychiatry, 34(1), 67-69.
[14] Aguinis, H., & Gottfredson, R. K. (2010). Best-practice recommendations for estimating interaction effects using moderated multiple regression. Journal of Organizational Behavior, 31(6), 776-786.
[15] Altweck L., Marshall T. C., Ferenczi, N. & Lefringhausen, K. (2015). Mental health literacy: A cross-cultural approach to knowledge and beliefs about depression, schizophrenia and generalized anxiety disorder. Front Psychol, 6, 1272.
[16] Amarasuriya, S. D., Jorm, A. F. & Reavley, N. J. (2015). Depression literacy of undergraduates in a non-western developing context: The case of Sri Lanka. BMC Res Notes, 8, 593.
[17] Anderson, R. J. & Pierce, D. (2012). Assumptions associated with mental health literacy training-Insights from initiatives in rural Australia. Adv Ment Health, 10, 258-67.
[18] Bouckenooghe D., de Clercq D., & Raja U. (2019).A person- centered, latent profile analysis of psychological capital. Australian Journal of Management, 44(1), 91-108.
[19] Derogatis, L. R. (2001). Brief Symptom Inventory-18 (BSI-18): administration, scoring and procedures manual. NCS Pearson.
[20] Geng Y., Ni X., Wang Y., Fan J., Qian, Y. & Li, X. (2022). Factor Structure and Measurement Invariance of the Brief Symptom Inventory-18 Among Chinese Adults. Frontiers in Psychology, 13, Article e882815.
[21] Gong, A. T., & Furnham, A. (2014). Mental health literacy: Public knowledge and beliefs about mental disorders in mainland China. PsyCh Journal, 3(2), 144-158.
[22] Grimm K. J., Mazza G. L., & Davoudzadeh P. (2017). Model selection in finite mixture models: A k-fold cross-validation approach. Structural Equation Modeling: A Multidisciplinary Journal, 24(2), 246-256.
[23] Hengartner M. P., Loch A. A., Lawson F. L., Guarniero F. B., Wang Y.-P., Rössler W., & Gattaz W. F. (2013). Public stigmatization of different mental disorders: a comprehensive attitude survey. Epidemiology and Psychiatric Sciences, 22(3), 269-274.
[24] Jorm, A. F. (2012). Mental health literacy: Empowering the community to take action for better mental health. American Psychologist, 67(3), 231-243.
[25] Jorm A. F., Korten A. E., Jacomb P. A., Christensen H., Rodgers B., & Pollitt P. (1997). Mental health literacy: A survey of the public's ability to recognise mental disorders and their beliefs about the effectiveness of treatment. The Medical journal of Australia, 166(4), 182-186.
[26] Kayrouz R., Dear B. F., Johnston L., Keyrouz L., Nehme E., Laube R., & Titov N. (2015). Intergenerational and cross-cultural differences in emotional wellbeing, mental health service utilisation, treatment-seeking preferences and acceptability of psychological treatments for Arab Australians. The International Journal of Social Psychiatry, 61(5), 484-491.
[27] Kutcher S., Wei Y. F., & Coniglio C. (2016). Mental health literacy: Past, present, and future. The Canadian Journal of Psychiatry, 61(3), 154-158.
[28] Lam, L. T. (2014). Mental health literacy and mental health status in adolescents: A population-based survey. Child and Adolescent Psychiatry and Mental Health, 8, 26.
[29] Li F., Li S., Zhou C., & Wang F. (2019). Mental Health Literacy Among Chinese Rural Residents A Survey From Hubei Province in Central China on People's Perception of Mental Illnesses. Journal of Nervous and Mental Disease, 207(10), 875-883.
[30] Mäkikangas A., Tolvanen A., Aunola K., Feldt T., Mauno S., & Kinnunen U. (2018). Multilevel latent profile analysis with covariates: Identifying job characteristics profiles in hierarchical data as an example. Organizational Research Methods, 21(4), 931-954.
[31] Mason R. J., Hart L. M., Rossetto, A. & Jorm, A. F. (2015). Quality and predictors of adolescents' first aid intentions and actions towards a peer with a mental health problem. Psychiatry Res, 228, 31-8
[32] Massons C., Lopez-Morinigo J.-D., Pousa E., Ruiz A., Ochoa S., Usall J., .. & Dutta R. (2017). Insight and suicidality in psychosis: A cross-sectional study. Psychiatry Research, 252, 147-153.
[33] O'Connor, M., & Casey, L. (2015). The mental health literacy scale (MHLS): A new scale-based measure of mental health literacy. Psychiatry Research, 229(1-2), 511-516.
[34] Robey, A. (2020). A latent profile analysis of student restudy decisions. Metacognition and Learning, 15(1), 77-88.
[35] Shi Y., Shao Y., Li H., Wang S., Ying J., Zhang M., .. & Sun J. (2019). Correlates of affiliate stigma among family caregivers of people with mental illness: A systematic review and meta-analysis. Journal of Psychiatric & Mental Health Nursing, 26(1-2), 49-61.
[36] Simonsohn, U., Simmons, J. P. & Nelson, L. D. (2019, October 29). Specification Curve: Descriptive and Inferential Statistics on All Reasonable Specifications. Retrieved Nov 11, 2023, from https://ssrn.com/abstract=2694998
[37] Simpson K. R. S., Meadows G. N., Frances A. J., & Patten S. B. (2012). Is mental health in the Canadian population changing over time? Canadian Journal of Psychiatry [Revue Canadienne de Psychiatrie], 57(5), 324-331.
[38] Spiker, D. A., & Hammer, J. H. (2019). Mental health literacy as theory: Current challenges and future directions. Journal of Mental Health, 28(3), 238-242.
[39] Sun T., Tang Q. S., Liu D. P., Zhao L., Wang F. Z., & Xie H. (2021). Mental health literacy about depression among rural left-behind children in China: a comparative and cross-sectional study. Journal of Mental Health, 30(2), 263-270.
[40] Wei Y. F., McGrath P. J., Hayden J., & Kutcher S. (2015). Mental health literacy measures evaluating knowledge, attitudes and help-seeking: A scoping review. BMC Psychiatry, 15, 291.
[41] Weick, K. E. (1995). What theory is not, theorizing is. Admin Sci Quart, 40, 385-90.
[42] Wu J., Wang C. X., Lu Y., Zhu X., Li Y. Q., Liu G. D., & Jiang G. R. (2022). Development and initial validation of the mental health literacy questionnaire for Chinese adults. Current Psychology. Early Access.
[43] Wu Q., Luo X., Chen S., Qi C., Long J., Xiong Y., .. & Liu T. (2017). Mental health literacy survey of non-mental health professionals in six general hospitals in Hunan Province of China. PloS ONE, 12(7), e0180327.