Risk management and healthcare policy · 2026
Mental Health Literacy and Associated Factors in Ethnic Minority Border Regions of Guangxi, China: A Cross-Sectional Study.
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Zhu Jun-Lin, Li Hong-Heng, Chen Yu, Ye Fan-Pei, Ma A-Jun, Li Zhi-Hua, Li Jin-Pei, Yang Yu-Xin, Sulieman Sara, Liu Si-Yuan, Tian Yao-Ming, Xie Meng-Kai, Cui Peng, Luo Hong-Ye
Аннотация
PURPOSE: This study aims to assess mental health literacy (MHL) in Guangxi, a border province in China with one of the largest ethnic minority populations, and to analyze its influencing factors.
METHODS: This cross-sectional study used a multistage stratified cluster sampling approach to conduct face-to-face interviews with 9,744 residents aged 18 years and older in Guangxi. Guided by the socio-ecological model (SEM), we evaluated individual, interpersonal, community, and structural variables. Binary logistic regression and optimal scaling regression were used to identify independent factors associated with MHL and their relative importance.
RESULTS: Of the 9,444 residents included, the overall MHL attainment rate was 12.7%; attainment in the mental health knowledge dimension was 16.6%. Recognition rates were 27.4% for depression and 46.2% for social anxiety disorder. MHL scores were significantly lower in rural ethnic minority areas than in urban areas (P < 0.05). Regression analyses showed that older age, being from the Dong ethnic group, lower education, a history of psychological treatment, and poor self-reported health were risk factors for low MHL. In contrast, male gender, employment in healthcare or technical professions, higher income, and daily internet use of less than three hours were protective factors.
CONCLUSION: MHL levels in Guangxi are suboptimal, particularly for recognizing depression and social anxiety disorder, with insufficient mental health knowledge emerging as a key barrier. Digital access and socio-economic advantages play a pivotal role in enhancing MHL. Strengthening mental health education in ethnic minority regions through culturally tailored, internet-based interventions and prioritizing high-risk groups, such as older adults, individuals with lower education or income, and those in rural Dong communities, may help reduce mental health inequalities.
METHODS: This cross-sectional study used a multistage stratified cluster sampling approach to conduct face-to-face interviews with 9,744 residents aged 18 years and older in Guangxi. Guided by the socio-ecological model (SEM), we evaluated individual, interpersonal, community, and structural variables. Binary logistic regression and optimal scaling regression were used to identify independent factors associated with MHL and their relative importance.
RESULTS: Of the 9,444 residents included, the overall MHL attainment rate was 12.7%; attainment in the mental health knowledge dimension was 16.6%. Recognition rates were 27.4% for depression and 46.2% for social anxiety disorder. MHL scores were significantly lower in rural ethnic minority areas than in urban areas (P < 0.05). Regression analyses showed that older age, being from the Dong ethnic group, lower education, a history of psychological treatment, and poor self-reported health were risk factors for low MHL. In contrast, male gender, employment in healthcare or technical professions, higher income, and daily internet use of less than three hours were protective factors.
CONCLUSION: MHL levels in Guangxi are suboptimal, particularly for recognizing depression and social anxiety disorder, with insufficient mental health knowledge emerging as a key barrier. Digital access and socio-economic advantages play a pivotal role in enhancing MHL. Strengthening mental health education in ethnic minority regions through culturally tailored, internet-based interventions and prioritizing high-risk groups, such as older adults, individuals with lower education or income, and those in rural Dong communities, may help reduce mental health inequalities.