为进一步了解我国国民心理健康素养的结构特点及其与心理健康的关系, 研究采用潜在类别分析, 对我国公众心理健康素养各成分的组合模式进行探索。研究1采用潜在类别分析方法对1050名普通公众的心理健康素养结构进行整体揭示。研究2则利用728名普通公众构成的样本探讨了不同的心理健康素养结构与个体心理健康水平间的关系。研究发现, 公众中存在以“高知识态度行为”“低知识态度行为”“低知识态度高行为”和“高知识态度低行为”为特点的4种不同心理健康素养结构的子群体; 心理健康素养的潜在类别结构存在跨时间、跨样本稳定性; 不同心理健康素养结构子群体的心理健康水平不同, 心理健康素养潜类别变量对心理健康水平存在解释增益。
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.
关键词
心理健康素养 /
异质性 /
潜在类别分析 /
心理健康
Key words
mental health literacy /
heterogeneity /
latent class analysis /
mental health
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基金
*本研究得到国家社会科学基金重点项目（19ASH012）的资助
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