Association Between Mental Health Literacy and Its Dimensions with Adolescent Depression and Anxiety: A Cross-Sectional Study Among 5759 Adolescents in China

Introduction: Adolescent depression and anxiety are major public health concerns. Previous studies showed that low mental health literacy is associated with depressive and anxiety symptoms. However, how its core dimensions—knowledge, attitudes, and skills—differentially relate to emotional symptoms remains unclear. Methods: A school-based survey was conducted among 6400 adolescents in Guangdong, China. Eligible participants completed the MHL questionnaire and assessments for depressive and anxiety symptoms. We assessed whether MHL was associated with depressive and anxiety symptoms in adolescents. Machine learning algorithms with SHAP analysis were applied to explore complex associations and validate key findings. Results: A total of 5759 adolescents were included. MHL and the knowledge dimension were negatively associated with depressive and anxiety symptoms. The attitudes dimension showed a negative association with both mental health outcomes (depression: OR = 0.83; anxiety: OR = 0.84) and machine learning confirmed attitudes as the key factor. Skills were unrelated to depressive symptoms. At the highest quartile, skills showed a positive association with anxiety symptoms (OR = 1.29). Conclusions: The attitudes dimension is negatively associated with adolescent depressive and anxiety symptoms and emerged as a key feature in ML identification models.