X Guo1, Q Liu2, H Wang3, K Huang4, X Lei5, F Zhang6, Y Wang7. 1. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: 545571339@qq.com. 2. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: liuqin81622@163.com. 3. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: wangh111111@yahoo.com.cn. 4. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: 466302712@qq.com. 5. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: leixun521@163.com. 6. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: 415204428@qq.com. 7. School of Public Health and Management, Chongqing Medical University, No.1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China. Electronic address: wy525023@yahoo.com.cn.
Abstract
BACKGROUND: Left-behind middle school students are a common phenomenon in the rural Three Gorges areas causing wide concerns as students in puberty undergoing rapid development of the mind and body. This study examines the mental health of the left-behind middle school students from a positive perspective instead of emphasizing negative factors, which may explore a new way to study their mental health. STUDY DESIGN: A cross-sectional survey. METHODS: A cross-sectional study was conducted among middle school students in the Yunyang County of the Rural Three Gorges areas. Information about demographic characteristics was collected using a self-designed questionnaire; mental health status, resilience status, and the influential factors of resilience were collected using Mental Health Test (MHT) and Resilience and Youth Development Module (RYDM) scales. RESULTS: The detection rate of mental health problems in left-behind students was 6.01%. The difference in detection rates between left-behind students and non-left-behind students was not significant. The detection rates of low resilience in left-behind students was 0.95%, of medium resilience was 54.15%, and of high resilience was 44.90%. Binary logistic regression analysis showed that influential factors associated with the resilience of left-behind students included grade, contradiction with the guardian, and students' worry about their parents working outside the county. CONCLUSIONS: Future studies should explore the links between each influential factor and its influencing mechanism. Meanwhile, the appropriate mental health education activities should be conducted in line with local conditions.
BACKGROUND: Left-behind middle school students are a common phenomenon in the rural Three Gorges areas causing wide concerns as students in puberty undergoing rapid development of the mind and body. This study examines the mental health of the left-behind middle school students from a positive perspective instead of emphasizing negative factors, which may explore a new way to study their mental health. STUDY DESIGN: A cross-sectional survey. METHODS: A cross-sectional study was conducted among middle school students in the Yunyang County of the Rural Three Gorges areas. Information about demographic characteristics was collected using a self-designed questionnaire; mental health status, resilience status, and the influential factors of resilience were collected using Mental Health Test (MHT) and Resilience and Youth Development Module (RYDM) scales. RESULTS: The detection rate of mental health problems in left-behind students was 6.01%. The difference in detection rates between left-behind students and non-left-behind students was not significant. The detection rates of low resilience in left-behind students was 0.95%, of medium resilience was 54.15%, and of high resilience was 44.90%. Binary logistic regression analysis showed that influential factors associated with the resilience of left-behind students included grade, contradiction with the guardian, and students' worry about their parents working outside the county. CONCLUSIONS: Future studies should explore the links between each influential factor and its influencing mechanism. Meanwhile, the appropriate mental health education activities should be conducted in line with local conditions.