17. Effects of educational instructional supervision on the development of an early identification and intervention system for students with depressive tendencies

Abstract Background In recent years, depressive tendencies among middle school and university students have risen steadily, while traditional psychological screening methods are limited by inadequate coverage, delayed identification, and insufficient teacher involvement. These shortcomings make it difficult to detect high-risk students at an early stage. Educational instructional supervision, which plays an essential role in classroom observation, learning behavior monitoring, and teacher guidance, offers natural advantages for supplementing early identification of students with depressive tendencies. However, how supervisory mechanisms can be integrated into psychological risk screening and contribute to building a “early identification–early warning–early intervention” system remains insufficiently validated. Therefore, this study evaluated the role of educational instructional supervision in developing an early identification and intervention framework for students with depressive tendencies, aiming to determine its effects on risk-identification accuracy, teacher sensitivity, and changes in students’ emotional risk levels. Methods A total of 312 students from four middle schools in a metropolitan area were selected using cluster sampling and assigned either to schools implementing an instructional supervision–based intervention or to schools maintaining regular administrative practices. The experimental schools conducted a 12-week supervision support program that included classroom behavior observation, continuous tracking of learning engagement, teacher training in psychological risk recognition, and establishment of an early-warning feedback mechanism. The control schools continued standard teaching management. Before and after the intervention, students were assessed on depressive tendencies (Center for Epidemiological Studies Depression Scale, CES-D), learning engagement (Student Engagement Scale, SES), teacher psychological risk-recognition sensitivity (Teacher Mental Health Recognition Accuracy, TMHRA), and perceived school support (School Support Scale, SSS). Early-risk identification accuracy (ERIA) was also calculated. Additionally, emotional risk dynamics were continuously monitored throughout the 12-week period. Two-way ANOVA and logistic regression models were used to assess the intervention effects. Results After 12 weeks, CES-D scores in the experimental schools decreased from 21.84 ± 6.13 to 16.27 ± 5.42, a 25.4% reduction that was significantly greater than the 8.1% reduction in the control schools (p<.001), indicating a marked alleviation of depressive tendencies. SES scores increased by 18.7% (p=.004), reflecting improved learning engagement. TMHRA rose from 62.3% to 81.5% (p<.001), and ERIA increased from 58.7% to 76.9% (p=.002), demonstrating enhanced teacher ability to identify students at emotional risk. SSS scores increased by 14.2% (p=.01), suggesting a more supportive school environment. Emotional risk monitoring showed a 27.6% reduction in the experimental schools, significantly higher than the 9.8% reduction in the control schools (p=.008), indicating a sustained positive effect of the supervision mechanism. Discussion The findings indicate that integrating educational instructional supervision into the school psychological health system can significantly improve early identification of students with depressive tendencies and positively influence teacher sensitivity and the overall school support environment. Classroom observation and learning behavior data provide timely signals for risk detection, enabling more effective coordination between instructional supervision and psychological interventions. These results suggest that school mental health protection should not rely solely on psychological teachers but should involve multiple stakeholders to enhance identification and intervention efficiency. Future research should examine the applicability of such supervisory mechanisms across different grade levels and school types and explore integration with digital monitoring tools to establish a more sustainable and scalable psychological support system.