110. The link between math learning stress and student depression and coping strategies

Abstract Background Mathematical learning stress is a common source of psychological stress among undergraduate students, especially in highly competitive educational environments, where it can exacerbate depressive symptoms and negatively impact mental health. Previous research has shown a significant association between academic stress and depressive symptoms, but studies specific to mathematical learning stress are limited, and there is a lack of evidence-based assessments of coping strategies. This study aims to explore the direct link between mathematical learning stress and depressive symptoms in undergraduate students and to evaluate the effectiveness of cognitive behavioral intervention (CBI) as a coping strategy. By clarifying the neuropsychological mechanisms of stress and depression, this research aims to provide practical evidence for school-based mental health care, helping to identify high-risk individuals and implement early intervention. Methods This study employed a cross-sectional survey and randomized controlled trial design, recruiting 500 undergraduate students aged 18-20 years as participants. First, baseline assessments were conducted using the Mathematics Learning Stress Scale (MLSS) and the Beck Depression Inventory (BDI) to measure stress levels and depressive symptoms. Participants were then randomly assigned to an intervention group (n = 250) and a control group (n = 250). The intervention group received an 8-week cognitive-behavioral intervention, including stress identification, cognitive restructuring, and behavioral activation; the control group received routine health education. The intervention’s effectiveness was assessed through pre- and post-test comparisons. Data analysis employed Pearson correlation analysis, independent samples t-tests, and linear regression models. All statistical analyses were performed using SPSS software, with a significance level set at α = 0.05. Results Baseline data showed a significant positive correlation between math learning stress and depression scores (r = 0.52, p<.001). After the intervention, the depression score in the intervention group decreased from 18.3 ± 4.1 to 11.2 ± 3.5, while the control group showed no significant change in score, with a pre-test score of 17.9 ± 4.3 and a post-test score of 16.8 ± 4.0. Intergroup comparisons showed a statistically significant difference in depression scores after the intervention (t = 5.87, p=.003). Furthermore, regression analysis indicated that for every 1 unit increase in math learning stress, the depression score increased by 0.48 units (β = 0.48, p<.001), and the intervention effect was more pronounced in the high-stress group. Discussion The results showed that the learning pressure was an important predictor of depression, and the cognitive behavioral intervention could effectively relieve the depression symptoms. These findings highlight the practical significance of integrating stress management into school mental health practices, such as reducing the risk of depression through regular screening and targeted interventions. Future research directions should include long-term tracking of the sustainability of intervention effects, exploring mediating variables (such as self-esteem or social support) in the stress-depression pathway, and validating the universality of strategies across different cultural and educational contexts. Overall, this research supports the development of evidence-based programs to promote student mental health, contributing to the prevention of depression and related mental disorders.