7. The intervention effect of psychological health education based on digital decision support system on anxiety symptoms of college students

Abstract Background Currently, the detection rate of anxiety symptoms among college students remains high, and traditional mental health education faces bottlenecks such as insufficient personalization and weak intervention timeliness. Existing research has confirmed the improvement effect of digital interventions on anxiety, but there is a lack of intervention studies that combine decision support systems to achieve precise matching of needs. To break through the limitations of traditional models and explore the application value of digital decision support systems in mental health education, a randomized controlled trial was conducted to verify the intervention effect and construct a digital decision support system that integrates needs assessment and program matching. The research findings aim to clarify that the system can significantly alleviate anxiety symptoms in college students, quantify the effectiveness of intervention, and identify key influencing factors. Methods 120 students from a certain university with a Generalized Anxiety Disorder (GAD-7) score of ≥8 were selected and divided into an intervention group (60 people) and a control group (60 people). There was no significant difference in baseline GAD-7 scores between the two groups (p>.05). The intervention group used a digital decision support system to complete 12 psychological needs assessments through the system, generate personalized education plans, and use them 3 times a week for 40 minutes each time for 8 weeks; The control group received routine offline mental health lectures. GAD-7 and General Self Efficacy Scale (GSES) were used for evaluation before intervention (T0), at 4 weeks of intervention (T1), and at 8 weeks of intervention (T2). SPSS 26.0 was used for repeated measures analysis of variance. Results The GAD-7 score of the intervention group decreased from 11.2 ± 2.3 points to 5.3 ± 1.8 points at T2, while the GAD-7 score of the control group decreased from 10.9 ± 2.1 points to 8.7 ± 2.0 points; The intervention group had an effective intervention rate of 68.3%, significantly higher than the control group's 26.7% (χ2 = 18.65, p<.001). The intra group comparison results showed that the intervention group had significantly lower T1 and T2 scores than T0 (p<.001), while the control group had only T2 scores lower than T0 (p<.05). The GSES score of the intervention group increased from 24.5 ± 3.2 points to 32.8 ± 3.5 points, while there was no significant change in the control group (p>.05). Discussion The results show that the intervention of DSS can effectively relieve the anxiety symptoms of college students, and the effective rate is 2.6 times higher than that of the control group. The advantage of the system is that the intervention can be targeted by matching the precise needs. The advantage of the proposed system is that it can improve intervention targeting through precise demand matching. However, research has not yet explored the evaluation dimensions of combining psychological crisis warning with physiological indicators. In the future, the system's functions can be further expanded by incorporating crisis warning modules and constructing a multidimensional evaluation system based on objective physiological indicators such as heart rate variability and salivary cortisol, in order to improve the accuracy of psychological state assessment. Funding No. 25JDSZK083; No. KYTD202404; No. 25F30.