医学生焦虑抑郁网络的模拟干预分析OA

Objective:To examine the network structure of anxiety and depressive symptoms among medical students,and to identify potential symptom intervention targets through network analysis combined with in silico intervention.Meth-ods:A total of 4,882 students from three medical colleges in Hunan Province were surveyed.Symptoms were assessed us-ing the self-rating anxiety scale(SAS)and self-rating depression scale(SDS).With individual items as nodes,a symptom network was constructed based on the Ising model,and simulation intervention analysis was conducted using the nodeIdenti-fyR algorithm(NIRA).Results:SAS3 exhibited the highest expected influence,indicating its central role in the network.SAS19,SDS 4 and SDS1 showed prominent bridge centrality.NIRA results indicated that alleviating SDS16 produced the greatest reduction in overall network activation(P＜0.001),whereas aggravating SDS20 led to the most pronounced increase(P＜0.001).Conclusion:In this sample of medical students predominantly from a medical higher vocational college,anxiety and depressive symptoms were closely interconnected at the network level.Computational simulation suggests that indeci-siveness and dissatisfaction may serve as important intervention targets for this population.