Qin Yan, Niu Sifang, Niu Xingmeng, Guo Yangziye, Sun Yu, Hu Shuzhang, Mu Fuqin, Zhang Ying, Liu Min, Wang Jianli, Liu Yan
School of Public Health, Jining Medical University, Jining, 272013, China.
School of Public Health, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, 250117, China.
BMC Psychiatry. 2025 Apr 22;25(1):409. doi: 10.1186/s12888-025-06827-y.
There are fewer studies on prospective predictors of first-time suicidal thoughts and behaviors (STB) among first-year university students and fewer studies prospectively identifying and screening for those at high risk of suicide among college students. This study assessed the impact of prospective baseline variables on the risk of new STB onset among first-year university students over two years and developed a multivariate risk prediction model.
4,560 first-year university students (38.4% males, mean age:18.34) from China participated and completed this prospective cohort study over a three-year period from 2018 to 2020. LASSO regression, and logistic regression models under resilient networks, were used for risk predictor variable screening and final prediction model building. Independent validation sets were used for external validation of the models. Independent validation sets were used for external validation of the models. Area Under the Curve (AUC), accuracy, F1 scores, and Hosmer-Lemeshow test metrics were used to evaluate the model performance.
The incidence rates of suicidal thoughts, suicidal behaviors, and STB within two years were 4.89%,1.03%, and 4.96%, respectively. Predictors in the final model included females, always solo activity, bigotry under pressure, socially oriented perfectionism, drinking to relieve stress, autonomy attitude, poorer parental marriage satisfaction, maternal emotional warmth, perceived others social support, and number of lifetime severe traumatic events. The predictive model had an AUC of 0.738 (95% CI: 0.697-0.780) for predictive accuracy in the training dataset as well as 0.710 (95% CI: 0.657-0.763) for predictive accuracy in the validation dataset, which represents a high degree of model discrimination.
Based on this predictive model of suicidal thoughts and behaviors, this study may help to assess and screen college students at risk for STB and develop suicide prevention strategies for at-risk populations.
关于大学一年级学生首次出现自杀念头和行为（STB）的前瞻性预测因素的研究较少，前瞻性识别和筛查大学生中自杀高风险人群的研究也较少。本研究评估了前瞻性基线变量对大学一年级学生两年内新发STB风险的影响，并建立了多变量风险预测模型。
来自中国的4560名大学一年级学生（男性占38.4%，平均年龄：18.34岁）参与并完成了这项从2018年至2020年为期三年的前瞻性队列研究。使用套索回归以及弹性网络下的逻辑回归模型进行风险预测变量筛选和最终预测模型构建。独立验证集用于模型的外部验证。使用曲线下面积（AUC）、准确率、F1分数和霍斯默-莱梅肖检验指标来评估模型性能。
两年内自杀念头、自杀行为和STB的发生率分别为4.89%、1.03%和4.96%。最终模型中的预测因素包括女性、总是独自活动、压力下的偏执、社会导向的完美主义、借酒减压、自主态度、父母婚姻满意度较低、母亲的情感温暖、感知到的他人社会支持以及一生中严重创伤事件的数量。预测模型在训练数据集中的预测准确率AUC为0.738（95%CI：0.697 - 0.780），在验证数据集中的预测准确率AUC为0.710（95%CI：0.657 - 0.763），这代表了较高的模型区分度。
基于这个自杀念头和行为的预测模型，本研究可能有助于评估和筛查有STB风险的大学生，并为高危人群制定自杀预防策略。
