大学生心理行为问题的识别:基于潜在剖面分析

为探索潜在剖面分析(latent profile analysis, LPA)在心理行为问题识别上的应用, 对12718名大学生进行心理普查, 并对644名学生由心理咨询师、辅导员和兼职班主任对其心理状况进行评定, 采用评定结果和阳性症状检出率作为"黄金标准"分析了诊断的敏感度与特异度。结果发现:(1)潜在剖面分析发现本研究大学生样本的心理行为问题可划分为三个亚群体:风险组、困扰组和健康组, 分别占比9.86%、19.15%和70.99%;(2)风险组表现为突出的精神症状(Z≥2.6SD), 有61.21%的被试出现阳性症状, 远高于困扰组的38.28%和健康组的8.36%;此外, 困扰组以认知与情绪症状为主;(3)潜在剖面分析方法比传统划界分数方法在敏感度上能提高8.93%~35.26%, 更为科学有效。

Identifying Psychological or Behavioral Problems of College Students: Based on Latent Profile Analysis

To explore the applicability of latent profile analysis (LPA) in detecting psychological or behavioral problems, a total of 12718 college students were tested for psychological health. The psychological status of the 644 students was evaluated by psychologists, counselors and class supervisors. Using evaluation results and the 90 Symptom checklist (SCL90) positive detection rate as the "golden standard" for diagnostic accuracy, sensitivity and specificity were compared between LPA and the traditional demarcation method. The results showed that: (1) Student's psychological and behavioral problems can be divided into three sub-groups: high risk group (9.86%), mental confusion group (19.15%) and healthy group (70.99%). (2) High risk groups were characterized by prominent mental symptoms (Z≥2.6SD). The positive symptom of mental health risk in high risk group is 61.21%, which is far above that of mental confusion group (38.28%) and mental health group (8.36%). (3) LPA improved sensitivity by 8.93%-35.26% and showed better diagnostic accuracy comparing with the traditional demarcation method.