高职高专学生抑郁症状的潜在剖面分析

Latent profile analysis of depressive symptoms in higher vocational college students

目的 对高职高专学生的抑郁症状进行潜在剖面分析,并探讨不同人口学特征与抑郁症状潜在类别的关联。方法采用方便取样的方法,于2020年3—7月,使用流调用抑郁自评量表(CES-D)对贵州省毕节市4所高职高专学校的1 539名高职高专学生进行调查,采用描述性统计分析方法探讨抑郁症状的检出率,采用潜在剖面分析方法探讨抑郁症状的潜在类别,采用多元Logistic回归分析探讨不同人口学特征与抑郁症状潜在类别的关联。结果 高职高专学生无抑郁症状的占25.8%(397/1 539),可能有抑郁症状的占17.9%(276/1 539),有抑郁症状的占56.3%(866/1 539)。潜在剖面分析发现,高职高专学生的抑郁症状分为3个潜在类别,即无抑郁-不稳定型、低抑郁-不稳定型和中度抑郁-稳定型,分别占比26.5%(408/1 539)、56.3%(867/1 539)和17.2%(264/1 539)。多元Logistic回归分析显示:高职高专学生的年龄、学段、是否精准扶贫家庭、学业压力和身体健康状况是抑郁症状潜在类别分组的有效预测变量。结论 高职高专学生抑郁症状的检出率较高,应根据抑郁症状的不同潜在类别制定个性化干预措施,提升学生的心理防护能力。

Objective The objective of this study is to perform a latent profile analysis of depressive symptoms in higher vocational college students and to explore the association between different demographic characteristics and the latent categories of depressive symptoms.Methods From March to July 2020,1539 students from 4 vocational colleges in Bijie were investigated by the Center for Epidemiologic Studies Depression Scale(CES-D).Descriptive statistical analysis was used to explore the detection rate of depressive symptoms.Potential profile analysis was employed to explore the potential categories of depressive symptoms.Multiple logistic regression analysis was adopted to investigate the association between different demographic characteristics and potential categories of depressive symptoms.Results Twenfy-five point eight percent(397/1539)of college students showed no depressive symptoms;17.9%(276/1539),possible depressive symptoms,and 56.3%(866/1539),depressive symptoms.Potential profile analysis indicated that depressive symptoms in higher vocational college students were divided into three potential categories:no depression-instability,low depression-instability,and moderate depression-stability,accounting for 26.5%(408/1539),56.3%(867/1539),and 17.2%(264/1539),respectively.Multiple logistic regression analysis showed that age,grade,whether or not to come from a targeted poverty alleviation family,academic stress,and physical health status of vocational college students were effective predictive variables for potential category grouping of depressive symptoms.Conclusion The detection rate of depressive symptoms remains high in vocational college students.Personalized intervention measures should be made following different potential categories of depressive symptoms to improve students'psychological protection ability.