Liu Yan, Zhang Ning, Bao Guangyi, Huang Yubei, Ji Bingyuan, Wu Yili, Liu Chuanxin, Li Gongying
School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China.
School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China.
J Affect Disord. 2019 Feb 1;244:196-208. doi: 10.1016/j.jad.2018.10.084. Epub 2018 Oct 6.
To explore predictors of depressive symptoms in college students.
We performed a systematic review and meta-analysis on the predictors of depressive symptoms. PubMed/Medline, Embase, Springerlink, EBSCOhost, Cochrane review, PsycINFO, China Knowledge Resource Integrated Database, Weipu database and Wanfang database were searched for cohort or longitudinal studies. Stata version 13.1 was used for statistical meta-analysis.
Among 30 cohort studies, 24 studies covering 25,154 college students with the NOS of 6 and over were selected for systematic review and 15 studies met the inclusion criteria for meta-analysis. The predictors of depressive symptoms in college students were gender, baseline depression, neuroticism or psychoticism, negative automatic thoughts or negative rumination, dysfunctional attitude, childhood abuse, sex abuse, and stressful life events. The combined risk ratios and its 95% confidence interval (CI) of each previous predictors were 1.11 (95% CI: 1.02, 1.21), 1.28 (95% CI: 1.10, 1.45), 1.25 (95% CI: 1.04, 1.45), 1.03 (95% CI: 1.01,1.05), 1.17 (95% CI: 1.05, 1.29), 1.05(95% CI: 1.02,1.08), 1.01 (95% CI: 1.00,1.02), and 1.16 (95% CI: 1.04, 1.27), respectively. Perceived social support and family function did not displayed significant predictive effects. Funnel plots showed that publication bias was possible.
Screening tools for depressive symptoms do not have the power or specificity of the gold standard measures for depression like the Structured Clinical Interview (SCID) or the Composite International Diagnostic Interview (CIDI) based on Diagnostic and Statistical Manual of Mental Disorders (DSM), which would influence the study validity and the combined estimates.
Specific biological, psychological and environmental factors contribute to depressive symptoms in college students. Consideration of these prognostic factors might be conducive to improve understanding and management of future interventions against depressive symptoms among college students. Due to the highly sophisticated course of depression, it is crucial to summarize theoretical frameworks for depressive symptom interventions among college students.
探讨大学生抑郁症状的预测因素。
我们对抑郁症状的预测因素进行了系统评价和荟萃分析。检索了PubMed/Medline、Embase、Springerlink、EBSCOhost、Cochrane综述、PsycINFO、中国知网、维普数据库和万方数据库,查找队列研究或纵向研究。使用Stata 13.1版进行统计荟萃分析。
在30项队列研究中,选择了24项涵盖25154名大学生、NOS为6及以上的研究进行系统评价,15项研究符合荟萃分析的纳入标准。大学生抑郁症状的预测因素有性别、基线抑郁、神经质或精神质、消极自动思维或消极反刍、功能失调性态度、童年期虐待、性虐待和应激性生活事件。各预测因素的合并风险比及其95%置信区间(CI)分别为1.11(95%CI:1.02, 1.21)、1.28(95%CI:1.10, 1.45)、1.25(95%CI:1.04, 1.45)、1.03(95%CI:1.01, 1.05)、1.17(95%CI:1.05, 1.29)、1.05(95%CI:1.02, 1.08)、1.01(95%CI:1.00, 1.02)和1.16(95%CI:1.04, 1.27)。感知到的社会支持和家庭功能未显示出显著的预测作用。漏斗图显示可能存在发表偏倚。
抑郁症状的筛查工具不像基于《精神障碍诊断与统计手册》(DSM)的结构化临床访谈(SCID)或复合国际诊断访谈(CIDI)那样具有抑郁症金标准测量的效力或特异性,这会影响研究的有效性和合并估计值。
特定的生物、心理和环境因素导致大学生出现抑郁症状。考虑这些预后因素可能有助于增进对大学生抑郁症状未来干预措施的理解和管理。由于抑郁症病程高度复杂,总结大学生抑郁症状干预的理论框架至关重要。