Predictors of depressive symptoms in college students: A systematic review and meta-analysis of cohort studies
•The first meta-analysis for predictive factors of depressive symptoms among college students.•Gender (female) and baseline depression could positively predict depressive symptoms among college students.•Neuroticism or psychoticism, negative automatic thoughts or negative rumination, dysfunctional a...
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| Published in | Journal of affective disorders Vol. 244; pp. 196 - 208 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.02.2019
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| Online Access | Get full text |
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| Abstract | •The first meta-analysis for predictive factors of depressive symptoms among college students.•Gender (female) and baseline depression could positively predict depressive symptoms among college students.•Neuroticism or psychoticism, negative automatic thoughts or negative rumination, dysfunctional attitude, childhood abuse, sex abuse and stressful life events could positively predict depressive symptoms among college students.
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. |
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| AbstractList | •The first meta-analysis for predictive factors of depressive symptoms among college students.•Gender (female) and baseline depression could positively predict depressive symptoms among college students.•Neuroticism or psychoticism, negative automatic thoughts or negative rumination, dysfunctional attitude, childhood abuse, sex abuse and stressful life events could positively predict depressive symptoms among college students.
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. To explore predictors of depressive symptoms in college students.BACKGROUNDTo 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.METHODSWe 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.RESULTSAmong 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.LIMITATIONSScreening 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.CONCLUSIONSSpecific 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. 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. |
| Author | Liu, Yan Liu, Chuanxin Huang, Yubei Ji, Bingyuan Bao, Guangyi Li, Gongying Wu, Yili Zhang, Ning |
| Author_xml | – sequence: 1 givenname: Yan surname: Liu fullname: Liu, Yan email: hakunaly@163.com organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 2 givenname: Ning surname: Zhang fullname: Zhang, Ning organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 3 givenname: Guangyi surname: Bao fullname: Bao, Guangyi organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 4 givenname: Yubei surname: Huang fullname: Huang, Yubei organization: Cancer Molecular Epidemiology and Biostatistics Laboratory, Tianjin Medical University Cancer Institute & Hospital, Tianjin, PR China – sequence: 5 givenname: Bingyuan surname: Ji fullname: Ji, Bingyuan email: jby2006@126.com organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 6 givenname: Yili orcidid: 0000-0002-2369-6974 surname: Wu fullname: Wu, Yili organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 7 givenname: Chuanxin surname: Liu fullname: Liu, Chuanxin organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China – sequence: 8 givenname: Gongying surname: Li fullname: Li, Gongying email: ligongying2005@126.com organization: School of Mental Health, Shandong Key Laboratory of Behavioral Medicine, Jining Medical University, No. 133 Hehua Road, Jining, PR China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30352363$$D View this record in MEDLINE/PubMed |
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| Snippet | •The first meta-analysis for predictive factors of depressive symptoms among college students.•Gender (female) and baseline depression could positively predict... To explore predictors of depressive symptoms in college students. We performed a systematic review and meta-analysis on the predictors of depressive symptoms.... To explore predictors of depressive symptoms in college students.BACKGROUNDTo explore predictors of depressive symptoms in college students.We performed a... |
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| SubjectTerms | China Cohort Studies College student Depression - psychology Depressive symptom Family Female Humans Male Mass Screening Predictor Risk Factors Social Support Students - psychology Universities |
| Title | Predictors of depressive symptoms in college students: A systematic review and meta-analysis of cohort studies |
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S0165032718315362 https://dx.doi.org/10.1016/j.jad.2018.10.084 https://www.ncbi.nlm.nih.gov/pubmed/30352363 https://www.proquest.com/docview/2125298403 |
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