Literature DB >> 29587888

Depression and hopelessness as risk factors for suicide ideation, attempts and death: meta-analysis of longitudinal studies.

Jessica D Ribeiro1, Xieyining Huang1, Kathryn R Fox2, Joseph C Franklin3.   

Abstract

BACKGROUND: Many studies have documented robust relationships between depression and hopelessness and subsequent suicidal thoughts and behaviours; however, much weaker and non-significant effects have also been reported. These inconsistencies raise questions about whether and to what degree these factors confer risk for suicidal thoughts and behaviours.AimsThis study aimed to evaluate the magnitude and clinical utility of depression and hopelessness as risk factors for suicide ideation, attempts and death.
METHOD: We conducted a meta-analysis of published studies from 1971 to 31 December 2014 that included at least one longitudinal analysis predicting suicide ideation, attempt or death using any depression or hopelessness variable.
RESULTS: Overall prediction was weaker than anticipated, with weighted mean odds ratios of 1.96 (1.81-2.13) for ideation, 1.63 (1.55-1.72) for attempt and 1.33 (1.18-1.49) for death. Adjusting for publication bias further reduced estimates. Effects generally persisted regardless of sample severity, sample age or follow-up length.
CONCLUSIONS: Several methodological constraints were prominent across studies; addressing these issues would likely be fruitful moving forward.Declaration of interestNone.

Entities:  

Keywords:  Suicide; depression; hopelessness; meta-analysis; risk factors

Mesh:

Year:  2018        PMID: 29587888     DOI: 10.1192/bjp.2018.27

Source DB:  PubMed          Journal:  Br J Psychiatry        ISSN: 0007-1250            Impact factor:   9.319


  96 in total

1.  Prospective prediction of first lifetime onset of suicidal ideation in a national study of substance users.

Authors:  Rachel F L Walsh; Ana E Sheehan; Richard T Liu
Journal:  J Psychiatr Res       Date:  2018-10-01       Impact factor: 4.791

2.  Suicide risk around the world: a meta-analysis of longitudinal studies.

Authors:  E M Guzmán; C B Cha; J D Ribeiro; J C Franklin
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2019-09-04       Impact factor: 4.328

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8.  Using Machine Learning to Predict Suicide Attempts in Military Personnel.

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9.  Acute stressors and clinical characteristics differentiate death by suicide, accident, or natural causes among illicit and prescription opiate users.

Authors:  Alison J Athey; Eleanor E Beale; James C Overholser; Craig A Stockmeier; Courtney L Bagge
Journal:  Drug Alcohol Depend       Date:  2020-01-11       Impact factor: 4.492

10.  A Pilot Study of an Intervention to Prevent Suicide After Psychiatric Hospitalization.

Authors:  Natalie B Riblet; Brian Shiner; Paula Schnurr; Martha L Bruce; Danuta Wasserman; Sarah Cornelius; Robert Scott; Bradley V Watts
Journal:  J Nerv Ment Dis       Date:  2019-12       Impact factor: 2.254

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