UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Life events and treatment prognosis for depression: A systematic review and individual patient data meta-analysis

Buckman, JEJ; Saunders, R; Arundell, L-L; Oshinowo, ID; Cohen, ZD; O'Driscoll, C; Barnett, P; ... Pilling, S; + view all (2022) Life events and treatment prognosis for depression: A systematic review and individual patient data meta-analysis. Journal of Affective Disorders , 299 pp. 298-308. 10.1016/j.jad.2021.12.030. Green open access

[thumbnail of 1-s2.0-S0165032721013458-main (1).pdf]
Preview
Text
1-s2.0-S0165032721013458-main (1).pdf - Published Version

Download (957kB) | Preview

Abstract

Objective: To investigate associations between major life events and prognosis independent of treatment type: (1) after adjusting for clinical prognostic factors and socio-demographics; (2) amongst patients with depressive episodes at least six-months long; and (3) patients with a first life-time depressive episode. // Methods: Six RCTs of adults seeking treatment for depression in primary care met eligibility criteria, individual patient data (IPD) were collated from all six (n = 2858). Participants were randomized to any treatment and completed the same baseline assessment of life events, demographics and clinical prognostic factors. Two-stage random effects meta-analyses were conducted. // Results: Reporting any major life events was associated with poorer prognosis regardless of treatment type. Controlling for baseline clinical factors, socio-demographics and social support resulted in minimal residual evidence of associations between life events and treatment prognosis. However, removing factors that might mediate the relationships between life events and outcomes reporting: arguments/disputes, problem debt, violent crime, losing one's job, and three or more life events were associated with considerably worse prognoses (percentage difference in 3–4 months depressive symptoms compared to no reported life events =30.3%(95%CI: 18.4–43.3)). // Conclusions: Assessing for clinical prognostic factors, social support, and socio-demographics is likely to be more informative for prognosis than assessing self-reported recent major life events. However, clinicians might find it useful to ask about such events, and if they are still affecting the patient, consider interventions to tackle problems related to those events (e.g. employment support, mediation, or debt advice). Further investigations of the efficacy of such interventions will be important.

Type: Article
Title: Life events and treatment prognosis for depression: A systematic review and individual patient data meta-analysis
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jad.2021.12.030
Publisher version: https://doi.org/10.1016/j.jad.2021.12.030
Language: English
Additional information: © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Depression; Treatment outcome; Stressful life events; Individual patient data meta-analysis; Systematic review
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Clinical, Edu and Hlth Psychology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10140691
Downloads since deposit
42Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item