Internet-Based Cognitive Behavioral Therapy to Reduce Suicidal Ideation: A Systematic Review and Meta-analysis.


Journal

JAMA network open
ISSN: 2574-3805
Titre abrégé: JAMA Netw Open
Pays: United States
ID NLM: 101729235

Informations de publication

Date de publication:
01 04 2020
Historique:
entrez: 29 4 2020
pubmed: 29 4 2020
medline: 23 10 2020
Statut: epublish

Résumé

Suicidal ideation is a widespread phenomenon. However, many individuals at risk for suicide do not seek treatment, which might be addressed by providing low-threshold, internet-based self-help interventions. To investigate whether internet-based self-help interventions directly targeting suicidal ideation or behavior are associated with reductions in suicidal ideation. A systematic search of PsycINFO, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), and the Centre for Research Excellence of Suicide Prevention (CRESP) databases for trials from inception to April 6, 2019, was performed, supplemented by reference searches. Search strings consisted of various search terms related to the concepts of internet, suicide, and randomized clinical trials. Two independent researchers reviewed titles, abstracts, and full texts. Randomized clinical trials evaluating the effectiveness of internet-based self-help interventions to reduce suicidal ideation were included. Interventions were eligible if they were based on psychotherapeutic elements. Trials had to report a quantitative measure of a suicide-specific outcome. Mobile-based and gatekeeper interventions were excluded; no further restrictions were placed on participant characteristics or date of publication. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. Standardized mean differences were calculated using a random-effects model. Suicidal ideation was the a priori primary outcome. Six unique eligible trials (1567 unique participants; 1046 [66.8%] female; pooled mean [SD] age, 36.2 [12.5] years) were included in the systematic review and meta-analysis. All identified interventions were internet-based cognitive behavioral therapy (iCBT). Participants assigned to the iCBT condition experienced a significantly reduced suicidal ideation compared with controls following intervention in all 6 trials (standardized mean difference, -0.29; 95% CI, -0.40 to -0.19; P < .001). Heterogeneity was low (I2 = 0%). The effect appeared to be maintained at follow-up in 4 trials (standardized mean difference, -0.18; 95% CI, -0.34 to -0.02; P = .03; I2 = 36%). Studies did not report sufficient data on completed suicides and suicide attempts to assess potential associations. These results show that iCBT interventions are associated with significant reductions in suicidal ideation compared with control conditions. Considering their high scalability, iCBT interventions have the potential to reduce suicide mortality. Future research should assess the effect of these digital health interventions on suicidal behavior and identify moderators and mediators to advance understanding of the mechanisms of effectiveness of these interventions.

Identifiants

pubmed: 32343354
pii: 2765056
doi: 10.1001/jamanetworkopen.2020.3933
pmc: PMC7189224
doi:

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e203933

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Auteurs

Rebekka Büscher (R)

Department of Rehabilitation Psychology and Psychotherapy, University of Freiburg, Freiburg, Germany.

Michelle Torok (M)

Black Dog Institute, University of New South Wales, Sydney, Australia.

Yannik Terhorst (Y)

Department of Research Methods, Institute of Psychology and Education, University of Ulm, Ulm, Germany.
Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany.

Lasse Sander (L)

Department of Rehabilitation Psychology and Psychotherapy, University of Freiburg, Freiburg, Germany.

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Classifications MeSH