4.6 Article

Dismantling and personalising task-sharing psychosocial interventions for common mental disorders: a study protocol for an individual participant data component network meta-analysis

期刊

BMJ OPEN
卷 13, 期 11, 页码 -

出版社

BMJ PUBLISHING GROUP
DOI: 10.1136/bmjopen-2023-077037

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Systematic Review; Depression & mood disorders; STATISTICS & RESEARCH METHODS

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Common mental disorders, such as depression and anxiety, are leading causes of disability worldwide. In low-resource settings, psychosocial interventions delivered through task-sharing modalities have been proven effective in expanding access to mental healthcare. However, the specific components of these interventions that are most efficacious in reducing symptoms of common mental disorders, and for whom, have yet to be substantiated by evidence.
Introduction Common mental disorders, including depression, anxiety and related somatic health symptoms, are leading causes of disability worldwide. Especially in low-resource settings, psychosocial interventions delivered by non-specialist providers through task-sharing modalities proved to be valid options to expand access to mental healthcare. However, such interventions are usually eclectic multicomponent interventions consisting of different combinations of evidence-based therapeutic strategies. Which of these various components (or combinations thereof) are more efficacious (and for whom) to reduce common mental disorder symptomatology is yet to be substantiated by evidence.Methods and analysis Comprehensive search was performed in electronic databases MEDLINE, Embase, PsycINFO and the Cochrane Register of Controlled Trials-CENTRAL from database inception to 15 March 2023 to systematically identify all randomised controlled trials that compared any single component or multicomponent psychosocial intervention delivered through the task-sharing modality against any active or inactive control condition in the treatment of adults suffering from common mental disorders. From these trials, individual participant data (IPD) of all measured outcomes and covariates will be collected. We will dismantle psychosocial interventions creating a taxonomy of components and then apply the IPD component network meta-analysis (IPD-cNMA) methodology to assess the efficacy of individual components (or combinations thereof) according to participant-level prognostic factors and effect modifiers.Ethics and dissemination Ethics approval is not applicable for this study since no original data will be collected. Results from this study will be published in peer-reviewed journals and presented at relevant conferences.

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