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

Papola, Davide; Karyotaki, Eirini; Purgato, Marianna; Sijbrandij, Marit; Tedeschi, Federico; Cuijpers, Pim; Efthimiou, Orestis; Furukawa, Toshi A; Patel, Vikram; Barbui, Corrado (2023). Dismantling and personalising task-sharing psychosocial interventions for common mental disorders: a study protocol for an individual participant data component network meta-analysis. BMJ open, 13(11), e077037. BMJ Publishing Group 10.1136/bmjopen-2023-077037

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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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