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Objective: To design, develop, and evaluate a personalized intervention for the universal prevention of depression and anxiety in the general population based on risk algorithms, ICTs, and decision support systems (DSS).
Methods: A double-blind, parallel-group, randomized controlled trial with a twelve-month follow-up. The entire process of recruitment, random allocation, intervention, and follow-up will be conducted through the 'PredictPlusPrevent' platform and its associated apps. Following a media campaign, at least 9,000 Spanish participants aged 18 to 55 years without depression and/or anxiety at baseline will be randomly assigned to the intervention or active control group "PredictPlusPrevent". The "PredictPlusPrevent" intervention will be self-guided and implemented through participants' smartphones via an app; it will have a biopsychosocial and multi-component approach (8 modules: physical exercise, improving sleep, expanding relationships, problem-solving, improving communication, assertiveness, decision-making, and managing thoughts). The "PredictPlusPrevent" intervention is based on validated risk algorithms for depression and anxiety and a DSS that will help participants develop their own personalized depression prevention plans, which they will implement themselves while the platform monitors and provides feedback. The active control "PredictPlusPrevent" will include information from the risk algorithms and 24 self-help booklets. The primary outcome will be the incidence of new cases of depression and/or anxiety assessed using the PRIME-MD questionnaire, and secondary outcomes will include reductions in depression (PHQ-9) and anxiety symptoms (GAD-7), probability of depression and anxiety risk (predictD and predictA algorithms), and physical and mental quality of life (SF-12).
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9,000 participants in 2 patient groups
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Juan Á. Bellón, PhD
Data sourced from clinicaltrials.gov
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