Clinical trials

The general goal is to design, develop and evaluate a personalized, self-guided and trans-diagnostic internet-based intervention to prevent anxiety and depression, based on predictive risk algorithms and decision support systems (DSS), in Spanish and Chilean adult population. Methods: We will conduct a three-arm parallel randomized controlled trial with one year of follow-up. A total of 2,595 depression- or/and anxiety-free participants (865 per group), aged 18-65, will be recruited and randomly assigned to one of two intervention groups or to the usual-care group (in a 1:1:1 ratio). Both interventions, Pandora-1 and Pandora-2, will be implemented via a smartphone application, the Pandora App. Pandora-1 is a self-guided and transdiagnostic intervention that includes 4 interactive intervention modules (move more, sleep better, improve relationships and emotional well-being), as well as predictive risk algorithms, decision support systems, and monitoring and feedback to implement personalized plans for the prevention of anxiety and depression. Pandora-2 is a psycho-educative intervention with predictive risk algorithms, minimally interactive and without personalization. The primary outcome is the combined rate of the onset of anxiety or depression (DSM-V diagnoses as measured by the CIDI interview) at 6 and 12 months. The secondary outcomes are the reduction of depressive (PHQ-9) and anxious (GAD-7) symptoms, risk of depression and anxiety (predictD and predictA risk algorithms), and the improvement of mental \& physical quality of life (SF-12), as well as acceptation and satisfaction with Pandora apps (u-MARS) and adverse effects (ad hoc questionnaire), which will be assessed at 1, 6 and 12 months. As mediators will be measured social support (Duke-UNC-2 items), physical activity (BPAQ-2), sleep (AIS-5), and repetitive negative thinking (PTQ-9) evaluated at 1, 6 and 12 months. We will use ActiGraph-GT3X accelerometers to assess physical activity and sleep at 1 and 6 months, in a subsample of 404 sedentary study participants.

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).