PRimary carE digital Support ToOl in mental health (PRESTO): Design, development and study protocols

Background: About 30-50% of Primary Care (PC) users in Spain suffer mental health problems, mostly mild to moderate anxious and depressive symptoms, which account for 2% of Spain's total Gross domestic product and 50% of the costs associated to all mental disorders. Mobile health tools have demonstrated to cost-effectively reduce anxious and depressive symptoms while machine learning (ML) techniques have shown to accurately detect severe cases. The main aim of this project is to develop a comprehensive ML digital support platform (PRESTO) to cost-effectively screen, assess, triage, and provide personalized treatments for anxious and depressive symptoms in PC. Methods: The project will be carried out in 3 complementary phases: First, a ML predictive severity model will be built based on all the cases referred to the PC mental health support programme during the last 5 years in Catalonia. Simultaneously, a smartphone app to monitor and deliver psychological interventions for anxiety and depressive symptoms will be developed and tested in a clinical trial. Finally, the ML models and the app will be integrated in a comprehensive decision -support platform (PRESTO) which will triage and assign to each patient a specific intervention based on individual personal and clinical characteristics. The effectiveness of PRESTO to reduce waiting times in receiving mental healthcare will be tested in a stepped -wedge cluster randomized controlled trial in 5 PC centres. vDiscussion: PRESTO will offer timely and personalized cost-effective mental health treatment to people with mild to moderate anxious and depressive symptoms. This will result in a reduction of the burden of mental health problems in PC and on society as a whole.