PERMEPSY

Despite the importance of psychological interventions in people with psychosis, fewer patients receive them and there are no studies aiming to characterise patient phenotype in relation to patient response. This project poses the challenge of integrating new technologies (harmonization, Machine Learning –ML-, technological platforms) for guaranteeing a more personalized treatment regarding an effective psychological intervention, named Metacognitive Training (MCT). The aims are: a) to identify the characteristics of responding patients detected through multimodal retrospective databases based on a stratification strategy by using ML; b) to perform a prospective clinical trial as a proof of concept for validating the relevant variables detected in the previous ML analysis, including the user’s perspective. The final purpose is to develop an open platform for clinicians to predict the response to MCT, as a useful tool for personalized treatment. The proposal is organized in 3 modules: clinical research, enabling technology towards application in healthcare and ethical and legal issues, divided in 2 sub-studies. The first sub-study is based on the harmonization of previous data of 500 patients from clinical partners regarding sociodemographic –sex and ethnic- and lifestyle and environmental variables, biomarkers, clinical, cognitive and meta-cognitive profiling data and the use of ML techniques (Wp1 and Wp2). The second sub-study will validate the previous variables in a prospective clinical trial in which one group will received face-to-face MCT and the other online MCT, in a sample of 200 patients from 4 countries: Poland, Germany, France and Spain. Moreover, users’ perspective will be assessed in focus groups (Wp3). An open platform to help clinicians in decision-taking tasks will be developed considering the results (Wp4). Legal and ethical issues (Wp5), a communication plan (Wp6) and coordination of the project are also described.