EvalDepApps: Co-creation of an evidence-based tool to assess health apps to manage Depression

Abstract Background mental health apps represent a revolution as they are a fast, versatile and manageable tool, available 24/7, empowering patients and professionals, while reducing stigmatization. However, currently there is not a standardized method to assess its effectiveness and safety. The aim of EvalDepApps project is to develop an evidence-based tool to evaluate apps focused on managing depression. Methods The project develops in different stages: a systematic mapping of the apps available in the marketplaces; a meta-analysis to evaluate their effectiveness in treating depression; identification of a set of criteria by end users and co-creation workshops with all stakeholders. Currently the app is being piloted with 15 professionals and 15 patients. Results 30 apps were identified and 29 RCT were included in the meta-analysis, showing that the most common elements included in digital health interventions for depression were psychoeducation, goal setting and gamification. Significant effect for mHealth interventions in reducing depressive symptoms compared with non-active control (95% CI − 0.87,−0.37; I2=87%) was identified. Hybrid interventions were the most effective. Delphi study reached consensus in 28 criteria, which together with outcomes of co-creation workshops were implemented in the EvalDepApps tool. During co-creation workshops elements of interest for end-users were identified (ranking of the apps and recommendation systems). All these elements were implemented in the EvalDepApps tool which is currently being piloted. Conclusions mHealth interventions can be effective in reducing depressive symptoms. It is important to standardize evaluation tools to identify which are the most effective ones. Human-centered approach improves its engagement and effectiveness. Thanks to inputs given by professionals and patients, together with existing evidence, EvalDepApps tool will be a tool to assess health apps based on a robust methodological approach. Key messages • mHealth interventions can be effective in reducing depressive symptoms. • Human-centered approach improves engagement and effectiveness of digital health interventions.