Building an early warning system for depression: rationale, objectives, and methods of the WARN-D study

Abstract

Depression is common, debilitating, often chronic, and affects young people disproportionately. Given that only 50% of patients improve under initial treatment, experts agree that prevention is the most effective way to change depression’s global disease burden. The biggest barrier to successful prevention is to identify those at risk for depression in the near future. To close this gap, this protocol paper introduces the WARN-D study, our effort to build a personalized early warning system for depression. To develop the system, we follow around 2000 students over 2 years. Stage 1 comprises an extensive baseline assessment in which we collect a broad set of predictors for depression. Stage 2 lasts 3 months and zooms into participants’ daily experiences that may predict depression; we use smartwatches to collect digital phenotype data such as sleep and activity, and we use a smartphone app to query participants about their experiences 4 times a day and once every Sunday. In Stage 3, we follow participants for 21 months, assessing transdiagnostic outcomes (including stress, functional impairment, anxiety, and depression) as well as additional predictors for future depression every 3 months. Collected data will be utilized to build a personalized prediction model for depression onset. Overall, WARN-D will function similar to a weather forecast, with the core difference that one can only run or seek shelter from a thunderstorm, while depression may be successfully prevented before it occurs.

Authors 3

1. Eiko I. Fried corresponding Aachen Department of Clinical Psychology

   Leiden University

   Affiliation as printed

   Department of Clinical Psychology , Leiden University

   Department of Clinical Psychology, Leiden University

2. Carlotta Rieble Aachen Department of Clinical Psychology

   Leiden University

   Affiliation as printed

   Department of Clinical Psychology , Leiden University

   Department of Clinical Psychology, Leiden University

3. Ricarda K. K. Proppert Aachen Department of Clinical Psychology

   Leiden University

   Affiliation as printed

   Department of Clinical Psychology , Leiden University

   Department of Clinical Psychology, Leiden University