Common mental disorders, such as anxiety, substance use and depression, are highly prevalent and disabling conditions, affecting an estimated 20% of people globally each year. Prevalence rates are even higher when including the harmful use of substances such as tobacco and alcohol.
For a proper understanding of common mental disorders' etiology, maintenance and relapse, it is of utmost importance to have a complete overview of the evidence for all possible predictive and hypothesized factors that may contribute to their onset, relapse and maintenance.
Although thousands of such articles have been published on risk factors and mechanisms for common mental disorders, a clear and exhaustive overview of all possible risk- and preceding factors, and their potential interactions, still need to be included. We, therefore, investigated the current state of affairs on evidence in all published data on these topics.
The main aim of the current project is to use a systematic search with the help of machine learning to create a database that makes all potentially relevant studies on these topics available.