This is the website that contains all information and resources on the ehealth4mdd database. The database was created to systematically organize the vast literature on ICT systems for the treatment and prevention of major depressive disorder. In the course of the past 20 years, a large number of eHealth applications for mental health and more specifically for the treatment and prevention of depression have been developed. Various literature surveys and meta-analyses of the clinical outcomes of evaluations of these systems have reached the conclusion that the systems are more effective than waitlist and as effective as face-to-face treatment. However, a continuous concern in the domain are high attrition rates, especially in systems that leave users entirely to their own devices (self-guided systems). Surveys have, to date, mostly concerned themselves with the "what?" of eHealth solutions, i.e. the therapeutic framework of the intervention or the type of guidance, rather than the "how?" of eHealth solutions, i.e. the manner in which certain intervention aspects have been implemented or the types of technology used (mobile, website, virtual reality, etc.). We have therefore set out to construct database to provide a record of the various systems for eHealth for depression prevention and treatment, their versions, their intervention components, their technological realization, and their evaluation. The database hence strives to systematically link clinical outcomes not only to intervention content, but also to intervention form.
The database consists of a total of 14 tables that can be grouped into three larger clusters. The systems cluster details the e-mental health systems, their technological functionalities, and how these relate to therapeutic techniques (four tables). The systems are characterized on a macro-level (year of completion; whether its purpose is to prevent, treat, or monitor; whether it is guided, unguided, or an adjunct to face-to-face therapy; etc.) and on a micro-level, i.e. their functionalities. Functions are split into two separate types of functions: support and intervention functions. Support functions are functions that are aimed at increasing adherence to the intervention. These are again categorized into four subcategories: support functions for treatment planning (e.g. scheduling of sessions), treatment execution (e.g. reminders), monitoring (e.g. monitoring of symptoms), and social support (e.g. therapist support). Intervention functionalities are functionalities that support patient activities aimed at reducing depression symptoms. They are linked to specific therapeutic frameworks (e.g. the component “identifying and challenging automatic thoughts” is linked to Cognitive Therapy). Finally, each functional component of each system is rated with regard to its degree of technological advancement using a set of five scales developed specifically for this purpose. The scales can be found under the "Automation Degree Scales" tab on this website. The database currently contains a total of 265 systems with more than 2200 components. The second cluster of tables in the database is the evaluations cluster, detailing the empirical studies of the systems in the systems cluster, their design, the employed measurement instruments, and dropout rates per study arm (four tables). Finally, the publications cluster details articles describing systems and their evaluations and the authors of these articles (three tables). The remaining three tables link systems to evaluations, systems to publications, and publications to evaluations. A list of all fourteen tables and their content can found in the "Tables" tab on this website. Below is a graph of the database structure including all 14 tables, their attributes and how they connect. Tables are linked via their keys.