To date, meta-analyses of e-mental health systems for major depressive disorder (MDD) have largely overlooked the technological side of interventions. This warranted the creation of an open access database, EHealth4MDD, for the systematic study of the technological implementation in relation to intervention content, study design, and study outcomes. E-health systems were identified by conducting an exhaustive search on PubMed, Scopus, and Web of Science in 2017. The 5379 retrieved records yielded 267 systems. One coder extracted information from the records on 45 variables, organized into 14 tables in EHealth4MDD. A sample of each high-inference variable was double coded by a second coder to assess reliability. Percent agreement was satisfactory given that coders received no training and the number of possible categories was large. Furthermore, scales were developed to rate the degree of technological sophistication of system functions for each of five function types. Four of these scales demonstrated concurrent validity, as evidenced by the substantial to strong correlations observed when comparing the scales with the results of an unlabeled ordering task. For researchers in both computer science and clinical psychology, the database presents a useful tool to systematically study e-mental health interventions for depression.
|Number of pages||6|
|Journal||annual review of cybertherapy and telemedicine|
|Publication status||Published - 2018|