Reliability and validity analyses for the coding of information entered into the Ehealth4MDD database
datasetposted on 17.07.2018 by Franziska Burger, M.A. (Mark) Neerincx, Willem-Paul Brinkman
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This dataset contains all data and analysis scripts pertaining to the research conducted for the CyberPsychology23 conference paper: “EHealth4MDD: a database of e-health systems for the prevention and treatment of depressive disorders.” In the scope of the research conducted and described in this paper, we have developed a relational database to systematically describe e-mental health systems for the prevention and treatment of Major Depressive Disorder (MDD). For the purpose of creating this database, literature had to be retrieved from PubMed, Scopus, and Web of Knowledge and filtered for inclusion and exclusion based on title, abstract, and full-paper. Samples of records at each stage were double coded. Once the final body of literature was identified, information from the papers had to be extracted (coded) and entered into the database. Four of the database attributes were selected to be double coded again on samples. Furthermore, a set of scales was developed of which we assessed concurrent validity. We here deliver the version of the database used for the analyses as well as all files and documents required for potential replication.