Chris Liebold
In the latest publication of the Department of CCS, Max Schindler and Prof. Dr. Emese Domahidi provide insights into the use of computational methods in mental health research and the associated challenges by means of a systematic review. Three overarching problem areas were identified: (1) conceptual fragmentation of the field, (2) ethical considerations, and (3) methodological diversity. A field focused on a few concepts and methods emerges, with a large gap in ethical reporting. Of particular note is the focus of the work on ethical reflection by researchers, e.g., surveyed on the existence of ethics reports. Only one-third of the sample included an ethics report, and specific ethical challenges (e.g., privacy, stigma) were mentioned even less frequently. From this, the researchers derive the following challenges, among others, which need to be addressed in a timely manner: (1) The consistent embedding of ethical principles in studies on CMH (computational mental health research) needs to be enabled and promoted as an individual task of researchers and as a structural task of universities, journals, and third-party funders. (2) Best practices (e.g., user participation) that address the specific research field and the application of computational methods need to be developed in an interdisciplinary context.
For more information, please feel free to read the publication:
Schindler, M., & Domahidi, E. (2022). The computational turn in online mental health research: A systematic review. New Media & Society. https://doi.org/10.1177/14614448221122212