This systematic review examines studies linking passive data from smartphones and wearables to depression, identifying key methodological flaws and threats to reproducibility. It highlights biases such as representation, measurement, and evaluation bias, stemming from small, homogenous samples and inconsistent feature construction.
Although gender and race are not explicitly discussed, the lack of diversity in study populations suggests potential demographic bias. The review calls for improved reporting standards and broader sample inclusion to enhance generalizability and clinical relevance. These improvements are essential for ensuring that digital mental health tools are equitable and reliable across diverse populations.
Learn more about this review here: https://doi.org/10.1038/s41746-021-00548-8
Reference
De Angel, V., Lewis, S., White, K., Oetzmann, C., Leightley, D., Oprea, E., Lavelle, G., Matcham, F., Pace, A., Mohr, D. C., Dobson, R., & Hotopf, M. (2022). Digital health tools for the passive monitoring of depression: a systematic review of methods. NPJ digital medicine, 5(1), 3.