Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies

Conclusions Digital phenotyping data quality requires ongoing technical and protocol efforts to minimise missingness. Adding run-in periods, education with hands-on support and tools to easily monitor data coverage are all productive strategies studies can use today. Clinical implications While it is feasible to capture digital phenotyping data from diverse populations, clinicians should consider the degree of missingness in the data before using them for clinical decision-making.
Source: Evidence-Based Mental Health - Category: Psychiatry & Psychology Authors: Tags: Open access Digital mental health Source Type: research