Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease - George Roussos; Teresa Ruiz Herrero; Derek L. Hill; Ariel V. Dowling; Martijn L. T. M. Müller; Luc J. W. Evers; Jackson Burton; Adrian Derungs; Katherine Fisher; Krishna Praneeth Kilambi; Nitin Mehrotra; Roopal Bhatnagar; et al. (npj Digital Medicine, 2022)
Abstract Smartphones and wearables are widely recognised as the foundation for novel Digital Health Technologies (DHTs) for the clinical assessment of Parkinson’s disease. Yet, only limited progress has been made towards their regulatory acceptability as effective drug development tools. A key barrier in achieving this goal relates to the influence of a wide range of sources of variability (SoVs) introduced by measurement processes incorporating DHTs, on their ability to detect relevant changes to PD. This paper introduces a conceptual framework to assist clinical research teams investigating a specific Concept of Interest within a particular Context of Use, to identify, characterise, and when possible, mitigate the influence of SoVs. We illustrate how this conceptual framework can be applied in practice through specific examples, including two data-driven case studies.