ArticleNPJ digital medicine2022
Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease.
Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Powering Neurology Drug Development Trials to Reduce False Negative Results.Clinical and translational science · 2026Review
- Remote Assessment of Parkinson Disease Using Deep Learning on Structured Mouse-Trace Data From Suspected Cases: Machine-Learning Pilot Feasibility Study.JMIR formative research · 2026Article
- Locally adapting digital health technologies to address the global challenge of Parkinson's disease.Equity neuroscience · 2025Article
- Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem.Journal of medical Internet research · 2025Article
- Feasibility of an App-Assisted and Home-Based Video Version of the Timed Up and Go Test for Patients with Parkinson Disease: vTUG.Journal of clinical medicine · 2025Article
- Developing digital health technologies for frontotemporal degeneration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.Clinical and translational science · 2024Review
- Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art.NPJ digital medicine · 2024Review
- Online cognitive monitoring technology for people with Parkinson's disease and REM sleep behavioural disorder.NPJ digital medicine · 2024Article
- Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials.Frontiers in digital health · 2024Article
- Digital Biomarkers in Parkinson's Disease: Missing the Forest for the Trees?Movement disorders clinical practice · 2023Article
- Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management.Frontiers in digital health · 2023Article
- Metadata Framework to Support Deployment of Digital Health Technologies in Clinical Trials in Parkinson's Disease.Sensors (Basel, Switzerland) · 2022Article
- L-Dopa/Carbidopa intestinal gel infusion in advanced Parkinson's disease: real-life mobility insights from wearable sensors.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.