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Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease
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 ach...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284971/ https://www.ncbi.nlm.nih.gov/pubmed/35840653 http://dx.doi.org/10.1038/s41746-022-00643-4 |
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author | Roussos, George Herrero, Teresa Ruiz Hill, Derek L. Dowling, Ariel V. L. T. M. Müller, Martijn Evers, Luc J. W. Burton, Jackson Derungs, Adrian Fisher, Katherine Kilambi, Krishna Praneeth Mehrotra, Nitin Bhatnagar, Roopal Sardar, Sakshi Stephenson, Diane Adams, Jamie L. Ray Dorsey, E. Cosman, Josh |
author_facet | Roussos, George Herrero, Teresa Ruiz Hill, Derek L. Dowling, Ariel V. L. T. M. Müller, Martijn Evers, Luc J. W. Burton, Jackson Derungs, Adrian Fisher, Katherine Kilambi, Krishna Praneeth Mehrotra, Nitin Bhatnagar, Roopal Sardar, Sakshi Stephenson, Diane Adams, Jamie L. Ray Dorsey, E. Cosman, Josh |
author_sort | Roussos, George |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9284971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92849712022-07-15 Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease Roussos, George Herrero, Teresa Ruiz Hill, Derek L. Dowling, Ariel V. L. T. M. Müller, Martijn Evers, Luc J. W. Burton, Jackson Derungs, Adrian Fisher, Katherine Kilambi, Krishna Praneeth Mehrotra, Nitin Bhatnagar, Roopal Sardar, Sakshi Stephenson, Diane Adams, Jamie L. Ray Dorsey, E. Cosman, Josh NPJ Digit Med Article 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. Nature Publishing Group UK 2022-07-15 /pmc/articles/PMC9284971/ /pubmed/35840653 http://dx.doi.org/10.1038/s41746-022-00643-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Roussos, George Herrero, Teresa Ruiz Hill, Derek L. Dowling, Ariel V. L. T. M. Müller, Martijn Evers, Luc J. W. Burton, Jackson Derungs, Adrian Fisher, Katherine Kilambi, Krishna Praneeth Mehrotra, Nitin Bhatnagar, Roopal Sardar, Sakshi Stephenson, Diane Adams, Jamie L. Ray Dorsey, E. Cosman, Josh Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title | Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title_full | Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title_fullStr | Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title_full_unstemmed | Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title_short | Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease |
title_sort | identifying and characterising sources of variability in digital outcome measures in parkinson’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284971/ https://www.ncbi.nlm.nih.gov/pubmed/35840653 http://dx.doi.org/10.1038/s41746-022-00643-4 |
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