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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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.
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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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