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Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review
BACKGROUND: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of indiv...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482196/ https://www.ncbi.nlm.nih.gov/pubmed/34524089 http://dx.doi.org/10.2196/29875 |
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author | Shandhi, Md Mobashir Hasan Goldsack, Jennifer C Ryan, Kyle Bennion, Alexandra Kotla, Aditya V Feng, Alina Jiang, Yihang Wang, Will Ke Hurst, Tina Patena, John Carini, Simona Chung, Jeanne Dunn, Jessilyn |
author_facet | Shandhi, Md Mobashir Hasan Goldsack, Jennifer C Ryan, Kyle Bennion, Alexandra Kotla, Aditya V Feng, Alina Jiang, Yihang Wang, Will Ke Hurst, Tina Patena, John Carini, Simona Chung, Jeanne Dunn, Jessilyn |
author_sort | Shandhi, Md Mobashir Hasan |
collection | PubMed |
description | BACKGROUND: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. OBJECTIVE: We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. METHODS: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. RESULTS: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. CONCLUSIONS: Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust. |
format | Online Article Text |
id | pubmed-8482196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84821962021-11-24 Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review Shandhi, Md Mobashir Hasan Goldsack, Jennifer C Ryan, Kyle Bennion, Alexandra Kotla, Aditya V Feng, Alina Jiang, Yihang Wang, Will Ke Hurst, Tina Patena, John Carini, Simona Chung, Jeanne Dunn, Jessilyn J Med Internet Res Review BACKGROUND: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. OBJECTIVE: We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. METHODS: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. RESULTS: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. CONCLUSIONS: Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust. JMIR Publications 2021-09-15 /pmc/articles/PMC8482196/ /pubmed/34524089 http://dx.doi.org/10.2196/29875 Text en ©Md Mobashir Hasan Shandhi, Jennifer C Goldsack, Kyle Ryan, Alexandra Bennion, Aditya V Kotla, Alina Feng, Yihang Jiang, Will Ke Wang, Tina Hurst, John Patena, Simona Carini, Jeanne Chung, Jessilyn Dunn. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.09.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Review Shandhi, Md Mobashir Hasan Goldsack, Jennifer C Ryan, Kyle Bennion, Alexandra Kotla, Aditya V Feng, Alina Jiang, Yihang Wang, Will Ke Hurst, Tina Patena, John Carini, Simona Chung, Jeanne Dunn, Jessilyn Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title | Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title_full | Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title_fullStr | Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title_full_unstemmed | Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title_short | Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review |
title_sort | recent academic research on clinically relevant digital measures: systematic review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482196/ https://www.ncbi.nlm.nih.gov/pubmed/34524089 http://dx.doi.org/10.2196/29875 |
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