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Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis

OBJECTIVES: Although eHealth tools are potentially useful for remote disease monitoring, barriers include concerns of low engagement and high attrition. We aimed to summarise evidence on patients’ engagement and attrition with eHealth tools for remotely monitoring disease activity/impact in chronic...

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Autores principales: Doumen, Michaël, De Cock, Diederik, Van Lierde, Caroline, Betrains, Albrecht, Pazmino, Sofia, Bertrand, Delphine, Westhovens, René, Verschueren, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9621170/
https://www.ncbi.nlm.nih.gov/pubmed/36302561
http://dx.doi.org/10.1136/rmdopen-2022-002625
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author Doumen, Michaël
De Cock, Diederik
Van Lierde, Caroline
Betrains, Albrecht
Pazmino, Sofia
Bertrand, Delphine
Westhovens, René
Verschueren, Patrick
author_facet Doumen, Michaël
De Cock, Diederik
Van Lierde, Caroline
Betrains, Albrecht
Pazmino, Sofia
Bertrand, Delphine
Westhovens, René
Verschueren, Patrick
author_sort Doumen, Michaël
collection PubMed
description OBJECTIVES: Although eHealth tools are potentially useful for remote disease monitoring, barriers include concerns of low engagement and high attrition. We aimed to summarise evidence on patients’ engagement and attrition with eHealth tools for remotely monitoring disease activity/impact in chronic arthritis. METHODS: A systematic literature search was conducted for original articles and abstracts published before September 2022. Eligible studies reported quantitative measures of patients’ engagement with eHealth instruments used for remote monitoring in chronic arthritis. Engagement rates were pooled using random effects meta-analysis. RESULTS: Of 8246 references, 45 studies were included: 23 using smartphone applications, 13 evaluating wearable activity trackers, 7 using personal digital assistants, 6 including web-based platforms and 2 using short message service. Wearable-based studies mostly reported engagement as the proportion of days the tracker was worn (70% pooled across 6 studies). For other eHealth tools, engagement was mostly reported as completion rates for remote patient-reported outcomes (PROs). The pooled completion rate was 80%, although between-study heterogeneity was high (I(2) 93%) with significant differences between eHealth tools and frequency of PRO-collection. Engagement significantly decreased with longer study duration, but attrition varied across studies (0%–89%). Several predictors of higher engagement were reported. Data on the influence of PRO-reporting frequency were conflicting. CONCLUSION: Generally high patient engagement was reported with eHealth tools for remote monitoring in chronic arthritis. However, we found considerable between-study heterogeneity and a relative lack of real-world data. Future studies should use standardised measures of engagement, preferably assessed in a daily practice setting. TRIAL REGISTERATION NUMBER: The protocol was registered on PROSPERO (CRD42021267936).
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spelling pubmed-96211702022-11-01 Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis Doumen, Michaël De Cock, Diederik Van Lierde, Caroline Betrains, Albrecht Pazmino, Sofia Bertrand, Delphine Westhovens, René Verschueren, Patrick RMD Open Epidemiology OBJECTIVES: Although eHealth tools are potentially useful for remote disease monitoring, barriers include concerns of low engagement and high attrition. We aimed to summarise evidence on patients’ engagement and attrition with eHealth tools for remotely monitoring disease activity/impact in chronic arthritis. METHODS: A systematic literature search was conducted for original articles and abstracts published before September 2022. Eligible studies reported quantitative measures of patients’ engagement with eHealth instruments used for remote monitoring in chronic arthritis. Engagement rates were pooled using random effects meta-analysis. RESULTS: Of 8246 references, 45 studies were included: 23 using smartphone applications, 13 evaluating wearable activity trackers, 7 using personal digital assistants, 6 including web-based platforms and 2 using short message service. Wearable-based studies mostly reported engagement as the proportion of days the tracker was worn (70% pooled across 6 studies). For other eHealth tools, engagement was mostly reported as completion rates for remote patient-reported outcomes (PROs). The pooled completion rate was 80%, although between-study heterogeneity was high (I(2) 93%) with significant differences between eHealth tools and frequency of PRO-collection. Engagement significantly decreased with longer study duration, but attrition varied across studies (0%–89%). Several predictors of higher engagement were reported. Data on the influence of PRO-reporting frequency were conflicting. CONCLUSION: Generally high patient engagement was reported with eHealth tools for remote monitoring in chronic arthritis. However, we found considerable between-study heterogeneity and a relative lack of real-world data. Future studies should use standardised measures of engagement, preferably assessed in a daily practice setting. TRIAL REGISTERATION NUMBER: The protocol was registered on PROSPERO (CRD42021267936). BMJ Publishing Group 2022-10-27 /pmc/articles/PMC9621170/ /pubmed/36302561 http://dx.doi.org/10.1136/rmdopen-2022-002625 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Epidemiology
Doumen, Michaël
De Cock, Diederik
Van Lierde, Caroline
Betrains, Albrecht
Pazmino, Sofia
Bertrand, Delphine
Westhovens, René
Verschueren, Patrick
Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title_full Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title_fullStr Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title_full_unstemmed Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title_short Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
title_sort engagement and attrition with ehealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9621170/
https://www.ncbi.nlm.nih.gov/pubmed/36302561
http://dx.doi.org/10.1136/rmdopen-2022-002625
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