A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study

<h4>Background</h4> This study aims to understand how participants’ compliance and response rates to both traditional validated surveys and ecological momentary assessments (EMAs) vary across 4 cohorts who participated in the same mHealth study and received the same surveys and EMAs on t...

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Autores principales:	Tarun Reddy Katapally, Nour Hammami, Luan Manh Chu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/78b2cd38e1984109b8d86542fb6932d4
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spelling	oai:doaj.org-article:78b2cd38e1984109b8d86542fb6932d42021-11-11T06:44:24ZA randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study1932-6203https://doaj.org/article/78b2cd38e1984109b8d86542fb6932d42021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8559921/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4> This study aims to understand how participants’ compliance and response rates to both traditional validated surveys and ecological momentary assessments (EMAs) vary across 4 cohorts who participated in the same mHealth study and received the same surveys and EMAs on their smartphones, however with cohort-specific time-triggers that differed across the 4 cohorts. <h4>Methods</h4> As part of the Smart Platform, adult citizen scientists residing in Regina and Saskatoon, Canada, were randomly assigned to 4 cohorts in 2018. Citizen Scientists provided a complex series of subjective and objective data during 8 consecutive days using a custom-built smartphone application. All citizen scientists responded to both validated surveys and EMAs that captured physical activity. However, using Smart Platform, we varied the burden of responding to validated surveys and EMAs across cohorts by using different time-triggered push notifications. Participants in Cohort 1 (n = 10) received the full baseline 209-item validated survey on day 1 of the study; whereas participants in cohorts 2 (n = 26), 3 (n = 10), and 4 (n = 25) received the same survey in varied multiple sections over a period of 4 days. We used weighted One-way Analysis of Variance (ANOVA) tests and weighted, linear regression models to assess for differences in compliance rate across the cohort groups controlling for age, gender, and household income. <h4>Results</h4> Compliance to EMAs that captured prospective physical activity varied across cohorts 1 to 4: 50.0% (95% Confidence Interval [C.I.] = 31.4, 68.6), 63.0% (95% C.I. = 50.7, 75.2), 37.5% (95% C.I. = 18.9, 56.1), and 61.2% (95% C.I. = 47.4, 75.0), respectively. The highest completion rate of physical activity validated surveys was observed in Cohort 4 (mean = 97.9%, 95% C.I. = 95.5, 100.0). This was also true after controlling for age, gender, and household income. The regression analyses showed that citizen scientists in Cohorts 2, 3, and 4 had significantly higher compliance with completing the physical activity validated surveys relative to citizen scientists in cohort group 1 who completed the full survey on the first day. <h4>Conclusions & significances</h4> The findings show that maximizing the compliance rates of research participants for digital epidemiological and mHealth studies requires a balance between rigour of data collection, minimization of survey burden, and adjustment of time- and user-triggered notifications based on citizen or patient input.Tarun Reddy KatapallyNour HammamiLuan Manh ChuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tarun Reddy Katapally Nour Hammami Luan Manh Chu A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
description	<h4>Background</h4> This study aims to understand how participants’ compliance and response rates to both traditional validated surveys and ecological momentary assessments (EMAs) vary across 4 cohorts who participated in the same mHealth study and received the same surveys and EMAs on their smartphones, however with cohort-specific time-triggers that differed across the 4 cohorts. <h4>Methods</h4> As part of the Smart Platform, adult citizen scientists residing in Regina and Saskatoon, Canada, were randomly assigned to 4 cohorts in 2018. Citizen Scientists provided a complex series of subjective and objective data during 8 consecutive days using a custom-built smartphone application. All citizen scientists responded to both validated surveys and EMAs that captured physical activity. However, using Smart Platform, we varied the burden of responding to validated surveys and EMAs across cohorts by using different time-triggered push notifications. Participants in Cohort 1 (n = 10) received the full baseline 209-item validated survey on day 1 of the study; whereas participants in cohorts 2 (n = 26), 3 (n = 10), and 4 (n = 25) received the same survey in varied multiple sections over a period of 4 days. We used weighted One-way Analysis of Variance (ANOVA) tests and weighted, linear regression models to assess for differences in compliance rate across the cohort groups controlling for age, gender, and household income. <h4>Results</h4> Compliance to EMAs that captured prospective physical activity varied across cohorts 1 to 4: 50.0% (95% Confidence Interval [C.I.] = 31.4, 68.6), 63.0% (95% C.I. = 50.7, 75.2), 37.5% (95% C.I. = 18.9, 56.1), and 61.2% (95% C.I. = 47.4, 75.0), respectively. The highest completion rate of physical activity validated surveys was observed in Cohort 4 (mean = 97.9%, 95% C.I. = 95.5, 100.0). This was also true after controlling for age, gender, and household income. The regression analyses showed that citizen scientists in Cohorts 2, 3, and 4 had significantly higher compliance with completing the physical activity validated surveys relative to citizen scientists in cohort group 1 who completed the full survey on the first day. <h4>Conclusions & significances</h4> The findings show that maximizing the compliance rates of research participants for digital epidemiological and mHealth studies requires a balance between rigour of data collection, minimization of survey burden, and adjustment of time- and user-triggered notifications based on citizen or patient input.
format	article
author	Tarun Reddy Katapally Nour Hammami Luan Manh Chu
author_facet	Tarun Reddy Katapally Nour Hammami Luan Manh Chu
author_sort	Tarun Reddy Katapally
title	A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
title_short	A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
title_full	A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
title_fullStr	A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
title_full_unstemmed	A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study
title_sort	randomized community trial to advance digital epidemiological and mhealth citizen scientist compliance: a smart platform study
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/78b2cd38e1984109b8d86542fb6932d4
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A randomized community trial to advance digital epidemiological and mHealth citizen scientist compliance: A smart platform study

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