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Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study
OBJECTIVES: The purpose of this study was to develop a replicable methodology of mobile ecological momentary assessments (EMAs) to capture prospective physical activity (PA) within free-living social and physical contexts by leveraging citizen-owned smartphones running on both Android and iOS system...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322321/ https://www.ncbi.nlm.nih.gov/pubmed/32595163 http://dx.doi.org/10.1136/bmjopen-2020-036787 |
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author | Katapally, Tarun Reddy Chu, Luan Manh |
author_facet | Katapally, Tarun Reddy Chu, Luan Manh |
author_sort | Katapally, Tarun Reddy |
collection | PubMed |
description | OBJECTIVES: The purpose of this study was to develop a replicable methodology of mobile ecological momentary assessments (EMAs) to capture prospective physical activity (PA) within free-living social and physical contexts by leveraging citizen-owned smartphones running on both Android and iOS systems. DESIGN: Data were obtained from the cross-sectional pilots of the SMART Platform, a citizen science and mobile health initiative. SETTING: The cities of Regina and Saskatoon, Canada. PARTICIPANTS: 538 citizen scientists (≥18 years) provided PA data during eight consecutive days using a custom-built smartphone application, and after applying a rigid inclusion criteria, 89 were included in the final analysis. OUTCOME MEASURES: EMAs enabled reporting of light, moderate, and vigorous PA, as well as physical and social contexts of PA. Retrospective PA was reported using International Physical Activity Questionnaire (IPAQ). For both measures, PA intensities were categorised into mean minutes of light and moderate-to-vigorous PA per day. Wilcoxon signed ranks tests and Spearman correlation procedures were conducted to compare PA intensities reported via EMAs and IPAQ. RESULTS: Using EMAs, citizen scientists reported 140.91, 87.16 and 70.38 mean min/day of overall, light and moderate-to-vigorous PA, respectively, whereas using IPAQ they reported 194.39, 116.99 and 98.42 mean min/day of overall, light and moderate-to-vigorous PA, respectively. Overall (ρ=0.414, p<0.001), light (ρ=0.261, p=0.012) and moderate-to-vigorous PA (ρ=0.316, p=0.009) were fairly correlated between EMA and IPAQ. In comparison with EMAs, using IPAQ, citizen scientists reported significantly greater overall PA in active transportation (p=0.002) and recreation, sport and leisure-time domains (p=0.003). CONCLUSIONS: This digital epidemiological and citizen science methodology adapted mobile EMAs to capture not only prospective PA, but also important physical and social contexts within which individuals accumulate PA. Ubiquitous tools can be leveraged via citizen science to capture accurate active living patterns of large populations in free-living conditions through innovative EMAs. |
format | Online Article Text |
id | pubmed-7322321 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-73223212020-07-02 Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study Katapally, Tarun Reddy Chu, Luan Manh BMJ Open Epidemiology OBJECTIVES: The purpose of this study was to develop a replicable methodology of mobile ecological momentary assessments (EMAs) to capture prospective physical activity (PA) within free-living social and physical contexts by leveraging citizen-owned smartphones running on both Android and iOS systems. DESIGN: Data were obtained from the cross-sectional pilots of the SMART Platform, a citizen science and mobile health initiative. SETTING: The cities of Regina and Saskatoon, Canada. PARTICIPANTS: 538 citizen scientists (≥18 years) provided PA data during eight consecutive days using a custom-built smartphone application, and after applying a rigid inclusion criteria, 89 were included in the final analysis. OUTCOME MEASURES: EMAs enabled reporting of light, moderate, and vigorous PA, as well as physical and social contexts of PA. Retrospective PA was reported using International Physical Activity Questionnaire (IPAQ). For both measures, PA intensities were categorised into mean minutes of light and moderate-to-vigorous PA per day. Wilcoxon signed ranks tests and Spearman correlation procedures were conducted to compare PA intensities reported via EMAs and IPAQ. RESULTS: Using EMAs, citizen scientists reported 140.91, 87.16 and 70.38 mean min/day of overall, light and moderate-to-vigorous PA, respectively, whereas using IPAQ they reported 194.39, 116.99 and 98.42 mean min/day of overall, light and moderate-to-vigorous PA, respectively. Overall (ρ=0.414, p<0.001), light (ρ=0.261, p=0.012) and moderate-to-vigorous PA (ρ=0.316, p=0.009) were fairly correlated between EMA and IPAQ. In comparison with EMAs, using IPAQ, citizen scientists reported significantly greater overall PA in active transportation (p=0.002) and recreation, sport and leisure-time domains (p=0.003). CONCLUSIONS: This digital epidemiological and citizen science methodology adapted mobile EMAs to capture not only prospective PA, but also important physical and social contexts within which individuals accumulate PA. Ubiquitous tools can be leveraged via citizen science to capture accurate active living patterns of large populations in free-living conditions through innovative EMAs. BMJ Publishing Group 2020-06-28 /pmc/articles/PMC7322321/ /pubmed/32595163 http://dx.doi.org/10.1136/bmjopen-2020-036787 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://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/. |
spellingShingle | Epidemiology Katapally, Tarun Reddy Chu, Luan Manh Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title | Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title_full | Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title_fullStr | Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title_full_unstemmed | Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title_short | Digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a SMART Platform study |
title_sort | digital epidemiological and citizen science methodology to capture prospective physical activity in free-living conditions: a smart platform study |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322321/ https://www.ncbi.nlm.nih.gov/pubmed/32595163 http://dx.doi.org/10.1136/bmjopen-2020-036787 |
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