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Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study
Time on screens (screen time) on multiple digital devices (computers, mobile phones, tablets, television screens, etc.) due to varied motivations (work, leisure, entertainment, gaming, etc.) has become an integral part of population behaviour. However, a significant evidence gap exists in screen tim...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651165/ https://www.ncbi.nlm.nih.gov/pubmed/31252617 http://dx.doi.org/10.3390/ijerph16132275 |
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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 | Time on screens (screen time) on multiple digital devices (computers, mobile phones, tablets, television screens, etc.) due to varied motivations (work, leisure, entertainment, gaming, etc.) has become an integral part of population behaviour. However, a significant evidence gap exists in screen time accumulated over ubiquitous mobile devices such as smartphones. This study aimed to develop an accurate, reliable and replicable methodology to derive objective screen time (i.e., screen-state) from all types of citizen-owned smartphones. A convenience sample of 538 adults (≥18 years) from two largest urban centres in Saskatchewan, Canada (Regina and Saskatoon) was recruited in 2017 and 2018. Participants used a custom-built smartphone application to provide objective and subjective data. A novel methodology was developed to derive objective screen-state, and these data were compared with subjective measures. The findings showed that objective screen-state from smartphones can be derived and assessed across a range of cut-points that take into consideration varied measurement errors. When objective measures were compared with subjective reporting, the results indicated that participants consistently underreported screen time. This study not only provides a methodology to derive objective screen-state from ubiquitous mobile devices such as smartphones but also emphasises the need to capture context via subjective measures. |
format | Online Article Text |
id | pubmed-6651165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66511652019-08-07 Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study Katapally, Tarun Reddy Chu, Luan Manh Int J Environ Res Public Health Article Time on screens (screen time) on multiple digital devices (computers, mobile phones, tablets, television screens, etc.) due to varied motivations (work, leisure, entertainment, gaming, etc.) has become an integral part of population behaviour. However, a significant evidence gap exists in screen time accumulated over ubiquitous mobile devices such as smartphones. This study aimed to develop an accurate, reliable and replicable methodology to derive objective screen time (i.e., screen-state) from all types of citizen-owned smartphones. A convenience sample of 538 adults (≥18 years) from two largest urban centres in Saskatchewan, Canada (Regina and Saskatoon) was recruited in 2017 and 2018. Participants used a custom-built smartphone application to provide objective and subjective data. A novel methodology was developed to derive objective screen-state, and these data were compared with subjective measures. The findings showed that objective screen-state from smartphones can be derived and assessed across a range of cut-points that take into consideration varied measurement errors. When objective measures were compared with subjective reporting, the results indicated that participants consistently underreported screen time. This study not only provides a methodology to derive objective screen-state from ubiquitous mobile devices such as smartphones but also emphasises the need to capture context via subjective measures. MDPI 2019-06-27 2019-07 /pmc/articles/PMC6651165/ /pubmed/31252617 http://dx.doi.org/10.3390/ijerph16132275 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Katapally, Tarun Reddy Chu, Luan Manh Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title | Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title_full | Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title_fullStr | Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title_full_unstemmed | Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title_short | Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study |
title_sort | methodology to derive objective screen-state from smartphones: a smart platform study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651165/ https://www.ncbi.nlm.nih.gov/pubmed/31252617 http://dx.doi.org/10.3390/ijerph16132275 |
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