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Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study
BACKGROUND: Automated wearable cameras present a new opportunity to accurately assess human behavior. However, this technology is seldom used in the study of adolescent’s screen exposure, and the field is reliant on poor-quality self-report data. OBJECTIVE: This study aimed to examine adolescents’ s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8981006/ https://www.ncbi.nlm.nih.gov/pubmed/35311672 http://dx.doi.org/10.2196/28208 |
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author | Thomas, George Bennie, Jason A De Cocker, Katrien Dwi Andriyani, Fitria Booker, Bridget Biddle, Stuart J H |
author_facet | Thomas, George Bennie, Jason A De Cocker, Katrien Dwi Andriyani, Fitria Booker, Bridget Biddle, Stuart J H |
author_sort | Thomas, George |
collection | PubMed |
description | BACKGROUND: Automated wearable cameras present a new opportunity to accurately assess human behavior. However, this technology is seldom used in the study of adolescent’s screen exposure, and the field is reliant on poor-quality self-report data. OBJECTIVE: This study aimed to examine adolescents’ screen exposure by categorizing the type and context of behaviors using automated wearable cameras. METHODS: Adolescents (mean age 15.4 years, SD 1.6 years; n=10) wore a camera for 3 school evenings and 1 weekend day. The camera captured an image every 10 seconds. Fieldwork was completed between February and March 2020, and data were analyzed in August 2020. Images were date and time stamped, and coded for screen type, content, and context. RESULTS: Data representing 71,396 images were analyzed. Overall, 74.0% (52,842/71,396) of images contained screens and 16.8% (11,976/71,396) of images contained multiple screens. Most screen exposures involved television sets (25,950/71,396, 36.3%), smartphones (20,851/71,396, 29.2%), and laptop computers (15,309/71,396, 21.4%). The context of screen use differed by device type, although most screen exposures occurred at home (62,455/64,856, 96.3%) and with solitary engagement (54,430/64,856, 83.9%). The immediate after-school period saw high laptop computer use (4785/15,950, 30.0%), while smartphone use (2059/5320, 38.7%) peaked during prebedtime hours. Weekend screen exposure was high, with smartphone use (1070/1927, 55.5%) peaking in the early morning period and fluctuating throughout the day. CONCLUSIONS: There was evidence for high screen use during the after-school and weekend period, mostly through solitary engagement, and within the home environment. The findings may inform the basis of larger studies aimed at examining screen exposure in free-living conditions. |
format | Online Article Text |
id | pubmed-8981006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-89810062022-04-06 Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study Thomas, George Bennie, Jason A De Cocker, Katrien Dwi Andriyani, Fitria Booker, Bridget Biddle, Stuart J H JMIR Pediatr Parent Original Paper BACKGROUND: Automated wearable cameras present a new opportunity to accurately assess human behavior. However, this technology is seldom used in the study of adolescent’s screen exposure, and the field is reliant on poor-quality self-report data. OBJECTIVE: This study aimed to examine adolescents’ screen exposure by categorizing the type and context of behaviors using automated wearable cameras. METHODS: Adolescents (mean age 15.4 years, SD 1.6 years; n=10) wore a camera for 3 school evenings and 1 weekend day. The camera captured an image every 10 seconds. Fieldwork was completed between February and March 2020, and data were analyzed in August 2020. Images were date and time stamped, and coded for screen type, content, and context. RESULTS: Data representing 71,396 images were analyzed. Overall, 74.0% (52,842/71,396) of images contained screens and 16.8% (11,976/71,396) of images contained multiple screens. Most screen exposures involved television sets (25,950/71,396, 36.3%), smartphones (20,851/71,396, 29.2%), and laptop computers (15,309/71,396, 21.4%). The context of screen use differed by device type, although most screen exposures occurred at home (62,455/64,856, 96.3%) and with solitary engagement (54,430/64,856, 83.9%). The immediate after-school period saw high laptop computer use (4785/15,950, 30.0%), while smartphone use (2059/5320, 38.7%) peaked during prebedtime hours. Weekend screen exposure was high, with smartphone use (1070/1927, 55.5%) peaking in the early morning period and fluctuating throughout the day. CONCLUSIONS: There was evidence for high screen use during the after-school and weekend period, mostly through solitary engagement, and within the home environment. The findings may inform the basis of larger studies aimed at examining screen exposure in free-living conditions. JMIR Publications 2022-03-21 /pmc/articles/PMC8981006/ /pubmed/35311672 http://dx.doi.org/10.2196/28208 Text en ©George Thomas, Jason A Bennie, Katrien De Cocker, Fitria Dwi Andriyani, Bridget Booker, Stuart J H Biddle. Originally published in JMIR Pediatrics and Parenting (https://pediatrics.jmir.org), 21.03.2022. 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 JMIR Pediatrics and Parenting, is properly cited. The complete bibliographic information, a link to the original publication on https://pediatrics.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Thomas, George Bennie, Jason A De Cocker, Katrien Dwi Andriyani, Fitria Booker, Bridget Biddle, Stuart J H Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title | Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title_full | Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title_fullStr | Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title_full_unstemmed | Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title_short | Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study |
title_sort | using wearable cameras to categorize the type and context of screen-based behaviors among adolescents: observational study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8981006/ https://www.ncbi.nlm.nih.gov/pubmed/35311672 http://dx.doi.org/10.2196/28208 |
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