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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...

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Detalles Bibliográficos
Autores principales: Thomas, George, Bennie, Jason A, De Cocker, Katrien, Dwi Andriyani, Fitria, Booker, Bridget, Biddle, Stuart J H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
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
Descripción
Sumario: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.