Feasibility of automated cameras to measure screen use in adolescents.
Abstract
Introduction The influence of screens and technology on adolescent well-being is controversial and there is a need to improve methods to measure these behaviors. This study examines the feasibility and acceptability of using automated wearable cameras to measure evening screen use in adolescents.Methods A convenience sample of adolescents (aged 13-17 years, n=15) wore an automated camera for 3 evenings from 5:00pm to bedtime. The camera (Brinno TLC120) captured an image every 15 seconds. Fieldwork was completed between October and December 2017, and data analyzed in 2018. Feasibility was examined by quality of the captured images, wear time, and whether images could be coded in relation to contextual factors (e.g., type of screen and where screen use occurred). Acceptability was examined by participant compliance to the protocol and from an exit interview.Results Data from 39 evenings were analyzed (41,734 images), with a median of 268 minutes per evening. The camera was worn for 78% of the evening on Day 1, declining to 51% on Day 3. Nearly half of the images contained a screen in active use (46%), most commonly phones (13.7%), TV (12.6%), and laptops (8.2%). Multiple screen use was evident in 5% of images. Within the exit interview, participants raised no major concerns about wearing the camera, and data loss because of deletions or privacy concerns was minimal (mean, 14 minutes, 6%).Conclusions Automated cameras offer a feasible, acceptable method of measuring prebedtime screen behavior, including environmental context and aspects of media multitasking in adolescents.
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Only 2 previous studies appear to have used within-person analyses and objective measures (smartphone trackers) to examine how screens are associated with youth sleep.
“Only 2 previous studies appear to have used within-person analyses and objective measures (smartphone trackers) to examine how screens are associated with youth sleep.19,21”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [21]
The limited existing research in this area has reported few associations between device use before bed and subsequent sleep, although screen use was measured objectively in just 1 study (smartphones only).
“The limited existing research in this area has reported few associations between device use before bed and subsequent sleep,19,20,21 although screen use was measured objectively in just 1 study (smartphones only).19”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [21]
These 2 previous studies reported no significant reduction in total sleep time associated with before-bedtime smartphone use in youths but did not examine devices other than Android smartphones or the shut-eye latency period.
“They also reported no significant reduction in total sleep time associated with before-bedtime smartphone use in youths but did not examine devices other than Android smartphones or the shut-eye latency period.”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [21]
In Smith et al, 5% of images contained multiple screens.
“while 5% contained multiple screens”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
Smith et al demonstrated wearable cameras to be a feasible and acceptable method of measuring evening screen exposure among New Zealand adolescents.
“Smith et al recently demonstrated wearable cameras to be a feasible and acceptable method of measuring evening screen exposure among New Zealand adolescents [39]”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
Smith et al data were derived largely from nonschool days, owing to examination during study breaks or holidays, and thus the findings may not reflect adolescents' typical screen use.
“However, data were derived largely from nonschool days, owing to examination during study breaks or holidays, and thus, the findings may not reflect adolescents’ typical screen use.”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
Smith et al collected 41,734 images across 39 evenings.
“This study collected 41,734 images across 39 evenings”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
In Smith et al, almost half of the images contained screens, most commonly those of smartphones.
“showing that almost half of the images contained screens, most commonly those of smartphones”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
The rate of multiple screens identified in this study was more than 3 times the rate reported by Smith et al among adolescents in New Zealand.
“This rate was more than 3 times the rate reported by Smith et al among adolescents in New Zealand [39].”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
A high agreement between coders was reported, similar to a previous study using wearable cameras.
“A high agreement between coders was reported, similar to a previous study using wearable cameras [39].”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [39]
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- Authors
- Smith, C., Galland, B. C., de Bruin, W. E., & Taylor, R. W.
- Affiliations
- University of Otago (NZ)
- Corresponding author
- Smith, Claire
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 57
- Issue
- 3
- Pages
- 417-424
- ISSN
- 0749-3797 (ISSN-L)
- OpenAlex
- W2964818196
- Cited by
- 34
- References
- 38
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 11 · 2023: 4 · 2022: 2 · 2021: 1 · 2020: 4 · 2019: 4
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Preventive Medicine (publishedVersion)
- PubMed (publishedVersion)
- Otago University Research Archive (University of Otago) (submittedVersion)
- Funders
- Division of Health Sciences, University of Otago
- Lottery Health Research
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Keywords
- adolescents, media multitasking, smartphone use, television viewing, laptop use, feasibility, acceptability, privacy concerns
- MeSH terms
- Behavior Observation Techniques, Wearable Electronic Devices, Screen Time, Adolescent, Adolescent Behavior, Feasibility Studies, Female, Humans, Male, New Zealand, Photography
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