Literature DB >> 31377085

Feasibility of Automated Cameras to Measure Screen Use in Adolescents.

Claire Smith1, Barbara C Galland2, Willemijn E de Bruin3, Rachael W Taylor3.   

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.
Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2019        PMID: 31377085     DOI: 10.1016/j.amepre.2019.04.012

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   5.043


  5 in total

1.  The effect of mild sleep deprivation on diet and eating behaviour in children: protocol for the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized cross-over trial.

Authors:  Aimee L Ward; Barbara C Galland; Jillian J Haszard; Kim Meredith-Jones; Silke Morrison; Deborah R McIntosh; Rosie Jackson; Dean W Beebe; Louise Fangupo; Rosalina Richards; Lisa Te Morenga; Claire Smith; Dawn E Elder; Rachael W Taylor
Journal:  BMC Public Health       Date:  2019-10-22       Impact factor: 3.295

2.  Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study.

Authors:  George Thomas; Jason A Bennie; Katrien De Cocker; Fitria Dwi Andriyani; Bridget Booker; Stuart J H Biddle
Journal:  JMIR Pediatr Parent       Date:  2022-03-21

3.  Type of screen time moderates effects on outcomes in 4013 children: evidence from the Longitudinal Study of Australian Children.

Authors:  Taren Sanders; Philip D Parker; Borja Del Pozo-Cruz; Michael Noetel; Chris Lonsdale
Journal:  Int J Behav Nutr Phys Act       Date:  2019-11-29       Impact factor: 6.457

4.  Home-Based Monitoring of Eating in Adolescents: A Pilot Study.

Authors:  Ghassan Idris; Claire Smith; Barbara Galland; Rachael Taylor; Christopher John Robertson; Mauro Farella
Journal:  Nutrients       Date:  2021-12-03       Impact factor: 5.717

5.  An Objective System for Quantitative Assessment of Television Viewing Among Children (Family Level Assessment of Screen Use in the Home-Television): System Development Study.

Authors:  Anil Kumar Vadathya; Salma Musaad; Alicia Beltran; Oriana Perez; Leo Meister; Tom Baranowski; Sheryl O Hughes; Jason A Mendoza; Ashutosh Sabharwal; Ashok Veeraraghavan; Teresia O'Connor
Journal:  JMIR Pediatr Parent       Date:  2022-03-24
  5 in total

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