Am J Prev Med. 2023 May 6:S0749-3797(23)00206-4. doi: 10.1016/j.amepre.2023.05.004. Online ahead of print.
ABSTRACT
INTRODUCTION: Screen time is predominantly measured using questionnaires assessing a limited range of activities. This project aimed to develop a coding protocol that reliably identified screen time, including device type and specific screen behaviours, from video camera footage.
METHODS: Screen use was captured from wearable and stationary PatrolEyes video cameras in 43 participants (10-14 years) within the home environment (May-December 2021, coding 2022, statistical analysis 2023). Following extensive piloting, the inter-rater reliability of the final protocol was determined in four coders using 600 minutes of footage from 18 participants who spent unstructured time on digital devices. Coders independently annotated all footage to determine 8 device types (e.g. phone, TV) and 9 screen activities (e.g. social media, video gaming) using Observer XT (behavioural coding software). Reliability was calculated using weighted Cohen’s Kappa (κ) for duration/sequence (meets criteria for total time in each category) and frequency/sequence (meets criteria for total time in each category and order of use) for every coder pair on a per-participant and footage type basis.
RESULTS: Overall reliability of the full protocol was excellent (≥ 0.8) for both duration/sequence (κ = 0.89-0.93) and the more conservative frequency/sequence (κ = 0.83-0.86) analyses. This protocol reliably differentiates between different device types (κ = 0.92-0.94) and screen behaviours (κ = 0.81-0.87). Coder agreement ranged from 91.7 to 98.8% across 28.6 to 107.3 different instances of screen use.
CONCLUSIONS: This protocol reliably codes screen activities in adolescents, offering promise for improving understanding of the impact of different screen activities on health.
PMID:37156402 | DOI:10.1016/j.amepre.2023.05.004
