Sedentary behavior in children by wearable cameras: development of an annotation protocol.
Open accessAbstract
INTRODUCTION: There is increasing evidence that not all types of sedentary behavior have the same harmful effects on children's health. Hence, there has been a growing interest in the use of wearable cameras. The aim of this study is to develop a protocol to categorize children's wearable camera data into sedentary behavior components. METHODS: Wearable camera data were collected in 3 different samples of children in 2014. A development sample (3 children aged 4-8 years) was used to design the annotation protocol. A training sample (4 children aged 10 years) was used to train 3 different coders. The independent reliability sample (14 children aged 9-11 years) was used for independent coding of wearable camera images and to estimate inter-rater agreement. Data were analyzed in 2018. Cohen's κ was calculated for every rater pair on a per-participant basis. Means and SDs were then calculated across per-participant κ scores. RESULTS: A total of 41,651 images from 14 participants were considered for analysis. Inter-rater agreement over all raters over all the sedentary behavior components was almost perfect (mean κ=0.85, 95% CI=0.83, 0.87). Inter-rater reliability for screen-based sedentary behavior (mean κ=0.72, 95% CI=0.62, 0.82) and nonscreen sedentary behavior (κ=0.69, 95% CI=0.65, 0.72) showed substantial agreement. Inter-rater reliability for location (κ=0.91, 95% CI=0.88, 0.93) showed almost perfect agreement. CONCLUSIONS: A reliable annotation protocol to categorize wearable camera data of children into sedentary behavior components was developed. Once applied to larger samples in children, this protocol can ultimately help to better understand the potential harms of screen time and sedentary behavior in children.
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Sleep variables were obtained using an automated script developed in MATLAB that uses a count-scaled algorithm validated for this age group.
“Sleep variables were obtained using an automated script developed in MATLAB (MathWorks) that uses a count-scaled algorithm to estimate sleep variables specific to each individual for each day32 and has been validated for this age group.33”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [33]
The Methods (p. 1) and Discussion (p. 4) describe developing and assessing the reliability of a wearable-camera annotation protocol for children's sedentary behavior. Searches for sleep variables, a MATLAB script, and a count-scaled algorithm found no passage addressing validation of a sleep algorithm for this age group. (LLM, conf=0.76)
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References 37 · Cited by 14
- Authors
- Hänggi, J. M., Spinnler, S., Christodoulides, E., Gramespacher, E., Taube, W., & Doherty, A.
- Affiliations
- University of Fribourg (CH)
- University of Basel (CH)
- University of Central Lancashire Cyprus (CY)
- FHNW University of Applied Sciences and Arts Northwestern Switzerland (CH)
- John Radcliffe Hospital (GB)
- Corresponding author
- Hänggi, Johanna M.
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 59
- Issue
- 6
- Pages
- 880-886
- ISSN
- 0749-3797 (ISSN-L)
- OpenAlex
- W3097591465
- Cited by
- 14
- References
- 37
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 1
- FWCI
- 0.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Preventive Medicine (publishedVersion, cc-by)
- PubMed (publishedVersion)
- edoc (University of Basel) (acceptedVersion)
- CLOK (University of Central Lancashire) (acceptedVersion)
- RERO DOC (Universität Bern) (submittedVersion)
- Funders
- Bundesamt für Sport
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Social Sciences › Education › Child Development and Digital Technology
- Keywords
- sedentary behavior, children, wearable cameras, annotation protocol, inter-rater reliability, screen-based sedentary behavior, activity location, screen time
- MeSH terms
- Wearable Electronic Devices, Screen Time, Child, Humans, Reproducibility of Results, Observer Variation, Sedentary Behavior
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