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Updated: Jan 23, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Comparing measures of free-living sleep in school-aged children
Keith Brazendale1, Michael W Beets1, R Glenn Weaver1
1Arnold School of Public Heath, Department of Exercise Science, University of South Carolina, Columbia, SC, 29208, USA.
Insights
Consumer sleep trackers show good agreement for children's sleep and wake times. However, more research is needed to accurately measure total sleep time using these devices.
Area of Science:
- Pediatric Sleep Medicine
- Wearable Technology in Health
- Biomedical Engineering
Background:
- Emerging consumer-friendly sleep assessment products offer new tools for researchers.
- Capturing free-living sleep in children presents unique challenges and opportunities.
Purpose of the Study:
- To compare free-living sleep characteristics, including duration and timing, across different assessment measures in children.
- To evaluate the agreement between various wearable devices and parent logs for sleep assessment.
Main Methods:
- Elementary school-aged children (N=30) wore ActiGraph GT9X Link and Fitbit Charge HR devices.
- A Beddit 3 Sleep Monitor was used concurrently with parent-reported sleep logs.
- Data were collected over two consecutive weekend nights, with analysis including Bland-Altman plots.
Main Results:
- Total sleep time (TST) varied across measures, from 458 min/night (ActiGraph) to 613 min/night (Parent report).
- Bedtimes and wake times showed moderate correlations (r=0.30-0.71) across measures.
- The Beddit 3 Sleep Monitor and Fitbit Charge HR demonstrated the highest agreement for TST.
Conclusions:
- High agreement exists for sleep and wake times across various measures in children.
- Further research is required to accurately determine total sleep time using consumer sleep assessment tools.
Objective/Background:
Recent technological advances and emerging commercially-available consumer-friendly sleep assessment products affords researchers with a host of tools to consider for capturing free-living sleep in children. The purpose of this study was to compare free-living sleep characteristics (duration and bed/wake times) across different measures in children.
Methods:
Elementary school-aged children (N = 30, mean age 7.2 years, 63% boys, 87% non-Hispanic white) wore an ActiGraph GT9X Link© and Fitbit Charge HR© on the non-dominant wrist, with a Beddit 3 Sleep Monitor© affixed to their mattress for two consecutive weekend nights of free-living sleep. Parents completed a sleep log of bed and wake times. Absolute differences in bed and wake times were examined and Bland Altman plots assessed the level of agreement across sleep measures.
Results:
Across the four sleep measures, total sleep time (TST) ranged from 458 min/night (ActiGraph GT9X Link©) to 613 min/night (Parent report). Mean bed and wake times ranged from 8:46PM to 9:03PM, and 6:52AM to 7:16AM, respectively. Pearson correlation coefficients were moderate between all four sleep measures (range r = 0.30-0.71). Bland-Altman plots indicated the highest level of agreement for TST was between Beddit 3 Sleep Monitor© and Fitbit Charge HR© (mean difference -11.7, limits of agreement: 119.0, -142.4 min).
Conclusions:
The findings from this study show a high level of agreement of when a child goes to sleep and wakes up across a variety of sleep measures; however, more work is needed to classify TST once the sleep period has commenced.
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