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Comparing the activPAL software's Primary Time in Bed Algorithm against Self-Report and van der Berg's Algorithm.

J B Courtney1, K Nuss1, K Lyden2

  • 1Colorado State University, Fort Collins, Colorado.

Measurement in Physical Education and Exercise Science
|July 30, 2021
PubMed
Summary
This summary is machine-generated.

The activPAL device accurately estimates bedtime and wake time but needs adjustments for time in bed estimation. Researchers can manually input self-reported data for accurate time in bed analysis.

Keywords:
AccelerometryMethodologySleepValidation Studies

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Area of Science:

  • Physical activity monitoring
  • Sleep science
  • Biomedical engineering

Background:

  • Accurate measurement of sleep and wake patterns is crucial for understanding health behaviors.
  • Wearable activity trackers like activPAL offer objective data but require validation against established methods.
  • Previous algorithms for estimating sleep parameters have varying degrees of accuracy.

Purpose of the Study:

  • To compare activPAL algorithm-estimated time in bed (TIB), wake time (WT), and bedtime (BT) with self-report and a validated algorithm.
  • To assess the agreement and equivalence of activPAL's estimations for key sleep-wake variables.
  • To provide recommendations for optimizing the use of activPAL in research settings.

Main Methods:

  • Secondary analysis of baseline data from the Community Activity for Prevention Study (CAPS).
  • Participants (adults ≥ 18 years) wore the activPAL device for seven consecutive days.
  • Statistical comparison using mixed-effects models, Bland-Altman plots for agreement, and two-one-sided tests for equivalence.

Main Results:

  • activPAL algorithm was not equivalent to self-report or the van der Berg algorithm for estimating TIB.
  • activPAL demonstrated equivalence with self-report for estimating BT.
  • activPAL showed equivalence with the van der Berg algorithm for estimating WT.

Conclusions:

  • The current activPAL algorithm requires modifications for reliable TIB estimation in research.
  • Manual input of self-reported BT and WT into activPAL can facilitate accurate TIB calculation.
  • These findings support the use of activPAL, with adjustments, for comprehensive 24-hour movement and sleep pattern analysis.