Comparing the activPAL Software’s Primary Time in Bed Algorithm against Self-Report and van Der Berg’s Algorithm

ABSTRACT

The purpose of this study was to compare activPAL algorithm-estimated values for time in bed (TIB), wake time (WT) and bedtime (BT) against self-report and an algorithm developed by van der Berg and colleagues. Secondary analyses of baseline data from the Community Activity for Prevention Study (CAPs) were used in which adults ≥ 18 years wore the activPAL for seven days. Mixed-effects models compared differences between TIB, WT, and BT for all three methods. Bland-Altman plots examined agreement and the two-one-sided test examined equivalence. activPAL was not equivalent to self-report or van der Berg in estimating TIB, but was equivalent to self-report for estimating BT, and was equivalent to van der Berg for estimating WT. The activPAL algorithm requires adjustments before researchers can use it to estimate TIB. However, researchers can use activPAL’s option to manually enter self-reported BT and WT to estimate TIB and better understand 24-hour movement patterns.

KEYWORDS:

• Sleep
• accelerometry
• methodology
• validation Studies

Acknowledgments

Thank you to the CAPs study participants. Thank you to Dr. Zach Weller in the CSU Statistics Department for consulting on the analyses and R code. Thank you to van der Berg and colleagues for making their algorithm freely available and providing trouble-shooting tips.

Declaration of conflicts of interest

Kate Lyden is the Chief Science Officer at VivoSense, Inc. She previously worked as an independent consultant for several wearable device manufacturers, including PAL Technologies.

Additional information

Funding

This project was supported by the Research Scholars Grant (130091-RSG-16-169-01-CPPB) from the American Cancer Society. Additional support was provided by the University of Colorado Cancer Center and the University of Colorado Boulder. JBC was supported by the Prevention and Methodology Training Program (T32 DA017629; MPIs: J. Maggs & S. Lanza) with funding from the National Institute on Drug Abuse. KA was supported by the USDA National Institute of Food and Agriculture/Michigan AgBioResearch Hatch project MICL02410.