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dc.contributor.authorMcVeigh, Joanne
dc.contributor.authorWinkler, E.
dc.contributor.authorHealy, Genevieve
dc.contributor.authorSlater, J.
dc.contributor.authorEastwood, Peter
dc.contributor.authorStraker, Leon
dc.identifier.citationMcVeigh, J. and Winkler, E. and Healy, G. and Slater, J. and Eastwood, P. and Straker, L. 2016. Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults. Physiological Measurement. 37 (10): pp. 1636-1652.

Researchers are increasingly using 24 h accelerometer wear protocols. No automated method has been published that accurately distinguishes 'waking' wear time from other data ('in-bed', non-wear, invalid days) in young adults. This study examined the validity of an automated algorithm developed to achieve this for hip-worn Actigraph GT3X + 60 s epoch data. We compared the algorithm against a referent method ('into-bed' and 'out-of-bed' times visually identified by two independent raters) and benchmarked against two published algorithms. All methods used the same non-wear rules. The development sample (n = 11) and validation sample (n = 95) were Australian young adults from the Raine pregnancy cohort (54% female), all aged approximately 22 years. The agreement with Rater 1 in each minute's classification (yes/no) of waking wear time was examined as kappa (κ), limited to valid days (10 h waking wear time per day) according to the algorithm and Rater 1. Bland-Altman methods assessed agreement in daily totals of waking wear and in-bed wear time. Excellent agreement (κ > 0.75) was obtained between the raters for 80% of participants (median κ = 0.94). The algorithm showed excellent agreement with Rater 1 (κ >.75) for 89% of participants and poor agreement (κ < 0.40) for 1%. In this sample, the algorithm (median κ = 0.86) performed better than algorithms validated in children (median κ = 0.77) and adolescents (median κ = 0.66). The mean difference (95% limits of agreement) between Rater 1 and the algorithm was 7 (−220, 234) min d−1 for waking wear time on valid days and  −41 (−309, 228) min d−1 for in-bed wear time.In this population, the automated algorithm's validity for identifying waking wear time was mostly good, not worse than inter-rater agreement, and better than the evaluated published alternatives. However, the algorithm requires improvement to better identify in-bed wear time.

dc.publisherInstitute of Physics Publishing Ltd
dc.titleValidity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24 h wear protocol in young adults
dc.typeJournal Article
dcterms.source.titlePhysiological Measurement
curtin.departmentSchool of Physiotherapy and Exercise Science
curtin.accessStatusFulltext not available

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