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Sheri J. Hartman, Catherine R. Marinac, Lisa Cadmus-Bertram, Jacqueline Kerr, Loki Natarajan, Suneeta Godbole, Ruth E. Patterson, Brittany Morey and Dorothy D. Sears

, Zderic TW , Schuna JM Jr , Hamilton MT , Tudor-Locke C . Free-living activity counts-derived breaks in sedentary time: are they real transitions from sitting to standing? Gait Posture. 2015 ; 42 ( 1 ): 70 – 72 . PubMed doi:10.1016/j.gaitpost.2015.04.008 25953504 10.1016/j.gaitpost.2015

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Daniel Arvidsson, Elias Johannesson, Lars Bo Andersen, Magnus Karlsson, Per Wollmer, Ola Thorsson and Magnus Dencker

). This is a uniaxial accelerometer recording acceleration signals along the vertical axis to generate activity counts corresponding to activity intensity. 19 Recordings of physical activity in the present study were performed during the whole autumn school term. Children were instructed to wear the

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Kin-Kit Li, Lorna Ng, Sheung-Tak Cheng and Helene H. Fung

more. Activity counts were converted into minutes of moderate- to vigorous-intensity PA per day based on the cutoffs suggested by Fredman, Bertrand, Martire, Hochberg, and Harris ( 2006 ). Covariates Several demographic and health-related factors were measured and controlled for in the analyses. The

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Mallory S. Kobak, Andrew Lepp, Michael J. Rebold, Hannah Faulkner, Shannon Martin and Jacob E. Barkley

a significant main effect of condition for accelerometer counts ( F  = 5.3, P  = .03; Figure  1 ). Children accumulated significantly greater total physical activity counts per METs when playing without the iPad present [101,733 (60,015) counts, 5.3 (4.0) METs/min or moderate intensity] versus

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Molly P. O’Sullivan, Matthew R. Nagy, Shannon S. Block, Trevor R. Tooley, Leah E. Robinson, Natalie Colabianchi and Rebecca E. Hasson

of ≥60 minutes of zero activity counts were also defined as nonwear time, allowing for 1–2 minutes of counts between 0 and 100 ( 20 ). Nonwear times were excluded from the analyses. The Evenson ( 5 ) cut points were used to derive activity intensities (sedentary: 0–100 counts per minute; low

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Elroy J. Aguiar, John M. Schuna Jr., Tiago V. Barreira, Emily F. Mire, Stephanie T. Broyles, Peter T. Katzmarzyk, William D. Johnson and Catrine Tudor-Locke

monitored hours per day, with nonwear time defined as ≥60 min of consecutive zero-activity counts per minute, allowing for minimal interruptions (up to 2 min of counts between 0 and 100; Troiano et al., 2008 ). All individuals with at least one valid day of data were retained in the analysis ( Tudor

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Barbara Resnick, Elizabeth Galik, Marie Boltz, Erin Vigne, Sarah Holmes, Steven Fix and Shijun Zhu

). Prior evidence of reliability of the MotionWatch 8 was based on the consistency between recordings across 3 days of wear. Evidence of validity of the MotionWatch 8 was based on a consistent match between the activity counts and recorded activity performed and a statistically significant difference in

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Jana Slaght, Martin Sénéchal and Danielle R. Bouchard

the pedometer data we measured the total number of minutes spent in MVPA per week based on their individualized threshold at 40% VO 2 R. The raw accelerometer data was analyzed to see what activity count was associated with the same number of minutes in MVPA as the pedometer information. For accuracy

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Juliana S. Oliveira, Leanne Hassett, Catherine Sherrington, Elisabeth Ramsay, Catherine Kirkham, Shona Manning and Anne Tiedemann

use of a waist-worn accelerometer (ActiGraph GT3X+, Pensacola, FL) and was expressed as mean activity counts/min/day and mean number of steps/day. Goal Setting Participants nominated two function-related goals that met the S.M.A.R.T criteria. Goals were determined in a collaborative manner by the

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Laura E. Juliff, Jeremiah J. Peiffer and Shona L. Halson

piezoelectric accelerometer, which sampled activity counts in 1-minute epochs. Epoch-for-epoch concordance rates of 81% to 90% with polysomnography (gold standard sleep measure) have been found for sleep/wake activity using Actical® wrist actigraphy monitors. 14 Participants wore the monitor at all times