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Ryan McGrath, Chantal A. Vella, Philip W. Scruggs, Mark D. Peterson, Christopher J. Williams and David R. Paul

and to identify how accelerometer wear time affects individual PAGA misclassifications. We also sought to determine how measurement error from low accelerometer wear time alters the results of a linear regression model examining the association between moderate to vigorous physical activity (MVPA) and

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Lisa Price, Katrina Wyatt, Jenny Lloyd, Charles Abraham, Siobhan Creanor, Sarah Dean and Melvyn Hillsdon

/convenience/waterproofing and manipulating the wear-time protocol should yield higher compliance, in turn, leading to more precise estimates of PA across the entire week. Despite evidence of high compliance at single measurement point ( 8 ) with wrist-worn devices, evidence regarding compliance over multiple measure periods is

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Bouwien Smits-Engelsman, Wendy Aertssen and Emmanuel Bonney

agreement between the 2 measurement occasions, we calculated LOA (95% interval) by using the mean and the SD of the differences between 2 measurements. Bland–Altman plots were made to visualize the measurement bias and the LOA. To investigate systematic bias, a paired Student t test was conducted to test

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Ryan M. Hulteen, Lisa M. Barnett, Philip J. Morgan, Leah E. Robinson, Christian J. Barton, Brian H. Wrotniak and David R. Lubans

provided their home postal code, which was used as a proxy measure of SES according to the Australian Socio-economic Indexes for Areas ( Australian Bureau of Statistics, 2011 ). Motor Competence Motor competence was assessed using the Lifelong Physical Activity Skills Battery. The measurement properties

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Erika Rees-Punia, Charles E. Matthews, Ellen M. Evans, Sarah K. Keadle, Rebecca L. Anderson, Jennifer L. Gay, Michael D. Schmidt, Susan M. Gapstur and Alpa V. Patel

feasible and cost-effective option for large-scale epidemiologic studies ( Haskell, 2012 ; Masse & de Niet, 2012 ; Sallis & Saelens, 2000 ). Given these issues, it is important to conduct validity studies of PA surveys to understand how measurement error may affect results of future association studies

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Kimberly A. Clevenger, Karin A. Pfeiffer and Cheryl A. Howe

Accurate measurement of energy expenditure is critical for research on the benefits of physical activity and monitor validation and for intervention design, exercise prescription, or quantification of self-reported activity ( 29 , 30 ). Portable metabolic units (PMUs) are valuable tools for

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Jaap Swanenburg, Karel H. Stappaerts, Bart Tirez, Daniel Uebelhart and Geert Aufdemkampe

The purpose of this study was to present a method for repeated measurement of flexion force of the hallux in the metatarsophalangeal joint. The reliability of this measurement device was also examined. This device is suitable for situations where weight-bearing is contraindicated or when it is not possible for patients to bear load on their toes, such as hallux valgus patients. Since most such patients are female, the participants in this study were 24 healthy female volunteers. Age, weight, height, and leg dominance were determined for each. Muscle strength was measured using a device with a built-in MicroFET dynamometer. The result for the left hallux was ICC(3,1) .89 (95% CI .77–.95). The result for the right hallux was ICC(3,1) .94 (95% CI .87–.97). In the Bland and Altman plots, the reliability again appeared to be sufficient. The Pearson product-moment correlations gave poor results for the association between body weight, height, age, and mean force of the four trails. The test results indicate good reliability of the measurement device as used in this study. The advantage of this testing device is that it makes it easier to standardize measurements as opposed to the MicroFET used as a hand-held dynamometer. Also, patients can be tested in a nonload situation, which makes it possible to test hallux valgus at any time, and therefore it is possible to monitor variations in progression (or regression).

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Stacy A. Clemes and Stuart J.H. Biddle


Pedometers are increasingly being used to measure physical activity in children and adolescents. This review provides an overview of common measurement issues relating to their use.


Studies addressing the following measurement issues in children/adolescents (aged 3−18 years) were included: pedometer validity and reliability, monitoring period, wear time, reactivity, and data treatment and reporting. Pedometer surveillance studies in children/adolescents (aged: 4−18 years) were also included to enable common measurement protocols to be highlighted.


In children > 5 years, pedometers provide a valid and reliable, objective measure of ambulatory activity. Further evidence is required on pedometer validity in preschool children. Across all ages, optimal monitoring frames to detect habitual activity have yet to be determined; most surveillance studies use 7 days. It is recommended that standardized wear time criteria are established for different age groups, and that wear times are reported. As activity varies between weekdays and weekend days, researchers interested in habitual activity should include both types of day in surveillance studies. There is conflicting evidence on the presence of reactivity to pedometers.


Pedometers are a suitable tool to objectively assess ambulatory activity in children (> 5 years) and adolescents. This review provides recommendations to enhance the standardization of measurement protocols.

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Margaret A. Finley, Laura Dipietro, Jill Ohlhoff, Jill Whitall, Hermano I. Krebs and Christopher T. Bever

We are expanding the use of the MIT-MANUS robotics to persons with impairments due exclusively to orthopedic disorders, with no neurological deficits. To understand the reliability of repeated measurements of the robotic tasks and the potential for registering changes due to learning is critical. Purposes of this study were to assess the learning effect of repeated exposure to robotic evaluations and to demonstrate the ability to detect a change in protocol in outcome measurements. Ten healthy, unimpaired subjects (mean age = 54.1 ± 6.4 years) performed six repeated evaluations consisting of unconstrained reaching movements to targets and circle drawing (with and without a visual template) on the MIT-MANUS. Reaching outcomes were aiming error, mean and peak speed, movement smoothness and duration. Outcomes for circle drawing were axis ratio metric and shoulder–elbow joint angles correlation metric (was based on a two-link model of the human arm and calculated hand path during the motions). Repeated-measures ANOVA (p ≤ .05) determined if difference existed between the sessions. Intraclass correlations (R) were calculated. All variables were reliable, without learning across testing sessions. Intraclass correlation values were good to high (reaching, R ≥ .80; circle drawing, R ≥ .90). Robotic measurement ability to differentiate between similar but distinct tasks was demonstrated as measured by axis ratio metric (p < .001) and joint correlation metric (p = .001). Outcome measures of the MIT-MANUS proved to be reliable yet sensitive to change in healthy adults without motor learning over the course of repeated measurements.

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Robert G. Weaver, Aaron Beighle, Heather Erwin, Michelle Whitfield, Michael W. Beets and James W. Hardin

specific types of PA (ie, biking and swimming), 1 , 2 whereas DO can be used to assess all types of PA. Thus, DO has several distinct advantages over other methods of PA measurement. A common protocol used in DO instruments that quantify children’s PA is focal child observation. 3 – 5 This technique