Literature DB >> 15354049

Reliability of accelerometry-based activity monitors: a generalizability study.

Gregory J Welk1, Jodee A Schaben, James R Morrow.   

Abstract

INTRODUCTION: Numerous studies have examined the validity of accelerometry-based activity monitors but few studies have systematically studied the reliability of different accelerometer units for assessing a standardized bout of physical activity. Improving understanding of error in these devices is an important research objective because they are increasingly being used in large surveillance studies and intervention trials that require the use of multiple units over time.
METHODS: Four samples of college-aged participants were recruited to collect reliability data on four different accelerometer types (CSA/MTI, Biotrainer Pro, Tritrac-R3D, and Actical). The participants completed three trials of treadmill walking (3 mph) while wearing multiple units of a specific monitor type. For each trial, the participant completed a series of 5-min bouts of walking (one for each monitoring unit) with 1-min of standing rest between each bout. Generalizability (G) theory was used to quantify variance components associated with individual monitor units, trials, and subjects as well as interactions between these terms.
RESULTS: The overall G coefficients range from 0.43 to 0.64 for the four monitor types. Corresponding intraclass correlation coefficients (ICC) ranged from 0.62 to 0.80. The CSA/MTI was found to have the least variability across monitor units and trials and the highest overall reliability. The Actical was found to have the poorest reliability.
CONCLUSION: The CSA/MTI appeared to have acceptable reliability for most research applications (G values above 0.60 and ICC values above 0.80), but values with the other devices indicate some possible concerns with reliability. Additional work is needed to better understand factors contributing to variability in accelerometry data and to determine appropriate calibration protocols to improve reliability of these measures for different research applications.

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Mesh:

Year:  2004        PMID: 15354049

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  158 in total

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4.  Relationship between accelerometer-based measures of physical activity and the Yale Physical Activity Survey in adults with arthritis.

Authors:  Pamela Semanik; Jungwha Lee; Larry Manheim; Loretta Dipietro; Dorothy Dunlop; Rowland W Chang
Journal:  Arthritis Care Res (Hoboken)       Date:  2011-12       Impact factor: 4.794

5.  Accelerometer use in a physical activity intervention trial.

Authors:  Melissa A Napolitano; Kelley E Borradaile; Beth A Lewis; Jessica A Whiteley; Jaime L Longval; Alfred F Parisi; Anna E Albrecht; Christopher N Sciamanna; John M Jakicic; George D Papandonatos; Bess H Marcus
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7.  Sedentary behavior and physical function: objective evidence from the Osteoarthritis Initiative.

Authors:  Jungwha Lee; Rowland W Chang; Linda Ehrlich-Jones; C Kent Kwoh; Michael Nevitt; Pamela A Semanik; Leena Sharma; Min-Woong Sohn; Jing Song; Dorothy D Dunlop
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8.  A longitudinal study of the effects of instrumental and emotional social support on physical activity in underserved adolescents in the ACT trial.

Authors:  E Rebekah Siceloff; Dawn K Wilson; Lee Van Horn
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9.  Does the intensity of daily walking matter for protecting against the development of a slow gait speed in people with or at high risk of knee osteoarthritis? An observational study.

Authors:  S A M Fenton; T Neogi; D Dunlop; M Nevitt; M Doherty; J L Duda; R Klocke; A Abhishek; A Rushton; W Zhang; C E Lewis; J Torner; G Kitas; D K White
Journal:  Osteoarthritis Cartilage       Date:  2018-05-02       Impact factor: 6.576

10.  GIS-measured walkability, transit, and recreation environments in relation to older Adults' physical activity: A latent profile analysis.

Authors:  Michael Todd; Marc A Adams; Jonathan Kurka; Terry L Conway; Kelli L Cain; Matthew P Buman; Lawrence D Frank; James F Sallis; Abby C King
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