scholarly journals Test—retest reliability of the StepWatch Activity Monitor outputs in individuals with chronic stroke

2008 ◽  
Vol 22 (10-11) ◽  
pp. 871-877 ◽  
Author(s):  
Suzie Mudge ◽  
N. Susan Stott
2019 ◽  
Author(s):  
Stephanie A Maganja ◽  
David C Clarke ◽  
Scott A Lear ◽  
Dawn C Mackey

BACKGROUND To assess whether commercial-grade activity monitors are appropriate for measuring step counts in older adults, it is essential to evaluate their measurement properties in this population. OBJECTIVE This study aimed to evaluate test-retest reliability and criterion validity of step counting in older adults with self-reported intact and limited mobility from 6 commercial-grade activity monitors: Fitbit Charge, Fitbit One, Garmin vívofit 2, Jawbone UP2, Misfit Shine, and New-Lifestyles NL-1000. METHODS For test-retest reliability, participants completed two 100-step overground walks at a usual pace while wearing all monitors. We tested the effects of the activity monitor and mobility status on the absolute difference in step count error (%) and computed the standard error of measurement (SEM) between repeat trials. To assess criterion validity, participants completed two 400-meter overground walks at a usual pace while wearing all monitors. The first walk was continuous; the second walk incorporated interruptions to mimic the conditions of daily walking. Criterion step counts were from the researcher tally count. We estimated the effects of the activity monitor, mobility status, and walk interruptions on step count error (%). We also generated Bland-Altman plots and conducted equivalence tests. RESULTS A total of 36 individuals participated (n=20 intact mobility and n=16 limited mobility; 19/36, 53% female) with a mean age of 71.4 (SD 4.7) years and BMI of 29.4 (SD 5.9) kg/m<sup>2</sup>. Considering test-retest reliability, there was an effect of the activity monitor (<i>P</i>&lt;.001). The Fitbit One (1.0%, 95% CI 0.6% to 1.3%), the New-Lifestyles NL-1000 (2.6%, 95% CI 1.3% to 3.9%), and the Garmin vívofit 2 (6.0%, 95 CI 3.2% to 8.8%) had the smallest mean absolute differences in step count errors. The SEM values ranged from 1.0% (Fitbit One) to 23.5% (Jawbone UP2). Regarding criterion validity, all monitors undercounted the steps. Step count error was affected by the activity monitor (<i>P</i>&lt;.001) and walk interruptions (<i>P</i>=.02). Three monitors had small mean step count errors: Misfit Shine (−1.3%, 95% CI −19.5% to 16.8%), Fitbit One (−2.1%, 95% CI −6.1% to 2.0%), and New-Lifestyles NL-1000 (−4.3%, 95 CI −18.9% to 10.3%). Mean step count error was larger during interrupted walking than continuous walking (−5.5% vs −3.6%; <i>P</i>=.02). Bland-Altman plots illustrated nonsystematic bias and small limits of agreement for Fitbit One and Jawbone UP2. Mean step count error lay within an equivalence bound of ±5% for Fitbit One (<i>P</i>&lt;.001) and Misfit Shine (<i>P</i>=.001). CONCLUSIONS Test-retest reliability and criterion validity of step counting varied across 6 consumer-grade activity monitors worn by older adults with self-reported intact and limited mobility. Walk interruptions increased the step count error for all monitors, whereas mobility status did not affect the step count error. The hip-worn Fitbit One was the only monitor with high test-retest reliability and criterion validity.


2010 ◽  
Vol 7 (5) ◽  
pp. 671-676 ◽  
Author(s):  
Suzie Mudge ◽  
Denise Taylor ◽  
Oliver Chang ◽  
Rosita Wong

Background:Activity Monitors give an objective measure of usual walking performance. This study aimed to examine the test-retest reliability of the StepWatch Activity Monitor outputs (mean steps/day; peak activity index; sustained activity indices of 1, 5, 20, 30, 60 minutes; steps at high, medium, and low stepping rates).Methods:Thirty healthy adults age 18 to 49 years wore the StepWatch for 2 3-day periods at least 1 week apart.Results:The intraclass correlation coefficients of the StepWatch outputs ranged from 0.44 to 0.91 over 3 days. The coefficient of variation ranged from 3.0% to 51.3% over the monitoring periods, with higher variation shown for shorter monitoring periods. The most reliable 5 outputs had 95% limits of agreement between 3-day periods that were less than 40%. These were mean steps/day (±39.1%), highest step rate in 1 (±17.3%) and 5 (±37.4%) minutes, peak activity index (±25.6%), and percentage of inactive time (±9.52%).Conclusions:Mean steps/day, highest step rate in 1 and 5 minutes, peak activity index, and percentage of inactive time have good test-retest reliability over a 3-day monitoring period, with lower reliability shown by the other StepWatch outputs. Monitoring over 1 or 2 days is less reliable.


2016 ◽  
Vol 30 (11) ◽  
pp. 1120-1127 ◽  
Author(s):  
Elisabeth Ekstrand ◽  
Jan Lexell ◽  
Christina Brogårdh

2018 ◽  
Vol 30 (10) ◽  
pp. 1271-1277 ◽  
Author(s):  
Polykarpos Angelos Nomikos ◽  
Nicola Spence ◽  
Mansour Abdullah Alshehri

2020 ◽  
Vol 41 (9) ◽  
pp. 2514-2526
Author(s):  
Allison F. Lewis ◽  
Makenzie Myers ◽  
Jenny Heiser ◽  
Melissa Kolar ◽  
Jessica F. Baird ◽  
...  

2007 ◽  
Vol 21 (4) ◽  
pp. 347-352 ◽  
Author(s):  
Hui-Mei Chen ◽  
Ching-Lin Hsieh ◽  
Sing Kai Lo ◽  
Lih-Jiun Liaw ◽  
Shih-Ming Chen ◽  
...  

Brain Injury ◽  
2013 ◽  
Vol 27 (10) ◽  
pp. 1148-1154 ◽  
Author(s):  
Hui-Chun Chen ◽  
Chia-Lin Koh ◽  
Ching-Lin Hsieh ◽  
I-Ping Hsueh

10.2196/16537 ◽  
2020 ◽  
Vol 4 (8) ◽  
pp. e16537 ◽  
Author(s):  
Stephanie A Maganja ◽  
David C Clarke ◽  
Scott A Lear ◽  
Dawn C Mackey

Background To assess whether commercial-grade activity monitors are appropriate for measuring step counts in older adults, it is essential to evaluate their measurement properties in this population. Objective This study aimed to evaluate test-retest reliability and criterion validity of step counting in older adults with self-reported intact and limited mobility from 6 commercial-grade activity monitors: Fitbit Charge, Fitbit One, Garmin vívofit 2, Jawbone UP2, Misfit Shine, and New-Lifestyles NL-1000. Methods For test-retest reliability, participants completed two 100-step overground walks at a usual pace while wearing all monitors. We tested the effects of the activity monitor and mobility status on the absolute difference in step count error (%) and computed the standard error of measurement (SEM) between repeat trials. To assess criterion validity, participants completed two 400-meter overground walks at a usual pace while wearing all monitors. The first walk was continuous; the second walk incorporated interruptions to mimic the conditions of daily walking. Criterion step counts were from the researcher tally count. We estimated the effects of the activity monitor, mobility status, and walk interruptions on step count error (%). We also generated Bland-Altman plots and conducted equivalence tests. Results A total of 36 individuals participated (n=20 intact mobility and n=16 limited mobility; 19/36, 53% female) with a mean age of 71.4 (SD 4.7) years and BMI of 29.4 (SD 5.9) kg/m2. Considering test-retest reliability, there was an effect of the activity monitor (P<.001). The Fitbit One (1.0%, 95% CI 0.6% to 1.3%), the New-Lifestyles NL-1000 (2.6%, 95% CI 1.3% to 3.9%), and the Garmin vívofit 2 (6.0%, 95 CI 3.2% to 8.8%) had the smallest mean absolute differences in step count errors. The SEM values ranged from 1.0% (Fitbit One) to 23.5% (Jawbone UP2). Regarding criterion validity, all monitors undercounted the steps. Step count error was affected by the activity monitor (P<.001) and walk interruptions (P=.02). Three monitors had small mean step count errors: Misfit Shine (−1.3%, 95% CI −19.5% to 16.8%), Fitbit One (−2.1%, 95% CI −6.1% to 2.0%), and New-Lifestyles NL-1000 (−4.3%, 95 CI −18.9% to 10.3%). Mean step count error was larger during interrupted walking than continuous walking (−5.5% vs −3.6%; P=.02). Bland-Altman plots illustrated nonsystematic bias and small limits of agreement for Fitbit One and Jawbone UP2. Mean step count error lay within an equivalence bound of ±5% for Fitbit One (P<.001) and Misfit Shine (P=.001). Conclusions Test-retest reliability and criterion validity of step counting varied across 6 consumer-grade activity monitors worn by older adults with self-reported intact and limited mobility. Walk interruptions increased the step count error for all monitors, whereas mobility status did not affect the step count error. The hip-worn Fitbit One was the only monitor with high test-retest reliability and criterion validity.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Tai-Wa Liu ◽  
Shamay S. M. Ng ◽  
Gabriel Y. F. Ng

Objectives. To (1) translate and culturally adapt the English version Community Integration Measure into Chinese (Cantonese), (2) report the results of initial validation of the Chinese (Cantonese) version of CIM (CIM-C) including the content validity, internal consistency, test-retest reliability, and factor structure of CIM-C for use in stroke survivors in a Chinese community setting, and (3) investigate the level of community integration of stroke survivors living in Hong Kong.Design. Cross-sectional study.Setting. University-based rehabilitation centre.Participants. 62 (n=62) subjects with chronic stroke.Methods. The CIM-C was produced after forward-backward translation, expert panel review, and pretesting. 25 (n=25) of the same subjects were reassessed after a 1-week interval.Results. The items of the CIM-C demonstrated high internal consistency with a Cronbach’sαof 0.84. The CIM-C showed good test-retest reliability with an intraclass correlation coefficient (ICC) of 0.84 (95% confidence interval, 0.64–0.93). A 3-factor structure of the CIM-C including “relationship and engagement,” “sense of knowing,” and “independent living,” was consistent with the original theoretical model. Hong Kong stroke survivors revealed a high level of community integration as measured by the CIM-C (mean (SD): 43.48 (5.79)).Conclusions. The CIM-C is a valid and reliable measure for clinical use.


Author(s):  
Alyssa D. Stookey ◽  
Richard F. Macko ◽  
Frederick M. Ivey ◽  
Leslie I. Katzel

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