The Preliminary Criterion Validity of the Activ8 Activity Monitor to Measure Physical Activity in Youth Using a Wheelchair

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Kristel Lankhorst ◽  
Marleen Sol ◽  
Rita van den Berg-Emons ◽  
Herwin Horemans ◽  
Janke de Groot
Keyword(s):  
Physical Activity ◽  
Activity Monitor ◽  
Criterion Validity

Validation of a Noninvasive, Disposable Activity Monitor for Clinical Applications

2017 ◽  
Vol 14 (7) ◽  
pp. 546-551 ◽  
Author(s):  
Greg Welk ◽  
Youngwon Kim ◽  
Robin P. Shook ◽  
Laura Ellingson ◽  
Roberto L. Lobelo
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Physical Activity Behavior ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Sensewear Armband ◽  
Statistical Equivalence ◽  
Activity Behavior ◽  
Highly Correlated ◽  
And Behavior

Background:The study evaluated the concurrent and criterion validity of a new, disposable activity monitor designed to provide objective data on physical activity and energy expenditure in clinical populations.Methods:A sample of healthy adults (n = 52) wore the disposable Metria IH1 along with the established Sensewear armband (SWA) monitor for a 1-week period. Concurrent validity was examined by evaluating the statistical equivalence of estimates from the Metria and the SWA. Criterion validity was examined by comparing the relative accuracy of the Metria IH1 and the SWA for assessing walking/running. The absolute validity of the 2 monitors was compared by computing correlations and mean absolute percent error (MAPE) relative to criterion data from a portable metabolic analyzer.Results:The output from 2 monitors was highly correlated (correlations > 0.90) and the summary measures yielded nearly identical allocations of time spent in physical activity and energy expenditure. The monitors yielded statistically equivalent estimates and had similar absolute validity relative to the criterion measure (12% to 15% error).Conclusions:The disposable nature of the adhesive Metria IH1 monitor offers promise for clinical evaluation of physical activity behavior in patients. Additional research is needed to test utility for counseling and behavior applications.

scholarly journals Evaluation of the FitBark Activity Monitor for Measuring Physical Activity in Dogs

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 781
Author(s):  
Jessica Colpoys ◽  
Dean DeCock
Keyword(s):  
Physical Activity ◽  
Video Analysis ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Step Count ◽  
Phase 3 ◽  
Activity Data ◽  
Phase Approach ◽  
Low Correlation ◽  
Three Phase

Accelerometers track changes in physical activity which can indicate health and welfare concerns in dogs. The FitBark 2 (FitBark) is an accelerometer for use with dogs; however, no studies have externally validated this tool. The objective of this study was to evaluate FitBark criterion validity by correlating FitBark activity data to dog step count. Dogs (n = 26) were fitted with a collar-mounted FitBark and individually recorded for 30 min using a three-phase approach: (1) off-leash room explore; (2) human–dog interaction; and (3) on-leash walk. Video analysis was used to count the number of times the front right paw touched the ground (step count). Dog step count and FitBark activity were moderately correlated across all phases (r = 0.65, p < 0.001). High correlations between step count and FitBark activity were observed during phases 1 (r = 0.795, p < 0.001) and 2 (r = 0.758, p < 0.001), and a low correlation was observed during phase 3 (r = 0.498, p < 0.001). In conclusion, the FitBark is a valid tool for tracking physical activity in off-leash dogs; however, more work should be done to identify the best method of tracking on-leash activity.

scholarly journals Measuring Criterion Validity of Microinteraction Ecological Momentary Assessment (Micro-EMA): A Pilot Study with Physical Activity Measurement (Preprint)

2020 ◽  
Author(s):  
Aditya Ponnada ◽  
Binod Thapa Chhetry ◽  
Justin Manjourides ◽  
Stephen Intille
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
Ecological Momentary Assessment ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Self Report ◽  
Activity Measurement ◽  
Research Grade ◽  
Ecological Momentary ◽  
Momentary Assessment

BACKGROUND Ecological momentary assessment (EMA) is an in-situ method of gathering self-report on behaviors using mobile devices. Microinteraction-EMA (Micro-EMA or μEMA) is a type of EMA where all the self-report prompts are single-question surveys that can be answered using a one-tap glanceable microinteraction, conveniently on a smartwatch. Prior work suggests that μEMA may permit a substantially higher prompting rate than EMA with higher response rates. However, the validity of μEMA self-report has not yet been assessed. OBJECTIVE In this pilot study, we evaluated the criterion validity of μEMA on a smartwatch, using physical activity (PA) assessment as an example behavior of interest. METHODS Seventeen participants answered 72 μEMA prompts each day for one-week, self-reporting whether they were doing sedentary, light/standing, moderate/walking, or vigorous activities at each prompt. Responses were then compared with a research-grade activity monitor worn on the dominant ankle continuously measuring PA. RESULTS We observed significantly higher (P <.001) momentary PA levels on the activity monitor when participants self-reported (using μEMA) engaging in moderate/walking or vigorous activities as compared to sedentary or light/standing activities. CONCLUSIONS For PA measurement, high-frequency μEMA self-report could be used to capture the information comparable to that of a research-grade continuous sensor – suggesting criterion validity.

scholarly journals Effect of mindfulness on physical activity in primary healthcare patients: a randomised controlled trial pilot study

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Peter Nymberg ◽  
Susanna Calling ◽  
Emelie Stenman ◽  
Karolina Palmér ◽  
Eva Ekvall Hansson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Study Design ◽  
Controlled Trial ◽  
Dropout Rate ◽  
Activity Monitor ◽  
Activity Level ◽  
Self Report ◽  
Ethical Review ◽  
Mixed Effect ◽  
Registration Number

Abstract Increased physical activity can have health benefits among inactive individuals. In Sweden, the healthcare system uses physical activity on prescription (PAP) to motivate patients to increase their physical activity level. Mindfulness may further heighten the internal motivation to engage in physical activity. However, previous research has not demonstrated clear evidence of such an association. Aim Examine the feasibility of the study design as a preparation for a full-scale study, and examine the differences, between three interventions, in change over time in physical activity levels and in related variables. Method Comparison between three different interventions in an ordinary primary health care setting: PAP, mindfulness, and a combination of PAP and mindfulness. Physical activity was measured with self-report and ACTi Graph GT1X activity monitor. Statistical analysis was performed with a mixed-effect model to account for repeated observations and estimate differences both within groups and between groups at 3- and 6-months follow-up. Results Between September 2016 and December 2018, a total of 88 participants were randomised into three groups. The total dropout rate was 20.4%, the attendance rate to the mindfulness courses (52% > 6 times) and the web-based mindfulness training (8% > 800 min) was low according to the stated feasibility criteria. Eleven participants were excluded from analysis due to low activity monitor wear time. Neither the activity monitor data nor self-reported physical activity showed any significant differences between the groups. Conclusion The study design needs adjustment for the mindfulness intervention design before a fully scaled study can be conducted. A combination of PAP and mindfulness may increase physical activity and self-rated health more than PAP or mindfulness alone. Trial registration ClinicalTrials.gov, registration number NCT02869854. Regional Ethical Review Board in Lund registration number 2016/404.

scholarly journals Formative Evaluation of Consumer-Grade Activity Monitors Worn by Older Adults: Test-Retest Reliability and Criterion Validity of Step Counts (Preprint)

2019 ◽  
Author(s):  
Stephanie A Maganja ◽  
David C Clarke ◽  
Scott A Lear ◽  
Dawn C Mackey
Keyword(s):  
Older Adults ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Step Count ◽  
Retest Reliability ◽  
Activity Monitors ◽  
Limited Mobility ◽  
Step Counts ◽  
Test Retest Reliability ◽  
Mobility Status

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.

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