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Browsing by Author "McAvoy, Cayla R."

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    Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study
    (BMC, 2021) McAvoy, Cayla R.; Moore, Christopher C.; Aguiar, Elroy J.; Ducharme, Scott W.; Schuna, John M., Jr.; Barreira, Tiago V.; Chase, Colleen J.; Gould, Zachary R.; Amalbert-Birriel, Marcos A.; Chipkin, Stuart R.; Staudenmayer, John; Tudor-Locke, Catrine; Mora-Gonzalez, Jose; University of North Carolina; University of North Carolina Charlotte; University of North Carolina Chapel Hill; University of Alabama Tuscaloosa; California State University Long Beach; Oregon State University; Syracuse University; University of Massachusetts Amherst
    Background: Heuristic cadence (steps/min) thresholds of >= 100 and >= 130 steps/min correspond with absolutely-defined moderate (3 metabolic equivalents [METs]; 1 MET = 3.5 mL O-2 center dot kg(- 1)center dot min(- 1)) and vigorous (6 METs) intensity, respectively. Scarce evidence informs cadence thresholds for relatively-defined moderate (>= 64% heart rate maximum [HRmax = 220-age], >= 40%HR reserve [HRR = HRmax -HRresting, and >= 12 Rating of Perceived Exertion [RPE]); or vigorous intensity (>= 77%HRmax, >= 60%HRR, and >= 14 RPE). Purpose: To identify heuristic cadence thresholds corresponding with relatively-defined moderate and vigorous intensity in 21-60-year-olds. Methods: In this cross-sectional study, 157 adults (40.4 +/- 11.5 years; 50.6% men) completed up to twelve 5-min treadmill bouts, beginning at 0.5 mph and increasing by 0.5 mph. Steps were directly observed, HR was measured with chest-worn monitors, and RPE was queried in the final minute of each bout. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds, stratified by age (21-30, 31-40, 41-50, and 51-60 years). Reconciliation of the two analytical models, including trade-offs between sensitivity, specificity, positive and negative predictive values, and overall accuracy, yielded final heuristic cadences. Results: Across all moderate intensity indicators, the segmented regression models estimated optimal cadence thresholds ranging from 123.8-127.5 (ages 21-30), 121.3-126.0 (ages 31-40), 117.7-122.7 (ages 41-50), and 113.3-116.1 steps/min (ages 51-60). Corresponding values for vigorous intensity were 140.3-144.1, 140.2-142.6, 139.3-143.6, and 131.6-132.8 steps/min, respectively. ROC analysis estimated chronologically-arranged age groups' cadence thresholds ranging from 114.5-118, 113.5-114.5, 104.6-112.9, and 103.6-106.0 across all moderate intensity indicators, and 127.5, 121.5, 117.2-123.2, and 113.0 steps/min, respectively, for vigorous intensity. Conclusions: Heuristic cadence thresholds corresponding to relatively-defined moderate intensity for the chronologically-arranged age groups were >= 120, 120, 115, and 105 steps/min, regardless of the intensity indicator (i.e., % HRmax, %HRR, or RPE). Corresponding heuristic values for vigorous intensity indicators were >= 135, 130, 125, and 120 steps/min. These cadences are useful for predicting/programming intensity aligned with age-associated differences in physiological response to, and perceived experiences of, moderate and/or vigorous intensity.
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    Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study (vol 18, 27, 2021)
    (BMC, 2022) McAvoy, Cayla R.; Moore, Christopher C.; Aguiar, Elroy J.; Ducharme, Scott W.; Schuna, John M., Jr.; Barreira, Tiago V.; Chase, Colleen J.; Gould, Zachary R.; Amalbert-Birriel, Marcos A.; Chipkin, Stuart R.; Staudenmayer, John; Tudor-Locke, Catrine; Mora-Gonzalez, Jose; University of North Carolina; University of North Carolina Charlotte; University of North Carolina Chapel Hill; University of Alabama Tuscaloosa; California State University Long Beach; Oregon State University; Syracuse University; University of Massachusetts Amherst
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    A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
    (BMC, 2022) Mora-Gonzalez, Jose; Gould, Zachary R.; Moore, Christopher C.; Aguiar, Elroy J.; Ducharme, Scott W.; Schuna, John M., Jr.; Barreira, Tiago, V; Staudenmayer, John; McAvoy, Cayla R.; Boikova, Mariya; Miller, Taavy A.; Tudor-Locke, Catrine; University of Granada; University of North Carolina; University of North Carolina Charlotte; University of Massachusetts Amherst; University of North Carolina Chapel Hill; University of Alabama Tuscaloosa; California State University Long Beach; Oregon State University; Syracuse University
    Background Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. Purpose To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). Methods Two hundred fifty-eight adults (52.5 +/- 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). Results Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p <= 0.045). Conclusions Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.