Journal for the measurement of physical behaviour最新文献_第7页

Missing Step Count Data? Step Away From the Expectation–Maximization Algorithm 缺少步数数据?远离期望最大化算法

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0002

Mia S. Tackney, D. Ståhl, Elizabeth A. Williamson, J. Carpenter

{"title":"Missing Step Count Data? Step Away From the Expectation–Maximization Algorithm","authors":"Mia S. Tackney, D. Ståhl, Elizabeth A. Williamson, J. Carpenter","doi":"10.1123/jmpb.2022-0002","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0002","url":null,"abstract":"In studies that compare physical activity between groups of individuals, it is common for physical activity to be quantified by step count, which is measured by accelerometers or other wearable devices. Missing step count data often arise in these settings and can lead to bias or imprecision in the estimated effect if handled inappropriately. Replacing each missing value in accelerometer data with a single value using the Expectation–Maximization (EM) algorithm has been advocated in the literature, but it can lead to underestimation of variances and could seriously compromise study conclusions. We compare the performance in terms of bias and variance of two missing data methods, the EM algorithm and Multiple Imputation (MI), through a simulation study where data are generated from a parametric model to reflect characteristics of a trial on physical activity. We also conduct a reanalysis of the 2019 MOVE-IT trial. The EM algorithm leads to an underestimate of the variance of effects of interest, in both the simulation study and the reanalysis of the MOVE-IT trial. MI should be the preferred approach to handling missing data in accelerometer, which provides valid point and variance estimates.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84885446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Evaluation of Two Thigh-Worn Accelerometer Brands in Laboratory and Free-Living Settings 两种穿戴式加速度计品牌在实验室和自由生活环境下的评估

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0012

A. Montoye, Olivia Coolman, Amberly Keyes, Megan Ready, Jaedyn Shelton, Ethan Willett, Brian C. Rider

{"title":"Evaluation of Two Thigh-Worn Accelerometer Brands in Laboratory and Free-Living Settings","authors":"A. Montoye, Olivia Coolman, Amberly Keyes, Megan Ready, Jaedyn Shelton, Ethan Willett, Brian C. Rider","doi":"10.1123/jmpb.2022-0012","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0012","url":null,"abstract":"Background: Given the popularity of thigh-worn accelerometers, it is important to understand their reliability and validity. Purpose: Our study evaluated laboratory validity and free-living intermonitor reliability of the Fibion monitor and free-living intermonitor reliability of the activPAL monitor. Free-living comparability of the Fibion and activPAL monitors was also assessed. Methods: Nineteen adult participants wore Fibion monitors on both thighs while performing 11 activities in a laboratory setting. Then, participants wore Fibion and activPAL monitors on both thighs for 3 days during waking hours. Accuracy of the Fibion monitor was determined for recognizing lying/sitting, standing, slow walking, fast walking, jogging, and cycling. For the 3-day free-living wear, outputs from the Fibion monitors were compared, with similar analyses conducted for the activPAL monitors. Finally, free-living comparability of the Fibion and activPAL monitors was determined for nonwear, sitting, standing, stepping, and cycling. Results: The Fibion monitor had an overall accuracy of 85%–89%, with high accuracy (94%–100%) for detecting prone and supine lying, sitting, and standing but some misclassification among ambulatory activities and for left-/right-side lying with standing. Intermonitor reliability was similar for the Fibion and activPAL monitors, with best reliability for sitting but poorer reliability for activities performed least often (e.g., cycling). The Fibion and activPAL monitors were not equivalent for most tested metrics. Conclusion: The Fibion monitor appears suitable for assessment of sedentary and nonsedentary waking postures, and the Fibion and activPAL monitors have comparable intermonitor reliability. However, studies using thigh-worn monitors should use the same monitor brand worn on the same leg to optimize reliability.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"217 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74950925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Integrity and Performance of Four Tape Solutions for Mounting Accelerometry Devices: Lolland-Falster Health Study 四种磁带解决方案的完整性和性能安装加速度计设备:Lolland-Falster健康研究

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0024

Therese Lockenwitz Petersen, J. Brønd, E. Benfeldt, R. Jepsen

{"title":"Integrity and Performance of Four Tape Solutions for Mounting Accelerometry Devices: Lolland-Falster Health Study","authors":"Therese Lockenwitz Petersen, J. Brønd, E. Benfeldt, R. Jepsen","doi":"10.1123/jmpb.2022-0024","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0024","url":null,"abstract":"Background: Tape-mounted Axivity AX3 accelerometers are increasingly being used to monitor physical activity of individuals, but studies on the integrity and performance of diffe1rent attachment protocols are missing. Purpose: The purpose of this paper was to evaluate four attachment protocols with respect to skin reactions, adhesion, and wear time in children and adults using tape-mounted Axivity AX3 accelerometers and to evaluate the associated ease of handling. Methods: We used data from the Danish household-based population study, the Lolland-Falster Health Study. Participants were instructed to wear accelerometers for seven consecutive days and to complete a questionnaire on skin reactions and issues relating to adhesion. A one-way analysis of variance was used to examine differences in skin reactions and adhesion between the protocols. A Tukey post hoc test compared group means. Ease of handling was assessed throughout the data collection. Results: In total, 5,389 individuals were included (1,289 children and 4,100 adults). For both children and adults, skin reactions were most frequent in Protocols 1 and 2. Adhesion problems were most frequent in Protocol 3. Wear time was longest in Protocol 4. Skin reactions and adhesion problems were more frequent in children compared to adults. Adults achieved longest wear time. Discussion: Covering the skin completely with adhesive tape seemed to cause skin reactions. Too short pieces of fixation tape caused accelerometers to fall off. Protocols necessitating removal of remains of glue on the accelerometers required a lot of work. Conclusion: The last of the four protocols was superior in respect to skin reactions, adhesion, wear time, and ease of handling.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79107354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Validity of a Novel Algorithm to Detect Bedtime, Wake Time, and Sleep Time in Adults 一种检测成人就寝时间、起床时间和睡眠时间的新算法的有效性

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0027

Kyle R. Leister, J. Garay, T. Barreira

{"title":"Validity of a Novel Algorithm to Detect Bedtime, Wake Time, and Sleep Time in Adults","authors":"Kyle R. Leister, J. Garay, T. Barreira","doi":"10.1123/jmpb.2021-0027","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0027","url":null,"abstract":"Purpose: To determine accuracy of activPAL Technologies’ CREA algorithm to assess bedtime, wake time, and sleep time. Methods: As part of a larger study, 104 participants recorded nightly sleep logs (LOGs) and wore the activPAL accelerometer at the thigh and ActiGraph accelerometer at the hip for 24 hr/day, for seven consecutive days. For sleep LOGs, participants recorded nightly bed and daily wake times. Previously validated ActiGraph, proprietary activPAL, and the Winkler sleep algorithm were used to compute sleep variables. Eighty-seven participants provided 2+ days of valid data. Pearson correlations, paired samples t tests, and equivalency tests were used to examine relationships and differences between methods (activPAL vs. ActiGraph, activPAL vs. LOG, and activPAL vs. Winkler algorithm). Results: For screened data, moderately high to high correlations but significant mean differences were found between activPAL versus ActiGraph for bedtime (t86 = −6.80, p ≤ .01, r = .84), wake time (t86 = 4.80, p ≤ .01, r = .93), and sleep time (t86 = 7.99, p ≤ .01, r = .88). activPAL versus LOG comparisons also yielded significant mean differences and moderately high to high correlations for bedtime (t86 = −4.68, p ≤ .01, r = .82), wake time (t86 = 8.14, p ≤ .01, r = .93), and sleep time (t86 = 8.60, p ≤ .01, r = .72). Equivalency testing revealed that equivalency could not be claimed between activPAL versus LOG or activPAL versus ActiGraph comparisons, though the activPAL and Winkler algorithm were equivalent. Conclusion: The activPAL algorithm overestimated sleep time by detecting earlier bedtimes and later wake times. Because of the significant differences between algorithms, bedtime, wake time, and sleep time are not interchangeable between methods.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"87 2 Suppl 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88693515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Estimating Running Speed From Wrist- or Waist-Worn Wearable Accelerometer Data: A Machine Learning Approach 从手腕或腰部佩戴的可穿戴加速度计数据估计跑步速度:一种机器学习方法

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0011

John J. Davis, Blaise E. Oeding, A. Gruber

{"title":"Estimating Running Speed From Wrist- or Waist-Worn Wearable Accelerometer Data: A Machine Learning Approach","authors":"John J. Davis, Blaise E. Oeding, A. Gruber","doi":"10.1123/jmpb.2022-0011","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0011","url":null,"abstract":"Background: Running is a popular form of exercise, and its physiological effects are strongly modulated by speed. Accelerometry-based activity monitors are commonly used to measure physical activity in research, but no method exists to estimate running speed from only accelerometer data. Methods: Using three cohorts totaling 72 subjects performing treadmill and outdoor running, we developed linear, ridge, and gradient-boosted tree regression models to estimate running speed from raw accelerometer data from waist- or wrist-worn devices. To assess model performance in a real-world scenario, we deployed the best-performing model to data from 16 additional runners completing a 13-week training program while equipped with waist-worn accelerometers and commercially available foot pods. Results: Linear, ridge, and boosted tree models estimated speed with 12.0%, 11.6%, and 11.2% mean absolute percentage error, respectively, using waist-worn accelerometer data. Errors were greater using wrist-worn data, with linear, ridge, and boosted tree models achieving 13.8%, 14.0%, and 12.8% error. Across 663 free-living runs, speed was significantly associated with run duration (p = .009) and perceived run intensity (p = .008). Speed was nonsignificantly associated with fatigue (p = .07). Estimated speeds differed from foot pod measurements by 7.25%; associations and statistical significance were similar when speed was assessed via accelerometry versus via foot pod. Conclusion: Raw accelerometry data can be used to estimate running speed in free-living data with sufficient accuracy to detect associations with important measures of health and performance. Our approach is most useful in studies where research grade accelerometry is preferable to traditional global positioning system or foot pod-based measurements, such as in large-scale observational studies on physical activity.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84115352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Considerations for the Use of Consumer-Grade Wearables and Smartphones in Population Surveillance of Physical Activity 消费级可穿戴设备和智能手机用于人口体育活动监测的考虑

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0046

T. Strain, K. Wijndaele, M. Pearce, S. Brage

{"title":"Considerations for the Use of Consumer-Grade Wearables and Smartphones in Population Surveillance of Physical Activity","authors":"T. Strain, K. Wijndaele, M. Pearce, S. Brage","doi":"10.1123/jmpb.2021-0046","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0046","url":null,"abstract":"As smartphone and wearable device ownership increase, interest in their utility to monitor physical activity has risen concurrently. Numerous examples of the application of wearables in clinical and epidemiological research settings already exist. However, whether these devices are all suitable for physical activity surveillance is open for debate. In this article, we discuss four key issues specifically relevant to surveillance that we believe need to be tackled before consumer wearables can be considered for this measurement purpose: representative sampling, representative wear time, validity and reliability, and compatibility between devices. A recurring theme is how to deal with systematic biases by demographic groups. We suggest some potential solutions to the issues of concern such as providing individuals with standardized devices, considering summary metrics of physical activity less prone to wear time biases, and the development of a framework to harmonize estimates between device types and their inbuilt algorithms. We encourage collaborative efforts from researchers and consumer wearable manufacturers in this area. In the meantime, we caution against the use of consumer wearable device data for inference of population-level activity without the consideration of these issues.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84347329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Depressive Symptoms Are Associated With Accelerometer-Measured Physical Activity and Time in Bed Among Working-Aged Men and Women 在工作年龄的男性和女性中，抑郁症状与加速度计测量的身体活动和卧床时间有关

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0058

P. Husu, K. Tokola, H. Vähä-Ypyä, H. Sievänen, T. Vasankari

{"title":"Depressive Symptoms Are Associated With Accelerometer-Measured Physical Activity and Time in Bed Among Working-Aged Men and Women","authors":"P. Husu, K. Tokola, H. Vähä-Ypyä, H. Sievänen, T. Vasankari","doi":"10.1123/jmpb.2021-0058","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0058","url":null,"abstract":"Background: Depression is a significant health problem, whereas higher physical activity (PA) associates with fewer depressive symptoms. We examined how self-reported depressive symptoms are associated with accelerometer-measured PA, standing, sedentary behavior, and time in bed (TIB) among 20- to 69-year-old men and women. Methods: The study is a part of the cross-sectional, population-based FinFit2017 study, in which depressive symptoms were assessed by modified nine-item Finnish version of the Patient Health Questionnaire, and physical behavior in terms of PA, sedentary behavior, standing, and TIB was assessed 24/7 by a triaxial accelerometer. During waking hours, the accelerometer was hip worn. Intensity of PA was analyzed by mean amplitude deviation and body posture by angle for posture estimation algorithms. During TIB, the device was wrist worn, and the analysis was based on the wrist movements. A total of 1,823 participants answered the nine-item Finnish version of the Patient Health Questionnaire and used the accelerometer 24 hr at least 4 days per week. Results: Men without depressive symptoms had on average more standing, light, and moderate to vigorous PA and steps, and less low and high movement TIB than the men with at least moderate symptoms, when age group, education, work status, marital status, and fitness were adjusted for. The asymptomatic women had more moderate to vigorous PA and steps and less high movement TIB than the women with at least moderate symptoms. Conclusions: Depressive symptoms were associated with lower levels of PA and longer TIB. It is important to identify these symptoms as early as possible to be able to initiate and target preventive actions, including PA promotion, to these symptomatic persons on time.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88926022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

ActiGraph Cutpoints Impact Physical Activity and Sedentary Behavior Outcomes in Young Children 活动图截断点影响幼儿身体活动和久坐行为的结果

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2021-0042

Becky Breau, Hannah J. Coyle-Asbil, J. Haines, David W. L. Ma, L. Vallis, _

{"title":"ActiGraph Cutpoints Impact Physical Activity and Sedentary Behavior Outcomes in Young Children","authors":"Becky Breau, Hannah J. Coyle-Asbil, J. Haines, David W. L. Ma, L. Vallis, _","doi":"10.1123/jmpb.2021-0042","DOIUrl":"https://doi.org/10.1123/jmpb.2021-0042","url":null,"abstract":"Purpose: Examine the effect of cutpoint selection on physical activity (PA) metrics calculated from young children’s accelerometer data and on the proportion of children meeting PA guidelines. Methods: A total of 262 children (3.6 ± 1.4 years, 126 males) wore ActiGraph wGT3X-BT accelerometers on their right hip for 7 days, 24 hr/day. Ten cutpoint sets were applied to the sample categorized by age, based on populations of the original cutpoint calibration studies using ActiLife software. Resulting sedentary behavior, light PA, moderate to vigorous PA, and total PA were compared using repeated-measures analysis of variance. Proportion of children meeting age-appropriate PA guidelines based on each cutpoint set was assessed using Cochran’s q tests. Results: Children wore the accelerometer for an average of 7.6 ± 1.2 days for an average of 11.9 ± 1.2 hr/day. Significant differences in time spent in each intensity were found across all cutpoints except for sedentary, and total PA for three comparisons (Trost vs. Butte Vertical Axis [VA], Pate vs. Puyau, and Costa VA vs. Evenson) and moderate to vigorous PA for four comparisons (Trost vs. Pate, Trost vs. Pate and Pfeiffer, Pate vs. Pate and Pfeiffer, and van Cauwenberghe vs. Evenson). When examined within age-appropriate groups, all sets of cutpoints resulted in significant differences across all intensities and in the number of children meeting PA guidelines. Conclusion: Choice of cutpoints applied to data from young children significantly affects times calculated for different movement intensities, which in turn impacts the proportion of children meeting guidelines. Thus, comparisons of movement intensities should not be made across studies using different sets of cutpoints.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81454368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Physical Behaviour Partnership From Heaven: The Prospective Physical Activity, Sitting, and Sleep Consortium and the International Society for the Measurement of Physical Behaviour 来自天堂的身体行为伙伴关系:前瞻性身体活动、坐着和睡眠联盟和国际身体行为测量协会

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0027

E. Stamatakis, B. Clark, Matthew N. Ahmadi, J. M. Blodgett, M. Granat, A. Donnelly, A. Atkin, Li-Tang Tsai, G. Mielke, Richard Pulsford, Nidhi Gupta, Patrick Crawley, Matthew Stevens, Peter J. Johansson, L. Brocklebank, L. Sherar, V. Rangul, A. Holtermann, M. Hamer, A. Koster

引用次数: 1

Tracking of Walking and Running for Exercise: Alignment Between Ecological Momentary Assessment and Accelerometer-Based Estimates 步行和跑步运动的跟踪:生态瞬时评估和基于加速度计的估计之间的一致性

Journal for the measurement of physical behaviour Pub Date : 2022-01-01 DOI: 10.1123/jmpb.2022-0016

K. Strohacker, Lindsay P Toth, Lucas F. Sheridan, S. Crouter

{"title":"Tracking of Walking and Running for Exercise: Alignment Between Ecological Momentary Assessment and Accelerometer-Based Estimates","authors":"K. Strohacker, Lindsay P Toth, Lucas F. Sheridan, S. Crouter","doi":"10.1123/jmpb.2022-0016","DOIUrl":"https://doi.org/10.1123/jmpb.2022-0016","url":null,"abstract":"Ecological momentary assessment (EMA) and accelerometer-based devices can be used concurrently to better understand dimensions of physical activity. This study presents procedures for analyzing data derived from both methods to examine exercise-related walking and running, as well as determine evidence for alignment between these methods. The participants (N = 29) wore an ActiGraph GT3X+ and completed four EMA surveys/day across 2 weeks to report exercise (mode and duration). GT3X+ counts per 10 s were processed using the Crouter two-regression model to identify periods of walking/running (coefficient of variation in activity counts ≤10% and >0%). Two reviewers visually inspected Crouter two-regression model data and recorded durations of walking/running in time blocks corresponding to EMA reports of exercise. The data were classified as “aligned” if the duration of walking/running between methods were within 20% of one another. Frequency analyses determined the proportion of aligned versus nonaligned exercise durations. Reviewer reliability was examined by calculating interobserver agreement (classification of aligned vs. nonaligned) and intraclass correlation coefficients (ICC; duration based on coefficient of variation). Of the 139 self-reported bouts of walking and running exercise, 25% were classified as aligned with the Crouter two-regression model coefficient of variation. Initial interobserver agreement was 91, and ICCs across data classified as aligned (ICC = .992) and nonaligned (ICC = .960) were excellent. These novel procedures offer a means of isolating exercise-related physical activity for further analysis. Due to the inability to align evidence in most cases, we discuss key considerations for optimizing EMA survey questions, choice in accelerometer-based device, and future directions for visual analysis procedures.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90861401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1