Journal for the measurement of physical behaviour最新文献_第4页

Using Video Cameras as a Research Tool in Public Spaces: Addressing Ethical and Information Governance Challenges Under Data Protection Legislation 在公共场所使用摄像机作为研究工具:应对数据保护立法下的道德和信息治理挑战

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2022-0037

J. Benton, James Evans, M. Mourby, Mark J. Elliot, Jamie Anderson, J. Hipp, D. French

Systematic observation is a promising unobtrusive method of assessing human behavior in urban environments without many issues typically associated with self-report measures (e.g., recall bias, low response rates). Improvements in video camera technologies make it more feasible for researchers to conduct systematic observation, which could reduce the time, labor, and cost to facilitate high-quality observational research in urban environments at scale. However, there are important ethical and information governance challenges driven by data protection laws, which discourage many researchers from using camera-based observation methods. The European Union General Data Protection Regulation is a leading global standard for data protection. Drawing on our experiences of conducting three studies using video cameras in public spaces, we discuss how to conduct this kind of research in line with General Data Protection Regulation requirements. The paper outlines issues concerning data protection, privacy, informed consent, and confidentiality, and how we addressed them. In doing this, the paper provides support for responsible use of camera-based observation methods, which will be of value to researchers, ethics committees, and funders. Outlining how to use video cameras responsibly will enable more research to be conducted that, in turn, will build the case for its benefits to researchers and society.

系统观察是评估城市环境中人类行为的一种很有前途的不引人注目的方法，没有许多通常与自我报告方法相关的问题(例如，回忆偏差，低反应率)。视频摄像技术的进步使研究人员更有可能进行系统的观测，这可以减少时间、人力和成本，促进在城市环境中进行高质量的大规模观测研究。然而，数据保护法带来了重要的伦理和信息治理挑战，这阻碍了许多研究人员使用基于相机的观察方法。欧盟通用数据保护条例是数据保护的全球领先标准。根据我们在公共场所使用摄像机进行三项研究的经验，我们讨论了如何根据《通用数据保护条例》的要求进行此类研究。本文概述了有关数据保护、隐私、知情同意和保密的问题，以及我们如何解决这些问题。在此过程中，本文为负责任地使用基于相机的观察方法提供了支持，这将对研究人员、伦理委员会和资助者有价值。概述如何负责任地使用摄像机将使更多的研究得以进行，反过来，将为研究人员和社会的利益建立案例。

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引用次数: 0

Impact of Continuous Focal Sampling Time Thresholds on Physical Activity Metrics When Using Video-Recorded Direct Observation 使用录像直接观察时，连续焦点采样时间阈值对身体活动指标的影响

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2023-0004

Julian Martinez, J. Staudenmayer, S. Strath

Purpose: To determine differences in physical activity metrics between 1-, 5-, and 10-s direct observation (DO) time thresholds and compare annotation completion time between different time thresholds. Methods: Participants (n = 10, mean age 40.7 ± 22.3 years, five males) were video recorded for 2 hr within a free-living setting. DO videos were annotated by one experienced annotator with a priori developed Posture and Behavior schemas. The annotation order of video, time threshold, and schema used was randomized. For analysis, annotations were collapsed into posture and behavior domains. Total video time is reported. Time to code videos, overall percent agreement, and statistical bias of each posture and behavior domain for the 5-s time threshold and 10-s time threshold were compared to 1-s time threshold output. Results: 19.7 hr of DO were recorded. On average, the 1-s time threshold took 183.9 ± 34.2 min to annotate with the Posture schema and 118.8 ± 23.6 min with the Behavior schema. Under the Posture schema, the 5-s time threshold was 31.7% faster, had 91.5% agreement, and all biases were <±5 min, while the 10-s time threshold was 43.6% faster, had 89.2% agreement, and had biases ranging from −7.59 to 5.21 min. Under the Behavior schema, the 5-s time threshold was 16.0% faster, had 92.0% agreement, and had all biases <±2.1 min, while the 10-s time threshold was 27.6% faster, had 88.3% agreement, and had all biases <±3.9 min. Conclusion: Longer DO annotation time thresholds are accurate and faster but less precise for certain posture and behavior domains when compared to criterion 1-s time threshold in healthy adults.

目的:确定1秒、5秒和10秒直接观察(DO)时间阈值之间的身体活动指标差异，并比较不同时间阈值之间的注释完成时间。方法:参与者(n = 10，平均年龄40.7±22.3岁，5名男性)在自由生活环境中进行2小时的视频记录。由一名经验丰富的注释员用先验开发的姿势和行为图式对DO视频进行注释。视频标注顺序、时间阈值、模式使用随机化。为了便于分析，注释被分解为姿态和行为域。报告总视频时间。将5秒时间阈值和10秒时间阈值的每个姿势和行为域的编码时间、总体一致性和统计偏差与1秒时间阈值输出进行比较。结果:记录19.7 hr DO。姿势图式的1-s时间阈值平均为183.9±34.2 min，行为图式的1-s时间阈值为118.8±23.6 min。姿势模式下，5-s时间阈值快了31.7%，一致性91.5%，偏差均<±5 min; 10-s时间阈值快了43.6%，一致性89.2%，偏差范围为−7.59 ~ 5.21 min。行为模式下，5-s时间阈值快了16.0%，一致性92.0%，偏差均<±2.1 min; 10-s时间阈值快了27.6%，一致性88.3%，偏差均<±3.9 min。与健康成人标准1-s时间阈值相比，较长的DO注释时间阈值准确且更快，但在某些姿势和行为领域精度较低。

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引用次数: 0

Evaluation of Within- and Between-Site Agreement for Direct Observation of Physical Behavior Across Four Research Groups 对四个研究小组直接观察物理行为的场内和场内协议的评估

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2022-0048

S. Keadle, Julian Martinez, S. Strath, J. Sirard, D. John, S. Intille, Diego Arguello, Marcos Amalbert-Birriel, Rachel Barnett, B. Thapa-Chhetry, Melanna Cox, John Chase, Erin E. Dooley, Robert Marcotte, Alex Tolas, John W. Staudemayer

Direct observation (DO) is a widely accepted ground-truth measure, but the field lacks standard operational definitions. Research groups develop project-specific annotation platforms, limiting the utility of DO if labels are not consistent. Purpose: The purpose was to evaluate within- and between-site agreement for DO taxonomies (e.g., activity intensity category) across four independent research groups who have used video-recorded DO. Methods: Each site contributed video files (508 min) and had two trained research assistants annotate the shared video files according to their existing annotation protocols. The authors calculated (a) within-site agreement for the two coders at the same site expressed as intraclass correlation and (b) between-site agreement, the proportion of seconds that agree between any two coders regardless of site. Results: Within-site agreement at all sites was good–excellent for both activity intensity categories (intraclass correlation range: .82–.9) and posture/whole-body movement (intraclass correlation range: .77–.98). Between-site agreement for intensity categories was 94.6% for sedentary, 80.9% for light, and 82.8% for moderate–vigorous. Three of the four sites had common labels for eight posture/whole-body movements and had within-site agreements of 94.5% and between-site agreements of 86.1%. Conclusions: Distinct research groups can annotate key features of physical behavior with good-to-excellent interrater reliability. Operational definitions are provided for core metrics for researchers to consider in future studies to facilitate between-study comparisons and data pooling, enabling the deployment of deep learning approaches to wearable device algorithm calibration.

直接观测(DO)是一种被广泛接受的实地真值测量方法，但该领域缺乏标准的操作定义。研究小组开发特定于项目的注释平台，如果标签不一致，则限制了DO的效用。目的:目的是评估四个使用视频记录DO的独立研究小组对DO分类(例如，活动强度类别)的站点内和站点之间的一致性。方法:每个站点提供视频文件(508分钟)，并由两名经过培训的研究助理根据其现有的注释协议对共享的视频文件进行注释。作者计算了(a)两个编码员在同一站点的站点内一致性，表示为类内相关性;(b)站点间一致性，任何两个编码员在任何站点之间一致的秒数比例。结果:所有位点在活动强度类别(类内相关范围:0.82 - 0.9)和姿势/全身运动(类内相关范围:0.77 - 0.98)上的一致性均为良好-极好。在强度类别上，久坐组的一致性为94.6%，轻度组为80.9%，中度剧烈组为82.8%。4个站点中的3个站点具有8种姿势/全身运动的共同标签，站点内一致性为94.5%，站点间一致性为86.1%。结论:不同的研究小组能够以良好到优异的可信度注释身体行为的关键特征。提供了核心指标的操作定义，供研究人员在未来的研究中考虑，以促进研究之间的比较和数据池，从而能够将深度学习方法部署到可穿戴设备算法校准中。

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引用次数: 0

Validation of Smartphones and Different Low-Cost Activity Trackers for Step Counting Under Free-Living Conditions 验证智能手机和不同的低成本活动跟踪器在自由生活条件下的步数

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2022-0022

C. Goh, Nan Xin Wang, A. Müller, Rowena Yap, S. Edney, F. Müller-Riemenschneider

Background: Smartphones and wrist-worn activity trackers are increasingly popular for step counting purposes and physical activity promotion. Although trackers from popular brands have frequently been validated, the accuracy of low-cost devices under free-living conditions has not been adequately determined. Objective: To investigate the criterion validity of smartphones and low-cost wrist-worn activity trackers under free-living conditions. Methods: Participants wore a waist-worn Yamax pedometer and seven different low-cost wrist-worn activity trackers continuously over 3 days, and an activity log was completed at the end of each day. At the end of the study, the number of step counts reflected on the participants’ smartphone for each of the 3 days was also recorded. To establish criterion validity, step counts from smartphones and activity trackers were compared with the pedometers using Pearson’s correlation coefficient, mean absolute percentage error, and intraclass correlation coefficient. Results: Five of the seven activity trackers underestimated step counts and the remaining two and the smartphones overestimated step counts. Criterion validity was consistently higher for the activity trackers (r = .78–.92; mean absolute percentage error 14.5%–36.1%; intraclass correlation coefficient: .51–.91) than the smartphone (r = .37; mean absolute percentage error 55.7%; intraclass correlation coefficient: .36). Stratified analysis showed better validity of smartphones among female than for male participants. Phone wearing location also affected accuracy. Conclusions: Low-cost trackers demonstrated high accuracy in recording step counts and can be considered with confidence for research purposes or large-scale health promotion programs. The accuracy of using a smartphone for measuring step counts was substantially lower. Factors such as phone wear location and gender should also be considered when using smartphones to track step counts.

背景:智能手机和手腕上佩戴的活动追踪器越来越受欢迎，用于计算步数和促进体育活动。尽管流行品牌的追踪器经常得到验证，但低成本设备在自由生活条件下的准确性尚未得到充分确定。目的:探讨自由生活条件下智能手机与低成本腕带运动追踪器的效度。方法:参与者连续3天佩戴腰戴式Yamax计步器和7种不同的低成本腕戴式活动追踪器，并在每天结束时完成活动日志。在研究结束时，研究人员还记录了三天内参与者智能手机上显示的步数。为了建立标准效度，使用Pearson相关系数、平均绝对百分比误差和类内相关系数将智能手机和活动追踪器的步数与计步器进行比较。结果:七个运动追踪器中有五个低估了步数，其余两个和智能手机高估了步数。运动追踪者的标准效度持续较高(r = 0.78 - 0.92;平均绝对百分比误差14.5% ~ 36.1%;类内相关系数:0.51 - 0.91)高于智能手机(r = 0.37;平均绝对百分比误差55.7%;类内相关系数:0.36)。分层分析显示，智能手机在女性参与者中的有效性高于男性参与者。手机佩戴位置也会影响准确性。结论:低成本追踪器在记录步数方面具有较高的准确性，可以放心地考虑用于研究目的或大规模健康促进计划。使用智能手机测量步数的准确性要低得多。在使用智能手机跟踪步数时，还应考虑手机佩戴位置和性别等因素。

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引用次数: 0

Comparison of Six Accelerometer Metrics for Assessing the Temporal Patterns of Children’s Free-Play Physical Activity 六种加速计指标评估儿童自由游戏身体活动时间模式的比较

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2023-0007

Katherine L. McKee, K. Pfeiffer, A. Pearson, Kimberly A. Clevenger

Accelerometers are frequently used to measure physical activity in children, but lack of uniformity in data processing methods, such as the metric used to summarize accelerometer data, limits comparability between studies. The objective was to compare six accelerometer metrics (raw: mean amplitude deviation, Euclidean norm minus one, activity index, monitor-independent movement summary units; count: vertical axis, vector magnitude) for characterizing the intensity and temporal patterns of first and second graders’ (n = 88; age = 7.8 ± 0.7 years) recess physical activity. At a 5-s epoch level, Pearson’s correlations (r) between metrics ranged from .66 to .98. When each epoch was classified into one of four intensity levels based on quartiles, agreement between metrics as indicated by weighted kappa ranged from .81 to .96. When collapsed to time spent in each intensity level, metrics were strongly correlated (r = .76–.99) and most often statistically equivalent for estimating time spent in Quartile 3 or 4. Children were ranked from least to most active, and agreement between metrics was strong (Spearman’s correlation ≥ .87). Temporal patterns were characterized using five fragmentation indices calculated using each of the six metrics, which were fair-to-strongly correlated (r = .53–.99), with the strongest associations for number of high-intensity activity bouts (r ≥ .89). Most fragmentation indices were not statistically equivalent between metrics. While metrics captured similar trends in activity intensity and temporal patterns, caution is warranted when making comparisons of point estimates derived from different metrics. However, all metrics were able to similarly capture higher intensity activity (i.e., Quartile 3 or 4), the most common outcome of interest in intervention studies.

加速度计经常用于测量儿童的身体活动，但数据处理方法缺乏一致性，例如用于总结加速度计数据的度量，限制了研究之间的可比性。目的是比较六种加速度计指标(原始:平均振幅偏差，欧几里得范数- 1，活动指数，独立于监视器的运动汇总单位;计数:纵轴，矢量大小)用于表征一年级和二年级学生的强度和时间模式(n = 88;年龄= 7.8±0.7岁)休息体力活动。在5秒的epoch水平上，指标之间的Pearson相关性(r)在0.66到0.98之间。当每个epoch根据四分位数划分为四个强度水平之一时，加权kappa表示的指标之间的一致性范围为0.81至0.96。当分解到每个强度水平上花费的时间时，指标是强相关的(r = 0.76 - 0.99)，并且在估计四分位数3或4中花费的时间时，通常在统计上是相等的。儿童从最不活跃到最活跃进行排名，指标之间的一致性很强(Spearman相关≥0.87)。使用六个指标中的每一个计算的五个碎片化指数来表征时间模式，它们是公平到强相关的(r = 0.53 - 0.99)，与高强度活动次数的关联最强(r≥0.89)。大多数碎片化指数在指标之间不具有统计上的等价性。虽然指标在活动强度和时间模式上捕获了类似的趋势，但在比较来自不同指标的点估计时，需要谨慎。然而，所有指标都同样能够捕获更高强度的活动(即四分位数3或4)，这是干预研究中最常见的结果。

{"title":"Comparison of Six Accelerometer Metrics for Assessing the Temporal Patterns of Children’s Free-Play Physical Activity","authors":"Katherine L. McKee, K. Pfeiffer, A. Pearson, Kimberly A. Clevenger","doi":"10.1123/jmpb.2023-0007","DOIUrl":"https://doi.org/10.1123/jmpb.2023-0007","url":null,"abstract":"Accelerometers are frequently used to measure physical activity in children, but lack of uniformity in data processing methods, such as the metric used to summarize accelerometer data, limits comparability between studies. The objective was to compare six accelerometer metrics (raw: mean amplitude deviation, Euclidean norm minus one, activity index, monitor-independent movement summary units; count: vertical axis, vector magnitude) for characterizing the intensity and temporal patterns of first and second graders’ (n = 88; age = 7.8 ± 0.7 years) recess physical activity. At a 5-s epoch level, Pearson’s correlations (r) between metrics ranged from .66 to .98. When each epoch was classified into one of four intensity levels based on quartiles, agreement between metrics as indicated by weighted kappa ranged from .81 to .96. When collapsed to time spent in each intensity level, metrics were strongly correlated (r = .76–.99) and most often statistically equivalent for estimating time spent in Quartile 3 or 4. Children were ranked from least to most active, and agreement between metrics was strong (Spearman’s correlation ≥ .87). Temporal patterns were characterized using five fragmentation indices calculated using each of the six metrics, which were fair-to-strongly correlated (r = .53–.99), with the strongest associations for number of high-intensity activity bouts (r ≥ .89). Most fragmentation indices were not statistically equivalent between metrics. While metrics captured similar trends in activity intensity and temporal patterns, caution is warranted when making comparisons of point estimates derived from different metrics. However, all metrics were able to similarly capture higher intensity activity (i.e., Quartile 3 or 4), the most common outcome of interest in intervention studies.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84770900","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

Determinants of Consent in the SHARE Accelerometer Study SHARE加速计研究中同意的决定因素

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2022-0046

Fabio Franzese, Francesca Schrank, Michael Bergmann

The eighth wave of the Survey of Health, Aging and Retirement in Europe comprises a subsample of respondents who were asked to participate in a measurement of physical activity using thigh-worn accelerometers. This paper describes the process for obtaining consent, identifies determinants of consent, and analyzes the aggregated results of the accelerometer measurements for bias due to sample selection. The overall consent rate in the Survey of Health, Aging and Retirement in Europe accelerometer study was 54%, with variations between countries ranging from 34% to 70%. Multivariate logistic regressions show that various factors are correlated with consent such as respondents’ age, self-reported moderate activity, computer literacy, willingness to answer questions, and the interviewers’ age. After introducing inverse probability weights, there appears to be only a small and insignificant influence of participant selection and consent.

欧洲健康、老龄化和退休调查的第八波调查包括一个调查对象的子样本，他们被要求使用穿戴在大腿上的加速度计来测量身体活动。本文描述了获得同意的过程，确定了同意的决定因素，并分析了由于样本选择而导致的加速度计测量的汇总结果的偏差。欧洲加速计研究健康、老龄化和退休调查的总体同意率为54%，各国之间的差异从34%到70%不等。多变量逻辑回归表明，各种因素与同意相关，如受访者的年龄、自我报告的适度活动、计算机素养、回答问题的意愿和采访者的年龄。引入逆概率权重后，参与者选择和同意的影响似乎很小且不显著。

引用次数: 0

Context Matters: The Importance of Physical Activity Domains for Public Health 背景问题:体育活动领域对公众健康的重要性

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2023-0030

Tyler D. Quinn, Bethany Barone Gibbs

Physical activity can be performed across several domains, including leisure, occupation, household, and transportation, but physical activity research, measurement, and surveillance have historically been focused on leisure-time physical activity. Emerging evidence suggests differential health effects across these domains. In particular, occupational physical activity may be associated with adverse health outcomes. We argue that to adequately consider and evaluate such impacts, physical activity researchers and public health practitioners engaging in measurement, surveillance, and guideline creation should measure and consider all relevant physical activity domains where possible. We describe why physical activity science is often limited to the leisure-time domain and provide a rationale for expanding research and public health efforts to include all physical activity domains.

体育活动可以在多个领域进行，包括休闲、职业、家庭和交通，但体育活动的研究、测量和监测历来都集中在休闲时间的体育活动上。新出现的证据表明，这些领域对健康的影响是不同的。特别是，职业体力活动可能与不利的健康结果有关。我们认为，为了充分考虑和评估这些影响，从事测量、监测和指南制定的体育活动研究人员和公共卫生从业人员应该尽可能测量和考虑所有相关的体育活动领域。我们描述了为什么体育活动科学通常局限于休闲时间领域，并为扩大研究和公共卫生努力以包括所有体育活动领域提供了理由。

引用次数: 0

Methods to Estimate Energy Expenditure, Physical Activity, and Sedentary Time in Pregnant Women: A Validation Study Using Doubly Labeled Water 估算孕妇能量消耗、身体活动和久坐时间的方法:一项使用双标签水的验证研究

Journal for the measurement of physical behaviour

Pub Date : 2023-01-01 DOI: 10.1123/jmpb.2022-0033

S. Alomairah, S. P. Knudsen, C. B. Roland, Ida-Marie Hergel, S. Molsted, Tine D. Clausen, E. Løkkegaard, J. Bendix, R. Maddison, M. Löf, J. E. Larsen, Gerrit van Hall, B. Stallknecht

Background: Activity trackers and the Pregnancy Physical Activity Questionnaire (PPAQ) measures physical activity (PA) and sedentary time (SED). However, none of these tools have been validated against a criterion method in pregnancy. We aimed to compare a consumer activity tracker and the Danish version of PPAQ (PPAQ-DK) and to validate them using the doubly labeled water technique (DLW) as criterion method. Methods: A total of 220 healthy pregnant women participated. Total energy expenditure (TEE), PA energy expenditure (PAEE), and PA level were determined at gestational Weeks 28–29 using DLW and a Garmin Vivosport (Garmin, Olathe, KS) activity tracker. In addition, PAEE, moderate-to-vigorous intensity PA, and SED were determined using the activity tracker and PPAQ-DK during all three trimesters. Results: TEE from the activity tracker and DLW correlated (r = .63; p < .001), but the activity tracker overestimated TEE (503 kcal/day). Also, the activity tracker overestimated PAEE (303 kcal/day) and PA level compared with DLW. Likewise, PPAQ-DK overestimated PAEE (1,513 kcal/day) compared with DLW. Compared to PPAQ-DK, the activity tracker reported lower values of PAEE and moderate-to-vigorous intensity PA and higher values of SED during all three trimesters. Conclusions: When compared to DLW, we found better agreement of PAEE estimates from the activity tracker than from PPAQ-DK. TEE from the tracker and DLW correlated moderately well, but this was not the case for PAEE or PA level. The activity tracker measured lower PA and higher SED than PPAQ-DK throughout pregnancy. The consumer activity tracker performed better than the questionnaire, but both significantly overestimated PA compared to DLW.

背景:活动追踪器和妊娠身体活动问卷(PPAQ)测量身体活动(PA)和久坐时间(SED)。然而，这些工具都没有在怀孕的标准方法上得到验证。我们的目的是比较消费者活动追踪器和丹麦版的PPAQ (PPAQ- dk)，并使用双标签水技术(DLW)作为标准方法来验证它们。方法:对220名健康孕妇进行调查。总能量消耗(TEE)、PA能量消耗(PAEE)和PA水平在妊娠28-29周使用DLW和Garmin Vivosport (Garmin, Olathe, KS)活动追踪器进行测定。此外，在所有三个月期间，使用活动追踪器和PPAQ-DK测定PAEE，中高强度PA和SED。结果:活动追踪器TEE与DLW相关(r = 0.63;p < .001)，但活动追踪器高估TEE (503 kcal/day)。此外，与DLW相比，活动追踪器高估了PAEE(303千卡/天)和PA水平。同样，与DLW相比，PPAQ-DK高估了PAEE(1,513千卡/天)。与PPAQ-DK相比，活动追踪器在所有三个月中报告了较低的PAEE和中高强度PA值和较高的SED值。结论:与DLW相比，我们发现来自活动跟踪器的PAEE估计比来自PPAQ-DK的更一致。跟踪者的TEE与DLW的相关性中等，但PAEE或PA水平的情况并非如此。与PPAQ-DK相比，活动追踪器在整个怀孕期间测量到较低的PA和较高的SED。消费者活动追踪器比问卷表现更好，但与DLW相比，两者都显着高估了PA。

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引用次数: 1

Impact of COVID-19 Pandemic on Physical Activity, Pain, Mood, and Sleep in Adults with Knee Osteoarthritis. COVID-19大流行对膝关节骨性关节炎成人身体活动、疼痛、情绪和睡眠的影响

Journal for the measurement of physical behaviour

Pub Date : 2022-12-01 DOI: 10.1123/jmpb.2022-0019

Michael J Rose, Michael P LaValley, S Reza Jafarzadeh, Kerry E Costello, Nirali Shah, Soyoung Lee, Belinda Borrelli, Stephen P Messier, Tuhina Neogi, Deepak Kumar

Objective: To examine changes in physical activity, sleep, pain and mood in people with knee osteoarthritis (OA) during the ongoing COVID-19 pandemic by leveraging an ongoing randomized clinical trial (RCT).

Methods: Participants enrolled in a 12-month parallel two-arm RCT (NCT03064139) interrupted by the COVID-19 pandemic wore an activity monitor (Fitbit Charge 3) and filled out custom weekly surveys rating knee pain, mood, and sleep as part of the study. Data from 30 weeks of the parent study were used for this analysis. Daily step count and sleep duration were extracted from activity monitor data, and participants self-reported knee pain, positive mood, and negative mood via surveys. Metrics were averaged within each participant and then across all participants for pre-pandemic, stay-at-home, and reopening periods, reflecting the phased re-opening in the state of Massachusetts.

Results: Data from 28 participants showed small changes with inconclusive clinical significance during the stay-at-home and reopening periods compared to pre-pandemic for all outcomes. Summary statistics suggested substantial variability across participants with some participants showing persistent declines in physical activity during the observation period.

Conclusion: Effects of the COVID-19 pandemic on physical activity, sleep, pain, and mood were variable across individuals with OA. Specific reasons for this variability could not be determined. Identifying factors that could affect individuals with knee OA who may exhibit reduced physical activity and/or worse symptoms during major lifestyle changes (such as the ongoing pandemic) is important for providing targeted healthcare services and management advice towards those that could benefit from it the most.

目的:通过一项正在进行的随机临床试验(RCT)，研究正在进行的COVID-19大流行期间膝关节骨关节炎(OA)患者的身体活动、睡眠、疼痛和情绪的变化。方法:参加一项被COVID-19大流行中断的为期12个月的平行双臂随机对照试验(NCT03064139)的参与者佩戴活动监测器(Fitbit Charge 3)，并填写定制的每周调查，评估膝关节疼痛、情绪和睡眠，作为研究的一部分。本研究使用了30周的父母研究数据。每日步数和睡眠时间从活动监测数据中提取，参与者通过调查自我报告膝盖疼痛、积极情绪和消极情绪。对每个参与者的指标进行平均，然后对所有参与者在大流行前、呆在家里和重新开放期间的指标进行平均，反映了马萨诸塞州分阶段重新开放的情况。结果:来自28名参与者的数据显示，与大流行前相比，在居家和重新开放期间，所有结果都发生了微小变化，但没有确定的临床意义。总结统计数据表明，在观察期间，一些参与者的身体活动持续下降，参与者之间存在很大差异。结论:COVID-19大流行对OA患者身体活动、睡眠、疼痛和情绪的影响是不同的。这种差异的具体原因无法确定。确定可能影响膝关节OA患者的因素，这些患者在重大生活方式改变(如正在进行的大流行)期间可能表现出体力活动减少和/或症状加重，这对于向可能从中受益最多的人提供有针对性的医疗保健服务和管理建议非常重要。

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引用次数: 0

Agreement of Step-Based Metrics From ActiGraph and ActivPAL Accelerometers Worn Concurrently Among Older Adults. 同时佩戴 ActiGraph 和 ActivPAL 加速计的老年人步数指标的一致性。

Journal for the measurement of physical behaviour

Pub Date : 2022-12-01 Epub Date: 2022-10-11 DOI: 10.1123/jmpb.2022-0001

Eric T Hyde, Steve Nguyen, Fatima Tuz-Zahra, Christopher C Moore, Mikael Anne Greenwood-Hickman, Rod L Walker, Loki Natarajan, Dori Rosenberg, John Bellettiere

Purpose: Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AG_N) and the low frequency extension (AG_LFE), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.

Methods: Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AG_N - AP and AG_LFE - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.

Results: For AG_N - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AG_LFE - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.

Conclusions: Compared with estimates from the AP, the AG_N underestimated daily step counts by approximately 1,800 steps/day, while the AG_LFE overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AG_LFE and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.

目的：我们的研究评估了使用正常滤波器（AGN）和低频扩展（AGLFE）的髋部佩戴式 ActiGraph GT3X+ 加速度计与大腿佩戴式 activPAL3 micro（AP）加速度计之间在日平均步数、1 分钟峰值步频和 30 分钟峰值步频方面的一致性：从 2016 年开始，招募了 953 名老年人（≥65 岁）同时佩戴 ActiGraph 设备和 AP 4-7 天。以AP为参照测量，使用平均差（AGN - AP和AGLFE - AP）、平均绝对百分比误差（MAPE）、皮尔逊相关系数（Pearson）和一致性相关系数（conordance correlation coefficients）评估了每个基于步长的指标的设备一致性：对于 AGN - AP，平均差异和 MAPE 分别为：日步数 -1,851 步/天和 27.2%，1 分钟步速峰值 -16.2 步/分钟和 16.3%，30 分钟步速峰值 -17.7 步/分钟和 24.0%。皮尔逊系数分别为 0.94、0.85 和 0.91，一致性系数分别为 0.81、0.65 和 0.73。对于 AGLFE - AP，平均差异和 MAPE 分别为：日步数 4,968 步/天和 72.7%，1 分钟步速峰值 -1.4 步/分钟和 4.7%，30 分钟步速峰值 1.4 步/分钟和 7.0%。皮尔逊系数分别为.91、.91和.95，一致性系数分别为.49、.91和.94：与 AP 的估计值相比，AGN 低估了每日步数约 1,800 步/天，而 AGLFE 则高估了约 5,000 步/天。不过，AGLFE 和 AP 得出的峰值步速估计值具有很高的一致性（MAPE ≤ 7.0%）。为了更好地了解设备间的一致性，还需要对同时佩戴的加速度计所产生的基于步速的指标进行更多的趋同验证研究。

{"title":"Agreement of Step-Based Metrics From ActiGraph and ActivPAL Accelerometers Worn Concurrently Among Older Adults.","authors":"Eric T Hyde, Steve Nguyen, Fatima Tuz-Zahra, Christopher C Moore, Mikael Anne Greenwood-Hickman, Rod L Walker, Loki Natarajan, Dori Rosenberg, John Bellettiere","doi":"10.1123/jmpb.2022-0001","DOIUrl":"10.1123/jmpb.2022-0001","url":null,"abstract":"Purpose: Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AGN) and the low frequency extension (AGLFE), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.Methods: Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AGN - AP and AGLFE - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.Results: For AGN - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AGLFE - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.Conclusions: Compared with estimates from the AP, the AGN underestimated daily step counts by approximately 1,800 steps/day, while the AGLFE overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AGLFE and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"5 4","pages":"242-251"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934009/pdf/nihms-1870840.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10806913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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