Pub Date : 2022-09-13DOI: 10.1080/1091367X.2022.2123243
Nicholas D. Myers, Seungmin Lee, André G. Bateman, Meredith Wekesser, Isaac Prilleltensky, Adam McMahon, Ahnalee M. Brincks
ABSTRACT The objective of this study was to provide initial validity evidence for responses to the newly developed Well-Being Actions Self-Efficacy (WBASE) scale from adults with obesity under an exploratory latent variable approach. Longitudinal data (Nbaseline = 667 and N30 days post-baseline = 550) from the Well-Being and Physical Activity study (ClinicalTrials.gov, identifier: NCT03194854), which deployed the Fun For Wellness (FFW) intervention, were analyzed. The a priori measurement model exhibited close fit to baseline data within an exploratory framework. Similarly, there was strong evidence for at least partial temporal measurement invariance for the a priori WBASE scale measurement model. Convergent (and divergent) correlations between concordant (and discordant) pairs of well-being actions scores at baseline and latent well-being actions self-efficacy factors at 30 days post-baseline were observed. There was mixed evidence for the effectiveness of the FFW intervention to exert a direct effect on latent well-being actions self-efficacy at 30 days post-baseline.
{"title":"Initial Validity Evidence for Responses to the Newly Developed Well-Being Actions Self-Efficacy Scale from Adults with Obesity under an Exploratory Latent Variable Approach","authors":"Nicholas D. Myers, Seungmin Lee, André G. Bateman, Meredith Wekesser, Isaac Prilleltensky, Adam McMahon, Ahnalee M. Brincks","doi":"10.1080/1091367X.2022.2123243","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2123243","url":null,"abstract":"ABSTRACT The objective of this study was to provide initial validity evidence for responses to the newly developed Well-Being Actions Self-Efficacy (WBASE) scale from adults with obesity under an exploratory latent variable approach. Longitudinal data (Nbaseline = 667 and N30 days post-baseline = 550) from the Well-Being and Physical Activity study (ClinicalTrials.gov, identifier: NCT03194854), which deployed the Fun For Wellness (FFW) intervention, were analyzed. The a priori measurement model exhibited close fit to baseline data within an exploratory framework. Similarly, there was strong evidence for at least partial temporal measurement invariance for the a priori WBASE scale measurement model. Convergent (and divergent) correlations between concordant (and discordant) pairs of well-being actions scores at baseline and latent well-being actions self-efficacy factors at 30 days post-baseline were observed. There was mixed evidence for the effectiveness of the FFW intervention to exert a direct effect on latent well-being actions self-efficacy at 30 days post-baseline.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"151 - 170"},"PeriodicalIF":2.1,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43121265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-07DOI: 10.1080/1091367X.2022.2120356
R. Tanaka, Kanako Yakushiji, Satomi Tanaka, Michihiro Tsubaki, K. Fujita
ABSTRACT This study aimed to review the validity and/or reliability of light-intensity physical activity (LPA) questionnaires and identify the most suitable questionnaires for measurement of LPA in adults. Following the PRISMA-P 2020 guidelines, we searched MEDLINE, PsycINFO, CINAHL, Scopus, Embase, and MedNar. Only studies that targeted adults ≥18 years old and used LPA measured by accelerometer and/or heart rate monitor as an objective criterion were included. The search resulted in 2748 article hits, from which we extracted 16 studies with 14 questionnaires. The 7-Day Sedentary and LPA Log and LPA Questionnaire were specifically designed for LPA measurement, and the Community Health Activities Model Program for Seniors physical activity self-report questionnaire scale has been revised for LPA measurement. These questionnaires had comparatively high reliability and validity in this review. Most studies contained methodological limitations such as test-retest period. In the future, more accurate reliability/validity studies should be conducted for each questionnaire.
{"title":"Reliability and Validity of Light-Intensity Physical Activity Scales in Adults: A Systematic Review","authors":"R. Tanaka, Kanako Yakushiji, Satomi Tanaka, Michihiro Tsubaki, K. Fujita","doi":"10.1080/1091367X.2022.2120356","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2120356","url":null,"abstract":"ABSTRACT This study aimed to review the validity and/or reliability of light-intensity physical activity (LPA) questionnaires and identify the most suitable questionnaires for measurement of LPA in adults. Following the PRISMA-P 2020 guidelines, we searched MEDLINE, PsycINFO, CINAHL, Scopus, Embase, and MedNar. Only studies that targeted adults ≥18 years old and used LPA measured by accelerometer and/or heart rate monitor as an objective criterion were included. The search resulted in 2748 article hits, from which we extracted 16 studies with 14 questionnaires. The 7-Day Sedentary and LPA Log and LPA Questionnaire were specifically designed for LPA measurement, and the Community Health Activities Model Program for Seniors physical activity self-report questionnaire scale has been revised for LPA measurement. These questionnaires had comparatively high reliability and validity in this review. Most studies contained methodological limitations such as test-retest period. In the future, more accurate reliability/validity studies should be conducted for each questionnaire.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"136 - 150"},"PeriodicalIF":2.1,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48540076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-22DOI: 10.1080/1091367X.2022.2112683
Weimo Zhu, Daniel Konishi, G. Welk, M. Mahar, K. Laurson, K. Janz, F. Baptista
ABSTRACT This study evaluated test-equating methods to enable comparisons and conversions between the vertical jump (VJ) and standing long jump (SLJ) tests. A total of 528 youth (280 males) performed VJ and SLJ, and their scores were randomly split as the calibration (C) sample (n = 478) and cross-validation (CV) sample (n = 50). SLJ scores of the C sample were equated to the scale of VJ using linear and equipercentile equating, and established conversion between the tests was applied to SLJ scores of the CV sample. Overall, the correlations between VJ and equated VJ were moderately high to high and the absolute differences were small in both C and CV samples. There was little difference between the equating methods, but the results of the equipercentile method were used because it could provide a more robust conversion in theory. The conversion should be further crossly validated with large, more diverse samples.
{"title":"Linking Vertical Jump and Standing Broad Jump Tests: A Testing Equating Application","authors":"Weimo Zhu, Daniel Konishi, G. Welk, M. Mahar, K. Laurson, K. Janz, F. Baptista","doi":"10.1080/1091367X.2022.2112683","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2112683","url":null,"abstract":"ABSTRACT This study evaluated test-equating methods to enable comparisons and conversions between the vertical jump (VJ) and standing long jump (SLJ) tests. A total of 528 youth (280 males) performed VJ and SLJ, and their scores were randomly split as the calibration (C) sample (n = 478) and cross-validation (CV) sample (n = 50). SLJ scores of the C sample were equated to the scale of VJ using linear and equipercentile equating, and established conversion between the tests was applied to SLJ scores of the CV sample. Overall, the correlations between VJ and equated VJ were moderately high to high and the absolute differences were small in both C and CV samples. There was little difference between the equating methods, but the results of the equipercentile method were used because it could provide a more robust conversion in theory. The conversion should be further crossly validated with large, more diverse samples.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"26 1","pages":"335 - 343"},"PeriodicalIF":2.1,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43783802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-25DOI: 10.1080/1091367X.2022.2102924
M. Lopes, Bruno G. G. da Costa, L. Malheiros, H. Carvalho, I. Crochemore-Silva, K. Silva
ABSTRACT This study examined the within- and between-day variability of time-segmented sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) in adolescents. The sample comprised 154 adolescents (11–16 years old) from two public schools in Florianópolis, Brazil. The proportion of time spent in SB, LPA, and MVPA was measured using Actigraph GT3X+ accelerometers for the following weekday time segments: before school (07:00–07:59), school time (08:00–11:59), after school (12:00–12:59), afternoons (13:00–17:59), and evenings (18:00–23:00). Participants were more active during commuting-related time segments. Females showed lower MVPA than males during school time, afternoons, and evenings, but not before school and after school. Higher age was associated with higher SB and lower LPA during school time, afternoons, and evenings, and slightly lower MVPA during afternoons. The variability of SB, LPA, and MVPA for all time segments was mainly explained by within-participant day-to-day variations rather than between-participant differences of daily-averaged estimates.
{"title":"Time-segmented Physical Activity Patterns of Brazilian Adolescents: Within- and Between-day Variability","authors":"M. Lopes, Bruno G. G. da Costa, L. Malheiros, H. Carvalho, I. Crochemore-Silva, K. Silva","doi":"10.1080/1091367X.2022.2102924","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2102924","url":null,"abstract":"ABSTRACT This study examined the within- and between-day variability of time-segmented sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) in adolescents. The sample comprised 154 adolescents (11–16 years old) from two public schools in Florianópolis, Brazil. The proportion of time spent in SB, LPA, and MVPA was measured using Actigraph GT3X+ accelerometers for the following weekday time segments: before school (07:00–07:59), school time (08:00–11:59), after school (12:00–12:59), afternoons (13:00–17:59), and evenings (18:00–23:00). Participants were more active during commuting-related time segments. Females showed lower MVPA than males during school time, afternoons, and evenings, but not before school and after school. Higher age was associated with higher SB and lower LPA during school time, afternoons, and evenings, and slightly lower MVPA during afternoons. The variability of SB, LPA, and MVPA for all time segments was mainly explained by within-participant day-to-day variations rather than between-participant differences of daily-averaged estimates.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"125 - 135"},"PeriodicalIF":2.1,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48162590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-12DOI: 10.1080/1091367X.2022.2100222
H. Macdonald, Minsoo Kang
In the four decades since the Cooper Institute first developed FitnessGram, research, evaluation, validation, and program enhancement by the Scientific Advisory Board (SAB, https://fitnessgram.net/advisory-board/) have made FitnessGram “the most trusted and widely used fitness assessment, education, and reporting tool in the world” (Plowman et al., 2006; The Cooper Institute, 2022). The sustained commitment by the SAB to science-informed practice including use of criterionreferenced standards based on health outcomes (instead of performance indicators or normative data) has led to refinements in fitness assessments and standards including those for aerobic capacity and body composition (Welk et al., 2011). With the release of the Institute of Medicine’s (IOM) seminal report “Fitness Measures and Health Outcomes in Youth” in 2012, the SAB and The Cooper Institute acknowledged the need to review the FitnessGram musculoskeletal fitness assessments. Specifically, the SAB developed a comprehensive plan to establish and evaluate health-related fitness standards for musculoskeletal fitness. The FitnessGram battery historically included field-based assessments of muscle strength and endurance (i.e., curl-up, push-up, and trunk lift) and flexibility (i.e., back-save sit and reach), but evidence was lacking to support the utility of criterion-referenced health standards for these outcomes. Thus, in this special issue of MPEES, SAB researchers, and colleagues present their findings from a foundational series of studies that aim to fill knowledge gaps related to musculoskeletal fitness assessments in youth. In the first paper, Welk et al. (2022) review and summarize the concepts, approaches, and considerations used by the SAB to explore the development of criterion-referenced standards for musculoskeletal fitness in youth. The authors first outline their conceptual model of health-related fitness and musculoskeletal fitness, with the latter defined as per the IOM as a multidimensional construct encompassing the integrated function of muscle strength, muscle endurance, and muscle power (Institute of Medicine, 2012). The SAB’s model for musculoskeletal fitness guided selection of fitness tests to represent the upper (i.e., grip strength) and lower body (i.e., vertical and long jump) and core (i.e., plank test), with the acknowledgment that one single measure cannot capture this complex construct. As mentioned, criterion-referenced health standards are a foundational and unique element of FitnessGram (Cureton & Warren, 1990; Plowman et al., 2006; Zhu et al., 2011), and the SAB adhered to their established methods when developing standards for musculoskeletal fitness. The process first involves modeling age and sex effects using the Lambda Mu Sigma (LMS) procedures (described in detail elsewhere (Cole, 1990; Cole & Green, 1992)), which are used in three papers in this special issue (Laurson et al., 2022a, 2022b, 2021). Development of LMS curves is followed by re
自库珀研究所首次开发FitnessGram以来的四十年里，科学顾问委员会(SAB, https://fitnessgram.net/advisory-board/)的研究、评估、验证和项目改进使FitnessGram成为“世界上最值得信赖和广泛使用的健身评估、教育和报告工具”(Plowman等人，2006;库珀研究所，2022)。SAB对科学实践的持续承诺，包括使用基于健康结果的标准参考标准(而不是绩效指标或规范性数据)，导致了健身评估和标准的改进，包括有氧能力和身体成分的评估和标准(Welk等人，2011)。2012年，美国医学研究所(IOM)发布了一份开创性的报告《青少年的健身措施和健康结果》(Fitness Measures and Health Outcomes in Youth)， SAB和库珀研究所承认，有必要对FitnessGram的肌肉骨骼健康评估进行审查。具体而言，SAB制定了一项全面计划，以建立和评估与肌肉骨骼健康有关的健身标准。FitnessGram系列以前包括基于现场的肌肉力量和耐力评估(即，卷腹、俯卧撑和躯干举)和柔韧性评估(即，靠背坐姿和伸展)，但缺乏证据支持这些结果的标准参考健康标准的实用性。因此，在本期MPEES特刊中，SAB的研究人员及其同事介绍了他们从一系列基础研究中获得的发现，这些研究旨在填补与青少年肌肉骨骼健康评估相关的知识空白。在第一篇论文中，Welk等人(2022)回顾并总结了SAB在探索制定青少年肌肉骨骼健康标准时所使用的概念、方法和考虑因素。作者首先概述了他们的健康相关健身和肌肉骨骼健身的概念模型，后者根据IOM的定义是一个多维结构，包括肌肉力量、肌肉耐力和肌肉力量的综合功能(医学研究所，2012)。SAB的肌肉骨骼健身模型指导选择代表上半身(即握力)、下半身(即垂直和跳远)和核心(即平板支撑测试)的健身测试，并认识到单一的测量方法无法捕捉这种复杂的结构。如前所述，参照标准的健康标准是FitnessGram的基础和独特元素(Cureton & Warren, 1990;Plowman et al.， 2006;Zhu etal .， 2011)和SAB在制定肌肉骨骼适能标准时坚持了他们既定的方法。这个过程首先涉及使用Lambda Mu Sigma (LMS)程序对年龄和性别影响进行建模(在其他地方有详细描述(Cole, 1990;Cole & Green, 1992))，这在本期特刊的三篇论文中使用(Laurson et al.， 2022a, 2022b, 2021)。绘制LMS曲线后，进行受试者操作特征(ROC)分析，以确定预测相关健康结果的阈值。与SAB在改进有氧健身和身体成分标准时使用的开创性方法类似，ROC分析定义了两个不同的阈值，允许将健身分数分为三个区域-健康区域，风险区域和边缘或中间区域。Welk及其同事概述了SAB在制定肌肉骨骼健康标准时的其他独特考虑，包括优先考虑与肌肉骨骼系统直接相关的指标(即骨骼和肌肉健康)，基于力量和耐力的绝对指标而不是相对于体重的指标，以及为三个主要指标制定标准化方案
{"title":"Refining the FitnessGram with criterion-referenced Standards for Musculoskeletal Fitness","authors":"H. Macdonald, Minsoo Kang","doi":"10.1080/1091367X.2022.2100222","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2100222","url":null,"abstract":"In the four decades since the Cooper Institute first developed FitnessGram, research, evaluation, validation, and program enhancement by the Scientific Advisory Board (SAB, https://fitnessgram.net/advisory-board/) have made FitnessGram “the most trusted and widely used fitness assessment, education, and reporting tool in the world” (Plowman et al., 2006; The Cooper Institute, 2022). The sustained commitment by the SAB to science-informed practice including use of criterionreferenced standards based on health outcomes (instead of performance indicators or normative data) has led to refinements in fitness assessments and standards including those for aerobic capacity and body composition (Welk et al., 2011). With the release of the Institute of Medicine’s (IOM) seminal report “Fitness Measures and Health Outcomes in Youth” in 2012, the SAB and The Cooper Institute acknowledged the need to review the FitnessGram musculoskeletal fitness assessments. Specifically, the SAB developed a comprehensive plan to establish and evaluate health-related fitness standards for musculoskeletal fitness. The FitnessGram battery historically included field-based assessments of muscle strength and endurance (i.e., curl-up, push-up, and trunk lift) and flexibility (i.e., back-save sit and reach), but evidence was lacking to support the utility of criterion-referenced health standards for these outcomes. Thus, in this special issue of MPEES, SAB researchers, and colleagues present their findings from a foundational series of studies that aim to fill knowledge gaps related to musculoskeletal fitness assessments in youth. In the first paper, Welk et al. (2022) review and summarize the concepts, approaches, and considerations used by the SAB to explore the development of criterion-referenced standards for musculoskeletal fitness in youth. The authors first outline their conceptual model of health-related fitness and musculoskeletal fitness, with the latter defined as per the IOM as a multidimensional construct encompassing the integrated function of muscle strength, muscle endurance, and muscle power (Institute of Medicine, 2012). The SAB’s model for musculoskeletal fitness guided selection of fitness tests to represent the upper (i.e., grip strength) and lower body (i.e., vertical and long jump) and core (i.e., plank test), with the acknowledgment that one single measure cannot capture this complex construct. As mentioned, criterion-referenced health standards are a foundational and unique element of FitnessGram (Cureton & Warren, 1990; Plowman et al., 2006; Zhu et al., 2011), and the SAB adhered to their established methods when developing standards for musculoskeletal fitness. The process first involves modeling age and sex effects using the Lambda Mu Sigma (LMS) procedures (described in detail elsewhere (Cole, 1990; Cole & Green, 1992)), which are used in three papers in this special issue (Laurson et al., 2022a, 2022b, 2021). Development of LMS curves is followed by re","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"26 1","pages":"267 - 275"},"PeriodicalIF":2.1,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42946393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-26DOI: 10.1080/1091367x.2022.2092740
Jordan T. Sutcliffe, Alex J. Benson, Colin D. McLaren, Mark W Bruner
Drawing from theory of the multidimensional nature of social identity, the purpose of this study was to assess an adapted measure of social identity in sport that captures the extent to which paren...
{"title":"Part of the Team: The Social Identity Questionnaire for Sport Parents (SIQS-P)","authors":"Jordan T. Sutcliffe, Alex J. Benson, Colin D. McLaren, Mark W Bruner","doi":"10.1080/1091367x.2022.2092740","DOIUrl":"https://doi.org/10.1080/1091367x.2022.2092740","url":null,"abstract":"Drawing from theory of the multidimensional nature of social identity, the purpose of this study was to assess an adapted measure of social identity in sport that captures the extent to which paren...","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"19 11","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138510066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-15DOI: 10.1080/1091367X.2022.2088290
Nicholas Lerma, H. Gulgin
ABSTRACT This study evaluated the agreement between Kinect V2 with AssessLink and Vicon motion capture systems in children performing the vertical jump (JL) and forward leap (Leap). Eighteen healthy children (5–17 years) performed the movements while recorded simultaneously by both motion capture systems. Spearman correlation (ρ) and Bland-Altman were used to determine joint angle agreement. Overall, agreement varied by body segment, movement type, and phase. JL for knees and shoulder ranged from ρ = −.220 to .543; bias = 8.1 to 23.0° and ρ = −.743 to .410; bias = 8.1 to 56.5°, respectively. Leap had poorer correlation and bias for the appendicular segments (ρ = −.091 to .306; bias = −47.5 to 73.7°) than axial segments (ρ = .345 to .553; bias = 11.3 to 22.9°). The Kinect V2 should not replace criterion kinematic systems, but may improve gross motor assessment methods when selecting for specific movement observations.
{"title":"Agreement of a Portable Motion Capture System to Analyze Movement Skills in Children","authors":"Nicholas Lerma, H. Gulgin","doi":"10.1080/1091367X.2022.2088290","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2088290","url":null,"abstract":"ABSTRACT This study evaluated the agreement between Kinect V2 with AssessLink and Vicon motion capture systems in children performing the vertical jump (JL) and forward leap (Leap). Eighteen healthy children (5–17 years) performed the movements while recorded simultaneously by both motion capture systems. Spearman correlation (ρ) and Bland-Altman were used to determine joint angle agreement. Overall, agreement varied by body segment, movement type, and phase. JL for knees and shoulder ranged from ρ = −.220 to .543; bias = 8.1 to 23.0° and ρ = −.743 to .410; bias = 8.1 to 56.5°, respectively. Leap had poorer correlation and bias for the appendicular segments (ρ = −.091 to .306; bias = −47.5 to 73.7°) than axial segments (ρ = .345 to .553; bias = 11.3 to 22.9°). The Kinect V2 should not replace criterion kinematic systems, but may improve gross motor assessment methods when selecting for specific movement observations.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"105 - 113"},"PeriodicalIF":2.1,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44296742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-06DOI: 10.1080/1091367X.2022.2069467
K. Pfeiffer, C. Lisee, Bradford S. Westgate, Cheyenne Kalfsbeek, C. Kuenze, D. Bell, L. Cadmus-Bertram, Alexander Montoye
ABSTRACT A universal approach to characterizing sport-related physical activity (PA) types in sport settings does not yet exist. Young adults (n = 30), 19–33 years, engaged in a 15-min activity session, performing warm-ups, 3-on-3 soccer, and 3-on-3 basketball. Videos were recorded and manually coded as criterion PA types (walking, running, jumping, rapid lateral movements). Participants wore an accelerometer on their right hip. Multiple machine learning models were developed and compared for predicting PA type. Most models underestimated time spent completing the activities performed least commonly. Point estimates for percent agreement, sensitivity, specificity, F-scores, and kappa were similar across models, with Hidden Markov Models (HMMs) being best at classifying rare events. Models detected activity type during sport-related movements with modest accuracy (kappas ≤ .40). Given the better performance of HMMs, incorporating the temporal nature of sport-related activities is important for improving sport-related PA classification.
{"title":"Using Accelerometers to Detect Activity Type in a Sport Setting: Challenges with Using Multiple Types of Conventional Machine Learning Approaches","authors":"K. Pfeiffer, C. Lisee, Bradford S. Westgate, Cheyenne Kalfsbeek, C. Kuenze, D. Bell, L. Cadmus-Bertram, Alexander Montoye","doi":"10.1080/1091367X.2022.2069467","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2069467","url":null,"abstract":"ABSTRACT A universal approach to characterizing sport-related physical activity (PA) types in sport settings does not yet exist. Young adults (n = 30), 19–33 years, engaged in a 15-min activity session, performing warm-ups, 3-on-3 soccer, and 3-on-3 basketball. Videos were recorded and manually coded as criterion PA types (walking, running, jumping, rapid lateral movements). Participants wore an accelerometer on their right hip. Multiple machine learning models were developed and compared for predicting PA type. Most models underestimated time spent completing the activities performed least commonly. Point estimates for percent agreement, sensitivity, specificity, F-scores, and kappa were similar across models, with Hidden Markov Models (HMMs) being best at classifying rare events. Models detected activity type during sport-related movements with modest accuracy (kappas ≤ .40). Given the better performance of HMMs, incorporating the temporal nature of sport-related activities is important for improving sport-related PA classification.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"60 - 72"},"PeriodicalIF":2.1,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46589475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-05DOI: 10.1080/1091367X.2022.2072688
Xiong Qin, Weimo Zhu, Lin Zhu, Jing-xin Liu, Jing Liao
ABSTRACT To convert accelerometer-based devices onto the same scale, a platform called Monitor-Independent Movement Summary (MIMS) was created and used in national studies. Yet, its physical activity (PA) intensity cutoff scores have not been established, making it less useful. This study was to link MIMS with the ActiGraph Count, known as “the Count,” using the test-equating method. A total of 81 obese participants aged 10–17 years old (male = 56%) were recruited to perform one-minute warm-ups and walking or running at different speeds with ActiGraph on hips. Data with corresponding Count and MIMS were split into training (n = 65, male = 54%) and testing samples (n = 16, male = 63%). Linear and equipercentile equating were applied to the training sample to equate MIMS onto Count, creating MIMS-equated Count (MIMS-EQ-Count), a new MIMS-based unit. High correlation (≥.84), high agreements (>.7) and kappas (mostly >.5) between MIMS-EQ-Count and the Count in both training and testing samples under both linear and equipercentile methods. Equipercentile was the best equating method because of smaller standard errors. Yielded from equipercentile equating, a table linking MIMS and MIMS-EQ-Count was constructed, from which MIMS was linked and cross-validated with the well-studied Count. MIMS can now use the rich information accumulated for the Count of ActiGraph.
{"title":"Linking MIMS with ActiGraph Count: An Equating Study","authors":"Xiong Qin, Weimo Zhu, Lin Zhu, Jing-xin Liu, Jing Liao","doi":"10.1080/1091367X.2022.2072688","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2072688","url":null,"abstract":"ABSTRACT To convert accelerometer-based devices onto the same scale, a platform called Monitor-Independent Movement Summary (MIMS) was created and used in national studies. Yet, its physical activity (PA) intensity cutoff scores have not been established, making it less useful. This study was to link MIMS with the ActiGraph Count, known as “the Count,” using the test-equating method. A total of 81 obese participants aged 10–17 years old (male = 56%) were recruited to perform one-minute warm-ups and walking or running at different speeds with ActiGraph on hips. Data with corresponding Count and MIMS were split into training (n = 65, male = 54%) and testing samples (n = 16, male = 63%). Linear and equipercentile equating were applied to the training sample to equate MIMS onto Count, creating MIMS-equated Count (MIMS-EQ-Count), a new MIMS-based unit. High correlation (≥.84), high agreements (>.7) and kappas (mostly >.5) between MIMS-EQ-Count and the Count in both training and testing samples under both linear and equipercentile methods. Equipercentile was the best equating method because of smaller standard errors. Yielded from equipercentile equating, a table linking MIMS and MIMS-EQ-Count was constructed, from which MIMS was linked and cross-validated with the well-studied Count. MIMS can now use the rich information accumulated for the Count of ActiGraph.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"27 1","pages":"97 - 104"},"PeriodicalIF":2.1,"publicationDate":"2022-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46550094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-29DOI: 10.1080/1091367X.2022.2071126
Nicholas D. Myers, Seungmin Lee, Hae-Lee Chun, Stephen Silverman
ABSTRACT Purpose The purpose of this manuscript is to provide a summary of Measurement in Physical Education and Exercise Science (MPEES)-related activities in 2021. Manuscripts submitted In 2021 original submissions (i.e., not counting revised manuscripts) increased by ~20% as compared to 2020. Fifty-eight countries were represented across the 464 original manuscripts submitted to MPEES in 2021. MPEES continues to welcome high-quality submissions from around the world in 2022. Manuscripts submitted by section The seven sections of MPEES are: (1) exercise science, (2) physical activity, (3) physical education pedagogy, (4) psychology, (5) research methodology and statistics, (6) sport management and administration, and (7) tutorial and teacher’s toolbox. More than three-fourths of the manuscripts submitted to MPEES in 2021 were submitted to one of three sections: exercise science or physical activity or research methodology and statistics. MPEES continues to welcome high-quality submissions within each of the seven sections that comprise the journal in 2022. Review process: Each of the original manuscripts submitted to MPEES in 2021 had received an initial decision by April 4, 2022 (i.e., 464 of the 464 manuscripts received). When an immediate decision (e.g., desk-rejection) was rendered by the editor-in-chief it always (i.e., for 369 of 369 manuscripts) occurred within 10 days of receiving the manuscript. When a manuscript was assigned to a section editor by the editor-in-chief it typically (i.e., for 91 of 95 manuscripts) received an initial decision within 90 days of receiving the manuscript. Twenty-four countries were represented across reviewers for the original manuscripts sent out for external review by MPEES in 2021. We gratefully acknowledge, and list in the Appendix, the many scholars (N = 151) from around the world who served as a reviewer for MPEES in 2021. Manuscripts published Volume 25 (i.e., the volume published in 2021) of MPEES published a total of 37 manuscripts. More than two-thirds of the published manuscripts were submitted to one of two sections: exercise science or research methodology and statistics. MPEES continues to strive for publishing high-quality manuscripts within each of the seven sections that comprise the journal in 2022. Fourteen countries were represented across the manuscripts published in Volume 25 of MPEES. MPEES continues to strive for publishing high-quality manuscripts written by one or more authors from around the world in 2022. Impact factor The 2020 impact factor for MPEES was 2.30 representing an increase of ~31% compared to 2019 when the journal’s impact factor was 1.75. The value of the 2020 impact factor placed MPEES in the second quartile (i.e., ranked #131 out of 265 journals) within the Education & Educational Research category of Clarivate Analytics. The 2021 impact factor for MPEES is expected to be released in ~June 2022.
{"title":"Measurement in Physical Education and Exercise Science (MPEES): A Summary of MPEES-related Activities in 2021","authors":"Nicholas D. Myers, Seungmin Lee, Hae-Lee Chun, Stephen Silverman","doi":"10.1080/1091367X.2022.2071126","DOIUrl":"https://doi.org/10.1080/1091367X.2022.2071126","url":null,"abstract":"ABSTRACT Purpose The purpose of this manuscript is to provide a summary of Measurement in Physical Education and Exercise Science (MPEES)-related activities in 2021. Manuscripts submitted In 2021 original submissions (i.e., not counting revised manuscripts) increased by ~20% as compared to 2020. Fifty-eight countries were represented across the 464 original manuscripts submitted to MPEES in 2021. MPEES continues to welcome high-quality submissions from around the world in 2022. Manuscripts submitted by section The seven sections of MPEES are: (1) exercise science, (2) physical activity, (3) physical education pedagogy, (4) psychology, (5) research methodology and statistics, (6) sport management and administration, and (7) tutorial and teacher’s toolbox. More than three-fourths of the manuscripts submitted to MPEES in 2021 were submitted to one of three sections: exercise science or physical activity or research methodology and statistics. MPEES continues to welcome high-quality submissions within each of the seven sections that comprise the journal in 2022. Review process: Each of the original manuscripts submitted to MPEES in 2021 had received an initial decision by April 4, 2022 (i.e., 464 of the 464 manuscripts received). When an immediate decision (e.g., desk-rejection) was rendered by the editor-in-chief it always (i.e., for 369 of 369 manuscripts) occurred within 10 days of receiving the manuscript. When a manuscript was assigned to a section editor by the editor-in-chief it typically (i.e., for 91 of 95 manuscripts) received an initial decision within 90 days of receiving the manuscript. Twenty-four countries were represented across reviewers for the original manuscripts sent out for external review by MPEES in 2021. We gratefully acknowledge, and list in the Appendix, the many scholars (N = 151) from around the world who served as a reviewer for MPEES in 2021. Manuscripts published Volume 25 (i.e., the volume published in 2021) of MPEES published a total of 37 manuscripts. More than two-thirds of the published manuscripts were submitted to one of two sections: exercise science or research methodology and statistics. MPEES continues to strive for publishing high-quality manuscripts within each of the seven sections that comprise the journal in 2022. Fourteen countries were represented across the manuscripts published in Volume 25 of MPEES. MPEES continues to strive for publishing high-quality manuscripts written by one or more authors from around the world in 2022. Impact factor The 2020 impact factor for MPEES was 2.30 representing an increase of ~31% compared to 2019 when the journal’s impact factor was 1.75. The value of the 2020 impact factor placed MPEES in the second quartile (i.e., ranked #131 out of 265 journals) within the Education & Educational Research category of Clarivate Analytics. The 2021 impact factor for MPEES is expected to be released in ~June 2022.","PeriodicalId":48577,"journal":{"name":"Measurement in Physical Education and Exercise Science","volume":"26 1","pages":"256 - 265"},"PeriodicalIF":2.1,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45334981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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