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Qin, Xiong; Zhu, Weimo; Zhu, Lin; Liu, Jingxin; Liao, Jing – Measurement in Physical Education and Exercise Science, 2023
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…
Descriptors: Measurement Equipment, Physical Activity Level, Adolescents, Preadolescents
Pellerine, Liam P.; Petterson, Jennifer L.; Shivgulam, Madeline E.; Johansson, Peter J.; Hettiarachchi, Pasan; Kimmerly, Derek S.; Frayne, Ryan J.; O'Brien, Myles W. – Measurement in Physical Education and Exercise Science, 2023
Device-based measures often rely on the positive relationship between walking cadence and metabolic equivalents of task (METs) to estimate physical activity. It is unknown whether this relationship remains during jogging/running. The study purpose was to investigate the relationships between METs, cadence, and step length during walking and…
Descriptors: Physical Activity Level, Predictor Variables, Physical Activities, Young Adults
Peter Elsborg; Paulina S. Melby; Mette Kurtzhals; Helene Kirkegaard; Johannes Carl; Steffen Rask; Peter Bentsen; Glen Nielsen – Measurement in Physical Education and Exercise Science, 2024
This study aimed to develop and test MyPL, a questionnaire that measures self-reported physical literacy (PL) among children and adolescents. First, the item pool was developed and adapted, and face validity was tested with cognitive interviewing. Then, factor structures were identified through multidimensional scaling and exploratory factor…
Descriptors: Questionnaires, Children, Early Adolescents, Models
David LaRocca; Jennie Quinlan; Sharon Scarbro; Charlotte Farewell; Jini Puma – Measurement in Physical Education and Exercise Science, 2025
This study tested the equivalence of concurrently collected measurements of physical activity in children ages 3-5 years from the System for Observing Play and Leisure Activity in Youth (SOPLAY) and accelerometers. Accelerometry-based physical activity measurements were collected from 109 preschool children across 18 sites, and SOPLAY was used to…
Descriptors: Preschool Children, Physical Activity Level, Measurement Equipment, Measurement Techniques
Karaca, Ayda; Demirci, Necip; Yilmaz, Vedat; Hazir Aytar, Sinem; Can, Sema; Ünver, Evrim – Measurement in Physical Education and Exercise Science, 2022
This study aimed to determine the validity of the ActiGraph wGT3X-BT for step counts (SC) at five different body locations in laboratory settings. A total of 29 male adults participated in this study. The participants walked or ran for different speeds on the treadmill while wearing ActiGraph wGT3X-BT on their right wrist (RW), left wrist (LW),…
Descriptors: Measurement Equipment, Validity, Physical Activity Level, Males
Gabriel Felipe Arantes Bertochi; Jeffer Eidi Sasaki – Measurement in Physical Education and Exercise Science, 2025
This study compared the weekly training load (TL) variation across different measures. Fifty-two runners reported their heart rate and distance ran for each training session during four weeks of training. Heart rate measures were used to calculate the weekly TRaining IMPulse (W-TRIMP), whereas the distance ran was used to calculate the weekly…
Descriptors: Physical Education, Physical Activities, Athletics, Athletes
Molly C. Henneberry; Dana Agar-Newman; Seth Lenetsky; Marc D. Klimstra – Measurement in Physical Education and Exercise Science, 2025
Upper body force-velocity profiles to assess musculoskeletal performance are created using release speed (RS) of the barbell in a bench press throw (BPT). A more easily obtained variable is peak speed (PS) measured by a linear position transducer. We assessed the validity of predicting RS from measured PS. One hundred and seventy-eight throws from…
Descriptors: Athletics, Human Body, Muscular Strength, Biomechanics
Sunku Kwon; Yang Bai; Youngwon Kim; Ryan D. Burns; Timothy A. Brusseau; Wonwoo Byun – Measurement in Physical Education and Exercise Science, 2025
This study aimed to assess the agreement in physical activity (PA) estimates from Garmin Vivofit Jr. 3 (VFJ 3) and Fitbit Ace 3 (Ace 3) with a research-grade accelerometer (wGT3X-BT) in children under free-living conditions. Twenty-five children (Girls: 56%, Age: 10.1 ± 2.5 years, BMI: 17.1 ± 2.4 kg/m2) performed daily activities for 7 consecutive…
Descriptors: Physical Activity Level, Children, Validity, Handheld Devices
Juliano Dal Pupo; Rafael Lima Kons; Rodrigo Ghedini Gheller; Carlos W. P. Gonçalves; Amilton Vieira – Measurement in Physical Education and Exercise Science, 2025
This study aimed to analyze the intrasession reliability of the rate of force development (RFD) in different time windows in squat jumps (SJ) performed at different knee starting angles, and identify the relationship of RFD with vertical jump height (VJH). Twenty male volleyball and basketball players participated. Athletes randomly performed SJ…
Descriptors: Physical Education, Athletics, Physical Activities, Males
Cemre Yaren Güngörenler; Tülay Tarsuslu – Measurement in Physical Education and Exercise Science, 2025
The aim of this study is to investigate the test-retest reliability of the Closed Kinetic Chain Upper Extremity Stability Test (CKCUEST) and modified-CKCUEST in children aged 7-10 years and to compare the two test versions within the same group. The study was completed with fifty-three children. Average, normalized, and power scores were obtained…
Descriptors: Test Reliability, Physical Activities, Performance Tests, Children
Kozinc, Žiga; Pleša, Jernej – Measurement in Physical Education and Exercise Science, 2023
Vertical jump height is a widely used variable in sport science and physical education. This narrative review summarizes various numerical methods used to calculate vertical jump height. In force plate technology, the jump height is most commonly calculated using the flight time (FT) or the takeoff velocity (TOV), which provide only the distance…
Descriptors: Physical Activities, Scientific Concepts, Measurement Techniques, Computation
Lopes, Marcus V. V.; da Costa, Bruno G. G.; Malheiros, Luís E. A.; Carvalho, Humberto M.; Crochemore-Silva, Inácio; Silva, Kelly S. – Measurement in Physical Education and Exercise Science, 2023
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…
Descriptors: Foreign Countries, Adolescents, Physical Activity Level, Public Schools
Justin Kompf; Ryan Rhodes – Measurement in Physical Education and Exercise Science, 2024
The measurement of resistance training (RT) is often based on adaptations of aerobic physical activity measures which may not contain the elements necessary to assess RT. The purpose of this systematic review was to examine what measures are used to assess RT and appraise their composition. Specifically, the inclusion of frequency, duration,…
Descriptors: Physical Fitness, Training, Muscular Strength, Evaluation Methods
Myers, Nicholas D.; Lee, Seungmin; Bateman, André G.; Wekesser, Meredith; Prilleltensky, Isaac; McMahon, Adam; Brincks, Ahnalee M. – Measurement in Physical Education and Exercise Science, 2023
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 (N[subscript baseline] = 667 and N[subscript 30 days post-baseline] = 550) from the Well-Being and…
Descriptors: Test Validity, Self Efficacy, Adults, Obesity
Mayara S. Bianchim; Melitta A. McNarry; Alan R. Barker; Craig A. Williams; Sarah Denford; Lena Thia; Rachel Evans; Kelly A. Mackintosh – Measurement in Physical Education and Exercise Science, 2024
This study aimed to develop and validate machine learning models to predict intensities in children and adolescents with cystic fibrosis (CF) across different accelerometry brands and placements. Thirty-five children and adolescents with CF (11.6 ± 2.8 yrs; 15 girls) and 28 healthy youth (12.2 ± 2.7 yrs; 16 girls) performed six activities whilst…
Descriptors: Models, Prediction, Children, Adolescents