ABSTRACT Accelerometry is widely used in physical activity research, but processing approaches differ across studies. This study evaluated the agreement among raw use preprocessing in the entire document metrics (Activity Counts, Activity Index, Euclidean Norm Minus One – ENMO, Mean Amplitude Deviation – MAD, and Monitor Independent Summary Unit – MIMS) derived from two devices. Participants wore ActiGraph (wGT3X‑BT) and Google Pixel Watch 2 devices (50–100 Hz) on their non‑dominant wrist for 24 h. Data were converted to minimum acceleration of the most active minutes (MX) for each metric across 1–60‑s epochs. Agreement between device‑paired MX values was assessed using mean absolute percent error (MAPE) and Bland – Altman analysis. Data from 16 participants (25.4 ± 8.9 years) showed strong agreement for MAD and MIMS MX with MAPE of 6.8% ± 7.0% and 7.1% ± 3.5%. Only MIMS showed lowest bias and consistent MAPE across epochs without compounded error, supporting its use for device‑agnostic assessment. Larger samples and additional device configurations may strengthen generalizability.

ABSTRACT The objective of this study was to improve the validity of the physical activity self-efficacy (PASE) measurement. To accomplish this objective, a latent variable approach commonly advocated, but infrequently used in practice, for determining the internal structure of response patterns to a PASE scale was systematically studied. Data were simulated using Monte Carlo experimental methods under conditions commonly observed in practice (e.g. N; exploratory/confirmatory latent variable models) to maximize potential implications for data analysis in practice. Three sets of outcomes were monitored: convergence issues, model-data fit, and parameter estimates. A one-dimensional model outperformed two-dimensional exploratory and confirmatory models when the population model was one-dimensional. A two-dimensional exploratory model outperformed a two-dimensional confirmatory model and a one-dimensional model when the population model was two-dimensional. These findings provide an initial empirical basis for fuller adherence to the long proposed, but rarely fully followed, validity guidelines for measuring PASE – though experimental-design related limitations exist.

ABSTRACT This study aimed to evaluate the accuracy and reliability of the newly developed SomatoMetrics software for somatotype calculation and to compare its performance with existing methods. The study included 132 individuals aged 28–35 years (73 males, 59 females), and anthropometric measurements were obtained using the Heath – Carter method. SomatoMetrics, developed with a Flutter-based frontend and a GoLang-based backend, provides automated error checking, standardized data entry, and graphical outputs. Its accuracy was compared with the Somatotürk and Somatotype programs. Reliability was assessed using the intraclass correlation coefficient (ICC), Pearson correlation, Bland – Altman analysis, and Cohen’s kappa coefficient. The results demonstrated very high agreement and strong correlations between methods (ICC: 0.999–1.000; Pearson r > 0.99; p < .001), with no systematic bias observed. Cohen’s kappa values also indicated excellent agreement. Overall, SomatoMetrics is a fast, accessible, and user-friendly tool that offers high accuracy and reliability in somatotype assessment.

ABSTRACT This study evaluated the validity and reliability of start detection methods for determining 5-m sprint time using a resistance device with an encoder. Seventeen recreationally trained participants completed 12 resisted 5-m sprints across two sessions. Sprint start was identified using three encoder-based methods (position, velocity [MEv], and acceleration), a rear-foot release sensor and hip-marker kinematics (KIN) as a proxy for forward center-of-mass displacement. Reliability was evaluated using intraclass correlation coefficient (ICC), coefficient of variation (CV), typical error (TE), standard error of measurement (SEM), and minimal detectable change (MDC), while agreement was examined using Pearson correlations and Bland-Altman analysis. All methods showed moderate to excellent reliability (ICC = 0.54–0.93; CV ≤ 11.1%) and strong agreement with KIN (r = 0.90–0.94). MEv showed the smallest bias (−0.00 ± 0.07 s) and narrowest 95% limits of agreement, and is therefore preferred for sprint start detection in practical settings.

ABSTRACT The need to adequately measure and foster the mental health of elite athletes, including student-athletes, is widely discussed. One commonly used tool to measure mental health is the Mental Health Continuum-Short Form. Despite its common use, there are inconsistent findings regarding the scale’s factor structure, and there is a need to further examine its measurement properties in samples of student-athletes. The current study examined the factor structure of the scale and tested measurement invariance between collegiate student-athletes and a comparison group of non-athletes (N = 539; Mage = 20.04 ± 1.53 years). A bifactor model fitstatistically better than a three factor model with correlated factors. Configural, weak, and strong measurement invariance was supported. Researchers are encouraged to examine the factor structure, indices of factor quality, and measurement invariance in future work using the MHC-SF in collegiate student-athletes.

ABSTRACT The rapid expansion of online physical education (PE) has made it difficult to assess students’ engagement in psychomotor activities. The flow scale used in this study was originally developed for face-to-face PE classes; its suitability for online instruction has not yet been tested. This study evaluated the scale’s psychometric properties for online PE lectures using Rasch analysis of survey data from 416 South Korean university students enrolled in psychomotor PE lectures. Analyses of item fit, rating-scale functioning, item difficulty, person separation reliability, and differential item functioning supported a 27-item version with clear unidimensional structure and appropriate category use. The validated scale enables instructors and researchers to monitor students’ engagement in online PE lectures, compare engagement across lectures or groups, and evaluate the impact of instructional strategies and technologies. These findings provide a measurement foundation for designing, refining, and researching online PE curricula.

ABSTRACT The purpose of this study was to analyze the intra- and inter-evaluator reliability hip adduction (HAD), internal rotation (HIR) and external rotation (HER) range of motion (ROM) tests as well as the level of agreement between evaluators with different experience levels in young adults. Fifty-four physically active adults participated. Passive HAD, HIR and HER ROM were assessed using the ROM-SPORT I method on four occasions. ROM was measured with an inclinometer by two evaluators (expert and novice). Good-to-excellent intra- and inter-evaluator reliability was observed for all tests (ICC = 0.81–0.97; TEM = 1.09º-2.60º; CVTE = 3.3–6.0%; MDC95 = 2.99º–7.1º). Agreement analyses showed low systematic bias and acceptable limits of agreement between evaluators, indicating good measurement consistency. Overall, the ROM-SPORT I method provides reliable and consistent passive hip ROM assessment in physically active adults, even when applied by evaluators with different levels of experience.

ABSTRACT This study evaluated the validity of the SENS motion® system (SENS) for classifying activity intensity (sedentary, light, moderate-to-vigorous [MVPA]) and type (sedentary, standing, walking, running, cycling) across four wear locations: thigh, hip, non-dominant, and dominant wrist. In healthy adults (n = 62), SENS classifications were compared to activity intensity from compendium-derived MET levels for structured activities in a laboratory setting. The thigh placement showed excellent agreement for classifying activity intensity (κ=0.89, 95% CI: 0.86–0.93, p < .001; 90.9% agreement) and type (κ=0.81, 95% CI: 0.76–0.86, p < .001; 90.5% agreement). Sedentary and MVPA activities were classified with excellent accuracy (means = 97.7% and 83.8%, respectively), while light activities showed mixed results (42.6–87.9%). In contrast, the hip and wrist placements showed fair-to-slight agreement (κ≤0.30) and poor accuracy for light activities. These findings support the thigh as the optimal wear location and identify performance reductions for other locations. Further research should validate the SENS in free-living conditions and diverse populations.

ABSTRACT Gait reflects multisystem integrity and predicts morbidity and functional decline, underscoring its growing recognition as a “sixth vital sign.” This study developed and validated a transparent multivariable regression equation to estimate healthy step length in adults, incorporating age, sex, height, weight, and habitual walking speed. Data from 252 healthy adults (ages 18–90 years) were analyzed using multiple linear regression with 5-fold cross-validation to assess predictive accuracy and model stability. The final model demonstrated strong performance (adjusted R2 = 0.83; RMSE = 2.88 cm). The resulting equation was: step length (cm) = –16.14 – 0.06·Age +0.31·Height − 0.04·Weight + 0.02·Sex +0.30·Walking speed. Individualized 95% prediction intervals defined normative ranges for clinical and research applications. This empirically derived model provides a reproducible and interpretable reference for assessing gait health, enabling early detection of deviation and supporting fall prevention, rehabilitation, and digital health monitoring across diverse adult populations.

ABSTRACT Flow is a multidimensional psychological state associated with optimal performance in sport, yet athletes with similar overall flow levels may differ in how flow components are structurally organized. This study examined structural variations in dispositional flow using a residual-based grouping approach and network analysis. A total of 449 Japanese university athletes completed the nine-item short version of the Dispositional Flow Scale–2. Athletes were classified into positive and negative residual groups based on deviations from competitive level predicted by years of experience. Measurement invariance across groups was established prior to network analysis. Although both groups showed identical network density, clear topological differences emerged. The positive residual group displayed a structure centered on Clear Goals, with a unique link between Unambiguous Feedback and Loss of Self-Consciousness. In contrast, the negative residual group relied primarily on Concentration on the Task, indicating greater regulatory effort. These findings highlight distinct flow dynamics despite comparable levels.