Tiago Manuel Barbosa

This study examined inter-limb hand force asymmetry in competitive swimmers during front crawl at two paces (200 m and 50 m). Eight national-level swimmers (18.3 ± 2.5 years) performed 25 m trials at both intensities using wearable force-sensing paddles. Asymmetry was assessed with a traditional percentage-based index (BAI-1) and distribution-based estimates, namely the Minimal Detectable Difference (MDD) and an exploratory Minimal Important Difference (MID) estimate. Mean hand force was significantly higher at sprint pace (50 m) compared to 200 m pace (p < 0.001), confirming adherence to the prescribed intensities. Using BAI-1, swimmers showed a wide range of asymmetry values (10%), highlighting substantial inter-individual variability. Absolute BAI-1 was descriptively higher during the 50 m pace than during the 200 m pace, although this difference was not statistically significant. Distribution-based estimates refined the interpretation: MDD corresponded to 4.48% and 4.83% for the 50 m and 200 m paces, respectively, whereas the exploratory MID estimate corresponded to 2.68% and 2.89%. These findings illustrate how BAI-1, MDD, and MID may lead to complementary interpretations of asymmetry. The combined use of traditional indices and distribution-based estimates may support more individualized monitoring of inter-limb hand force asymmetry in swimming and potentially other bilateral sports.

Background and Objectives: Intra-cyclic variation in swimming velocity is one of the variables most commonly used to assess swimming performance, providing simple, straightforward information for coaches and swimmers. Therefore, the main aim of this study was to assess the consistency and association between the two most commonly used methods for calculating the intra-cyclic variation in velocity in swimming (coefficient of variation—dv1; and range: the difference between the maximum and minimum instantaneous velocities—dv2). Methods: Twenty-one young butterfly swimmers (11 males and 10 females) with an average age of 17.3 ± 2.8 years were recruited for analysis. The measurements were done in the butterfly stroke at maximal velocities. The consistency and association criteria included the intraclass correlation coefficient (ICC) and simple linear regression between the two methods. Results: The ICC between dvs was excellent for the overall sample (ICC = 0.972, p < 0.001), males (ICC = 0.978, p < 0.001), and females (ICC = 0.955, p < 0.001). The linear regression between methods was very high (overall: R² = 0.93, p < 0.001; males: R² = 0.91, p < 0.001; females: R² = 0.86, p < 0.001). Conclusions: Overall, coaches and researchers should be aware that although both methods yielded highly concordant results, they are based on different mathematical formulations and quantify distinct characteristics of the velocity signal. Therefore, their consistency and association should not be interpreted as mathematical equivalence or universal interchangeability.

Morais, JE and Barbosa, TM. Why swimmers go faster: Discriminating swimming velocity using propulsive force and arms coordination. J Strength Cond Res 40(11): e1258–e1262, 2026—The aim of this study was to determine whether propulsive force (PF) was associated with changes in the index of coordination (IdC) and whether both metrics were associated with swimming velocity in the front crawl stroke. The sample comprised 12 swimmers (9 males and 3 females) with an average age of 17.5 ± 1.2 years. Two swimming paces were considered: 200- and 50-m (all-out) paces. A univariate general linear model was used to examine the effect of the independent variables on the dependent variables, and effect sizes (Cohen's d and eta square—η ² ) were also calculated. Swimming velocity ( p < 0.001, d = 2.02) and PF ( p < 0.001, d = 1.71) increased between 200- and 50-m pace. The IdC changed between paces ( p < 0.001, d = 3.16), shifting from a catch-up to superposition mode. The IdC model retained the PF as a predictor ( p = 0.026, η ² = 0.21). The swimming velocity model retained the PF ( p = 0.004, η ² = 0.35) and IdC ( p = 0.050, η ² = 0.18) as predictors. Altogether, these findings indicate that greater PF and a superposition IdC were responsible for the fastest velocities. Coaches and researchers should be aware that increasing PF will promote a change in the swimmers' IdC (less time between propulsive phases), ultimately allowing swimmers to achieve the fastest velocities.

Osteoporosis and functional decline are major health concerns among postmenopausal women. Identifying factors associated with exercise responsiveness may improve understanding of interindividual variability in exercise adaptations and support the development of more individualized intervention strategies. This study investigated whether baseline body composition, bone health, and functional fitness characteristics were associated with exercise responsiveness in postmenopausal women. Eighty women participated in a 30-week supervised multicomponent exercise program and were classified as responders or non-responders according to changes in functional performance following the intervention. Body composition and bone health were assessed by dual-energy X-ray absorptiometry (DXA), and functional fitness was evaluated using the Senior Fitness Test battery. Unadjusted analyses suggested small differences in baseline Z-score (p = 0.038) and upper-body flexibility assessed by the Back Scratch test (p = 0.030), while total bone mineral content showed a trend toward significance (p = 0.056). However, none of these differences remained statistically significant after Benjamini–Hochberg false discovery rate correction. As a complementary analysis, multiple linear regression adjusted for baseline performance identified baseline body mass (p = 0.007), total bone mineral content (p = 0.018), and upper-body flexibility (p = 0.020) as factors independently associated with post-intervention functional performance. Exploratory machine learning analyses demonstrated limited ability to discriminate responders from non-responders using baseline characteristics alone, although Random Forest variable importance highlighted similar variables to those identified in the regression analysis. Overall, these findings suggest that baseline musculoskeletal characteristics alone are insufficient to accurately classify exercise responsiveness and that larger studies incorporating additional clinical, behavioural, physiological, and biological variables are needed to improve individualized exercise prescription.

Swimming performance is strongly influenced by the balance between propulsion and drag (Toussaint & Beek, 1992). Propulsion is the swimmer’s ability to generate force in the water to propel forward...

High-intensity interval training (HIIT) has emerged as a time-efficient exercise strategy with potential benefits for older adults. However, evidence regarding its effects on functional fitness, body composition, and quality of life in older women remains limited. This randomized controlled trial included community-dwelling older women allocated to a HIIT group or a control group. The intervention consisted of a 65-week HIIT program (3 sessions/week), while the control group maintained usual activities. Functional fitness was assessed using standardized field-based tests, body composition was evaluated by bioelectrical impedance analysis, and quality of life was measured using the WHOQOL-BREF questionnaire. Pre- and post-intervention assessments were performed under standardized conditions. Data were analyzed using mixed ANOVA models, with significance set at p < 0.05. Compared with the control group, the HIIT group significantly improved aerobic capacity (2MST: +25.4 vs. −19.6 repetitions; p < 0.001), lower-limb strength (30s CST: +4.8 vs. −2.6 repetitions; p < 0.001), and mobility (TUG: −0.3 vs. +0.4 s; p < 0.001). Body composition improved with reductions in body fat percentage (−1.8% vs. +1.9%; p < 0.001) and visceral fat index (−0.6 vs. +0.3; p < 0.001), alongside increased total body water (+2.3% vs. −1.8%; p < 0.001). Quality of life improved significantly in physical, psychological, and environmental domains (p < 0.001). HIIT was associated with improvements in functional fitness, body composition, and quality of life, with no major adverse events reported. These findings support the use of HIIT as a practical intervention to enhance health and functional independence in aging populations.

The aim of this study was to analyse lap performance stability, stroke kinematic variables in the clean swimming phase and turn performance in the finals of the four 200 m short course (SCM) events (freestyle, backstroke, breaststroke, and butterfly). The sample included thirty-two elite female swimmers who competed in the 200 m finals at the 2019 LEN European Short Course Championships in Glasgow. Lap times, stroke kinematics, and turns were analysed using two approaches: (i) official lap time comparison (50 m), and; (ii) comparison of consecutive segments (25 m). Based on the official lap time comparison, performance significantly decreased over time (p < 0.001) with strong effect sizes in all strokes (η ² between 0.89 and 0.96). Pairwise comparisons between consecutive 25 m segments were not significant. Turn time increased in all four strokes with strong effect sizes (p < 0.001; η ² between 0.71 and 0.84). The start contributed ∼6% and turns ∼52% of the total race time. These findings highlight that traditional pacing analysis based on official splits may lead to misleading interpretations of performance in SCM events. Analysing 25 m segments provides a more accurate representation of race dynamics and contributes to a clearer understanding of pacing stability in short-course swimming.

Introduction: Postmenopausal aging is accompanied by declines in functional fitness, changes in body composition, and increased osteoporosis risk, which may affect quality of life. Understanding how these factors interrelate is important for supporting healthy aging. Objective: To examine the associations between accelerometer-measured physical activity, functional fitness, DEXA-derived body composition and bone parameters, and quality of life in postmenopausal women. Methods: Forty community-dwelling postmenopausal women (68.7 ± 5.7 years) participated in this cross-sectional study. Physical activity was assessed using a wrist-worn accelerometer for seven days. Body composition and bone health were measured by DEXA, functional fitness by the Senior Fitness Test, and quality of life by the WHOQOL-BREF. Spearman correlations were applied. Results: Associations were predominantly weak to moderate. Higher-intensity physical activity showed the strongest association with the Physical Health domain of quality of life (ρ ≈ 0.29). Total bone mineral density was also positively associated with perceived physical health (ρ ≈ 0.36). Adiposity was inversely related to light and lifestyle activity. Conclusion: Physical activity, functional fitness, body composition, and perceived physical health co-occur in postmenopausal women, supporting the relevance of promoting active lifestyles in this population.