Journal of science and medicine in sport最新文献

Objectives: Monitoring body composition can help to optimize performance in female athletes. This study aimed to create a conversion equation between dual-energy X-ray absorptiometry-measured body fat percentage and ultrasound-measured subcutaneous thigh fat thickness in Division I female athletes as a more accessible, cost-effective alternative.

Design: Cross-sectional study.

Methods: We enrolled 82 Division I female athletes. Dual-energy X-ray absorptiometry was used to assess body fat percentage. Bilateral panoramic thigh ultrasound scans at 50 % of the femur length were used to calculate subcutaneous fat thickness overlying the rectus femoris muscle. The dataset was divided into a training (70 %, n = 57) and holdout (30 %, n = 25) sample to develop and validate the conversion equation, respectively. Using the training sample, a stepwise, linear regression was used to predict dual-energy X-ray absorptiometry body fat percentage from ultrasound fat thickness, mass, and height. Beta coefficients from this model were used to create a conversion equation. After applying the conversion equation to the holdout sample, intraclass correlation coefficients (ICC_2,k) and Bland-Altman plots were used to establish the agreement between the ultrasound-estimated and DXA-derived percent body fat.

Results: Within the training sample, dual-energy X-ray absorptiometry was significantly associated with ultrasound fat thickness, height, and mass (F = 31.9; p < 0.001; R² = 0.64). Within the holdout sample, when using the conversion equation to estimate body fat percentage, we found a strong agreement between estimated and DXA-derived percent body fat (ICC_2,k = 0.93; 95 % CI: 0.83-0.97).

Conclusions: Ultrasound-assessed subcutaneous thigh fat thickness predicts dual-energy X-ray absorptiometry-assessed body fat percentage in Division I female athletes.

Objectives: Sufficient gross motor skill proficiency is an essential prerequisite for the successful performance of sport-specific skills and physical activities. The Test of Gross Motor Development is the most common tool for assessing motor skills in paediatric populations, however, there is a lack of 'normative' data available against which children's scores can be compared. Normative data would enable the comparison of an individual's motor development to age-standardised norms. The aim of this study was to develop normative data for the Test of Gross Motor Development Third Edition scores for Italian children.

Design: The Test of Gross Motor Development Third Edition scores from >17,000 Italian children (aged 3-11+years) were analysed to develop normative scores and percentiles.

Methods: Total Test of Gross Motor Development Third Edition scores and locomotor and ball skills subscale scores were split by age and sex. Using the LMS method, based on the Box-Cox transformation, percentiles were calculated for each sex-specific age category.

Results: 17,026 children were included in the analysis (n=8262 girls; n=8766 boys).

Conclusions: This is the largest sample ever used to develop normative data for the Test of Gross Motor Development and the first set of normative data for European children. This normative data can be used to identity insufficient motor skill development and aid subsequent modification of activities to nurture sufficient motor skill proficiency. This is particularly important for children in the lower percentiles given the strong associations between early childhood fundamental motor skill competence and physical activity participation in adolescence and adulthood.

Objectives: To evaluate sport-specific basketball skills before and after 8 months of integrated and non-integrated basketball practice of participants with intellectual disability; in relation to the competitive basketball level and the degree of intellectual disability.

Design: Pre-test/training/post-test design.

Methods: Forty-one adult male players with intellectual disability were randomly divided into 21 athletes playing in the Integrated Basketball group together with 10 athletes without intellectual disability, and 20 athletes playing in the Non-integrated Basketball group. All players were assessed through pre and post basketball skill tests for assessing four levels of ability of increasing difficulty (levels I, II, III, and IV), each one characterized by the fundamental skills of the basketball game: ball handling, passing, receiving, and shooting. The athlete's global score based on the total score of all levels of ability was calculated for each player.

Results: Passing, receiving, shooting, ball handling, global, level I, and level II scores improved after the intervention independently by integrated basketball or non-integrated basketball. Post-pre (∆) scores in ball handling, receiving, passing, shooting, global, level I, and level II showed that the athletes in the Integrated Basketball group improved significantly more than athletes in the Non-integrated Basketball group. Ball handling, receiving, passing, shooting, global, level I, level II, and level III scores were negatively correlated with intellectual disability level.

Conclusions: Athletes with intellectual disability who performed both integrated basketball and non-integrated basketball improved significantly their basketball skills after an 8-month training. However, the athletes training in the Integrated Basketball group obtained the best scores.

Objective: This study aimed to systematically investigate whether polarized or non-polarized training leads to greater physiological and performance adaptations in cyclists.

Design: A systematic review and meta-analysis were conducted, focusing on interventions categorized as polarized, non-polarized, or unclear. Inclusion criteria required participants to be at least recreationally trained cyclists (VO_2max ≥ 59 ml/kg/min) and interventions lasting > 4 weeks.

Methods: A multi-level random-effects meta-analysis using restricted maximum likelihood estimation was performed. A multivariate meta-regression assessed associations between training volume, VO_2max, and time-trial performance.

Results: Forty-one studies, comprising 81 training groups and 797 participants, were included. Training significantly improved VO_2max across all groups (g = 0.42, 95 % confidence interval = 0.31-0.53, P ≤ 0.001) and time-trial performance (g = 0.39, 95 % confidence interval = 0.25-0.53, P ≤ 0.001), with no significant differences between training modalities (P > 0.05). Longer intervention durations positively influenced VO_2max (g = 0.03, 95 % confidence interval = 0.02-0.05, P < 0.001) and time-trial performance (g = 0.04, 95 % confidence interval = 0.03-0.06, P < 0.001). No associations were found between weekly or total training volume and changes in VO_2max or time-trial performance.

Conclusions: Polarized and non-polarized training modalities yield comparable improvements in VO_2max and time-trial performance in trained cyclists. Beyond achieving a necessary training volume, further increases do not appear to enhance performance. These findings encourage athletes and coaches to prioritize effective training distribution rather than fixating on total volume or a specific model.

Objectives: This study aimed to assess relationships of acute responses to short-format high-intensity interval training (HIIT) with the anaerobic speed reserve (ASR) of adolescent runners.

Design: Pre-post intervention design.

Methods: Eighteen highly-trained youth runners (15.83 ± 0.86 years) underwent maximal sprinting speed (MSS) and maximal aerobic speed (MAS) assessments to determine ASR (MSS minus MAS) and a standardized HIIT protocol (2 × (20 × 15 s/15 s @110 % MAS)) was administered. Pre/post-HIIT assessments included biochemical (i.e., creatine kinase (CK)), neuromuscular (countermovement jump, CMJ; reactive strength index, RSI), cardiac (i.e., heart rate recovery (HRR)), and athlete-reported outcome measures (e.g., single item for fatigue). Pearson's r was calculated to assess relationships between acute responses and ASR, MSS, MAS, and relative intensity of the HIIT (%ASR).

Results: Athletes' ASR and %ASR were significantly associated with the pre/post difference of CK (r = -0.75; p < 0.001; r = 0.74; p < 0.001, respectively), CMJ height, and RSI (r ≥ 0.69; p ≤ 0.002; r ≤ -0.49; p ≤ 0.04, respectively). However, HRR did not correlate significantly with ASR or %ASR (r ≤ 0.37, p ≥ 0.131, r ≥ -0.31; p ≥ 0.22, respectively). The pre/post difference of RSI correlated with MAS (r = -0.54; p = 0.02), and the pre/post difference of CK (r = -0.50; p = 0.034) and of CMJ height (r = 0.76; p < 0.001) with MSS. Regarding athlete-reported measures, ASR and %ASR showed significant associations with most fatigue and recovery variables (r ≥ 0.57; p ≤ 0.014, r ≥ 0.57; p ≤ 0.013, respectively). The pre/post difference of the single item for fatigue showed a positive relationship with MSS (r = 0.49; p = 0.037).

Conclusions: Acute biochemical, neuromuscular, and athlete-reported responses to short-format HIIT showed strong relationships with ASR and MSS, indicating higher internal load in athletes with a lower ASR and MSS by using a higher %ASR, compared to athletes with a higher ASR and MSS. These findings can help to tailor training programs to individual needs and avoid possible overload.

Objectives: To examine the validity and reliability of the Simple Motor Competence-check for Kids (SMC-Kids), which was developed to assess motor development in preschool children.

Design: A cross-sectional and repeated-measures design.

Methods: To assess validity, 71 children aged 4-6 years completed the Test of Gross Motor Development-3 (TGMD-3) and SMC-Kids (10 m shuttle run and paper ball throw). For inter-rater reliability, 91 children aged 3-6 years performed the SMC-Kids test, twice, by two different raters. To evaluate intra-rater reliability and quantify improvements beyond measurement error, 53 participants were reassessed by the same rater 7-10 days later.

Results: Spearman's rho between the 10 m shuttle run and the TGMD-3 locomotor score was -0.51 (95 % CI: -0.31, -0.66), and between the paper ball throw and TGMD-3 ball skill score was 0.80 (95 % CI: 0.70, 0.87). Confirmatory factor analysis showed strong associations of the 10 m shuttle run and paper ball throw with latent variables of locomotor and object control skills, with factor loadings of -0.97 and 0.88, respectively. Both tests showed good-to-excellent inter-rater (ICC = 0.898-0.96) and intra-rater reliabilities (ICC = 0.882-0.974). The smallest worthwhile changes were 0.25 s for the 10 m shuttle run and 0.42 m for the paper ball throw, with double coefficients of variation of 0.46 s and 0.99 m, and MDC 95 of 0.82 s and 1.52 m, respectively.

Conclusions: SMC-Kids is a simple tool to quickly measure preschooler locomotor and object control skills without the need for special equipment or large spaces.

Objectives: To explore the perspectives and experiences of Accredited Exercise Physiologists (AEPs) regarding their integration within the Australian healthcare setting.

Design: A qualitative descriptive approach utilising semi-structured interviews.

Methods: Practicing AEPs (n = 15) completed interviews via videoconferencing between May and July 2023. Interviews were digitally transcribed, and data analysed using reflexive thematic analysis.

Results: Five primary themes were identified: understanding (with three subthemes related to the general population, health professionals, and the role of an AEP in promoting greater understanding), communication (with three subthemes related to the value of communication between AEPs and the referrer, the referrer and the client, and AEPs and other health professionals), the need for greater mentorship, further education and professional development in early-career AEPs, and systemic factors (cost, access, and procedural difficulties).

Conclusions: The findings highlight the value of having AEPs co-located with other health professionals (including general practitioners) and suggest that greater education on the role and benefits of an AEP may be required. Future studies should explore the views of the general population, current clients and other health professionals to design solutions for optimising integration of AEP services within the Australian healthcare system.