European journal of sport science最新文献

Mental health has become increasingly important for the applied sport psychologist, a factor which may include screening, promoting literacy, individual support, and educational programs. However, despite of this importance, few checks have been made on the perceived preparedness of sport psychologists to undertake this work and whether differences may exist between those recently qualified compared to experienced practitioners. Underpinned by the theoretical domains framework, 62 Health and Care Professions Council registered practitioner sport and exercise psychologists (30 females: age: M = 46.13 years and SD = 10.44 years and 32 males: age: M = 43.25 years and SD = 10.47 years) completed an online survey to assess whether they felt equipped to address the mental health dimension of their work. The survey comprised three sections: Demographic and background information, a series of statements (n = 31) adapted from the determinants of implementation behavior questionnaire, and three questions with space for free text comments, inviting participants to explain their level of preparedness to incorporate and deliver mental health interventions. A 6 × 12 analyses of variance yielded significant differences between domain ratings but not across levels of experience or interactions. Data from free text comments were analyzed thematically and categorized into the following three themes: (a) complementing the performance role, (b) awareness of professional boundaries, and (c) importance of further continued professional development. Combined, although practitioners emphasized importance, preparedness ratings ranged from neutral to somewhat agree, calling for further specific sport psychology-based mental health training.

The effects of air pollution on health outcomes are well-established. However, little is known about perceptions of air pollution and how it may influence exercise behaviours. The aim of this study was to understand the perceived importance of air pollution during planned exercise, and where relevant, explore how those perceptions may differ between those living in different locations. A questionnaire was disseminated to several running and cycling clubs in the United Kingdom, covering population characteristics to determine urban, rural or coastal residents and exercisers, self-reported asthma, perceptions of air quality during active travel, planned exercise and attitudes towards learning more about the topic. Anonymised responses were gained from 381 adult participants (≥18 years and 60% female), 119 of whom answered questions related to active travel. More than half (54%) of all respondents think about the air quality they are exposed to during exercise and how it may affect their health. More urban than rural respondents (59% vs. 47% and p = 0.03) think about air quality and the impact it may have on their health when exercising. There were insufficient coastal respondents for direct comparison. Most survey respondents (57%) state that they would take the most severe course of action regarding exercise behaviour by avoiding it altogether during periods of heavy road traffic. Individuals with self-reported asthma (n = 60), irrespective of place of residence, are the most likely to be conscious of the potential effects of air pollution on their health and exercise performance compared to counterparts without self-reported asthma.

Strong relationships exist between sprint cycling torque and isometric mid-thigh pull (IMTP) force production at one timepoint; however, the relationships between the changes in these measures following a training period are not well understood. Accordingly, this study examined the relationships in the changes of sprint cycling torque and IMTP force following six-weeks of sprint cycling and resistance training performed by strength-trained novice cyclists (n = 14). Cycling power, cadence, torque and IMTP force (Peak force [PF]/torque, average and peak rate of force/torque development [RFD/RTD], and RFD/RTD from 0 to 100 ms and 0–200 ms) were assessed before and after training. Training consisted of three resistance and three sprint cycling sessions per week. Training resulted in improvements in IMTP PF (13.1%) and RFD measures (23.7%–32.5%), cycling absolute (10.7%) and relative (10.5%) peak power, peak torque (11.7%) and RTD measures (27.9%–56.7%). Strong-to-very strong relationships were observed between cycling torque and IMTP force measures pre- (r = 0.57–0.84; p < 0.05) and post-training (r = 0.63–0.87; p < 0.05), but no relationship (p > 0.05) existed between training-induced changes in cycling torque and IMTP force. Divergent training-induced changes in sprint cycling torque and IMTP force indicate that these measures assess distinct neuromuscular attributes. Training-induced changes in IMTP force are not indicative of training-induced changes in sprint cycling torque.

Aim of the study was to analyze the metabolic profile of badminton matches and training drills. Therefore, 11 male (23.2 ± 3.8 years, 182 ± 7 cm, 74.4 ± 8.4 kg) and five female (19.3 ± 1.5 years, 170 ± 6 cm, 62.6 ± 9.2 kg) elite badminton players participated in either a training match (T_M; n = 7) and/or three protocols of multifeeding drills (T₁₀, T_30, T_50; n = 13), that varied in interval and rest durations (10 s/10 s, 30 s/30 s, 50 s/50 s). Absolute and relative energetic costs (W_tot and E_tot) and contribution to oxidative (W_Oxid), phosphagen (W_PCr), and anaerobic glycolytic (W_La) metabolism were calculated by the three-component PCr-La-O₂-method based on an indirect calorimetric approach from oxygen consumption during exercise, post exercise, and net blood lactate concentration. A novel intermittent approach was used to consider replenishment of phosphocreatine during each resting phase. Results show that during T_M, E_tot was 676 ± 98J·kg⁻¹ min⁻¹, while metabolic pathways contributed by 56.9 ± 8.6% (W_Oxid), 42.7 ± 8.7% (W_PCr), and 0.4 ± 0.6% (W_La). In the multifeeding drills E_tot was comparable between T₁₀ (1020 ± 160J·kg⁻¹ min⁻¹) and T₃₀ (985 ± 173 J·kg⁻¹ min⁻¹) but higher in T₅₀ (1266 ± 194J·kg⁻¹ min⁻¹) (p < 0.001). Relative contribution of W_Oxid was lower in T₁₀ (47.3 ± 7.7%) but similar in T₃₀ (56.5 ± 6.2%) and T₅₀ (57.3 ± 6.0%) (p < 0.001). W_PCr was highest in T₁₀ (51.1 ± 8.3%) followed by T₃₀ (42.2 ± 6.9%) and lowest in T₅₀ (31.2 ± 7.7%) (p < 0.001). W_La was similar between T₁₀ (1.6 ± 1.0%) and T₃₀ (2.1 ± 1.0%) but higher in T₅₀ (11.6 ± 4.8%) (p < 0.001). Concludingly, metabolic costs in badminton are predominantly covered by oxidative and phosphagen energetic pathways. Metabolic profiles of the multifeeding drills differ depending on rally/interval duration, with increasing contribution of anaerobic glycolysis and decreasing phosphagen contribution in case of longer intervals.

It has been suggested that time at a high fraction (%) of maximal oxygen uptake (VO_2max) plays a decisive role for adaptations to interval training. Yet, no study has, to date, measured the % of VO_2max during all interval sessions throughout a prolonged training intervention and subsequently related it to the magnitude of training adaptations. Thus, the present study aimed to investigate the relationship between % of VO_2max achieved during an interval training intervention and changes in endurance performance and its physiological determinants in well-trained cyclists. Twenty-two cyclists (VO_2max 67.1 (6.4) mL·min⁻¹ ·kg⁻¹; males, n = 19; females, n = 3) underwent a 9-week interval training intervention, consisting 21 sessions of 5 × 8-min intervals conducted at their 40-min highest sustainable mean power output (PO). Oxygen uptake was measured during all interval sessions, and the relationship between % of VO_2max during work intervals and training adaptations were investigated using linear regression. A performance index was calculated from several performance measures. With higher % of VO_2max during work intervals, greater improvements were observed for maximal PO during the VO_2max test (R²_adjusted = 0.44, p = 0.009), PO at 4 mmol·L⁻¹ [blood lactate] (R²_adjusted = 0.25, p = 0.035), the performance index (R²_adjusted = 0.36, p = 0.013), and VO_2max (R²_adjusted = 0.54, p = 0.029). Other measures, such as % of maximal heart rate, were related to fewer outcome variables and exhibited poorer session-to-session repeatability compared to % of VO_2max. In conclusion, improvements in endurance measures were positively related to the % of VO_2max achieved during interval training. Percentage of VO_2max was the measure that best reflected the magnitude of training adaptations.

Nine cyclists (age: 26 ± 5 years, height: 168 ± 5 cm and mass 58.5 ± 4.5 kg) were observed using continuous glucose monitoring devices throughout a training camp. Interstitial glucose [iG] data were captured via the Abbott libre sense biosensor (Abbott Laboratories) and paired with the Supersapiens software (TT1 Products Inc.). [iG] data were split into time ranges, that is, overall (24-hourly), day-time (06:00–23:59), night-time (00:00–05:59) and exercise. [iG] data were stratified into percentage of time, below range ([TBR] < 70 mg/dl), in range ([TIR] 70–140 mg/dl) and above range ([TAR] ≥ 141 mg/dl). Differences in diurnal and nocturnal data were analysed via repeated measures analysis of variance and paired t-tests where appropriate. p-value of ≤0.05 was accepted as significant. Riders spent an average of 3 ± 1% TAR, 93 ± 2% TIR and 8 ± 3% TBR. Mean 24 h [iG] was 93 ± 2 mg/dl with a coefficient of variation (CV) of 18 ± 1%. Mean (day: 95 ± 3 vs. night: 86 ± 3 mg/dl and p < 0.001) and CV (day: 18 ± 1 vs. night: 9 ± 1% and p < 0.001) in [iG] were higher during the day-time hours. TAR was greater during the day (day: 3 ± 1 vs. night: 0 ± 0% and p < 0.001) but TBR and TIR were similar. Glucose levels below the clinical range may have implications for those without diabetes and warrants further investigation.

Selecting the right individuals for a sports team, organization, or military unit has a large influence on the achievements of the organization. However, the approaches commonly used for selection are either not reporting predictive performance or not explainable (i.e., black box models). In the present study, we introduce a novel approach to selection research, using various machine learning models. We examined 274 special forces recruits, of whom 196 dropped out, who performed a set of physical and psychological tests. On this data, we compared four machine learning models on their predictive performance, explainability, and stability. We found that a stable rule-based (SIRUS) model was most suitable for classifying dropouts from the special forces selection program. With an averaged area under the curve score of 0.70, this model had good predictive performance, while remaining explainable and stable. Furthermore, we found that both physical and psychological variables were related to dropout. More specifically, a higher score on the 2800 m time, need for connectedness, and skin folds was most strongly associated with dropping out. We discuss how researchers and practitioners can benefit from these insights in sport and performance contexts.