More than metrics: The role of socio-environmental factors in determining the success of athlete monitoring.

The perceived value of athlete monitoring systems (AMS) has recently been questioned. Poor perceptions of AMS are important, because where practitioners lack confidence in monitoring their ability to influence programming, and performance is likely diminished. To address this, researchers have primarily sought to improve factors related to monitoring metrics, e.g., validity rather than socio-environmental factors, e.g., buy-in. Seventy-five practitioners (response rate: n = 30) working with Olympic and Paralympic athletes were invited to take part in a survey about their perceptions of AMS value. Fifty-two per cent (n = 13) was confident in the sensitivity of their athlete self-report measures, but only 64% (n = 16), indicated their monitoring was underpinned by scientific evidence. A scientific base was associated with improved athlete feedback (rS (23) = 0.487, p =0.014*) and feedback correlated with athlete monitoring adherence (rS (22) = 0.675, p = <0.001**). If athletes did not complete their monitoring, 52% (n = 13) of respondents felt performance might be compromised. However, most respondents 56% (n = 14), had worked with internationally successful athlete(s) who did not complete their monitoring. While AMS can be a useful tool to aid performance optimisation, its potential value is not always realised. Addressing socio-environmental factors alongside metric-factors may improve AMS efficacy.

The effects of sleep deprivation, acute hypoxia, and exercise on cognitive performance: A multi-experiment combined stressors study.

INTRODUCTION: Both sleep deprivation and hypoxia have been shown to impair executive function. Conversely, moderate intensity exercise is known to improve executive function. In a multi-experiment study, we tested the hypotheses that moderate intensity exercise would ameliorate any decline in executive function after i) three consecutive nights of partial sleep deprivation (PSD) (Experiment 1) and ii) the isolated and combined effects of a single night of total sleep deprivation (TSD) and acute hypoxia (Experiment 2). METHODS: Using a rigorous randomised controlled crossover design, 12 healthy participants volunteered in each experiment (24 total, 5 females). In both experiments seven executive function tasks (2-choice reaction time, logical relations, manikin, mathematical processing, 1-back, 2-back, 3-back) were completed at rest and during 20 min semi-recumbent, moderate intensity cycling. Tasks were completed in the following conditions: before and after three consecutive nights of PSD and habitual sleep (Experiment 1) and in normoxia and acute hypoxia (FIO2 = 0.12) following one night of habitual sleep and one night of TSD (Experiment 2). RESULTS: Although the effects of three nights of PSD on executive functions were inconsistent, one night of TSD (regardless of hypoxic status) reduced executive functions. Significantly, regardless of sleep or hypoxic status, executive functions are improved during an acute bout of moderate intensity exercise. CONCLUSION: These novel data indicate that moderate intensity exercise improves executive function performance after both PSD and TSD, regardless of hypoxic status. The key determinants and/or mechanism(s) responsible for this improvement still need to be elucidated. Future work should seek to identify these mechanisms and translate these significant findings into occupational and skilled performance settings.

Athlete monitoring practices in elite sport in the United Kingdom.

Athlete monitoring systems (AMS) aid performance optimisation and support illness/injury prevention. Nonetheless, limited information exists on how AMS are employed across elite sports in the United Kingdom. This study explored how athlete monitoring (AM) data, in particular athlete self-report measures, were collected, analysed and disseminated within elite sports. Thirty elite sports practitioners representing 599 athletes responded to a survey on their AM methodologies. The majority, 83%, (n = 25) utilised an AMS, and a further 84% (n = 21) stated the collection of their AMS data was underpinned by a scientific rationale. Athlete self-report measures (ASRM) were the most commonly employed tool, with muscle soreness, sleep and energy levels amongst the most frequently collected measures. The ubiquitous use of custom single-item ASRM resulted in considerable variability in the questionnaires employed, thus potentially impacting questionnaire validity. Feedback processes were largely felt to be ineffective, with 44% (n = 11) respondents indicating that athletes did not receive sufficient feedback. Some respondents indicated that AMS data was never discussed with athletes and/or coaches. Overall, significant disparities exist in the use of athlete monitoring systems between research and elite sports practice, and the athlete, coach and practitioner experience of monitoring risks being poor if these disparities are not addressed.

Assessment of Fatigue and Recovery in Sport: Narrative Review.

Fatigue is a phenomenon associated with decreases in both physical and cognitive performances and increases in injury occurrence. Competitive athletes are required to complete demanding training programs with high workloads to elicit the physiological and musculoskeletal adaptations plus skill acquisition necessary for performance. High workloads, especially sudden rapid increases in training loads, are associated with the occurrence of fatigue. At present, there is limited evidence elucidating the underlying mechanisms associating the fatigue generated by higher workloads and with an increase in injury risk. The multidimensional nature and manifestation of fatigue have led to differing definitions and dichotomies of the term. Consequently, a plethora of physiological, biochemical, psychological and performance markers have been proposed to measure fatigue and recovery. Those include self-reported scales, countermovement jump performance, heart rate variability, and saliva and serum biomarker analyses. The purpose of this review is to provide an overview of fatigue and recovery plus methods of assessments.

Training-Monitoring Engagement: An Evidence-Based Approach in Elite Sport.

PURPOSE: Poor athlete buy-in and adherence to training-monitoring systems (TMS) can be problematic in elite sport. This is a significant issue, as failure to record, interpret, and respond appropriately to negative changes in athlete well-being and training status may result in undesirable consequences such as maladaptation and/or underperformance. This study examined the perceptions of elite athletes to their TMS and their primary reasons for noncompletion. METHODS: Nine national-team sprint athletes participated in semistructured interviews on their perceptions of their TMS. Interview data were analyzed qualitatively, based on grounded theory, and TMS adherence information was collected. RESULTS: Thematic analysis showed that athletes reported their main reason for poor buy-in to TMS was a lack of feedback on their monitoring data from key staff. Furthermore, training modifications made in response to meaningful changes in monitoring data were sometimes perceived to be disproportionate, resulting in dishonest reporting practices. CONCLUSIONS: Perceptions of opaque or unfair decision making on training-program modifications and insufficient feedback were the primary causes for poor athlete TMS adherence. Supporting TMS implementation with a behavioral-change model that targets problem areas could improve buy-in and enable limited resources to be appropriately directed.

An 8-Week Exercise Intervention Based on Zumba Improves Aerobic Fitness and Psychological Well-Being in Healthy Women.

BACKGROUND: Although Zumba is practiced by millions of people worldwide, there is a paucity of research about its potential benefits. The objective of this study was to investigate the effects of Zumba on physiological and psychological outcomes in healthy women. METHODS: Cardiovascular fitness, body composition, physical self-perception and psychological well-being were assessed before and immediately after 8 weeks of Zumba performed 3 times weekly (Zumba group, n = 22, age: 26.6 ± 5.4 years old; height: 165.8 ± 7.1 cm) or no intervention (control group, n = 22, age: 27.9 ± 6.0 years old; height: 164.7 ± 6.2 cm). All variables were analyzed by a 2-way (Group × Time) analysis of variance with repeated measures, and a Bonferroni post hoc test. Pearson correlation coefficient assessed the relationship between changes in anthropometric, physiological and psychological variables. RESULTS: Zumba provided significant positive changes in maximal aerobic fitness (+3.6%), self-perception of physical strength (+16.3%) and muscular development (+18.6%), greater autonomy (+8.0%), and purpose in life (+4.4%). No significant changes were observed in the control group. In addition, some psychological changes were significantly correlated to body fat at baseline, and changes in fitness. CONCLUSIONS: These results highlight that Zumba is beneficial to improve fitness and well-being in healthy women, but does not change body composition.

Physiological load associated with a Zumba(®) fitness workout: a comparison pilot study between classes and a DVD.

The objectives were to compare the metabolic load elicited by Zumba(®) classes and DVD workouts and link the physiological responses to participants' psychological characteristics. Fifteen women (25.4 ± 4.3 years old; 164.9 ± 5.1 cm; 56.9 ± 5.8 kg; 23.9 ± 4.9% body fat) performed three Zumba(®) classes and three Zumba(®) DVD workouts using a repeated measure design. Energy expenditure was assessed by extrapolating oxygen cost from heart rate (HR) using regressions from a preliminary incremental running test. Differences between Zumba(®) classes and Zumba(®) DVD workouts were assessed by Student's T tests and repeated measures analysis of variance and correlations between physiological and psychological variables by the Pearson's coefficient. Results showed that Zumba(®) classes allowed greater energy expenditure compared to Zumba(®) DVD workouts (6.8 ± 0.9 vs 5.6 ± 0.9 kcal · min(-1), 95% confidence interval (CI) limits: 0.3-2.1, P = 0.016), with significant differences in the time spent with a HR above 85% of HR reserve (14.7 vs 1.7%, 95% CI: 5.6-20.4, P = 0.021). Furthermore, women with a greater autonomy score showed a smaller difference between DVD and class (r = 0.511, P = 0.048), while greater differences were shown in women with greater interpersonal skills (r = -0.563, P = 0.028). The results suggest that while both types of workouts are suitable to maintain fitness Zumba(®) classes allow greater energy expenditure.