ECSS Paris 2023: OP-AP01
INTRODUCTION: Relaxation techniques have been shown to improve both sleep quality and quantity, potentially playing a critical role in increasing the individual coping ability when facing high stressor (1). However, their role in performance improvement is understudied, especially in the endurance context. Thus, the aim of this study is to determine whether relaxation techniques may improve a cycle-ergometer time-to-exhaustion task. Moreover, we explored the effects of two relaxation techniques with different mechanisms: Yoga Nidra (YN), a guided relaxation technique that induces a hypnagogic state blending deep rest with conscious awareness (1), and Body Scan (BS), a progressive muscle relaxation (PMR) technique that enhances bodily awareness while reducing muscular tension (2). Their influence on both performance and sleep parameters were assessed. METHODS: Thirty-six participants performed four cycling sessions until exhaustion on a cycle-ergometer. The first two sessions aimed to determine the heart rate deflection point to ensure a comparable load across participants, while the third and fourth sessions worked as baseline (T0) and post-intervention (T1) tests, respectively. Participants were randomly assigned to either a relaxation technique group (YN; BS) or a Control (C) group. In each case, they underwent five days of their respective intervention between T0 and T1. From the second session onward, sleep was monitored using actigraphy-based monitoring for a total of 10 - 12 nights, depending on weekend presence. RESULTS: First, we analyzed performance outcomes in the TTE test through a within-between-subjects RM-ANOVA to compare the time to complete the task associated with groups. The analysis showed improvements for both YN and BS groups when compared to the C group with a small effect (F = 1.07, n² = 0.04): YN: T0=15,2±1,5min; T1=16,3±1,7min. BS: T0=14,9±1,4min; T1=16,5±1,5min. C: T0=17±1,3min; T1=15±1,3min. A RM MANOVA was performed for sleep variables and significant differences for groups were noted (p=0.04). Particularly, differences in the number of awakenings were found per group (F=3.48, p=0.03, n2=0.02) and time (F=4.90, p=0.02; n2=0.02): YN: T0=16±4; T1=14±4. BS: T0=17±6; T1=16±5. C: T0=16±5; T1=16±5. Moreover, a trend was found in the interaction group*time for sleep latency (F=2.41; p=0.09; η2=0.01): YN: T0=26±21min; T1=19±18min. BS: T0=15±15min; T1=20±19min. C: T0=18±19 min; T1=17±17min. CONCLUSION: In this study, relaxation techniques seem to be a promising approach to improve sleep quality and endurance performance. Regarding the two adopted techniques, YN yielded the most positive sleep effects, decreasing both the time to fall asleep and the number of awakenings after sleep onset, two crucial indicators for sleep quality. References 1 Rusch et al., 2019 (doi: 10.1111/nyas.13996) 2 di Fronso et al., 2024 (doi: 10.1016/j.heliyon.2024.e24180) 3 Pelka et al., 2016 (doi.org/10.1016/j.peh.2016.05.003)
Read CV Gianluca Di PintoECSS Paris 2023: OP-AP01
INTRODUCTION: The Critical Power (CP) model describes the link between power and exercise duration and rests on two key assumptions: (i) the existence of a CP, representing the asymptote of the power-duration curve, and (ii) a fixed amount of work that can be performed above CP, referred to as the curvature constant (W). Previous research shows that test duration affects CP and W’, with shorter trials yielding lower W’; however, it is unclear if this is due to the higher CP estimates or a true reduction in W’. Additionally, W exhibits a consistently large standard error of estimation, and its physiological significance remains unclear (1). Therefore we examine the difference between W and the actual work above CP (W>CP) at different intensities using different CP models and explore associations between W’, W>CP, and well-established anaerobic markers. METHODS: Nineteen cyclists completed a ramp test to determine the power at peak oxygen uptake (MAP). Then, they performed five trials to exhaustion (Tlim) at 130%, 115%, 100%, 85%, and 80% of MAP, and a Wingate test. Accumulated oxygen deficit (AOD) for each Tlim was calculated. CP and W, were computed by the 2- and 3-parameter hyperbolic models (2HYP and 3HYP), the Work-Time model (W-T), and the inverse-time model (1/T). Actual W>CP during all Tlim were calculated. Pearson correlations were conducted to evaluate associations among variables and repeated measures ANOVA followed by Bonferroni post-hoc procedures to detect significant differences among conditions. Significance was set at P<.05. All data are expressed as mean ± SD. RESULTS: W derived from 2HYP and 3HYP were significantly higher than W>CP at 130, 115, and 100% MAP (P<.01). For both models, the W>CP was higher at 85 and 80% compared with 130 and 115% MAP (P<.05). W derived from W-T and 1/T were significantly higher than the actual W>CP at 80% MAP (P<.05). Notably, the W>CP predicted by W-T was lower at 130% and 115% MAP compared to 100% and 85% MAP (P<.05). A positive association was found between peak and mean power of the Wingate test, and the W>CP during Tlim at or above 100% MAP, regardless of the model used (P<.05). No significant correlations were observed between W (irrespective of the model) and maximal AOD. However, the W>CP during the 130% MAP trial was correlated with the corresponding AOD for all models (P<.05). Additionally, for the two hyperbolic models, this relationship also appeared for the W>CP at 115% MAP (P<.05). CONCLUSION: Our findings highlight that W’ may not be constant as previously assumed. Indeed, W>CP shows an intensity-dependent behaviour, with lower values for shorter efforts, increasing for longer efforts until reaching a plateau at intensities between CP and MAP. Furthermore, W shows weak correlations with AOD and Wingate test results, reinforcing that W alone cannot fully capture an athlete’s anaerobic capacity. 1. Maturana et al 2017, JSAMS
Read CV Simone Di GennaroECSS Paris 2023: OP-AP01
INTRODUCTION: Menstrual cycle (MC) and oral contraceptives (OC) create distinct hormonal environments. While MC phases are characterized by dynamic fluctuations of endogenous estrogen and progesterone, OC use suppresses these hormones, replacing them synthetically. Despite evidence suggesting phase-dependent variations in performance during the MC (1) and potential impairments under OC use due to hormonal suppression (2), findings remain inconsistent. To further address uncertainties, we conducted standardized testing across MC and OC cycles focusing on within-group changes and potential between group differences. METHODS: Twenty-two eumenorrheic women (age: 30±5y, VO2peak: 43±6ml/min/kg) and six women using OC (age: 29±5y, VO2peak: 46±6ml/min/kg) performed standardized tests in specified phases (MC: early follicular (EFP), ovulatory (OP), midluteal phase (MLP); OC: early inactive pill (EIPP), late inactive pill (LIPP), mid active pill phase (MAPP)) for one (n=6), two (n=22) or three test cycles (n=1). Testing included the Short Recovery and Stress Scale (SRSS), assessment of heart rate measures (RR, HR, RMSSD, SDNN, DFAa1) at rest (pre- and post-exercise), and during a 15-minute submaximal incremental cycling test (SCT) with intensities set at 90% of first ventilatory threshold (VT) 1, 110% VT1, and 100% VT2. SCT included blood lactate concentration (BLC) testing and rating of perceived exertion (RPE). Linear mixed-effects models and Cohens d were used to analyze data for MC, while descriptive analyses and Cohens d were applied for OC due to the small sample size. RESULTS: Pre-exercise SDNN showed MC effects (p=0.037), particularly between MLP with EFP (p=0.083, d=0.58) and OP (p=0.052, d=0.44). SRSS subscales emotional balance (EB; p=0.038) and emotional imbalance (EI; p=0.031) were significantly affected, notably between EFP and OP in MC (EB: 4.23 vs. 5.08, p=0.034, d=-0.55; EI: 3.66 vs. 2.70, p=0.039, d=0.57). In OC, all subscales except from EB, showed a substantial change between EIPP and LIPP or EIPP and MAPP (d>0.80). During SCT, most parameters were unaffected by MC and OC, except RPE, which showed significant MC effects (p<0.001) with moderate changes between EFP and OP for the first (11.9 vs. 11.3, p=0.024, d=0.59) and second intensity stage (15.1 vs. 14.6, p=0.073, d=0.50), and substantial changes for OC between EIPP and LIPP for the first stage (11.0 vs. 10.4, d=1.55). CONCLUSION: MC and OC phases had limited physiological but notable psychological effects . EFP (MC) and EIPP (OC) were associated with higher perceived stress and lower recovery. A closer examination of the SRSS subscales exhibited primarily emotional changes for MC, while OC showed substantial alterations in other facets like lack of activation or physical performance capacity. These findings emphasize the role of hormonal variability in psychological outcomes, even when physiological parameters remain largely unaffected. REFERENCES: 1. McNulty et al., Sports Med. 2020 2. Elliott-Sale et al., Sports Med. 2020
Read CV Marcelle SchaffarczykECSS Paris 2023: OP-AP01