The aim of this study was to compare the effect of active (AR) and passive recovery (PR) after a high-intensive repeated sprint running protocol on physiological parameters in children and adults. Blood lactate (La) and blood pH were obtained during two sets of 5 × 5 s all-out sprints and several times during subsequent 30-min recovery in 16 children and 16 adults. End-exercise La was significantly lower and pH significantly higher in children (La: 5.21 ± 2.73 mmol·L1; pH: 7.37 ± 0.06) compared with adults (La: 10.35 ± 5.76 mmol·L−1; pH: 7.27 ± 0.10) (p > .01). La half-life during postexercise recovery was significantly shorter in children (AR: 436 ± 371 s, PR: 830 ± 349 s) than in adults (AR: 733 ± 371 s, PR: 1361 ± 372 s), as well as in active compared with passive recovery for both age groups (p > .01). The age x recovery interaction for La half-life only approached statistical significance (p = .06). The results suggest a faster lactate disappearance and an earlier return to resting pH after a repeated sprint running protocol in children compared with adults and a less pronounced advantage of active recovery in children.
Jennifer Kappenstein, Jaime Fernández-Fernández, Florian Engel and Alexander Ferrauti
Maximilian Pelka, Alexander Ferrauti, Tim Meyer, Mark Pfeiffer and Michael Kellmann
A recovery process with optimal prerequisites that is interrupted is termed disrupted recovery. Whether this process has an influence on performance-related factors needs to be investigated. Therefore, the aim of this study was to examine how a short disturbance of a recovery phase is assessed and whether subsequent repeated-sprint performance is affected by it. A quasi-experimental 2 × 2-factor crossover design with 34 sport-science undergraduate students (age 20.3 ± 2.1 y) was applied. Factors were the type of intervention (power nap vs systematic breathing; between-subjects) and the experimental condition (disturbed vs nondisturbed break; within-subject). Repeated-sprint performance was measured through 6 × 4-s sprint protocols (with 20-s breaks) before and after a 25-min recovery break on 2 test days. Subjective evaluation of the interventions was measured through the Short Recovery and Stress Scale and a manipulation check assessing whether participants experienced the recovery phase as efficacious and pleasant. Regarding the objective data, no significant difference between sprint performances in terms of average peak velocity (m/s) on the treadmill was found. The manipulation check revealed that disturbed conditions were rated significantly lower than regular conditions in terms of appreciation, t 31 = 3.09, P = .01. Short disturbances of recovery do not seem to affect subsequent performance; nevertheless, participants assessed disturbed conditions more negatively than regular conditions. In essence, the findings indicate a negligible role of short interruptions on an objective level. Subjectively, they affected the performance-related assessment of the participants and should be treated with caution.
Wigand Poppendieck, Melissa Wegmann, Anne Hecksteden, Alexander Darup, Jan Schimpchen, Sabrina Skorski, Alexander Ferrauti, Michael Kellmann, Mark Pfeiffer and Tim Meyer
Purpose: Cold-water immersion is increasingly used by athletes to support performance recovery. Recently, however, indications have emerged suggesting that the regular use of cold-water immersion might be detrimental to strength training adaptation. Methods: In a randomized crossover design, 11 participants performed two 8-week training periods including 3 leg training sessions per week, separated by an 8-week “wash out” period. After each session, participants performed 10 minutes of either whole-body cold-water immersion (cooling) or passive sitting (control). Leg press 1-repetition maximum and countermovement jump performance were determined before (pre), after (post) and 3 weeks after (follow-up) both training periods. Before and after training periods, leg circumference and muscle thickness (vastus medialis) were measured. Results: No significant effects were found for strength or jump performance. Comparing training adaptations (pre vs post), small and negligible negative effects of cooling were found for 1-repetition maximum (g = 0.42; 95% confidence interval [CI], −0.42 to 1.26) and countermovement jump (g = 0.02; 95% CI, −0.82 to 0.86). Comparing pre versus follow-up, moderate negative effects of cooling were found for 1-repetition maximum (g = 0.71; 95% CI, −0.30 to 1.72) and countermovement jump (g = 0.64; 95% CI, −0.36 to 1.64). A significant condition × time effect (P = .01, F = 10.00) and a large negative effect of cooling (g = 1.20; 95% CI, −0.65 to 1.20) were observed for muscle thickness. Conclusions: The present investigation suggests small negative effects of regular cooling on strength training adaptations.
Daniel Hammes, Sabrina Skorski, Sascha Schwindling, Alexander Ferrauti, Mark Pfeiffer, Michael Kellmann and Tim Meyer
The Lamberts and Lambert Submaximal Cycle Test (LSCT) is a novel test designed to monitor performance and fatigue/recovery in cyclists. Studies have shown the ability to predict performance; however, there is a lack of studies concerning monitoring of fatigue/recovery. In this study, 23 trained male cyclists (age 29 ± 8 y, VO2max 59.4 ± 7.4 mL · min−1 · kg−1) completed a training camp. The LSCT was conducted on days 1, 8, and 11. After day 1, an intensive 6-day training period was performed. Between days 8 and 11, a recovery period was realized. The LSCT consists of 3 stages with fixed heart rates of 6 min at 60% and 80% and 3 min at 90% of maximum heart rate. During the stages, power output and rating of perceived exertion (RPE) were determined. Heart-rate recovery was measured after stage 3. Power output almost certainly (standardized mean difference: 1.0) and RPE very likely (1.7) increased from day 1 to day 8 at stage 2. Power output likely (0.4) and RPE almost certainly (2.6) increased at stage 3. From day 8 to day 11, power output possibly (–0.4) and RPE likely (–1.5) decreased at stage 2 and possibly (–0.1) and almost certainly (–1.9) at stage 3. Heart-rate recovery was likely (0.7) accelerated from day 1 to day 8. Changes from day 8 to day 11 were unclear (–0.1). The LSCT can be used for monitoring fatigue and recovery, since parameters were responsive to a fatiguing training and a following recovery period. However, consideration of multiple LSCT variables is required to interpret the results correctly.
Thimo Wiewelhove, Christian Raeder, Tim Meyer, Michael Kellmann, Mark Pfeiffer and Alexander Ferrauti
To investigate the effect of repeated use of active recovery during a 4-d shock microcycle with 7 high-intensity interval-training (HIT) sessions on markers of fatigue.
Eight elite male junior tennis players (age 15.1 ± 1.4 y) with an international ranking between 59 and 907 (International Tennis Federation) participated in this study. After each training session, they completed 15 min of either moderate jogging (active recovery [ACT]) or passive recovery (PAS) with a crossover design, which was interrupted by a 4-mo washout period. Countermovement-jump (CMJ) height, serum concentration of creatine kinase (CK), delayed-onset muscle soreness (DOMS), and perceived recovery and stress (Short Recovery and Stress Scale) were measured 24 h before and 24 h after the training program.
The HIT shock microcycle induced a large decrease in CMJ performance (ACT: effect size [ES] = –1.39, P < .05; PAS: ES = –1.42, P < .05) and perceived recovery (ACT: ES = –1.79, P < .05; PAS: ES = –2.39, P < .05), as well as a moderate to large increase in CK levels (ACT: ES = 0.76, P > .05; PAS: ES = 0.81, P >.05), DOMS (ACT: ES = 2.02, P < .05; PAS: ES = 2.17, P < .05), and perceived stress (ACT: ES = 1.98, P < .05; PAS: ES = 3.06, P < .05), compared with the values before the intervention. However, no significant recovery intervention × time interactions or meaningful differences in changes were noted in any of the markers between ACT and PAS.
Repeated use of individualized ACT, consisting of 15 min of moderate jogging, after finishing each training session during an HIT shock microcycle did not affect exercise-induced fatigue.
Sabrina Skorski, Jan Schimpchen, Mark Pfeiffer, Alexander Ferrauti, Michael Kellmann and Tim Meyer
Purpose: Despite indications of positive effects of sauna (SAU) interventions, effects on performance recovery are unknown. The aim of the current study was to investigate acute effects of SAU bathing after an intensive training session on recovery of swim performance. Methods: In total, 20 competitive swimmers and triathletes (3 female and 17 male) with a minimum of 2 y of competition experience (national level or higher) participated in the study. Athletes completed an intensive training session followed by either a SAU bathing intervention or a placebo (PLAC) condition in a randomized order. SAU consisted of 3 × 8 min of SAU bathing at 80–85°C, whereas during PLAC, athletes applied a deidentified, pH-balanced massage oil while passively resting in a seated position. Prior to training, swimmers conducted a 4 × 50-m all-out swim test that was repeated on the following morning. Furthermore, subjective ratings of fatigue and recovery were measured. Results: Swimmers performed significantly worse after SAU (4 × 50-m pre–post difference: +1.69 s) than after PLAC (−0.66 s; P = .02), with the most pronounced decrease in the first 50 m (P = .04; +2.7%). Overall performance of 15 athletes deteriorated (+2.6 s). The subjective feeling of stress was significantly higher after SAU than after PLAC (P = .03). Conclusion: Based on published findings, the smallest substantial change in swimming performance is an increase in time of more than 1.2 s; thus, the observed reductions appear relevant for competitive swimmers. According to the current results, coaches and athletes should be careful with postexercise SAU if high-intensity training and/or competitions are scheduled on the following day.
Anne Hecksteden, Werner Pitsch, Ross Julian, Mark Pfeiffer, Michael Kellmann, Alexander Ferrauti and Tim Meyer
Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport.
Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1–8 per athlete, years 2013–2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization.
For CK, error rates were significantly lower with individualized classification (P vs group-based: test-pass error rate P = .008; test-fail error rate P < .001). For urea, numerical improvements in error rates failed to reach significance.
Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.