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Andrew D. Govus, Aaron Coutts, Rob Duffield, Andrew Murray and Hugh Fullagar

Daily monitoring of a player’s internal and external training loads is critical in American college football since a high training load coupled with inadequate recovery can result in injury, illness, or overtraining. 1 One commonly used noninvasive method of monitoring an athlete

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Júlio A. Costa, João Brito, Fábio Y. Nakamura, Eduardo M. Oliveira and António N. Rebelo

important to highlight that monitoring training-related cardiac autonomic responses has been facilitated by the use of after waking ultra-short-term HRV measurement. 4 , 5 , 7 , 8 In spite of its usefulness, this method does not allow the analysis of the time course of the cardiac autonomic recovery

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Scott W. Cheatham and Russell Baker

, postexercise recovery, or vessel occlusion. 4 , 5 Future research should build upon these findings and develop more evidence-based guidelines for healthy and injured individuals. Conclusion This investigation should be considered the first step in developing evidence-based guidelines for the application of

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Steven H. Doeven, Michel S. Brink, Wouter G.P. Frencken and Koen A.P.M. Lemmink

During intensified phases of competition, attunement of exertion and recovery is crucial to maintain performance. Although a mismatch between coach and player perceptions of training load is demonstrated, it is unknown if these discrepancies also exist for match exertion and recovery.

Purpose:

To determine match exertion and subsequent recovery and to investigate the extent to which the coach is able to estimate players’ match exertion and recovery.

Methods:

Rating of perceived exertion (RPE) and total quality of recovery (TQR) of 14 professional basketball players (age 26.7 ± 3.8 y, height 197.2 ± 9.1 cm, weight 100.3 ± 15.2 kg, body fat 10.3% ± 3.6%) were compared with observations of the coach. During an in-season phase of 15 matches within 6 wk, players gave RPEs after each match. TQR scores were filled out before the first training session after the match. The coach rated observed exertion (ROE) and recovery (TQ-OR) of the players.

Results:

RPE was lower than ROE (15.6 ± 2.3 and 16.1 ± 1.4; P = .029). Furthermore, TQR was lower than TQ-OR (12.7 ± 3.0 and 15.3 ± 1.3; P < .001). Correlations between coach- and player-perceived exertion and recovery were r = .25 and r = .21, respectively. For recovery within 1 d the correlation was r = .68, but for recovery after 1–2 d no association existed.

Conclusion:

Players perceive match exertion as hard to very hard and subsequent recovery reasonable. The coach overestimates match exertion and underestimates degree of recovery. Correspondence between coach and players is thus not optimal. This mismatch potentially leads to inadequate planning of training sessions and decreases in performance during fixture congestion in basketball.

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Oliver R. Barley, Dale W. Chapman and Chris R. Abbiss

previous research indicating that even when provided with 24 hours of ad libitum fluid/food intake, athletes may not be adequately rehydrating. 2 , 12 Clearly, further research is needed to assess the recovery strategies and their efficacy in combat sports following weigh-ins. In this study, a wide range

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Thomas Losnegard, Martin Andersen, Matt Spencer and Jostein Hallén

Purpose:

To investigate the effects of an active and a passive recovery protocol on physiological responses and performance between 2 heats in sprint cross-country skiing.

Methods:

Ten elite male skiers (22 ± 3 y, 184 ± 4 cm, 79 ± 7 kg) undertook 2 experimental test sessions that both consisted of 2 heats with 25 min between start of the first and second heats. The heats were conducted as an 800-m time trial (6°, >3.5 m/s, ~205 s) and included measurements of oxygen uptake (VO2) and accumulated oxygen deficit. The active recovery trial involved 2 min standing/walking, 16 min jogging (58% ± 5% of VO2peak), and 3 min standing/walking. The passive recovery trial involved 15 min sitting, 3 min walk/jog (~ 30% of VO2peak), and 3 min standing/walking. Blood lactate concentration and heart rate were monitored throughout the recovery periods.

Results:

The increased 800-m time between heat 1 and heat 2 was trivial after active recovery (effect size [ES] = 0.1, P = .64) and small after passive recovery (ES = 0.4, P = .14). The 1.2% ± 2.1% (mean ± 90% CL) difference between protocols was not significant (ES = 0.3, P = .3). In heat 2, peak and average VO2 was increased after the active recovery protocol.

Conclusions:

Neither passive recovery nor running at ~58% of VO2peak between 2 heats changed performance significantly.

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Lynda M. Mainwaring, Sean M. Bisschop, Robin E.A. Green, Mark Antoniazzi, Paul Comper, Vicki Kristman, Christine Provvidenza and Doug W. Richards

Despite suggestions that emotions influence recovery from injury, there is little research into the emotional sequelae of mild traumatic brain injury (MTBI), or “concussion,” in sport. This examination compares emotional functioning of college athletes with MTBI to that of uninjured teammates and undergraduates. A short version of the Profile of Mood States (POMS; Grove & Prapavessis, 1992) assessed baseline emotions in all groups, and serial emotional functioning in the MTBI and undergraduate groups. Whereas preinjury profiles were similar across groups, the MTBI group showed a significant postinjury spike in depression, confusion, and total mood disturbance that was not seen for the other groups. The elevated mood disturbances subsided within 3 weeks postinjury. Given that concussed athletes were highly motivated to return to play, these data could be used as a benchmark of normal emotional recovery from MTBI. Findings are discussed in relation to current literature on emotional reaction to injury and directions for future research.

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Rachel Borne, Christophe Hausswirth and François Bieuzen

Purpose:

To investigate the effect of different limb blood-flow levels on cycling-performance recovery, blood lactate concentration, and heart rate.

Methods:

Thirty-three high-intensity intermittent-trained athletes completed two 30-s Wingate anaerobic test sessions, 3 × 30-s (WAnT 1–3) and 1 × 30-s (WAnT 4), on a cycling ergometer. WAnT 1–3 and WAnT 4 were separated by a randomly assigned 24-min recovery intervention selected from among blood-flow restriction, passive rest, placebo stimulation, or neuromuscular electrical-stimulation-induced blood flow. Calf arterial inflow was measured by venous occlusion plethysmography at regular intervals throughout the recovery period. Performance was measured in terms of peak and mean power output during WAnT 1 and WAnT 4.

Results:

After the recovery interventions, a large (r = .68 [90% CL .42; .83]) and very large (r = .72 (90% CL .49; .86]) positive correlation were observed between the change in calf arterial inflow and the change in mean and peak power output, respectively. Calf arterial inflow was significantly higher during the neuromuscular-electrical-stimulation recovery intervention than with the blood-flow-restriction, passive-rest, and placebo-stimulation interventions (P < .001). This corresponds to the only intervention that allowed performance recovery (P > .05). No recovery effect was linked to heart rate or blood lactate concentration levels.

Conclusions:

For the first time, these data support the existence of a positive correlation between an increase in blood flow and performance recovery between bouts of high-intensity exercise. As a practical consideration, this effect can be obtained by using neuromuscular electrical stimulation-induced blood flow since this passive, simple strategy could be easily applied during short-term recovery.

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Sarah Shaw, Tina Smith, Jenny Alexanders, Thomas Shaw, Lois Smith, Alan Nevill and Anna Anderson

Objective:

To investigate half-marathon runners’ frequency of use of recovery strategies, perceptions regarding the most beneficial recovery strategy, and reasons for using recovery strategies.

Design:

Cross-sectional survey.

Participants:

186 participants of the 13.1 mile BUPA Great North Run 2013.

Methods:

A questionnaire was developed which required participants to indicate how frequently they used 12 different recovery strategies, identify which recovery strategy they believed to be most beneficial, and rank 6 reasons for using recovery strategies in order of importance. Data were analyzed using a Friedman nonparametric ANOVA and additional nonparametric tests.

Results:

All participants used recovery strategies. Stretching was the most commonly used recovery strategy (P < .001), whereas the use of nutritional supplements was the most commonly selected most beneficial recovery strategy. More than 50% of respondents indicated that they never used strategies such as kinesio tape (80%), hydrotherapy (78%), or ice baths (71%). A significant difference was observed between reasons for using recovery strategy (χ2 (5) = 292.29, P < .001). Reducing muscle tightness (rank 4.87) and reducing injury (rank 4.35) were the most frequently chosen most important reasons for using recovery strategies. Minor sex and age differences in the responses were identified.

Conclusion:

Recovery strategy usage appears to be widespread among half-marathon runners; however, disparities exist between the frequency of use and perceived effectiveness of different recovery strategies. Further research in this area is needed to facilitate the development of recovery strategy guidelines which are both evidence-based and practically relevant.

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Brendon P. McDermott, Douglas J. Casa, Susan W. Yeargin, Matthew S. Ganio, Lawrence E. Armstrong and Carl M. Maresh

Objective:

To describe the current scientific evidence of recovery and return to activity following exertional heat stroke (EHS).

Data Sources:

Information was collected using MEDLINE and SPORTDiscus databases in English using combinations of key words, exertional heat stroke, recovery, rehabilitation, residual symptoms, heat tolerance, return to activity, and heat illness.

Study Selection:

Relevant peer-reviewed, military, and published text materials were reviewed.

Data Extraction:

Inclusion criteria were based on the article’s coverage of return to activity, residual symptoms, or testing for long-term treatment. Fifty-two out of the original 554 sources met these criteria and were included in data synthesis.

Data Synthesis:

The recovery time following EHS is dependent on numerous factors, and recovery length is individually based and largely dependent on the initial care provided.

Conclusion:

Future research should focus on developing a structured return-to-activity strategy following EHS.