It is important that an athlete train at the optimal training volume to achieve maximum performance gains. Training below this level will cause failure to achieve the proper physical and psychological adaptation for maximum performance, whereas training above may lead to a condition referred to as overtraining or burnout (1–4). One important aspect of successful training is the level of recovery for an individual before resuming training (1–4). Not permitting athletes with adequate recovery time is detrimental to obtaining peak performance (5,6). Over the years, research has demonstrated that programmed rest and variation in volume and intensity is probably the best mechanism for recovery (1–3).
Despite the importance of recovery time, the methods of measuring recovery that do exist use time consuming, invasive, and/or potentially taxing techniques that typically lead to low compliance by the subjects and may cause adverse side effects (1,5,7,8). However, Laurent et al. (9) proposed a perceived recovery status scale, which is similar but opposite to a perceived exertion scale (10–12). Both scales are based on the subjective physical and mental feelings of the athlete, as it pertains to their body either before or after a training session. The perceived recovery scale (PRS) demonstrated itself as an effective mechanism to determine the performance in a particular training session before a subject commences training (9). Furthermore, research suggests that the PRS may be well suited for the determination of overtraining syndrome and the prevention of overtraining (9).
Damaging skeletal muscle tissue is one of the outcomes of high-intensity exercise. One mechanism for determining the level of damage is by the examination of various blood markers such as creatine kinase (CK), lactate dehydrogenase, fast myosin, and myoglobin to name a few (13–15). Inflammation is another side effect of muscle damage and leads to increases in the levels of proteins such as C-reactive protein (CRP), prostaglandin E2, tumor necrosis factor-alpha (TNF-α), platelet activating factor, and interleukin 6 (16–20). These proteins may be used as indirect markers as part of the evaluation of damage to muscle tissue (21–24). Finally, the various catabolic and anabolic hormones play a significant role in recovery from muscle damage. The levels and expression of these hormones, cortisol, and testosterone, for example, vary with not only the level of damage but also with the level of hydration of the individuals (21–24). Both these direct and indirect markers for muscle damage have been used to corroborate perceived exertion among training and competing athletes (25,26).
The goal of this study was to examine and determine if there is a correlation between the perceived recovery status scale used by the subjects and the presence of blood markers and other indices of muscle damage and readiness to train. The second goal of this study was to determine the relationship between resting testosterone and cortisol levels and an individual's perceived readiness to train, as determined by the PRS. Therefore, we specifically assayed for the levels of CK, cortisol, testosterone, and CRP.
Experimental Approach to the Problem
This investigation was designed to determine the effects of a high-volume muscle damaging training session on PRS. Our secondary purpose was to determine the relationship between resting serum levels of testosterone and cortisol on PRS. All subjects were tested on 3 separate days. On day 1, subjects' 1 repetition maximum (1RM) performance on the full squat, bench press, and deadlift were assessed. In addition, lean body mass was assessed using dual x-ray absorbtiometery (iDXA; GE Lunar Corp., Madison, WI, USA). On day 2, which occurred 7 days after day 1, all subjects performed a high-volume resistance training protocol designed to elicit a large amount of fatigue and muscle damage. Before the resistance training bout, baseline blood, soreness, and PRS status were assessed. Forty-eight hours after the muscle damaging bout, subjects returned to the laboratory for postblood and PRS scores.
Thirty-five highly resistance-trained subjects aged 21.3 ± 1.9 years with an average squat, bench press, and deadlift of 1.7 ± 0.2, 1.38 ± 1.9, and 2.07 ± 2.7 times their bodyweight were recruited for the study (Table 1). All subjects had a minimum of 3 years of resistance training experience. An institution review board approved the study for human subjects, and written informed consent was obtained from each subject before any testing.
Resting Blood Draws
Resting blood draws were obtained via venipuncture by a trained phlebotomist at pretraining (day 2) and at 48 hours after the resistance training bout (day 3). Whole blood was collected and transferred into appropriate tubes for obtaining serum and plasma and centrifuged at 1500g for 15 minutes at 4° C. Resulting serum and plasma was aliquoted and stored at j80° C until subsequent analyses.
Two weeks before and throughout the study, subjects were placed on a diet consisting of 25% protein, 50% carbohydrates, and 25% fat by a registered dietician, who specialized in sport nutrition (RD, LDN, and CISSN).
Samples were thawed one time and analyzed in duplicate for each analyte. All blood draws were scheduled at the same time of day to negate confounding influences of diurnal hormonal variations. Serum total testosterone, cortisol, and CRP were assayed via enzyme-linked immunosorbent assay kits obtained from Diagnostic Systems Laboratories (Webster, TX, USA). All hormones were measured in the same assay on the same day to avoid compounded interassay variance. Intra-assay variance was less than 3% for all analytes. Serum CK was measured using colorimetric procedures at 340 nm (Diagnostics Chemicals, Oxford, CT, USA).
Resistance Training Protocol
All subjects participated in a high-volume resistance training session consisting of 3 sets of 10- to 12-repetition maximum loads for each of the following exercises: full squats, bench press, deadlifts, pullups, bent over rows, dips, shoulder press, barbell curls, and triceps extensions. Rest periods were 1 minute between sets and 2 minutes between exercises (Table 2).
Perceived Recovery Status Scale and Muscle Soreness
Perceived Recovery Status scale consists of values between 0 and 10, with 0–2 being very poorly recovered and with anticipated declines in performance, 4–6 being low to moderately recovered and expected similar performance, and 8–10 representing high perceived recovery with expected increases in performance. Muscle soreness was assessed using a scale of 0–10 for the legs, chest, and arms. On the scale, 0–1 represented little to no pain, 2 represented slight pain, 3–4 represented mild pain, 5–6 represented moderate pain, and 7–8 and 9–10 was indicative of severe to the worst pain, respectively, that the subject had experienced in their lives.
Means and SDs were generated for all subject characteristics, including strength relative to body weight (combined 1RMs for the squat, bench press, and deadlift divided by subject's body weight), age, and total volume lifted during the resistance training protocol ([weight] × [repetitions] × [total sets of each exercise]). A repeated measures analysis of variance was used to determine differences in PRS, soreness, and blood markers of muscle damage and hormone status. Finally, correlation coefficients were calculated for all variables by using a correlation matrix from raw scores to determine which variables were related to PRS scores. A Tukey HSD post hoc test was used to locate significance between time points if there was a main group or time effect. All significance was accepted at p ≤ 0.05. All statistical procedures were carried out on Statistica (StatSoft, Tulsa, OK, USA).
Average total weight lifted in the training session was 16,353 ± 3,691.8 kg (Table 1, p < 0.05). Perceived Recovery Status declined from 8.6 ± 2.3 to 4.2 ± 1.85 (p < 0.05) (Figure 1). Leg (0.58 ± 0.84 to 6.3 ± 2.3 cm, p < 0.05), chest (0.29 ± 0.53 to 3.7 ± 2.1 cm, p < 0.05), and arm soreness (0.48 ± 1.2 to 2.7 ± 2.6 cm, p < 0.05) increased from pre- to postexercise (Table 3). Serum CK significantly increased from pre- to postworkout (189.4 ± 100.2 to 512 ± 222.7 U/L, p < 0.05). Cortisol, testosterone, and free testosterone did not change from pre- to posttraining (Table 3, p < 0.05). There was a significant moderate and inverse relationship between leg soreness and PRS scores. There were also significant low inverse relationships between chest and arm soreness and PRS scores. There was a significant moderate inverse relationship between CK and PRS (Figure 2, p < 0.05). When muscle damage was low before training, cortisol and free and total testosterone were not correlated to PRS. However, when damage peaked at 48 hours postexercise, free testosterone, but not total testosterone, showed a low direct relationship with PRS (Figure 4, p < 0.05).
The main goal of this study was to examine and determine if there is a correlation between the perceived recovery status scale used by the subjects and the presence of blood markers and other indices of muscle damage and readiness to train as verification of recovery and potential training performance.
Subjects (Table 1) noted a significant drop in their physical status following the high-volume resistance training session (Table 2). The subjects reported their level of recovery, using the PRS (Figure 1B), and on the level of muscle soreness both before and after the training session. Significant changes in muscle soreness in the legs, chest and arms were reported by the subjects (Table 3) leading to a significant, inverse relationship between soreness and the PRS for each subject (Figure 3). To determine if there was a correlation between muscle damage and the PRS, we decided to look at a blood marker, which has been shown to be a muscle damage indicator. Creatine kinase levels were assayed through blood draws before the workout and 48 hours after the workout. Results demonstrated a 2.5-foldincrease in serum levels of CK 48 hours postexercise verifying potential muscle damage (Figure 1A). However, it must be mentioned that tissue damage may have been compromised because of the receptor complexes that are not functioning (27). Yet, on statistical comparison between the PRS (Figure 1B) and CK levels (Figure 1A), the results demonstrated that there was a significant and moderate inverse relationship between the two (Figure 2). This suggests that the PRS may be used not only as a measure of readiness to train and potential performance but also as a measure of potential muscle damage. The initial study investigating the potential utility of the PRS was to investigate if individuals could subjectively assess their level of recovery relative to expected performance. Although novel, there are clearly a number of factors that influence an individual's performance during repeated bouts of work. Therefore, studies are needed to further examine specific markers that may influence an individual's level of readiness after training. The results from this study suggest that the PRS may have extended utility in not only identification of performance change, but may indicate the magnitude of damage done at the level of the muscle and/or the degree of recovery after a difficult bout of exercise. Clearly, the ability of an individual to assess either the level of recovery or degree of damage using a simple noninvasive perceptual scale is attractive across a number of populations and has tremendous potential in prescribing training loads on a day-to-day basis. Indeed, Laurent et al. (9), in the design of the PRS suggested that an individual may be able to use this measure as a means to manipulate daily workloads and, if done appropriately, could serve to not only maximize overload and training gains but also potentially avoid nonfunctional overreaching.
The second goal of this study was to examine testosterone (total and free), cortisol, and C-reactive protein and to determine any significant relationship between these biochemical levels and individual's perceived readiness to train as determined by the PRS. Results demonstrated no significant change in C-reactive protein or cortisol levels from pre- to postworkout (Table 3). Our results for C-reactive protein agreed with those of other researchers (18,28,29). Cortisol also displayed no significant level of change after the high-volume exercise, which was concurrent with results obtained by others (24). Although some researchers have noticed changes in levels of cortisol in blood and saliva after resistance exercise (30–33), samples in these studies were taken either immediately or shortly after (a few hours) exercise. Changes in cortisol levels may have occurred at time intervals different from the one chosen for our study. Further experimentation is needed to determine if these changes did occur. Our post exercise times for sampling were chosen because this is when maximal concentrations of muscle damage markers would be present.
Finally, testosterone levels were assayed both pre- and postworkout. There was no significant correlation in the levels of total and free testosterone to the PRS when muscle damage was low before training, however, there was a low and direct correlation between free testosterone and the subject's perceived level of recovery 48 hours postexercise. This result alludes to the role of testosterone in maintaining readiness for physical exertion in the presence of muscle damage (34–36). While there was only a modest correlation shared between these 2 variables, this finding is still novel. The literature has clearly indicated that perceptual response during exercise (i.e., RPE) is influenced by a number of different variables. Moreover, the degree to which a variable will influence RPE is not constant, as its influence may change relative to the intensity of the exercise and/or the duration of the exercise bout (37–39). Because the PRS was created analogous to the RPE scale, our results may indicate that different biochemical markers of damage and/or recovery (i.e., CK, testosterone, etc.) will influence readiness to train differently depending on the amount time an individual has recovered or how much damage had occurred during the exercise bout itself. Further investigation toward the rate of change of readiness and appearance and clearance of these biochemical markers, especially as they relate to performance change, is warranted.
The results of this study demonstrate another mechanism, which can be used by coaches and trainers of athletes to assess the readiness of an athlete for continued training and intensity of training to increase their performance. The PRS is a novel measurement and not as widely accepted as the RPE scale. By using perceived exertion, one is looking at the detrimental physiological and psychological changes to a subject during and immediately after an exercise session. As suggested by Laurent et al. (9), this measurement may not be the best mechanism to determine overtraining because the measurements are taken after the training session is over. To the contrary, the PRS looks at the readiness of a subject before the training session begins. This would be a better way to determine the readiness and potential performance of an athlete for a particular training session and may provide insight into potential onset of overtraining syndrome.
Clearly, what the data from this study suggest is that after a bout of heavy resistance training, an individual is able to indicate level of recovery using the PRS. Although the relationship shared between perception of recovery and the biochemical makers reported here is not overwhelming, considering the numerous factors that contribute to recovery, even a moderate relationship is novel. Moreover, the practical application of these findings are most important for those individuals that have neither the resources (time, monetary, or otherwise) nor the expertise to draw blood and perform chemical assays to determine recovery status and or muscle damage. In that sense, individuals working with large groups of athletes (e.g., collegiate strength and conditioning) may find the ability to estimate level of muscle damage as a result of a certain workout program quite attractive. This, in the bigger picture, may help appropriately design periodization plans designed aimed at functional overreaching and ensure proper overload. Moreover, and perhaps more importantly, the ability to indicate level of recovery following heavy resistance training expeditiously and accurately may be a critically important step in prevention of overtraining. Still, future work is needed addressing other variables influencing recovery and long-term studies investigating the usefulness of the PRS in training.
1. Bishop PA, Jones E, Woods AK. Recovery from training: a brief review: brief review. J Strength Cond Res 22: 1015–1024, 2008.
2. Lehmann M, Foster C, Keul J. Overtraining in endurance athletes: a brief review. Med Sci Sports Exerc 25: 854–862, 1993.
3. Budgett R. Overtraining syndrome. Br J Sports Med 24: 231–236, 1990.
4. Lane KN, Wenger HA. Effect of selected recovery conditions on performance of repeated bouts of intermittent cycling separated by 24 hours. J Strength Cond Res 18: 855–860, 2004.
5. Kentta G, Hassmen P. Overtraining and recovery. A conceptual model. Sports Med 26: 1–16, 1998.
6. Laursen PB, Jenkins DG. The scientific basis for high-intensity interval training: optimising training programmes and maximising performance in highly trained endurance athletes. Sports Med 32: 53–73, 2002.
7. Urhausen A, Kindermann W. Diagnosis of overtraining: what tools do we have? Sports Med 32: 95–102, 2002.
8. Lambert MB, Borresen J. A theoretical basis of monitoring fatigue: a practical approach for coaches. Int J Sports Sci Coach 1: 371–388, 2006.
9. Laurent CM, Green JM, Bishop PA, Sjökvist J, Schumacker RE, Richardson MT, Curtner-Smith M. A practical approach to monitoring recovery: development of a perceived recovery status scale. J Strength Cond Res 25: 620–628, 2011.
10. Noble BJ. Clinical applications of perceived exertion. Med Sci Sports Exerc 14: 406–411, 1982.
11. Robertson RJ, Goss FL, Rutkowski J, Lenz B, Dixon C, Timmer J, Frazee K, Dube J, Adreacci J. Concurrent validation of the OMNI perceived exertion scale for resistance exercise. Med Sci Sports Exerc 35: 333–341, 2003.
12. Goss F, Robertson R, DaSilva S, Suminski R, Kang J, Metz K. Ratings of perceived exertion and energy expenditure during light to moderate activity. Percept Mot Skills 96: 739–747, 2003.
13. Guerrero M, Guiu-Comadevall M, Cadefau JA, Parra J, Balius R, Estruch A, Rodas G, Bedini JL, Cussó R. Fast and slow myosins as markers of muscle injury. Br J Sports Med 42: 581–584, 2008; Discussion 584.
14. Baird MF, Graham SM, Baker JS, Bickerstaff GF. Creatine-kinase- and exercise-related muscle damage implications for muscle performance and recovery. J Nutr Metab 2012: 960363, 2012.
15. Clarkson PM, Nosaka K, Braun B. Muscle function after exercise-induced muscle damage and rapid adaptation. Med Sci Sports Exerc 24: 512–520, 1992.
16. Gleeson M. Immune function in sport and exercise. J Appl Physiol 103: 693–699, 2007.
17. Santos RV, Bassit RA, Caperuto EC, Costa Rosa LF. The effect of creatine supplementation upon inflammatory and muscle soreness markers after a 30km race. Life Sci 75: 1917–1924, 2004.
18. Milias GA, Nomikos T, Fragopoulou E, Athanasopoulos S, Antonopoulou S. Effects of eccentric exercise-induced muscle injury on blood levels of platelet activating factor (PAF) and other inflammatory markers. Eur J Appl Physiol 95: 504–513, 2005.
19. Mackinnon L. Advances in Exercise and Immunology. Champaign, IL: Human Kinetics; 1999.
20. Ronsen O, Pedersen BK, Øritsland TR, Bahr R, Kjeldsen-Kragh J. Leukocyte counts and lymphocyte responsiveness associated with repeated bouts of strenuous endurance exercise. J Appl Physiol 91: 425–434, 2001.
21. Judelson DA, Maresh CM, Yamamoto LM, Farrell MJ, Armstrong LE, Kraemer WJ, Volek JS, Spiering BA, Casa DJ, Anderson JM. Effect of hydration state on resistance exercise-induced endocrine markers of anabolism, catabolism, and metabolism. J Appl Physiol 105: 816–824, 2008.
22. Martinez AC, Seco Calvo J, Tur Marí JA, Abecia Inchaurregui LC, Orella EE, Biescas AP. Testosterone and cortisol
changes in professional basketball players through a season competition. J Strength Cond Res 24: 1102–1108, 2010.
23. Ahtiainen JP, Lehti M., Hulmi JJ, Kraemer WJ, Alen M, Nyman K, Selänne H, Pakarinen A, Komulainen J, Kovanen V, Mero AA, Häkkinen K. Recovery after heavy resistance exercise and skeletal muscle androgen receptor and insulin-like growth factor-I isoform expression in strength trained men. J Strength Cond Res 25: 767–777, 2011.
24. Goto K, Takahashi K, Yamamoto M, Takamatsu K. Hormone and recovery responses to resistance exercise with slow movement. J Physiol Sci JPS 58: 7–14, 2008.
25. Twist C, Eston RG. The effect of exercise-induced muscle damage on perceived exertion and cycling endurance performance. Eur J Appl Physiol 105: 559–567, 2009.
26. Burnett D, Burns S, Smith K. Perceived muscle soreness in recreational female runners. Int J Exerc Sci 3: 108–116, 2010.
27. Serra C, Tangherlini F, Rudy S, Lee D, Toraldo G, Sandor NL, Zhang A, Jasuja R, Bhasin S. Testosterone improves the regeneration of old and young mouse skeletal muscle. J Gerontol Biol Med Sci, 2012.
28. Franklin ME, Chamness M, Smith LL, Chenier TC, Sizemore CS, Rogers M, Forgione K. Effects of isokinetic soreness-inducing exercise on blood levels of C-reactive protein and creatine kinase. J Orthop Sports Phys Ther 16: 208–214, 1992.
29. Malm C, Sjödin B, Sjöberg B, Lenkei R, Renström P, Lundberg IE, Ekblom B. Leukocytes, cytokines, growth factors and hormones in human skeletal muscle and blood after uphill or downhill running. J Physiol 556: 983–1000, 2004.
30. Nunes JA, Crewther BT, Ugrinowitsch C, Tricoli V, Viveiros L, De Rose Jr D, Aoki MS. Salivary hormone and immune responses to three resistance exercise schemes in elite female athletes. J Strength Cond Res 25: 2322–2327, 2011.
31. Rogers RS, Dawson AW, Wang Z, Thyfault JP, Hinton PS. Acute response of plasma markers of bone turnover to a single bout of resistance training or plyometrics. J Appl Physiol 111: 1353–1360, 2011.
32. Szivak TK, Hooper DR, Dunn-Lewis C, Comstock BA, Kupchak BR, Apicella JM, Saenz C, Maresh CM, Denegar CR, Kraemer WJ. Adrenal cortical responses to high intensity, short rest, resistance exercise in men and women. J Strength Cond Res, 2012.
33. Leite RD, Prestes J, Rosa C, De Salles BF, Maior A, Miranda H, Simão R. Acute effect of resistance training volume on hormonal responses in trained men. J Sports Med Phys Fitness 51: 322–328, 2011.
34. Harridge SD. Plasticity of human skeletal muscle: gene expression to in vivo function. Exp Physiol 92: 783–797, 2007.
35. Rooyackers OE, Nair KS. Hormonal regulation of human muscle protein metabolism. Annu Rev Nutr 17: 457–485, 1997.
36. Phillips BE, Hill DS, Atherton PJ. Regulation of muscle protein synthesis in humans. Curr Opin Clin Nutr Metab Care 15: 58–63, 2012.
37. Robertson RJ, Noble BJ. Perception of physical exertion: methods, mediators, and applications. Exerc Sport Sci Rev 25: 407–452, 1997.
38. Green JM, McLester JR, Crews TR, Wickwire PJ, Pritchett RC, Redden A. RPE-lactate dissociation during extended cycling. Eur J Appl Physiol 94: 145–150, 2005.
39. Chen MJ, Fan X, Moe ST. Criterion-related validity of the Borg ratings of perceived exertion scale in healthy individuals: a meta-analysis. J Sports Sci 20: 873–899, 2002.