The Validity of Perceived Recovery Status as a Marker of Daily Recovery Following a High-Volume Back-Squat Protocol

in International Journal of Sports Physiology and Performance

Click name to view affiliation

Danilo V. Tolusso
Search for other papers by Danilo V. Tolusso in
Current site
Google Scholar
PubMed Close
,
Ward C. Dobbs
Search for other papers by Ward C. Dobbs in
Current site
Google Scholar
PubMed Close
,
Haley V. MacDonald
Search for other papers by Haley V. MacDonald in
Current site
Google Scholar
PubMed Close
,
Lee J. Winchester
Search for other papers by Lee J. Winchester in
Current site
Google Scholar
PubMed Close
,
C. Matthew Laurent
Search for other papers by C. Matthew Laurent in
Current site
Google Scholar
PubMed Close
,
Michael V. Fedewa
Search for other papers by Michael V. Fedewa in
Current site
Google Scholar
PubMed Close
, and
Michael R. Esco
Search for other papers by Michael R. Esco in
Current site
Google Scholar
PubMed Close
DOI:
https://doi.org/10.1123/ijspp.2021-0360
Keywords:
perception; resistance training; monitoring
First Published Online:
07 Mar 2022
In Print:
Volume 17: Issue 6
Page Range:
886–892
Restricted access

Although a variety of tools to monitor recovery have been developed, many are impractical for daily use due to cost, time, and challenges with interpretation. The Perceived Recovery Status (PRS) scale was recently developed as an expeditious, noninvasive tool to assess recovery status. While PRS has been strongly associated with repeated sprinting performance, a paucity of research exists relating PRS and performance recovery following resistance exercise. Purpose: The purpose of this study was to evaluate the sensitivity of PRS as a subjective marker of recovery up to 72 hours after a high-volume back-squat protocol. Methods: Eleven resistance-trained men reported to the laboratory on 5 separate occasions (1 familiarization session and 4 testing sessions). The first testing session was considered the baseline session and consisted of a nonfatiguing performance assessment (ie, countermovement jumps and back squats) and a fatiguing back-squat protocol of 8 sets of 10 at 70% 1-repetition maximum separated by 2 minutes of recovery. Participants returned 24, 48, and 72 hours following baseline to provide a PRS rating and complete the performance assessment. Results: Repeated-measures correlations revealed strong associations between PRS countermovement jump (r = .84) and mean bar velocity (r = .80) (both P < .001). Conclusions: The current findings suggest that PRS can be used as a method to effectively assess daily recovery following a fatiguing bout of resistance exercise. Practitioners are cautioned that the relationship between PRS and performance recovery is individualized, and equivalent PRS scores between individuals are not indicative of similar recovery.

Tolusso is with the School of Kinesiology, Recreation, and Sport, Western Kentucky University, Bowling Green, KY, USA. Tolusso, MacDonald, Winchester, Fedewa, and Esco are with the Dept of Kinesiology, University of Alabama, Tuscaloosa, AL, USA. Dobbs is with the Dept of Exercise and Sport Science, University of Wisconsin–La Crosse, La Crosse, WI, USA. Laurent is with the School of Kinesiology, Tarleton State University, Stephenville, TX, USA.

Tolusso (danilotolusso@gmail.com) is corresponding author.
  • Collapse
  • Expand

International Journal of Sports Physiology and Performance

Cover International Journal of Sports Physiology and Performance
  • 1.

    Kenttä G, Hassmén P. Overtraining and recovery. Sports Med. 1998;26(1):1–16. PubMed ID: 9739537 doi:10.2165/00007256-199826010-00001

  • 2.

    Kellmann M, Bertollo M, Bosquet L, et al. Recovery and performance in sport: consensus statement. Int J Sports Physiol Perform. 2018;13(2):240–245. PubMed ID: 29345524 doi:10.1123/ijspp.2017-0759

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Laurent C, Green JM, Bishop PA, et al. A practical approach to monitoring recovery: development of a perceived recovery status scale. J Strength Cond Res. 2011;25(3):620–628. PubMed ID: 20581704 doi:10.1519/JSC.0b013e3181c69ec6

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Bartolomei S, Sadres E, Church DD, et al. Comparison of the recovery response from high-intensity and high-volume resistance exercise in trained men. Eur J Appl Physiol. 2017;117(7):1287–1298. PubMed ID: 28447186 doi:10.1007/s00421-017-3598-9

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Coutts AJ, Slattery KM, Wallace LK. Practical tests for monitoring performance, fatigue and recovery in triathletes. J Sci Med Sport. 2007;10(6):372–381. PubMed ID: 17466593 doi:10.1016/j.jsams.2007.02.007

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Todd J, Simpson P, Estis J, Torres V, Wub AH. Reference range and short-and long-term biological variation of interleukin (IL)-6, IL-17A and tissue necrosis factor-alpha using high sensitivity assays. Cytokine. 2013;64(3):660–665. PubMed ID: 24128872 doi:10.1016/j.cyto.2013.09.018

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Bishop PA, Jones E, Woods AK. Recovery from training: a brief review: brief review. J Strength Cond Res. 2008;22(3):1015–1024. PubMed ID: 18438210 doi:10.1519/JSC.0b013e31816eb518

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Main L, Grove JR. A multi-component assessment model for monitoring training distress among athletes. Eur J Sport Sci. 2009;9(4):195–202. doi:10.1080/17461390902818260

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Galesic M, Bosnjak M. Effects of questionnaire length on participation and indicators of response quality in a web survey. Public Opin Q. 2009;73(2):349–360. doi:10.1093/poq/nfp031

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Korak JA, Green JM, O’Neal EK. Resistance training recovery: considerations for single vs. multi-joint movements and upper vs. lower body muscles. Int J Exerc Sci. 2015;8:85–96.

    • Search Google Scholar
    • Export Citation
  • 11.

    Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr. 1978;40(3):497–504. doi:10.1079/BJN19780152

  • 12.

    Earle R, Baechle T. Program design for resistance training. In: Haff GG, Triplett NN, eds. Essentials of Strength Training and Conditioning. 4th ed. Champaign, IL: Human Kinetics; 2015:453–456.

    • Search Google Scholar
    • Export Citation
  • 13.

    Bakdash JZ, Marusich LR. Repeated measures correlation. Front Psychol. 2017;8:456. PubMed ID: 28439244 doi:10.3389/fpsyg.2017.00456.

  • 14.

    Cormack SJ, Newton RU, McGuigan MR, Doyle TL. Reliability of measures obtained during single and repeated countermovement jumps. Int J Sports Physiol Perform. 2008;3(2):131–144. PubMed ID: 19208922 doi:10.1123/ijspp.3.2.131

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Sanchez-Medina L, Perez C, Gonzalez-Badillo J. Importance of the propulsive phase in strength assessment. Int J Sports Med. 2010;31(2):123–129. PubMed ID: 20222005 doi:10.1055/s-0029-1242815

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Jidovtseff B, Harris NK, Crielaard J-M, Cronin JB. Using the load-velocity relationship for 1RM prediction. J Strength Cond Res. 2011;25(1):267–270. PubMed ID: 19966589 doi:10.1519/JSC.0b013e3181b62c5f

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Watkins CM, Barillas SR, Wong MA, et al. Determination of vertical jump as a measure of neuromuscular readiness and fatigue. J Strength Cond Res. 2017;31(12):3305–3310. PubMed ID: 28902119 doi:10.1519/JSC.0000000000002231

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Morán-Navarro R, Pérez CE, Mora-Rodríguez R, et al. Time course of recovery following resistance training leading or not to failure. Eur J Appl Physiol. 2017;117(12):2387–2399. PubMed ID: 28965198 doi:10.1007/s00421-017-3725-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 19.

    Sikorski EM, Wilson JM, Lowery RP, et al. Changes in perceived recovery status scale following high-volume muscle damaging resistance exercise. J Strength Cond Res. 2013;27(8):2079–2085. PubMed ID: 23287827 doi:10.1519/JSC.0b013e31827e8e78

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Tolusso DV, Laurent CM, Fullenkamp AM, Tobar DA. Placebo effect: influence on repeated intermittent sprint performance on consecutive days. J Strength Cond Res. 2015;29(7):1915–1924. PubMed ID: 25853916 doi:10.1519/JSC.0000000000000844

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Laurent C, Tolusso D, Fullenkamp A, Douglas S, Kraft J, Green M. Impact of using perceptually regulated recovery periods during repeated sprint work. Med Sci Sports Exerc. 2017;49(5S):114. doi:10.1249/01.mss.0000517138.59413.7b

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Marston KJ, Peiffer JJ, Newton MJ, Scott BR. A comparison of traditional and novel metrics to quantify resistance training. Sci Rep. 2017;7(1):1–8. doi:10.1038/s41598-017-05953-2

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Schoenfeld BJ, Ratamess NA, Peterson MD, Contreras B, Sonmez G, Alvar BA. Effects of different volume-equated resistance training loading strategies on muscular adaptations in well-trained men. J Strength Cond Res. 2014;28(10):2909–2918. PubMed ID: 24714538 doi:10.1519/JSC.0000000000000480

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Byrne C, Eston R. The effect of exercise-induced muscle damage on isometric and dynamic knee extensor strength and vertical jump performance. J Sports Sci. 2002;20(5):417–425. PubMed ID: 12043831 doi:10.1080/026404102317366672

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Borresen J, Lambert MI. Quantifying training load: a comparison of subjective and objective methods. Int J Sports Physiol Perform. 2008;3(1):16–30. PubMed ID: 19193951 doi:10.1123/ijspp.3.1.16

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Cochrane-Snyman KC, Housh TJ, Smith CM, et al. Inter-individual variability in the patterns of responses for electromyography and mechanomyography during cycle ergometry using an RPE-clamp model. Eur J Appl Physiol. 2016;116:1639–1649. PubMed ID: 27325528 doi:10.1007/s00421-016-3394-y

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    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. 2002;20:873–899. PubMed ID: 12430990 doi:10.1080/026404102320761787

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Morgan WP. Psychological factors influencing perceived exertion. Med Sci Sports. 1973;5:97–103. PubMed ID: 4721014

  • 29.

    De Morree HM, Klein C, Marcora SM. Perception of effort reflects central motor command during movement execution. Psychophysiology. 2012;49:1242–1253. PubMed ID: 22725828 doi:10.1111/j.1469-8986.2012.01399.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Pageaux B. Perception of effort in exercise science: definition, measurement and perspectives. Eur J Sport Sci. 2016;16(8):885–894. PubMed ID: 27240002 doi:10.1080/17461391.2016.1188992

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Tucker R. The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br J Sports Med. 2009;43(6):392–400. PubMed ID: 19224911 doi:10.1136/bjsm.2008.050799

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hampson DB, Gibson ASC, Lambert MI, Noakes TD. The influence of sensory cues on the perception of exertion during exercise and central regulation of exercise performance. Sports Med. 2001;31(13):935–952. PubMed ID: 11708402 doi:10.2165/00007256-200131130-00004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 3698 1871 69
Full Text Views 74 50 6
PDF Downloads 78 44 7