Improving the Signal-To-Noise Ratio When Monitoring Countermovement Jump Performance.
Journal
Journal of strength and conditioning research
ISSN: 1533-4287
Titre abrégé: J Strength Cond Res
Pays: United States
ID NLM: 9415084
Informations de publication
Date de publication:
01 Jan 2021
01 Jan 2021
Historique:
pubmed:
10
5
2018
medline:
15
4
2021
entrez:
10
5
2018
Statut:
ppublish
Résumé
Kennedy, RA and Drake, D. Improving the signal-to-noise ratio when monitoring countermovement jump performance. J Strength Cond Res 35(1): 85-90, 2021-Countermovement jump (CMJ) performance has been routinely used to monitor neuromuscular status. However, the protocol used to establish the criterion score is not well documented. The purpose of this study was to examine how the protocol used would influence of the sensitivity of CMJ variables in rugby union players. Fifteen male (age: 19.7 ± 0.5 years) rugby union players performed 8 CMJs on 2 occasions, separated by 7 days. The between-session coefficient of variation (CV) was calculated using 2 techniques for treating multiple trials, the average, and the trial with the best jump height (JH), and then compared with the smallest worthwhile change (SWC). The signal-to-noise ratio was measured as the group mean change in a variable divided by the CV. Using the average value across multiple trials is superior to the best trial method, based on lower CVs for all variables. Only the average performance across 6 or more trials was classified as ideal (CV < 0.5 × SWC) for peak velocity (PV). In addition, the signal-to-noise ratio for peak concentric power (PCP), PV, and JH were classified as good, irrespective of the treatment method. Although increasing the number of trials can reduce the random error, it may be pragmatic to simply take the average from 2 to 3 trials, facilitating a CV < SWC for PV, PCP, and JH. Due to its simplicity, JH may be considered the principal variable to monitor neuromuscular fatigue.
Identifiants
pubmed: 29742747
pii: 00124278-202101000-00012
doi: 10.1519/JSC.0000000000002615
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
85-90Informations de copyright
Copyright © 2018 National Strength and Conditioning Association.
Références
Ahtianen JP, Häkkinen K. Strength athletes are capable to produce greater muscle activation and neural fatigue during high-intensity resistance training exercise than nonathletes. J Strength Cond Res 23: 1129–1134, 2009.
Al Haddad H, Simpson BM, Buchheit M. Monitoring changes in jump and sprint performance: Best or average values? Int J Sports Physiol Perform 10: 931–934, 2015.
Brownstein CG, Dent JP, Parker P, Hicks KM, Howatson G, Goodall S, Thomas K. Etiology and recovery of neuromuscular fatigue after simulated soccer match play. Front Physiol 8: 1–14, 2017.
Buchheit M. Monitoring training status with HR measures: Do all roads lead to Rome? Front Physiol 5: 1–19, 2014.
Claudino JG, Cronin J, Mezêncio B, McMaster DT, McGuigan M, Tricoli V, Amadio AC, Serrão JC. The countermovement jump to monitor neuromuscular status: A meta-analysis. J Sci Med Sport 20: 397–402, 2017.
Claudino JG, Mezncio B, Soncin R, Ferreira JC, Couto BP, Szmuchrowski LA. Pre vertical jump performance to regulate the training volume. Int J Sports Med 33: 101–107, 2012.
Cormack SJ. Neuromuscular fatigue and endocrine responses in elite Australian Rules match. Int J Sports Physiol Perform 3: 359–374, 2008.
Cormack SJ, Newton RU, McGulgan MR, Doyle TLA. Reliability of measures obtained during single and repeated countermovement jumps. Int J Sports Physiol Perform 3: 131–144, 2008.
Crowcroft S, McCleave E, Slattery K, Coutts AJ. Assessing the measurement sensitivity and diagnostic characteristics of athlete monitoring tools in national swimmers. Int J Sports Physiol Perform 12: 95–100, 2017.
Ebben WP, Petushek EJ. Using the reactive strength index modified to evaluate plyometric performance. J Strength Cond Res 24: 1983–1987, 2010.
Gathercole R, Sporer B, Stellingwerff T, Sleivert G. Alternative countermovement-jump analysis to quantify acute neuromuscular fatigue. Int J Sports Physiol Perform 10: 84–92, 2015.
Haugen T, Buchheit M. Sprint running performance monitoring: Methodological and practical considerations. Sports Med 46: 641–656, 2016.
Hetherington R. Within-subject variation, measurement error, and selection of a criterion score. Res Q 44: 113–117, 1973.
Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 30: 1–15, 2000.
Hopkins WG. How to interpret changes in an athletic performance test. Sportscience 8: 1–7, 2004.
Hopkins WG. Analysis of reliability with a spreadsheet. 2007. Available at: sportsci.org/resource/stats/xrely.xls .
Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 41: 3–12, 2009.
Impellizzeri FM, Marcora SM. Test validation in sport physiology: Lessons learned from clinimetrics. Int J Sports Physiol Perform 4: 269–277, 2009.
Johnston RD, Gibson NV, Twist C, Gabbett TJ, MacNay SA, MacFarlane NG. Physiological responses to an intensified period of rugby league competition. J Strength Cond Res 27: 643–654, 2012.
Kennedy RA, Drake D. Dissociated time course of recovery between strength and power after isoinertial resistance loading in rugby union players. J Strength Cond Res 32: 748–755, 2017.
Kroll W. Reliability theory and research decision in selection of a criterion score. Res Q 38: 412–419, 1967.
Mandic R, Jakovljevic S, Jaric S. Effects of countermovement depth on kinematic and kinetic patterns of maximum vertical jumps. J Electromyogr Kinesiol 25: 265–272, 2015.
McCaulley GO, McBride JM, Cormie P, Hudson MB, Nuzzo JL, Quindry JC, Triplett NT. Acute hormonal and neuromuscular responses to hypertrophy, strength and power type resistance exercise. Eur J Appl Physiol 105: 695–704, 2009.
Mundy PD, Lake JP, Carden PJC, Smith NA, Lauder MA. Agreement between the force platform method and the combined method measurements of power output during the loaded countermovement jump. Sports Biomech 15: 23–35, 2016.
Rodano R, Squadrone R. Stability of selected lower limb joint kinetic parameters during vertical jump. J Appl Biomech 18: 83–89, 2002.
Roe G, Darrall-Jones J, Till K, Phibbs P, Read D, Weakly J, Jones B. Between-day reliability and sensitivity of common fatigue measure in rugby players. Int J Sport Physiol Perform 11: 581–586, 2016.
Rowell AE, Aughey RJ, Hopkins WG, Stewart AM, Cormack SJ. Identification of sensitive measures of recovery following external load from football match play. Int J Sports Physiol Perform 12: 969–976, 2017.
Saunders PU, Pyne DB, Telford RD, Hawley JA. Reliability and variability of running economy in elite distance runners. Med Sci Sports Exerc 36: 1972–1976, 2004.
Silva JR, Rumpf MC, Hertzog M, Castagna C, Farooq A, Girard O, Hader K. Acute and residual soccer match-related fatigue: A systematic review and meta-analysis. Sports Med 48: 539–583, 2017.
Taylor KL, Cronin J, Gill ND, Chapman DW, Sheppard J. Sources of variability in isoinertial jump assessments. Int J Sports Physiol Perform 5: 546–558, 2010.
Thomas K, Dent J, Howatson G, Goodall S. Etiology and recovery of neuromuscular fatigue after simulated soccer match play. Med Sci Sports Exerc 49: 955–964, 2017.
Thorlund JB, Michalsik LB, Madsen K, Aagaard P. Acute fatigue-induced changes in muscle mechanical properties and neuromuscular activity in elite handball players following a handball match. Scand J Med Sci Sport 18: 462–472, 2008.
Weakley JJS, Till K, Read DB, Roe GAB, Darrall-Jones J, Phibbs PJ, Jones B. The effects of traditional, superset, and tri-set resistance training structures on perceived intensity and physiological responses. Eur J Appl Physiol 117: 1877–1889, 2017.
Winter EM, Abt G, Brookes FBC, Challis JH, Fowler NE, Knudson DV, Knuttgen HG, Kraemer WJ, Lane AM, van Mechelen W, Morton RH, Newton RU, Williams C, Yeadon MR. Misuse of “power” and other mechanical terms in sport and exercise science research. J Strength Cond Res 30: 292–300, 2016.