Validity of the Online Athlete Management System to Assess Training Load

in International Journal of Sports Physiology and Performance
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Purpose: To validate the quantification of training load (session rating of perceived exertion [s-RPE]) in an Australian Olympic squad (women’s water polo), assessed with the use of a modified RPE scale collected via a newly developed online system (athlete management system). Methods: Sixteen elite women water polo players (age = 26 [3] y, height  = 1.78 [0.05] m, and body mass  = 75.5 [7.1] kg) participated in the study. Thirty training sessions were monitored for a total of 303 individual sessions. Heart rate was recorded during training sessions using continuous heart-rate telemetry. Participants were asked to rate the intensity of the training sessions on the athlete management system RPE scale, using an online application within 30 min of completion of the sessions. Individual relationships between s-RPE and both Banister training impulse (TRIMP) and Edwards’ method were analyzed. Results: Individual correlations with s-RPE ranged between r = .51 and .79 (Banister TRIMP) and r = .54 and .83 (Edwards’ method). The percentages of moderate and large correlation were 81% and 19% between s-RPE method and Banister TRIMP, and 56% and 44% between s-RPE and Edwards’ method. Conclusions: The online athlete management system for assessing s-RPE was shown to be a valid indicator of internal training load and can be used in elite sport.

M.J. Menaspà is with Physical Therapies Dept, Australian Inst of Sport, Canberra, ACT, Australia. M.J. Menaspà and Clark are with Water Polo Australia, Sydney, NSW, Australia. P. Menaspà is with the School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia. Clark is also with Physiology Dept, Australian Inst of Sport, Canberra, ACT, Australia. Fanchini is with the Dept of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy, and the U.S. Sassuolo Football Club, Sassuolo, Italy.

M.J. Menaspà (miranda.menaspa@ausport.gov.au) is corresponding author.
  • 1.

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109–115. PubMed ID: 11708692

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Lupo C, Capranica L, Tessitore A. The validity of the session-RPE method for quantifying training load in water polo. Int J Sports Physiol Perform. 2014;9(4):656–660. PubMed ID: 24231176 doi:10.1123/ijspp.2013-0297

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

    Scott TJ, Black CR, Quinn J, Coutts AJ. Validity and reliability of the session-RPE method for quantifying training in Australian football: a comparison of the CR10 and CR100 scales. J Strength Cond Res. 2013;27(1):270–276. PubMed ID: 22450253 doi:10.1519/JSC.0b013e3182541d2e

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

    Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora SM. Use of RPE-based training load in soccer. Med Sci Sports Exerc. 2004;36(6):1042–1047. PubMed ID: 15179175 doi:10.1249/01.MSS.0000128199.23901.2F

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

    Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(suppl 2):139–147. doi:10.1007/s40279-014-0253-z

  • 6.

    Drew MK, Finch CF. The relationship between training load and injury, illness and soreness: a systematic and literature review. Sports Med. 2016;46(6):861–883. PubMed ID: 26822969 doi:10.1007/s40279-015-0459-8

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

    Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–280. PubMed ID: 26758673 doi:10.1136/bjsports-2015-095788

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

    Borg E, Borg G. A comparison of AME and CR100 for scaling perceived exertion. Acta Psychol. 2002;109(2):157–175. doi:10.1016/S0001-6918(01)00055-5

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

    Borg E, Kaijser L. A comparison between three rating scales for perceived exertion and two different work tests. Scand J Med Sci Sports. 2006;16(1):57–69. PubMed ID: 16430682 doi:10.1111/j.1600-0838.2005.00448.x

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

    Fanchini M, Ferraresi I, Modena R, Schena F, Coutts AJ, Impellizzeri FM. Use of CR100 scale for session rating of perceived exertion in soccer and its interchangeability with the CR10. Int J Sports Physiol Perform. 2016;11(3):388–392. PubMed ID: 26309332 doi:10.1123/ijspp.2015-0273

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Russell WD. On the current status of rated perceived exertion. Percept Mot Skills. 1997;84(3, pt 1):799–808. PubMed ID: 9172185 doi:10.2466/pms.1997.84.3.799

  • 12.

    Borg G. Psychophysical scaling with applications in physical work and the perception of exertion. Scand J Work Environ Health. 1990;16(suppl 1):55–58. doi:10.5271/sjweh.1815

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Morgan WP. Psychological components of effort sense. Med Sci Sports Exerc. 1994;26(9):1071–1077. PubMed ID: 7808238 doi:10.1249/00005768-199409000-00001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Schuman H, Presser S. Questions and Answers in Attitude Surveys:Experiments on Question Form, Wording, and Context. New York, NY: Academic Press; 1981.

    • Search Google Scholar
    • Export Citation
  • 15.

    Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377–381. PubMed ID: 7154893 doi:10.1249/00005768-198205000-00012

  • 16.

    Borg G, Borg E. A new generation of scaling methods: level-anchored ratio scaling. Psychologica. 2001;28:15–45.

  • 17.

    Ritchie C. Rating of perceived exertion (RPE). J Physiother. 2012;58(1):62. PubMed ID: 22341388 doi:10.1016/S1836-9553(12)70078-4

  • 18.

    Borg G. Borg’s Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics; 1998.

  • 19.

    Impellizzeri FM, Borg E, Coutts AJ. Intersubjective comparisons are possible with an accurate use of the Borg CR scales. Int J Sports Physiol Perform. 2011;6(1):2–7. PubMed ID: 21506437 doi:10.1123/ijspp.6.1.2

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

    Menaspa P. Building evidence with flawed data? The importance of analysing valid data. Br J Sports Med. 2017;51(15):1173. PubMed ID: 28223302 doi:10.1136/bjsports-2016-097029

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

    Collins D. Pretesting survey instruments: an overview of cognitive methods. Qual Life Res. 2003;12(3):229–238. PubMed ID: 12769135 doi:10.1023/A:1023254226592

  • 22.

    Foster C, Rodriguez-Marroyo JA, de Koning JJ. Monitoring training loads: the past, the present, and the future. Int J Sports Physiol Perform. 2017;12(suppl 2):22–28. PubMed ID: 28253038 doi:10.1123/IJSPP.2016-0388

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

    Piacentini MF, Meeusen R. An online training-monitoring system to prevent nonfunctional overreaching. Int J Sports Physiol Perform. 2015;10(4):524–527. PubMed ID: 25310521 doi:10.1123/ijspp.2014-0270

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

    Bowling A. Mode of questionnaire administration can have serious effects on data quality. J Public Health. 2005;27(3):281–291. doi:10.1093/pubmed/fdi031

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

    Marcano Belisario JS, Jamsek J, Huckvale K, O’Donoghue J, Morrison CP, Car J. Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods. Cochrane Database Syst Rev. 2015;(7):MR000042.

    • Search Google Scholar
    • Export Citation
  • 26.

    Edwards S. The Heart Rate Monitor Book. Sacramento, CA: Fleet Feet Press; 1993.

  • 27.

    Banister EW. Modeling elite athletic performance. In: Green HJ, McDougal JD, Wenger HA, eds. Physiological Testing of Elite Athletes. Champaign, IL: Human Kinetics; 1991:403–424.

    • Search Google Scholar
    • Export Citation
  • 28.

    Clark SJ, D’Auria S. Water polo players. In: Tanner RK, Gore CJ, eds. Physiological tests for elite athletes. Champaign, IL: Human Kinetics; 2013:487–498.

    • Search Google Scholar
    • Export Citation
  • 29.

    Manzi V, D’Ottavio S, Impellizzeri FM, Chaouachi A, Chamari K, Castagna C. Profile of weekly training load in elite male professional basketball players. J Strength Cond Res. 2010;24(5):1399–1406. PubMed ID: 20386474 doi:10.1519/JSC.0b013e3181d7552a

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

    Minganti C, Capranica L, Meeusen R, Amici S, Piacentini MF. The validity of session rating of perceived exertion method for quantifying training load in teamgym. J Strength Cond Res. 2010;24(11):3063–3068. PubMed ID: 20838255 doi:10.1519/JSC.0b013e3181cc26b9

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

    Clarke N, Farthing JP, Norris SR, Arnold BE, Lanovaz JL. Quantification of training load in Canadian football: application of session-RPE in collision-based team sports. J Strength Cond Res. 2013;27(8):2198–2205. PubMed ID: 23222076 doi:10.1519/JSC.0b013e31827e1334

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

    Garcia-Ramos A, Feriche B, Calderon C, et al. Training load quantification in elite swimmers using a modified version of the training impulse method. Eur J Sport Sci. 2015;15(2):85–93. PubMed ID: 24942164 doi:10.1080/17461391.2014.922621

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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