Jones, B

Sawczuk, T

Scantlebury, S

Till, K

Leeds Beckett Repository

SENSITIVITY OF DAILY WELLBEING AND NEUROMUSCULAR FATIGUE MEASURES TO TRAINING LOAD AND SLEEP IN HIGH SCHOOL AGE ATHLETESThomas Sawczuk1,2, Ben Jones1,2,3, Sean Scantlebury1,2, Kevin Till1,3t.sawczuk@leedsbeckett.ac.uk ;        @Tom_Sawczuk1Leeds Beckett University, Leeds, UK  2Queen Ethelburga’s Collegiate, York, UK 3Yorkshire Carnegie RUFC, UK•Fifty-two high school age athletes (age 17.3 ± 0.6 years, height 173.0 ± 18.2 cm, body mass 73.7 ±12.6 kg) volunteered to participate in this eight week study.•Prior to their first training session of the day, participants:• Completed DWB and PRS• Provided details on the previous day’s training loads and sleep length• Completed 3 maximal CMJs•Partial correlations were used to assess the linear relationship between DWB, PRS and CMJ with training load and sleep length. •Correlation coefficients (r) were calculated and magnitude based inferences were used to assess for practical significance. The research, travel and conference fees for this poster were funded by the Carnegie Adolescent Rugby Research (CARR) project.METHODSRESULTSINTRODUCTION•Previous studies have shown the sensitivity of daily wellbeing questionnaires (DWB) and countermovement jumps to training load in elite adult athletes. 1,2•Sleep length has previously been shown to affect mood, but no study has yet considered its impact on wellbeing questionnaires alongside training load. 3•The purpose of this study was to assess the sensitivity of a DWB, the Perceived Recovery Status scale4 (PRS) and countermovement jumps (CMJ) to training load and sleep length in high school age athletes.PRACTICAL APPLICATIONSACKNOWLEDGEMENTSREFERENCES1 McLean, B. D., Coutts, A. J., Kelly, V., McGuigan, M. R., & Cormack, S. J. (2010). Neuromuscular, endocrine, and perceptual fatigue responses during different length between-match microcycles in professional rugby league players. International Journal of Sports Physiology and Performance, 5, 367–383.2 Thorpe, R. T., Strudwick, A. J., Buchheit, M., Atkinson, G., Drust, B., & Gregson, W. (2017). The influence of changes in acute training load on daily sensitivity of morning measured fatigue variables in elite soccer players. International Journal of Sports Physiology and Performance, 12, S2107-S2113.3 Oginska, H., & Pokorski, J. (2006). Fatigue and mood correlates of sleep length in three age-social groups: School children, students, and employees. Chronobiology International, 23, 1317-1328.4 Laurent, C. M., Green, J. M., Bishop, P. A., Sjokvist, J., Schumacher, R. E., Richardson, M. T., & Curtner-Smith, M. (2011). A practical approach to monitoring recovery: Development of a perceived recovery status scale. Journal of Strength and Conditioning Research, 25, 620–628.Figure 1: Graphical depiction of correlation coefficients for DWB, PRS and CMJ. Asterixes denote the likelihood that the correlation coefficient is greater than the smallest worthwhile change (shaded area): * likely; ** very likely; *** most likely.•There was a most likely small positive relationship between DWB and sleep length (r = 0.28; ± 0.05).•There was a most likely small negative relationship between PRS and training load (r = -0.23; ± 0.05).• Subjective measures of wellbeing are more sensitive to training loads and sleep length than neuromuscular measures.• The PRS is a simple tool for monitoring an individual’s response to training.•The DWB may provide a more complete understanding of the high school athlete’s wellbeing but this comes at the expense of its sensitivity to training load.RESULTS

Sensitivity of daily wellbeing and neuromuscular fatigue measures to training load and sleep in high school age athletes

http://eprints.leedsbeckett.ac.uk/6209/1/SensitivityDailyWellbeingNeuromuscularFatigueMeasureTrainingLoadSleepHighSchoolAgeAthletesPV-SAWCZUK.pdf

Sensitivity of daily wellbeing and neuromuscular fatigue measures to training load and sleep in high school age athletes

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