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Dudley C, Johnston R, Jones B, Till K, Westbrook H, Weakley J. Methods of Monitoring Internal and External Loads and Their Relationships with Physical Qualities, Injury, or Illness in Adolescent Athletes: A Systematic Review and Best-Evidence Synthesis. Sports Med 2023; 53:1559-1593. [PMID: 37071283 PMCID: PMC10356657 DOI: 10.1007/s40279-023-01844-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/19/2023] [Indexed: 04/19/2023]
Abstract
BACKGROUND With the increasing professionalisation of youth sports, training load monitoring is increasingly common in adolescent athletes. However, the research examining the relationship between training load and changes in physical qualities, injury, or illness in adolescent athletes is yet to be synthesised in a systematic review. OBJECTIVE The aim of this review was to systematically examine the research assessing internal and external methods of monitoring training load and physical qualities, injury, or illness in adolescent athletes. METHODS Systematic searches of SPORTDiscus, Web of Science, CINAHL and SCOPUS were undertaken from the earliest possible records to March 2022. Search terms included synonyms relevant to adolescents, athletes, physical qualities, injury, or illness. To be eligible for inclusion, articles were required to (1) be original research articles; (2) be published in a peer-reviewed journal; (3) include participants aged between 10 and 19 years and participating in competitive sport; (4) report a statistical relationship between a measure of internal and/or external load and physical qualities, injury or illness. Articles were screened and assessed for methodological quality. A best-evidence synthesis was conducted to identify trends in the relationships reported. RESULTS The electronic search yielded 4125 articles. Following screening and a review of references, 59 articles were included. The most commonly reported load monitoring tools were session ratings of perceived exertion (n = 29) and training duration (n = 22). Results of the best-evidence synthesis identified moderate evidence of positive relationships between resistance training volume load and improvement in strength, and between throw count and injury. However, evidence for other relationships between training load and change in physical qualities, injury, or illness were limited or inconsistent. CONCLUSIONS Practitioners should consider monitoring resistance training volume load for strength training. Additionally, where appropriate, monitoring throw counts may be useful in identifying injury risk. However, given the lack of clear relationships between singular measures of training load with physical qualities, injury, or illness, researchers should consider multivariate methods of analysing training load, as well as factors that may mediate the load-response relationship, such as maturation.
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Affiliation(s)
- Charles Dudley
- School of Behavioural and Health Sciences, Australian Catholic University, Banyo Campus, Brisbane, Australia.
- St Joseph's Nudgee College, Boondall, Brisbane, Australia.
| | - Rich Johnston
- School of Behavioural and Health Sciences, Australian Catholic University, Banyo Campus, Brisbane, Australia
- Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK
| | - Ben Jones
- Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK
- Health through Physical Activity, Lifestyle and Sport Research Centre (HPALS), Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Premiership Rugby, London, UK
- Leeds Rhinos Rugby League Club, Leeds, UK
- England Performance Unit, The Rugby Football League, Leeds, UK
| | - Kevin Till
- Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK
- Leeds Rhinos Rugby League Club, Leeds, UK
| | | | - Jonathon Weakley
- School of Behavioural and Health Sciences, Australian Catholic University, Banyo Campus, Brisbane, Australia
- Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK
- Sports Performance, Recovery, Injury and New Technologies (SPRINT) Research Centre, Australian Catholic University, Brisbane, Australia
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Bliss A, Waldron M, Maxwell N. Predicting middle-distance track and cross-country performances of national and international level adolescent runners. Eur J Sport Sci 2021; 22:305-313. [PMID: 33460365 DOI: 10.1080/17461391.2020.1867650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
AbstractThis study evaluated the contribution of physiological data collected during laboratory testing in predicting race performances of trained junior middle-distance track (TK) and cross-country (XC) athletes. Participants performed a submaximal incremental ramp test, followed by an incremental test to exhaustion in a laboratory, with the results used to predict either 800 m TK, 1500 m TK or 4000-6000 m XC race performance. Twenty-eight participants (male (M), 15; female (F), 13) were analysed (age = 17 ± 2 years, height = 1.72 ± 0.08 m, body mass = 58.9 ± 8.9 kg). Performance times (min:s) for 800 m were: M, 1:56.55 ± 0:05.55 and F, 2:14.21 ± 0:03.89; 1500 m: M, 3:51.98 ± 0:07.35 and F 4:36.71 ± 0:16.58; XC: M (4900 ± 741 m), 16:00 ± 01:53; F (4628 ± 670 m), 17:41 ± 02:09. Stepwise regression analysis indicated significant contributions of speed at V̇O2max (V̇O2max), and heart rate maximum (HRmax) to the prediction of 800 m TK (F(2,15) = 22.51, p < 0.001, adjusted R2 = 0.72), V̇O2max for 1500 m TK (F(1,13) = 36.65, p < 0.001, adjusted R2 = 0.72) and V̇O2max, allometrically scaled to body mass and speed at lactate threshold (sLT) for XC (F(2,17) = 25.1, p < 0.001, adjusted R2 = 0.72). Laboratory-based physiological measures can explain 72% of the variance in junior TK and XC events, although factors that explain performance alter depending on the race distance and tactics. The factors determining performance in TK and XC events are not interchangeable.
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Affiliation(s)
- Alex Bliss
- Faculty of Sport, Applied Health and Performance Sciences, St Mary's University, London, UK
| | - Mark Waldron
- College of Engineering, Swansea University, Swansea, UK.,School of Science and Technology, University of New England, Armidale, Australia
| | - Neil Maxwell
- School of Sport and Service Management, University of Brighton, UK
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