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Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review

Published on Mar 1, 2016in British Journal of Sports Medicine11.64
· DOI :10.1136/bjsports-2015-094758
Anna E. Saw5
Estimated H-index: 5
(Deakin University),
Luana C. Main12
Estimated H-index: 12
(Deakin University),
Paul B. Gastin20
Estimated H-index: 20
(Deakin University)
Cite
Abstract
Background Monitoring athlete well-being is essential to guide training and to detect any progression towards negative health outcomes and associated poor performance. Objective (performance, physiological, biochemical) and subjective measures are all options for athlete monitoring. Objective We systematically reviewed objective and subjective measures of athlete well-being. Objective measures, including those taken at rest (eg, blood markers, heart rate) and during exercise (eg, oxygen consumption, heart rate response), were compared against subjective measures (eg, mood, perceived stress). All measures were also evaluated for their response to acute and chronic training load. Methods The databases Academic search complete, MEDLINE, PsycINFO, SPORTDiscus and PubMed were searched in May 2014. Fifty-six original studies reported concurrent subjective and objective measures of athlete well-being. The quality and strength of findings of each study were evaluated to determine overall levels of evidence. Results Subjective and objective measures of athlete well-being generally did not correlate. Subjective measures reflected acute and chronic training loads with superior sensitivity and consistency than objective measures. Subjective well-being was typically impaired with an acute increase in training load, and also with chronic training, while an acute decrease in training load improved subjective well-being. Summary This review provides further support for practitioners to use subjective measures to monitor changes in athlete well-being in response to training. Subjective measures may stand alone, or be incorporated into a mixed methods approach to athlete monitoring, as is current practice in many sport settings.
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  • References (113)
  • Citations (119)
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References113
Newest
Published on Nov 1, 2015in British Journal of Sports Medicine11.64
Richard Burden6
Estimated H-index: 6
(St. Mary's University),
Katie L. Morton9
Estimated H-index: 9
(St. Mary's University)
+ 2 AuthorsCharles R. Pedlar16
Estimated H-index: 16
(St. Mary's University)
Purpose The aim of this study was to determine whether iron treatments improve the iron status and aerobic capacity of iron deficient non-anaemic endurance athletes. Method A meta-analysis of studies that investigated the effects of iron treatment on serum ferritin (sFer), serum iron (sFe), transferrin saturation (Tsat), haemoglobin concentration ([Hb]) and (Graphic). Seventeen eligible studies were identified from online databases. Results Analysis of pooled data indicated that iron treatments ...
Published on Mar 1, 2015in Journal of Sports Science and Medicine1.77
Anna E. Saw5
Estimated H-index: 5
,
Luana C. Main12
Estimated H-index: 12
,
Paul B. Gastin20
Estimated H-index: 20
Monitoring athletic preparation facilitates the evaluation and adjustment of practices to optimize performance outcomes. Self-report measures such as questionnaires and diaries are suggested to be a simple and cost-effective approach to monitoring an athlete’s response to training, however their efficacy is dependent on how they are implemented and used. This study sought to identify the perceived factors influencing the implementation of athlete self-report measures (ASRM) in elite sport settin...
Published on Dec 1, 2014in Scandinavian Journal of Medicine & Science in Sports3.63
J. R. Grove2
Estimated H-index: 2
(UWA: University of Western Australia),
Luana C. Main12
Estimated H-index: 12
(Deakin University)
+ 4 AuthorsLeah J. Ferguson9
Estimated H-index: 9
(U of S: University of Saskatchewan)
Three studies were conducted to validate the Training Distress Scale (TDS), a 19-item measure of training-related distress and performance readiness. Study 1 was a randomized, controlled laboratory experiment in which a treatment group undertook daily interval training until a 25% decrement occurred in time-to-fatigue performance. Comparisons with a control group showed that TDS scores increased over time within the treatment group but not in the control group. Study 2 was a randomized, controll...
Published on Nov 1, 2014in Sports Medicine7.58
Shona L. Halson26
Estimated H-index: 26
(AIS: Australian Institute of Sport)
Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of t...
Published on Jul 1, 2014in Sports Medicine7.58
Gustaaf Reurink14
Estimated H-index: 14
(EUR: Erasmus University Rotterdam),
Gert Jan Goudswaard9
Estimated H-index: 9
+ 3 AuthorsJohannes L. Tol29
Estimated H-index: 29
Background Injection therapies are widely used for muscle injuries. As there is only limited evidence of their efficacy, physicians should be aware of the potential harmful effects of these injected preparations.
Ian Rollo1
Estimated H-index: 1
,
Franco M. Impellizzeri48
Estimated H-index: 48
+ 1 AuthorsF. Marcello Iaia11
Estimated H-index: 11
The physical-performance profiles of subelite male footballers were monitored during 6 wk of a competitive season. The same squad of players played either 1 (1G, n = 15) or 2 (2G, n = 15) competitive matches per week. On weeks 0, 3, and 6, 48 h postmatch, players completed countermovement jump (CMJ), 10- and 20-m sprints, the Yo-Yo Intermittent Recovery Test (YYIRT), and the Recovery-Stress Questionnaire. Both groups undertook 2 weekly training sessions. The 2G showed after 6 wk lower YYIRT (–11...
Published on Feb 1, 2014in British Journal of Sports Medicine11.64
John P. DiFiori22
Estimated H-index: 22
(UCLA: University of California, Los Angeles),
Holly J. Benjamin15
Estimated H-index: 15
(U of C: University of Chicago)
+ 4 AuthorsAnthony Luke16
Estimated H-index: 16
(UCSF: University of California, San Francisco)
### Background Youth sport participation offers many benefits including the development of self-esteem, peer socialisation and general fitness. However, an emphasis on competitive success, often driven by goals of elite-level travel team selection, collegiate scholarships, Olympic and National team membership and even professional contracts, has seemingly become widespread. This has resulted in an increased pressure to begin high-intensity training at young ages. Such an excessive focus on early...
Published on Jan 20, 2014in Journal of Sports Science and Medicine1.77
Vinicius Flavio Milanez7
Estimated H-index: 7
,
Solange de Paula Ramos8
Estimated H-index: 8
+ 2 AuthorsFábio Yuzo Nakamura21
Estimated H-index: 21
The aim of this study was: to describe typical training load (TL) carried out by a professional female futsal team for a period of 5 weeks; and to verify the relationship between TL, stress symptoms, salivary secretory immunoglobulin A (SIgA) levels, and symptoms of upper respiratory infections (URI). Over 45 sessions, the TL of the athletes was monitored daily by means of session-RPE method during the in-season period prior to the main national competition. Stress symptoms were measured weekly ...
Published on Jan 1, 2014in European Journal of Applied Physiology3.06
Lee Wallace9
Estimated H-index: 9
(UTS: University of Technology, Sydney),
Katie M. Slattery13
Estimated H-index: 13
(UTS: University of Technology, Sydney),
Aaron J. Coutts47
Estimated H-index: 47
(UTS: University of Technology, Sydney)
Purpose To assess the validity of methods for quantifying training load, fitness and fatigue in endurance athletes using a mathematical model.
Published on Nov 7, 2013
David Joyce2
Estimated H-index: 2
,
Daniel Lewindon2
Estimated H-index: 2
,
Mark Verstegen1
Estimated H-index: 1
Part I. Building Robust Athletes Part II. Developing Athletic Capacity Part III. Delivering Performance.
Cited By119
Newest
Published on Dec 1, 2019in Sports Medicine - Open
João Gustavo Claudino4
Estimated H-index: 4
(USP: University of São Paulo),
Daniel de Oliveira Capanema + 3 AuthorsGeorge P Nassis (Unity College)
The application of artificial intelligence (AI) opens an interesting perspective for predicting injury risk and performance in team sports. A better understanding of the techniques of AI employed and of the sports that are using AI is clearly warranted. The purpose of this study is to identify which AI approaches have been applied to investigate sport performance and injury risk and to find out which AI techniques each sport has been using. Systematic searches through the PubMed, Scopus, and Web...
Published on Mar 28, 2019in European Journal of Sport Science2.38
Rebecca Cross2
Estimated H-index: 2
(USYD: University of Sydney),
Jason C. Siegler21
Estimated H-index: 21
(USYD: University of Sydney)
+ 1 AuthorsRichard J Lovell21
Estimated H-index: 21
(USYD: University of Sydney)
ABSTRACTThe aim of this study was to determine the in-season micro-cycle scheduling strategies used in professional team sport with particular reference to the reasoning and perceptions that underpin current practice. An online survey was completed by 35 practitioners from professional collision (C; Australian rules football: n = 9; rugby league: n = 6; rugby union: n = 2) and non-collision (NC; soccer; n = 18) sports. Respondents identified a common 48 h post-match recovery period, with few sch...
Published on May 13, 2019in European Journal of Sport Science2.38
Suzanna Russell1
Estimated H-index: 1
(Queensland Academy of Sport),
David G. Jenkins45
Estimated H-index: 45
(UQ: University of Queensland)
+ 2 AuthorsVincent G. Kelly8
Estimated H-index: 8
(QUT: Queensland University of Technology)
AbstractMental fatigue is a psychobiological state caused by prolonged periods of demanding cognitive activity shown to negatively influence physical performance. Variation exists across the literature regarding the manifestations and impact of mental fatigue; with little knowledge of the domain-specific manifestations in elite sport. The difficulties in defining mental fatigue may explain why it is not consistently assessed by coaching or support staff. The aim of this study was therefore to in...
Published on Dec 1, 2018in British Journal of Sports Medicine11.64
Johann Windt8
Estimated H-index: 8
,
David Taylor79
Estimated H-index: 79
+ 1 AuthorsBruno D. Zumbo45
Estimated H-index: 45
(UBC: University of British Columbia)
Athlete self-report measures (ASRMs) are an extremely popular athlete monitoring tool in professional sports.1 Their popularity stems from their ease of use, low/no cost, and a growing body of literature that highlights that ASRMs are more sensitive to injury/illness risk than many physiological biomarkers.2 Whether ASRMs are used to examine athletes’ data once (eg, preseason baseline testing) or to regularly monitor athletes over time (eg, daily or weekly), the results are often used to drive d...
Published on 2019in Physiology & Behavior2.63
Filipe Manuel Clemente2
Estimated H-index: 2
(Polytechnic Institute of Viana do Castelo),
Alireza Rabbani4
Estimated H-index: 4
,
João Pedro Araújo
Abstract The purpose of this study was to examine the interchangeability of a new perceived recovery status scale (PRS) of 100 points through a comparison to the original 10-point version. This study also aimed to test the interchangeability of CR100 scale (Borg's rate of perceived exertion scale) in comparison to the CR10. Twenty-five male elite youth soccer players (age: 18.0 ± 0.5 years old; body mass: 70.1 ± 6.7 kg; height: 177.8 ± 6.5 cm; experience: 11.7 ± 1.2 years) from the same team com...
Jason D. Vescovi22
Estimated H-index: 22
(U of T: University of Toronto),
Alexander Klas (U of T: University of Toronto), Iva Mandic (U of T: University of Toronto)
Steven Doeven2
Estimated H-index: 2
(Hanze University of Applied Sciences),
Michel Brink13
Estimated H-index: 13
(UMCG: University Medical Center Groningen)
+ 2 AuthorsKoen Lemmink32
Estimated H-index: 32
(UMCG: University Medical Center Groningen)
During rugby sevens tournaments it is crucial to balance match load and recovery to strive for optimal performance.Purpose:To determine changes in wellbeing, recovery and neuromuscular performance ...
Arne Jaspers5
Estimated H-index: 5
(Katholieke Universiteit Leuven),
Tim Op De Beéck3
Estimated H-index: 3
(Katholieke Universiteit Leuven)
+ 4 AuthorsWerner F. Helsen3
Estimated H-index: 3
(Katholieke Universiteit Leuven)
Purpose:The influence of preceding load and perceived wellness on the future perceived wellness of professional soccer players is unexamined. This paper simultaneously evaluates the external and in...
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