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Load, capacity and health: Critical pieces of the holistic performance puzzle

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Evert Verhagen
Evert Verhagen
Evert Verhagen
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Tim Gabbett at Gabbett Performance Solutions
Tim Gabbett
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VerhagenE, GabbettT. Br J Sports Med Month 2018 Vol 0 No 0
Load, capacity and health: critical pieces
of the holistic performancepuzzle
Evert Verhagen,1,2 Tim Gabbett3,4
Relationships between load, load capacity,
performance and health are topics of
contemporary interest. At what intensity
should an athlete train to achieve the best
physiological response? How much (or
little) can an athlete train without detri-
mentally affecting health? Most studies
addressing such questions have used a
reductionist approach wherein factors
were studied in isolation, thereby ignoring
the complex inter-relationships and
balance between factors. This editorial
discusses the association between load and
load capacity, and their relationship with
athlete performance and health. We illus-
trate the practical use of a model for the
management of athlete performance and
health, and provide directions for future
practice and research.
A BALANCING ACT
Figure 1 shows the intertwined rela-
tionships between load, load capacity,
performance and health. To stimulate
adaptation the basic principle of any
training programme is to apply a load
(ie, the amount of mechanical, physio-
logical or mental stress) through training
or competition that is greater than an
athlete’s current load capacity (ie, the
ability to tolerate load).1 With the optimal
balance between both constructs, an
appropriate training stimulus will elicit
performance and health benefits.
In this relationship, an athlete’s load
capacity will determine which load, in
terms of volume, intensity and frequency,
is beneficial. Equally, applying the
correct amount of load will benefit the
load capacity; for example, through an
improvement in strength, (mental) resil-
ience, bone mass, etc. However, one
should keep in mind that an athlete’s load
and load capacity, as well as the balance
between both, are influenced by context
and environment, both of which are
temporal.2 3 This means that the balance
between load and load capacity today may
be tipped tomorrow due to fluctuations in
fatigue, mental state, motivation, etc.
When load is off-balance with load
capacity, there is heightened risk for
detrimental health effects such as injury
or illness. Such negative effects have
been described after both overloading
and underloading.4 5 Suboptimal health
directly affects performance through
reduced ability to perform (eg, through
pain, restrictions, etc), but also indirectly
through a reduced load capacity (eg,
through reduced strength, stress, changes
in tissue integrity). The latter, in turn,
demands changes in the applied load to
improve load capacity and manage the risk
of further negative health changes.
FINDING THE BALANCE IN PRACTICE
The presented approach outlines that
the modifiable factors of load and load
capacity, and the outcomes of perfor-
mance and health are interlinked.
Any change in one component of the
model affects others. Consequently, the
various components must be considered
together; adaptations in load alone will
be insufficient to optimise performance
while protecting athletes’ health. As
an example, Møller et al6 showed that
handball players with reduced external
rotational strength or scapular dyski-
nesis could withstand a lower increase
in weekly handball load compared with
players without such shoulder deficits.
One could either adapt the load to the
capacity of each player or improve the
shoulder function of affected players,
or preferably both. Another example is
given by Malone et al7 who described
in Gaelic football players an increased
injury risk related to high weekly work-
loads and acute:chronic workload ratios
(>2.0). However, high aerobic capacity
and greater playing experience moder-
ated these effects and were protective
for injury. The latter study illustrated the
need to adapt training session content
and intensity to the capacity of individual
athletes, and the presence of modifiable
load capacity factors which may vary
during a season (eg, aerobic capacity).
WHERE TO NEXT?
In order to better understand the
complex relationships between compo-
nents and their strength and temporality,
continuous and prospective moni-
toring is needed on each aspect. Such
monitoring should not focus solely on
objective physiological measures, but
should also consider subjective (athlete
reported) outcomes (eg, rate of perceived
exertion (RPE)), psychological measures
(eg, stress, coping mechanisms) and
1Department of Public and Occupational Health,
Amsterdam Collaboration for Health and Safety in
Sports, Amsterdam UMC, Vrije Universiteit Amsterdam,
Amsterdam Movement Sciences, Amsterdam, The
Netherlands
2Department of Human Biology, Faculty of Health
Sciences, UCT/MRC Research Unit for Exercise Science
and Sports Medicine (ESSM), University of Cape Town,
Cape Town, South Africa
3Gabbett Performance Solutions, Brisbane, Queensland,
Australia
4Institute for Resilient Regions, University of Southern
Queensland, Ipswich, Queensland, Australia
Correspondence to Dr Evert Verhagen, Department
of Public and Occupational Health, Amsterdam
Collaboration for Health and Safety in Sports, VU
University Medical Center, Amsterdam 1081 BT, The
Netherlands; e. verhagen@ vumc. nl
Editorial
Figure 1 An integrated view on load, load capacity, performance and health in sports. Dotted
lines represent negative relationships and solid lines represent positive relationships.
on 1 October 2018 by guest. Protected by copyright.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2018-099819 on 25 September 2018. Downloaded from
2VerhagenE, GabbettT. Br J Sports Med Month 2018 Vol 0 No 0
Editorial
lifestyle-related factors such as diet, sleep,
etc. This implies that many stakeholders
within a sports context are involved in
each of the model’s components and
should register and access necessary
parts of information. Such an integrated
approach that holistically encapsulates
various load, capacity, performance and
health aspects is certainly not novel in
the sports setting. However, little of the
lessons learnt in sports practice trickle
down to the peer-reviewed scientific
literature. In addition, the available
literature only paints a small part of
the full picture by describing relation-
ships in isolation without full consider-
ation of contextual sports practice that
needs to deal with the complex interac-
tions as outlined in figure 1. We need to
approach performance as the result of a
complex interaction between a variety of
temporal factors. Only then can we opti-
mise the use of load and load capacity
concepts in sports practice.
Contributors All authors contributed equally to the
inception, thinking and writing for this editorial.
Funding The authors have not declared a specific
grant for this research from any funding agency in the
public, commercial or not-for-profit sectors.
Competing interests TJG works as a consultant
to several high performance organisations, including
sporting teams, industry, military and higher education
institutions. Both authors serve in a voluntary capacity
as Senior Associate Editors of BJSM.
Patient consent Not required.
Provenance and peer review Not commissioned;
externally peer reviewed.
© Author(s) (or their employer(s)) 2018. No commercial
re-use. See rights and permissions. Published by BMJ.
To cite VerhagenE, GabbettT. Br J Sports Med Epub
ahead of print: [please include Day Month Year].
doi:10.1136/bjsports-2018-099819
Accepted 9 September 2018
Br J Sports Med 2018;0:1–2.
doi:10.1136/bjsports-2018-099819
RefeRences
1 Morton RH. Modeling training and overtraining. J Sports
Sci 1997;15:335–40.
2 Bolling C, van Mechelen W, Pasman HR, et al.
Context matters: revisiting the first step of the
’sequence of prevention’ of sports injuries. Sports Med
2018;14:2227–34.
3 Windt J, Gabbett TJ. How do training and
competition workloads relate to injury? The
workload-injury aetiology model. Br J Sports Med
2017;51:428–35.
4 Stovitz SD, Johnson RJ. "Underuse" as a cause
for musculoskeletal injuries: is it time that we
started reframing our message? Br J Sports Med
2006;40:738–9.
5 Gabbett TJ. Influence of training and match
intensity on injuries in rugby league. J Sports Sci
2004;22:409–17.
6 Møller M, Nielsen RO, Attermann J, et al. Handball
load and shoulder injury rate: a 31-week cohort study
of 679 elite youth handball players. Br J Sports Med
2017;51:231–7.
7 Malone S, Roe M, Doran DA, et al. Protection against
spikes in workload with aerobic fitness and playing
experience: the role of the acute:chronic workload ratio
on injury risk in elite gaelic football. Int J Sports Physiol
Perform 2017;12:393–401.
on 1 October 2018 by guest. Protected by copyright.http://bjsm.bmj.com/Br J Sports Med: first published as 10.1136/bjsports-2018-099819 on 25 September 2018. Downloaded from
... Furthermore, it has been acknowledged that regular testing can contribute to prevent injuries and overtraining by tracking training adaptions [6,9]. On the other hand, training methods aim to increase and optimise athletes' performance to cope with the specific demands of their sport [4,11]. Distributed across two main periods (e.g. ...
... Assessing load measures allows for the evaluation of an athlete's adaptation, fatigue and recovery status, adjustment of an individual training programme, its impact on performance, and minimising the risk of injury and illness [12,13]. Hence, an optimal training load management would yield performance and health benefits, acknowledging that both the temporal context and environment influence an athlete's load and load capacity [4]. In respect to injury prevention, the training load has been suggested to drive the athlete towards or away from an injury [4,13,14]. ...
... Hence, an optimal training load management would yield performance and health benefits, acknowledging that both the temporal context and environment influence an athlete's load and load capacity [4]. In respect to injury prevention, the training load has been suggested to drive the athlete towards or away from an injury [4,13,14]. Taken together, given the evolution of equipment, changing environmental factors (e.g. weather and snow conditions), and the complexity and nature of these snow sports disciplines, multiple factors come into play in relation to athletes' performance and health [1,9,15]. ...
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Background and Objective Competitive alpine skiing, snowboarding and freestyle skiing, all different in nature and risks, are known for their high injury and illness burden. Testing measures and training methods may be considered for athletes’ preparation to support performance enhancement while safeguarding their health. We explored the perspectives and perceptions of competitive alpine skiing, snowboarding and freestyle skiing stakeholders regarding testing and training practices in their competitive snow sports. Methods We conducted an exploratory qualitative study based on grounded theory principles through 13 semi-structured interviews about testing and training practices with athletes, on-snow and off-snow coaches, managers and healthcare providers from different national teams. The interviews were inductively analysed through a constant comparative data analysis. Results Participants described winning as the end goal of testing and training practices, which requires athletes to perform in their best condition. To do so, they mentioned two main targets: performance enhancement and health protection. Participants acknowledged health as a premise to perform optimally, considering testing and monitoring approaches, goal setting, and training to support and protect athlete performance. This continuous cyclic process is driven by communication and shared decision making among all stakeholders, using testing and monitoring outputs to inform goal setting, training (e.g. on-snow and off-snow) and injury prevention. Such an approach helps athletes achieve their goal of winning while being fit and healthy throughout their short-term and long-term athletic career development. Conclusions The ultimate goal of testing measures and training methods in such competitive snow sports is winning. Performance enhancement and health protection act as pillars in systematic, tailored and flexible processes to guarantee athletes’ best preparation to perform. Moreover, athletes’ assessments, goal setting, monitoring tools, open communication and shared decision making strongly guide this cyclic process.
View
... Although the link between CFs and TL has been suggested multiple times, there does not appear to be a single clear mechanistic underpinning but rather a myriad of suggested pathways [6,13]. This is understandable due to the broad definition of CFs [3,14]. ...
... Both add up and potentially interact to determine the load of players [7]. This supports the premise of a complex system with inter-relationships between important CFs and TL, yet the precise mechanisms in this linkage remain unspecified [7,13]. ...
... The lack of research regarding the breadth and extent of the relationship between CFs and TL was somewhat surprising since it has been theorized that CFs affect TL [3,6,7,13]. Mainly factors related to the sports context, such as match-related factors (e.g., match outcome) and phase of the season have been investigated. ...
A Scoping Review on the Influence of Contextual Factors on Training Load in Adolescent Soccer Players: What Do We Know?
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This scoping review aimed to systematically explore the breadth and extent of the literature regarding the relationship between contextual factors (CFs) and training load (TL) in adolescent soccer players. Further aims included comprehending potential underlying mechanisms and identifying knowledge gaps. CFs were defined as factors not part of the main training process, such as the coach–athlete relationship and educational responsibilities. PubMed, EBSCO APA PsycINFO, Web of Science, ProQuest Dissertations & Theses A&I, and SportRxiv were searched. Studies involving adolescent soccer players that investigated the CF–TL relationship and measured TL indicators were deemed eligible. Seventeen studies were included, reflecting the limited number of articles published regarding the CF–TL relationship. CFs were mostly related to match-play (N = 13) and phase of the season (N = 7). Moreover, these factors appeared to affect TL. CF related to players’ personal environment (N = 3) were underrepresented in the reviewed studies. Overall, the CF–TL relationship appears to be rarely scrutinized. A likely cause for this lack of research is the segregation of the physiological and psychological research domains, where the CF–TL relationship is often speculated upon but not measured. Therefore, a holistic approach is warranted which also investigates the effect of personal environment, such as stressful life stress events, on TL.
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... Competitive snow sports are performance-driven and carry high injury risks [1][2][3][4][5], which can impact athletes 'performance [6,7]. The International Ski and Snowboard Federation (FIS) has established various prevention efforts to mitigate these risks [8][9][10]. ...
A Survey on Current Practices, Needs, Responsibilities and Preferences for Knowledge Dissemination in the Field of Injury and Illness Prevention Among Competitive Snow Sports Stakeholders
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Background Injury and illness prevention practices in competitive snow sports must be better understood among stakeholders. In particular, there is a need for a greater understanding of what context-specific stakeholders require for prevention. Therefore, this study surveyed stakeholders’ current practices, needs, responsibilities and knowledge dissemination preferences related to injury and illness prevention in competitive snow sports and described the main commonalities and differences between stakeholder groups. Methods We conducted a cross-sectional study that used an online survey developed using Kipling’s principle (the “5W1H” method) and targeted athletes, coaches, team staff, ski racing suppliers, and representatives from all competition levels and all competitive snow sports governed by the International Ski and Snowboard Federation. The data were analysed following both quantitative and qualitative descriptive analyses. Results Most of the 436 respondents believed in and reported needing more information on injury and illness prevention. The participants stated that the main goal of prevention was to avoid injuries and minimise their time away from being on snow, and they stressed their different underlying motivations. Despite the differences across subgroups, participants highlighted knee and head injuries and concussions as their primary injury prevention targets and priorities for additional information. Respiratory and cardiovascular illnesses were reported as their main targets of illness prevention, but more information on all illnesses was reported. Current practices and priorities for additional information fell under athlete-, equipment-, snow/environment-, and course-related prevention areas. Moreover, stakeholders highlighted their need for more information on mental health and training. Shared responsibilities were identified across the development, dissemination, and implementation of prevention, along with stakeholders’ preferred communication channels. Conclusions Our study provides meaningful insights across athlete, equipment-, snow/environment-, and course-related prevention areas related to snow sports, roles, and competition levels. These insights may inform the development, dissemination and further implementation of any tailored and context-driven preventive measure by better addressing end-users’ needs. These findings may support successful future preventive interventions by providing key elements and a clear path to improve athletes’ health and safety.
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... Although load capacity is improved through graded exposure to training stress [105][106][107], there may be occasions where training loads need to be regressed before sensibly progressing [108]. In these instances, practitioners are encouraged to maintain global loading to minimize the systemic effects of detraining and moderate the risk of reinjury upon reintroducing sport-specific activities. ...
From Tissue to System: What Constitutes an Appropriate Response to Loading?
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Optimal loading involves the prescription of an exercise stimulus that promotes positive tissue adaptation, restoring function in patients undergoing rehabilitation and improving performance in healthy athletes. Implicit in optimal loading is the need to monitor the response to load, but what constitutes a normal response to loading? And does it differ among tissues (e.g., muscle, tendon, bone, cartilage) and systems? In this paper, we discuss the “normal” tissue response to loading schema and demonstrate the complex interaction among training intensity, volume, and frequency, as well as the impact of these training variables on the recovery of specific tissues and systems. Although the response to training stress follows a predictable time course, the recovery of individual tissues to training load (defined herein as the readiness to receive a similar training stimulus without deleterious local and/or systemic effects) varies markedly, with as little as 30 min (e.g., cartilage reformation after walking and running) or 72 h or longer (e.g., eccentric exercise-induced muscle damage) required between loading sessions of similar magnitude. Hyperhydrated and reactive tendons that have undergone high stretch–shorten cycle activity benefit from a 48-h refractory period before receiving a similar training dose. In contrast, bone cells desensitize quickly to repetitive loading, with almost all mechanosensitivity lost after as few as 20 loading cycles. To optimize loading, an additional dose (≤ 60 loading cycles) of bone-centric exercise (e.g., plyometrics) can be performed following a 4–8 h refractory period. Low-stress (i.e., predominantly aerobic) activity can be repeated following a short (≤ 24 h) refractory period, while greater recovery is needed (≥ 72 h) between repeated doses of high stress (i.e., predominantly anaerobic) activity. The response of specific tissues and systems to training load is complex; at any time, it is possible that practitioners may be optimally loading one tissue or system while suboptimally loading another. The consideration of recovery timeframes of different tissues and systems allows practitioners to determine the “normal” response to load. Importantly, we encourage practitioners to interpret training within an athlete monitoring framework that considers external and internal load, athlete-reported responses, and objective markers, to contextualize load–response data.
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... 19,20 This lack of control might cause interfering or redundant stimuli, as well as overloading or underloading of shifting players. 21 It is worth noting, however, that only one-fifth of our shifting players disagreed with the statement that monitoring of their training load was adequate and that they had enough time to recover. Nevertheless, load was not consistently quantified during the study period, as it is challenging for practitioners to track shifting players if both secondand first-team staff are not tightly coordinated. ...
View
... In order to improve capacity, the training load applied must exceed the athlete's current capacity, but not be so great that it results in tissue damage. 8 Progressive overload involves the systematic application of training stress and is the cornerstone of rehabilitation, return-to-sport, and performance training programs. 3 Closely aligned with progressive overload is the principle of specificity, as early as the 1940s, researchers demonstrated that the biochemical response of a tissue depended on the type of training that was performed. ...
View
... However, if the findings are true, one could either adapt the load to the capacity of each player or improve the shoulder function of affected players to withstand greater loads, but preferably both. 93 We suggest a minimum set of requirements for efficient workload monitoring for youth athletes in overhead and contact/collision sports, and a build-on for adult and professional athletes who may have additional resources available (TABLE 3). These suggestions guide clinicians, athletes, and coaches to extend the load monitoring principles, and are designed to be employed alongside clinical-reasoning principles for the specific individual or team situation. ...
View
... In this perspective, those individuals with fewer weekly training sessions may have less experience and skill in the techniques of the modality and less adaptation to the load stimuli. Thus, these practitioners may not have the necessary ability to deal with the burden of sport and, thus, present negative effects on their health 21 . ...
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This study aimed to investigate the prevalence of injuries in CrossFit® practitioners and the influence of sports practice and demographic characteristics on these injuries. A retrospective cohort study was carried out with 180 CrossFit® practitioners who answered a questionnaire with demographic characteristics (age, body mass, height, and sex), sports characteristics (number of years practicing CrossFit®; training frequency, duration, and training program; and practice of other sports), and presence of any injury suffered and its characteristics (number of injuries, region, and type of injury). The Mann-Whitney U test investigated the difference in continuous variables between those with and without injury history. The chi-square test and Fisher’s exact test investigated the association between categorical variables and the presence or not of injury over the last year. The chi-square goodness-of-fit test investigated if the frequency of injuries per body location and type differed from the expected one. Injury prevalence was 63%. Participants with a history of injury showed a shorter time of CrossFit® practice. The presence of injury history was associated with lesser weekly and daily training frequency, shorter training duration, and Scale training program. The frequency of injuries on leg, knee, lumbar spine, shoulder, and wrist, and the muscle and tendon was greater than expected. The other variables were neither different between groups nor associated with injury presence. Thus, most participants presented injury over the last year, influenced by the sports characteristics but not by demographic characteristics. Keywords: Injuries; Epidemiology; CrossFit; Sports
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The effect of progressive and individualised sport-specific training on the prevalence of injury in football and handball student athletes: a randomised controlled trial
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Full-text available
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Objective To evaluate the effectiveness of communication and coordination combined with designing a progressive and individualised sport-specific training program for reducing injury prevalence in youth female and male football and handball players transitioning to a sports academy high school. An additional aim was to investigate the characteristics of the reported injuries. Methods Forty-two Norwegian athletes were randomised into an intervention or control group. Mean age, height, weight and BMI was 15.5 ± 0.5 years, 178.6 cm ± 6.3 cm, 71.3 ± 9.8 kg, 22.3 ± 2.7 BMI for the intervention group (IG) (n = 23), and 15.4 ± 0.5 years, 175.6 cm ± 6.6 cm, 67.1 ± 9.8 kg, 21.7 ± 2.4 BMI for the control group (CG) (n = 19). During the summer holiday, the intervention group received weekly progressive, individualised sport-specific training programs and weekly follow-up telephone calls from the researchers. All athletes completed a baseline questionnaire and a physical test battery. Training data and injuries were recorded prospectively for 22 weeks using the Oslo Sports Trauma Research Center Questionnaire on Health Problems (OSTRC-H2). A two-way chi-square (χ²) test of independence was conducted to examine the relationship between groups and injury. Results Average weekly prevalence of all injuries was 11% (95% CI: 8%–14%) in IG and 19% (95% CI: 13%–26%) in CG. Average weekly prevalence of substantial injuries was 7% (95% CI: 3%–10%) in IG and 10% (95% CI: 6%–13%) in CG. The between-group difference in injuries was significant: χ² (1, N = 375) = 4.865, p = .031, φ = .114, with 1.8 times higher injury risk in CG vs. IG during the first 12 weeks after enrolment. Conclusions For student athletes transitioning to a sports academy high school, progressive individualised, sport-specific training programs reduced the prevalence of all-complaint injuries following enrolment. Clubs and schools should prioritise time and resources to implement similar interventions in periods where student athletes have less supervision, such as the summer holidays, to facilitate an optimal transition to a sports academy high school.
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Context Matters: Revisiting the First Step of the ‘Sequence of Prevention’ of Sports Injuries
Article
Full-text available
  • Oct 2018
  • SPORTS MED
It is possible to prevent sports injuries. Unfortunately, the demonstrated efficacy and effectiveness of injury prevention approaches are not translated into lasting real-world effects. Contemporary views in sports medicine and injury prevention suggest that sports injuries are ‘complex’ phenomena. If the problem we aim to prevent is complex, then the first step in the ‘sequence of prevention’ that defines the ‘injury problem’ already needs to have considered this. The purpose of this paper is to revisit the first step of the ‘sequence of prevention’, and to explore new perspectives that acknowledge the complexity of the sports injury problem. First, this paper provides a retrospective of the ‘sequence of prevention’, acknowledging contemporary views on sports injuries and their prevention. Thereafter, from the perspective of the socioecological model, we demonstrate the need for taking into account the complex nature of sports injuries in the first step. Finally, we propose an alternative approach to explore and understand injury context through qualitative research methods. A better understanding of the injury problem in context will guide more context-sensitive studies, thus providing a new perspective for sports injury prevention research.
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Handball load and shoulder injury rate: A 31-week cohort study of 679 elite youth handball players
Article
Full-text available
  • Jan 2017
Background Knowledge of injury patterns, an essential step towards injury prevention, is lacking in youth handball. Aim To investigate if an increase in handball load is associated with increased shoulder injury rates compared with a minor increase or decrease, and if an association is influenced by scapular control, isometric shoulder strength or glenohumeral range of motion (ROM). Methods 679 players (14–18 years) provided weekly reports on shoulder injury and handball load (training and competition hours) over 31 weeks using the SMS, phone and medical examination system. Handball load in a given week was categorised into (1) <20% increase or decrease (reference), (2) increase between 20% and 60% and (3) increase >60% relative to the weekly average amount of handball load the preceding 4 weeks. Assessment of shoulder isometric rotational and abduction strength, ROM and scapular control was performed at baseline and midseason. Results An increase in handball load by >60% was associated with greater shoulder injury rate (HR 1.91; 95% CI 1.00 to 3.70, p=0.05) compared with the reference group. The effect of an increase in handball load between 20% and 60% was exacerbated among players with reduced external rotational strength (HR 4.0; 95% CI 1.1 to 15.2, p=0.04) or scapular dyskinesis (HR 4.8; 95% CI 1.3 to 18.3, p=0.02). Reduced external rotational strength exacerbated the effect of an increase above 60% (HR 4.2; 95% CI 1.4 to 12.8, p=0.01). Conclusions A large increase in weekly handball load increases the shoulder injury rate in elite youth handball players; particularly, in the presence of reduced external rotational strength or scapular dyskinesis.
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How do training and competition workloads relate to injury? The workload—injury aetiology model
Article
Full-text available
  • Jul 2016
Injury aetiology models that have evolved over the previous two decades highlight a number of factors which contribute to the causal mechanisms for athletic injuries. These models highlight the pathway to injury, including (1) internal risk factors (eg, age, neuromuscular control) which predispose athletes to injury, (2) exposure to external risk factors (eg, playing surface, equipment), and finally (3) an inciting event, wherein biomechanical breakdown and injury occurs. The most recent aetiological model proposed in 2007 was the first to detail the dynamic nature of injury risk, whereby participation may or may not result in injury, and participation itself alters injury risk through adaptation. However, although training and competition workloads are strongly associated with injury, existing aetiology models neither include them nor provide an explanation for how workloads alter injury risk. Therefore, we propose an updated injury aetiology model which includes the effects of workloads. Within this model, internal risk factors are differentiated into modifiable and non-modifiable factors, and workloads contribute to injury in three ways: (1) exposure to external risk factors and potential inciting events, (2) fatigue, or negative physiological effects, and (3) fitness, or positive physiological adaptations. Exposure is determined solely by total load, while positive and negative adaptations are controlled both by total workloads, as well as changes in load (eg, the acute:chronic workload ratio). Finally, we describe how this model explains the load—injury relationships for total workloads, acute:chronic workload ratios and the training load—injury paradox.
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Aerobic Fitness and Playing Experience Protect Against Spikes in Workload: The Role of the Acute:Chronic Workload Ratio on Injury Risk in Elite Gaelic Football
Article
Full-text available
  • Jul 2016
  • Int J Sports Physiol Perform
Purpose To examine the association between combined session rating of perceived exertion (RPE) workload measures and injury risk in elite Gaelic footballers. Methods Thirty-seven elite Gaelic footballers (mean ± SD age 24.2 ± 2.9 y) from 1 elite squad were involved in a single-season study. Weekly workload (session RPE multiplied by duration) and all time-loss injuries (including subsequent-wk injuries) were recorded during the period. Rolling weekly sums and wk-to-wk changes in workload were measured, enabling the calculation of the acute:chronic workload ratio by dividing acute workload (ie, 1-weekly workload) by chronic workload (ie, rolling-average 4-weekly workload). Workload measures were then modeled against data for all injuries sustained using a logistic-regression model. Odds ratios (ORs) were reported against a reference group. Results High 1-weekly workloads (≥2770 arbitrary units [AU], OR = 1.63–6.75) were associated with significantly higher risk of injury than in a low-training-load reference group (<1250 AU). When exposed to spikes in workload (acute:chronic workload ratio >1.5), players with 1 y experience had a higher risk of injury (OR = 2.22) and players with 2–3 (OR = 0.20) and 4–6 y (OR = 0.24) of experience had a lower risk of injury. Players with poorer aerobic fitness (estimated from a 1-km time trial) had a higher injury risk than those with higher aerobic fitness (OR = 1.50–2.50). An acute:chronic workload ratio of (≥2.0) demonstrated the greatest risk of injury. Conclusions These findings highlight an increased risk of injury for elite Gaelic football players with high (>2.0) acute:chronic workload ratios and high weekly workloads. A high aerobic capacity and playing experience appears to offer injury protection against rapid changes in workload and high acute:chronic workload ratios. Moderate workloads, coupled with moderate to high changes in the acute:chronic workload ratio, appear to be protective for Gaelic football players.
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Influence of training and match intensity on injuries in rugby league
Article
Full-text available
  • May 2004
The aim of this study was to examine the influence of perceived intensity, duration and load of matches and training on the incidence of injury in rugby league players. The incidence of injury was prospectively studied in 79 semi-professional rugby league players during the 2001 season. All injuries sustained during matches and training sessions were recorded. Training sessions were conducted from December to September, with matches played from February to September. The intensity of individual training sessions and matches was estimated using a modified rating of perceived exertion scale. Training load was calculated by multiplying the training intensity by the duration of the training session. The match load was calculated by multiplying the match intensity by the time each player participated in the match. Training load increased from December (278.3 [95% confidence interval, CI 262.2 to 294.5] units) to February (385.5 [95% CI 362.4 to 408.5] units), followed by a decline until September (98.4 [95% CI 76.5 to 120.4] units). Match load increased from February (204.0 [95% CI 186.2 to 221.8] units) to September (356.8 [95% CI 302.5 to 411.1] units). More training injuries were sustained in the first half of the season (first vs second: 69.2% vs 30.8%, P < 0.001), whereas match injuries occurred more frequently in the latter stages of the season (53.6% vs 46.4%, P < 0.001). A significant relationship (P < 0.05) was observed between changes in training injury incidence and changes in training intensity (r = 0.83), training duration (r = 0.79) and training load (r = 0.86). In addition, changes in the incidence of match injuries were significantly correlated (P < 0.05) with changes in match intensity (r = 0.74), match duration (r = 0.86) and match load (r = 0.86). These findings suggest that as the intensity, duration and load of rugby league training sessions and matches is increased, the incidence of injury is also increased.
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"Underuse" as a cause for musculoskeletal injuries: Is it time that we started reframing our message?
Article
Full-text available
  • Oct 2006
  • BRIT J SPORT MED
Promoting physical activity Sports medicine clinicians need to be leaders in the field of physical activity promotion. As such, we must avoid language that inappropriately discourages exercise. Articles on musculoskeletal injuries typically divide the causes into either “acute” or “overuse”. Both of these terms implicate activity as the basis for the musculoskeletal pain. However, as we learn more about the epidemiology, pathophysiology, treatment, and prevention of these injuries, it is clear that, in fact, inactivity may be the underlying cause of many of these conditions. “Underuse injuries” may be a more appropriate term to explain the aetiology of many conditions seen by those in the field of sports medicine. A May 2006 Medline search for articles with the keyword “overuse injuries” registered 7649 “hits” over the past 40 years, and 3970 in just the past 10 years. The vast majority clearly suggest that overuse is the reason for the injury. To be fair, a search of “underuse injuries” reveals seven findings. However, none implicate “underuse” as the cause of the injury. For example, one article deals with underuse of imaging, another with the underuse of analgesia, and a third with the …
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Modeling training and overtraining
Article
  • Jul 1997
This paper adapts the dose-response research tool, well established in pharmacological studies, to an exercise and performance setting. Training is measured in quantitative units as the dosage inputs, and their effects on fitness, fatigue, overtraining and performance responses are modelled. In this way, one can answer such questions as 'what performance level would be predicted if a certain amount of training was undertaken?' More specifically, athletes and their coaches are interested in designing a training schedule to maximize performance potential at some future date and minimize the risk of overtraining during that time, for some minimal training inputs. This approach leads to the practical recommendation that athletes should train more intensely but only on alternate days, for a 5 month session, in a triangular-shaped training profile, with the heaviest training occurring between weeks 12 and 4 before competition.
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