More than a Metric:How Training Load is Used in Elite Sport for Athlete Management

Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.</p

Getting the most out of intensive longitudinal data: a methodological review of workload–injury studies

Objectives:To systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components. Design Methodological review. Methods After finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (>20 observations per athlete) and examined the elationship between athletic workloads and injuries. Using Professor Linda Collins’ three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research. Results Statistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n=3). Conclusions Rapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen

The innate immune system in chronic cardiomyopathy : a European Society of Cardiology (ESC) scientific statement from the Working Group on Myocardial Function of the ESC

Funded by Regione Campania CISI-Lab European Union Commission's Seventh Framework . Grant Number: 305507, 602904 FP7-Health-2013-Innovations-1. Grant Number: 602156 FWO Flanders, Belgium. Grant Number: FWO G080014 N European Union Horizon2020. Grant Number: UE LSHM-CT-05-018833, FNRS PDR T.0144.13 Bundesministerium für Bildung und Forschung. Grant Number: BMBF01 EO1004 Deutsche Forschungsgemeinschaft. Grant Number: SFB688 TP A10Peer reviewedPublisher PD

Turning exercise into medicine : exploring the feasibility of a 3 step physician workshop to promote the physical activity prescription behaviours of family physicians

Objective: To investigate the feasibility of an educational workshop with the provision of practical tools to change the proportion of family physicians in our sample who provided their patients with written physical activity prescriptions. Design: A pre-post study. Setting: Abbotsford and Mission, British Columbia. Participants: 25 family physicians registered with the Abbotsford or Mission Divisions of Family Practice. Intervention: A three-hour educational workshop for family physicians combined with practical tools to facilitate physical activity prescription. The educational content of the workshop included 1) assessing patients’ physical activity levels, 2) using motivational interviewing techniques to encourage physical activity, and 3) providing written physical activity prescriptions when appropriate. Tools to facilitate physician behaviour changes included a 1) ‘physical activity vital sign’, a measure of patient self-reported physical activity, and 2) copies of the “Exercise Prescription and Referral Tool” designed by the Exercise is Medicine Canadian Taskforce, a written prescription pad for physicians to provide physical activity prescriptions to their patients. Participating physicians completed a bespoke questionnaire before and four weeks after their attendance at the workshop. Outcome Measures: The feasibility of the intervention was ascertained by assessing changes in the proportion of family physicians who reported providing written physical activity prescriptions at four week follow up, compared to baseline. Exploratory outcomes included changes in physicians’: 1) other physical activity prescription behaviours, 2) the perceived importance of various barriers to physical activity prescription, 3) knowledge and confidence regarding physical activity prescription, 4) knowledge of the Canadian Physical Activity Guidelines and 5) self-reported physical activity levels. McNemar’s test evaluated changes in proportions before and after the workshop, while Wilcoxon signed-rank tests evaluated changes in Likert data. Results: Twenty five family physicians completed the baseline questionnaire and attended the workshop, with 100% follow up response rate. The proportion of family physicians who reported providing written physical activity prescriptions in their clinical practice increased from 10 (40%) at baseline to 17 (68%) four weeks after the intervention. Conclusion: Educational workshops combined with practical tools appear to be a feasible method to encourage the use of written physical activity prescriptions among family physicians in this setting.Medicine, Faculty ofMedicine, Department ofExperimental Medicine, Division ofGraduat

Longitudinal workload monitoring to keep athletes healthy and performing : conceptual, methodological, and applied considerations in sports injury aetiology

Sports injury aetiology is a process in which internal and external risk factors contribute to an inciting event. The last decade has seen a rapid growth in research that identified how training and competition workloads relate to sports injury risk. My literature review highlighted that existing aetiology models do not describe how workloads contribute to injury. Furthermore, injury risk fluctuates on a time-scale in parallel to these workloads (e.g. daily), which creates several methodological and statistical challenges that have largely been ignored. If researchers are to understand how athletes’ workloads relate to injury risk, their conceptual aetiological models must be updated to incorporate training and competition workloads, and they should use appropriate statistical analyses. After my literature review, I divide this dissertation into three parts. In Part 1 I discuss how workloads relate to injury. I present a novel workload—injury aetiology model, which expands on previous aetiological frameworks and details 3 ways that workloads contribute to injury: 1) exposing athletes to external risk factors and potential inciting events, 2) reducing injury risk through beneficial physiological changes, and 3) increasing injury risk through transient negative changes in athletes’ internal risk profiles. I then present mediation and moderation as potential causal approaches to understand how athlete risk factors interact with workload changes to alter injury risk. In Part 2 I tackle the methodological challenges of analysing workload—injury data. I reviewed prospective cohort studies that reported intensive longitudinal data to analyse workload—injury data in team sports. I identified that few studies utilised statistical approaches that align with theoretical aetiology models or addressed the methodological challenges associated with longitudinal data. My analysis leads me to recommend mixed modeling as one advance, and I exemplify how it can be used by studying how player unavailability affects player outputs. In Part 3 I integrate the conceptual and methodological considerations into two applied settings. First, I describe how a methodological/mathematical concern (mathematical coupling) may influence applied practice (multifaceted player load management) and research (explicitly reporting calculations). Finally, I use mixed modeling to examine pre-season workload and in-season injury risk, controlling for athletes’ weekly workloads.Medicine, Faculty ofExperimental Medicine, Division ofMedicine, Department ofGraduat

How do training and competition workloads relate to injury? The workload-injury aetiology model

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

Cost-benefit analysis underlies training decisions in elite sport

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