A conceptual model and detailed framework for stress-related, strain-related, and overuse athletic injury

Magnitude, Frequency, and Accumulation: Workload Among Injured and Uninjured Youth Basketball Players

Overuse injuries are common in basketball. Wearable technology enables the workload to be monitored in sport settings. However, workload-injury models lack a biological basis both in the metrics recorded and how workload is accumulated. We introduce a new metric for monitoring workload: weighted jump height, where each jump height is weighted to represent the expected effect of the jump magnitude on damage to the tendon. The objectives of this study were to use principal components analysis to identify distinct modes of variation in all workload metrics accumulated over 1, 2, 3, and 4 weeks and to examine differences among the modes of variation in workload metrics between participants before the injury and uninjured participants. Forty-nine youth basketball players participated in their typical basketball practices and games, and lower extremity injuries were classified as patellar or Achilles tendinopathy, other overuse, or acute. An inertial measurement unit recorded the number and height of all jumps, and session rating of perceived exertion was recorded. The previous 1-, 2-, 3-, and 4-week workloads of jump count, jump height, weighted jump height, and session rating of perceived exertion were summed for each participant-week. Principal components analysis explained the variance in the accumulated workload variables. Using the retained principal components, the difference between the workload of injured participants in the week before the injury and the mean workload of uninjured participants was described for patellar or Achilles tendinopathy, overuse lower extremity injury, and any lower extremity injury. Participants with patellar or Achilles tendinopathy and overuse lower extremity injuries had a low workload magnitude for all variables in the 1, 2, 3, and 4 weeks before injury compared with the weeks before no injury. Participants with overuse lower extremity injuries and any lower extremity injury had a high previous 1-week workload for all variables along with a low previous 3- and 4-week jump count, jump height, and weighted jump height before injury compared with the weeks before no injury. Weighted jump height represents the cumulative damage experienced by tissues due to repetitive loads. Injured youth basketball athletes had a low previous 3- and 4-week workloads coupled with a high previous 1-week workload.

A comparison of ground reaction force waveforms and step length between recreational endurance runners with hamstring injuries and healthy controls

BACKGROUND

Acute hamstring injuries during sprinting have been attributed, in part, to the ground reaction forces experienced during early stance. However, no studies have investigated the factors associated with overuse hamstring injuries in endurance runners. Our purpose was to compare early stance ground reaction forces and step length between runners with overuse hamstring injuries and healthy controls.

METHODS

23 runners (5 men/ 18 women) who presented to a running clinic with an overuse hamstring injury were matched with healthy controls for sex, running speed and age. All participants ran on an instrumented treadmill, embedded with force plates. A 3-min warm-up was given, at a self-selected training pace, followed by 16-s of ground reaction force data collection (≈20 strides). Statistical parametric mapping was used to compared ground reaction force waveforms. Additionally, discrete force variables were calculated, including vertical average/instantaneous. Mean comparisons for discrete ground reaction force variables and step length were performed.

FINDINGS

Differences in ground reaction force waveforms did not reach statistical significance (p > 0.05). However, mean vertical loading rates were found to be higher in the Hamstring Injury group compared to Controls (p = 0.03-0.04) with small to moderate effect sizes (d = 0.47-0.52). No differences were found in mean step length.

INTERPRETATION

These results provide evidence that vertical loading rates may be associated with overuse hamstring injuries. However, further research is needed to identify the contribution of joint kinematics/kinetics and muscle activity.

A Field-Based Approach to Determine Soft Tissue Injury Risk in Elite Futsal Using Novel Machine Learning Techniques

Lower extremity non-contact soft tissue (LE-ST) injuries are prevalent in elite futsal. The purpose of this study was to develop robust screening models based on pre-season measures obtained from questionnaires and field-based tests to prospectively predict LE-ST injuries after having applied a range of supervised Machine Learning techniques. One hundred and thirty-nine elite futsal players underwent a pre-season screening evaluation that included individual characteristics; measures related to sleep quality, athlete burnout, psychological characteristics related to sport performance and self-reported perception of chronic ankle instability. A number of neuromuscular performance measures obtained through three field-based tests [isometric hip strength, dynamic postural control (Y-Balance) and lower extremity joints range of motion (ROM-Sport battery)] were also recorded. Injury incidence was monitored over one competitive season. There were 25 LE-ST injuries. Only those groups of measures from two of the field-based tests (ROM-Sport battery and Y-Balance), as independent data sets, were able to build robust models [area under the receiver operating characteristic curve (AUC) score ≥0.7] to identify elite futsal players at risk of sustaining a LE-ST injury. Unlike the measures obtained from the five questionnaires selected, the neuromuscular performance measures did build robust prediction models (AUC score ≥0.7). The inclusion in the same data set of the measures recorded from all the questionnaires and field-based tests did not result in models with significantly higher performance scores. The model generated by the UnderBagging technique with a cost-sensitive SMO as the base classifier and using only four ROM measures reported the best prediction performance scores (AUC = 0.767, true positive rate = 65.9% and true negative rate = 62%). The models developed might help coaches, physical trainers and medical practitioners in the decision-making process for injury prevention in futsal.

Training Load and Injury: Causal Pathways and Future Directions

Causal pathways between training loads and the mechanisms of tissue damage and athletic injury are poorly understood. Here, the relation between specific training load measures and metrics, and causal pathways of gradual onset and traumatic injury are examined. Currently, a wide variety of internal and external training load measures and metrics exist, with many of these being commonly utilized to evaluate injury risk. These measures and metrics can conceptually be related to athletic injury through the mechanical load-response pathway, the psycho-physiological load-response pathway, or both. However, the contributions of these pathways to injury vary. Importantly, tissue fatigue damage and trauma through the mechanical load-response pathway is poorly understood. Furthermore, considerable challenges in quantifying this pathway exist within applied settings, evidenced by a notable absence of validation between current training load measures and tissue-level mechanical loads. Within this context, the accurate quantification of mechanical loads holds considerable importance for the estimation of tissue damage and the development of more thorough understandings of injury risk. Despite internal load measures of psycho-physiological load speculatively being conceptually linked to athletic injury through training intensity and the effects of psycho-physiological fatigue, these measures are likely too far removed from injury causation to provide meaningful, reliable relationships with injury. Finally, we used a common training load metric as a case study to show how the absence of a sound conceptual rationale and spurious links to causal mechanisms can disclose the weaknesses of candidate measures as tools for altering the likelihood of injuries, aiding the future development of more refined injury risk assessment methods.

WITHDRAWN: Sports and sportsmen as role models - or otherwise - in the COVID-19 era

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

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.

Workload a-WEAR-ness: Monitoring Workload in Team Sports With Wearable Technology. A Scoping Review

OBJECTIVES

To (1) identify the wearable devices and associated metrics used to monitor workload and assess injury risk, (2) describe the situations in which workload was monitored using wearable technology (including sports, purpose of the analysis, location and duration of monitoring, and athlete characteristics), and (3) evaluate the quality of evidence that workload monitoring can inform injury prevention.

DESIGN

Scoping review.

LITERATURE SEARCH

We searched the CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Embase, HealthSTAR, MEDLINE, PsycINFO, SPORTDiscus, and Web of Science databases.

STUDY SELECTION CRITERIA

We included all studies that used wearable devices (eg, heart rate monitor, inertial measurement units, global positioning system) to monitor athlete workload in a team sport setting.

DATA SYNTHESIS

We provided visualizations that represented the workload metrics reported, sensors used, sports investigated, athlete characteristics, and the duration of monitoring.

RESULTS

The 407 included studies focused on team ball sports (67% soccer, rugby, or Australian football), male athletes (81% of studies), elite or professional level of competition (74% of studies), and young adults (69% of studies included athletes aged between 20 and 28 years). Thirty-six studies of 7 sports investigated the association between workload measured with wearable devices and injury.

CONCLUSION

Distance-based metrics derived from global positioning system units were common for monitoring workload and are frequently used to assess injury risk. Workload monitoring studies have focused on specific populations (eg, elite male soccer players in Europe and elite male rugby and Australian football players in Oceania). Different injury definitions and reported workload metrics and poor study quality impeded conclusions regarding the relationship between workload and injury. J Orthop Sports Phys Ther 2020;50(10):549-563. doi:10.2519/jospt.2020.9753.

Impact-Related Ground Reaction Forces Are More Strongly Associated With Some Running Injuries Than Others

BACKGROUND

Inconsistent associations have been reported for impact-related ground reaction force variables and running injuries when grouping all injuries together. However, previous work has shown more consistent associations when focusing on specific injuries.

PURPOSE

To compare ground reaction force variables between healthy and injured runners as a group and within specific common injuries.

STUDY DESIGN

Controlled laboratory study.

METHODS

A total of 125 runners presenting with patellofemoral pain, tibial bone stress injury, plantar fasciitis, Achilles tendinopathy, or iliotibial band syndrome and 65 healthy controls completed an instrumented treadmill assessment at a self-selected speed. Impact-related ground reaction force variables included vertical average (VALR) and instantaneous (VILR) load rates, posterior and medial/lateral instantaneous load rates, and vertical stiffness at initial loading (VSIL). Mean comparisons were made between the general and specific injury and control groups (α = .05). Cutoff thresholds were established and evaluated using several criteria.

RESULTS

VALR (+17.5%; P < .01), VILR (+15.8%; P < .01), and VSIL (+19.7%; P < .01) were significantly higher in the overall injured versus control groups. For individual injuries, VALR, VILR, and VSIL were significantly higher for patellofemoral pain (+23.4%-26.4%; P < .01) and plantar fasciitis (+17.5%-29.0%; P < .01), as well as VSIL for Achilles tendinopathy (+29.4%; P < .01). Cutoff thresholds showed better diagnostic criteria for individual versus grouped injuries.

CONCLUSION

Impact variables (VALR, VILR, and VSIL) were significantly higher when assessing the injured group as a whole. However, these findings were driven by specific injury groups, highlighting the importance of taking an injury-specific approach to biomechanical risk factors for running injury.

CLINICAL RELEVANCE

These results suggest that practitioners may want to address impact loading in their treatment of injured runners, especially in those with patellofemoral pain and plantar fasciitis.

Training Load and Injury Part 2: Questionable Research Practices Hijack the Truth and Mislead Well-Intentioned Clinicians

BACKGROUND

In this clinical commentary, we highlight issues related to conceptual foundations and methods used in training load and injury research. We focus on sources of degrees of freedom that can favor questionable research practices such as P hacking and hypothesizing after the results are known, which can undermine the trustworthiness of research findings.

CLINICAL QUESTION

Is the methodological rigor of studies in the training load and injury field sufficient to inform training-related decisions in clinical practice?

KEY RESULTS

The absence of a clear conceptual framework, causal structure, and reliable methods can promote questionable research practices, selective reporting, and confirmation bias. The fact that well-accepted training principles (eg, overload progression) are in line with some study findings may simply be a consequence of confirmation bias, resulting from cherry picking and emphasizing results that align with popular beliefs. Identifying evidence-based practical applications, grounded in high-quality research, is not currently possible. The strongest recommendation we can make for the clinician is grounded in common sense: "Do not train too much, too soon"-not because it has been confirmed by studies, but because it reflects accepted generic training principles.

CLINICAL APPLICATION

The training load and injury research field has fundamental conceptual and methodological weaknesses. Therefore, making decisions about planning and modifying training programs for injury reduction in clinical practice, based on available studies, is premature. Clinicians should continue to rely on best practice, experience, and well-known training principles, and consider the potential influence of contextual factors when planning and monitoring training loads. J Orthop Sports Phys Ther 2020;50(10):577-584. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9211.

How Has Workload Been Defined and How Many Workload-Related Exposures to Injury Are Included in Published Sports Injury Articles? A Scoping Review

OBJECTIVE

To describe how workload-related exposure variables have been defined in sports injury articles, and to identify the number of workload-related exposure variables included in comparative analyses.

DESIGN

Scoping review.

LITERATURE SEARCH

PubMed, SPORTDiscus, and Scopus were systematically searched on March 13, 2020. Two reviewers independently screened the retrieved literature and selected articles for inclusion.

STUDY SELECTION CRITERIA

Prospective cohort studies using workload-related variables as the primary exposure to sports injury were eligible for inclusion.

DATA SYNTHESIS

The type (eg, distance, balls bowled) and construct of workload-related exposure variables (eg, acute-chronic workload ratio) were extracted and summarized in frequency tables.

RESULTS

A total of 648 articles were identified, and 45 were eligible for inclusion. Workload definition differed greatly, as sports- and workload-related exposure variables could be, but were not limited to, distance, balls bowled, session rating of perceived exertion, accelerations, soreness, and sleep. Within and across articles, authors used different constructs for workload-related exposure variables. For example, distance was represented as total distance, distance per week, distance per 2 weeks, and acute-chronic workload ratio. The number of workload-related exposure variables included in comparative analyses ranged from 1 to 336.

CONCLUSION

Studies used different definitions of workload-related exposure variables. The number of workload-related exposure variables in a single study ranged from 1 to 336. J Orthop Sports Phys Ther 2020;50(10):538-548. doi:10.2519/jospt.2020.9766.

Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls

In part 2 of this clinical commentary, we highlight the conceptual and methodologic pitfalls evident in current training-load-injury research. These limitations make these studies unsuitable for determining how to use new metrics such as acute workload, chronic workload, and their ratio for reducing injury risk. The main overarching concerns are the lack of a conceptual framework and reference models that do not allow for appropriate interpretation of the results to define a causal structure. The lack of any conceptual framework also gives investigators too many degrees of freedom, which can dramatically increase the risk of false discoveries and confirmation bias by forcing the interpretation of results toward common beliefs and accepted training principles. Specifically, we underline methodologic concerns relating to (1) measure of exposures, (2) pitfalls of using ratios, (3) training-load measures, (4) time windows, (5) discretization and reference category, (6) injury definitions, (7) unclear analyses, (8) sample size and generalizability, (9) missing data, and (10) standards and quality of reporting. Given the pitfalls of previous studies, we need to return to our practices before this research influx began, when practitioners relied on traditional training principles (eg, overload progression) and adjusted training loads based on athletes' responses. Training-load measures cannot tell us whether the variations are increasing or decreasing the injury risk; we recommend that practitioners still rely on their expert knowledge and experience.

The Training-Performance Puzzle: How Can the Past Inform Future Training Directions?

Over the past 20 years, research on the training-load-injury relationship has grown exponentially. With the benefit of more data, our understanding of the training-performance puzzle has improved. What were we thinking 20 years ago, and how has our thinking changed over time? Although early investigators attributed overuse injuries to excessive training loads, it has become clear that rapid spikes in training load, above what an athlete is accustomed, explain (at least in part) a large proportion of injuries. In this respect, it appears that overuse injuries may arise from athletes being underprepared for the load they are about to perform. However, a question of interest to both athletic trainers (ATs) and researchers is why some athletes sustain injury at low training loads, while others can tolerate much greater training loads? A higher chronic training load and well-developed aerobic fitness and lower body strength appear to moderate the training-injury relationship and provide a protective effect against spikes in load. The training-performance puzzle is complex and dynamic-at any given time, multiple inputs to injury and performance exist. The challenge facing researchers is obtaining large enough longitudinal data sets to capture the time-varying nature of physiological and musculoskeletal capacities and training-load data to adequately inform injury-prevention efforts. The training-performance puzzle can be solved, but it will take collaboration between researchers and clinicians as well as an understanding that efficacy (ie, how training load affects performance and injury in an idealized or controlled setting) does not equate to effectiveness (ie, how training load affects performance and injury in the real-world setting, where many variables cannot be controlled).

Training Load and Its Role in Injury Prevention, Part I: Back to the Future

The purpose of this 2-part commentary series is† to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining "how much is too much" and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.

The Influence of Exercise-Induced Fatigue on Inter-Limb Asymmetries: a Systematic Review

BACKGROUND

Non-contact injuries such as anterior cruciate ligament ruptures often occur during physical load toward the end of a match. This is ascribed to emerging processes due to exercise-induced fatigue. Moreover, non-contact injuries often occur during dynamic actions such as landing or cutting movements. Inter-limb asymmetries are suggested as one possible cause for those injuries based on findings indicating that asymmetries between limbs are associated with a higher injury risk. Hence, assessing inter-limb asymmetry during physical load in the condition of exercise-induced fatigue is warranted to identify potentially relevant precursors for non-contact injuries.

OBJECTIVE

The objective of this study was to overview the current state of evidence concerning the influence of exercise-induced fatigue on inter-limb asymmetries through a systematic review.

METHODS

A systematic literature search was conducted using the databases Web of Science, Scopus, PubMed, SURF, and SPONET to identify studies that assessed inter-limb asymmetries of healthy people, calculated with an asymmetry equation, before and after, or during a loading protocol.

RESULTS

Thirteen studies were included in the systematic review. The loading protocols involved running, race walking, jumping, squatting, soccer, rowing, and combinations of different exercises. Moreover, different tasks/procedures were used to assess inter-limb asymmetries, e.g., squats, single-leg countermovement jumps, gait analysis, or isokinetic strength testing. The results seem to depend on the implemented loading protocol, the tasks/procedures, and the measured parameters.

CONCLUSIONS

Future research needs more systematization and consistency, assessing the effect of exercise-induced fatigue on inter-limb asymmetries. Moreover, the emergence of inter-limb asymmetries should be regarded in the context of sport-specific movements/tasks. Testing before, after, and during a physical loading protocol is advisable to consider the influence of exercise-induced fatigue on sport-specific tasks and to identify the possible mechanisms underlying load-dependent inter-limb asymmetries with regard to risk of non-contact injury.