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

Relationship Between Training Load, Neuromuscular Fatigue, and Daily Well-Being in Elite Young Wrestlers

Purpose: This study investigated acute workload (wAW), chronic workload (wCW), acute: chronic workload ratio (wACWR), training monotony (wTM), perceived load training strain indicators (wTS), and countermove- ment jump (CMJ) as indicators of wellness in one season and defined weekly variations. In addition, we analyzed the relationships between training load measurements and weekly reports. Methods: 16 elite young wrestlers were monitored daily with individual observations for 46 consecutive weeks throughout the season. Training load was obtained using the session rating of perceived effort. wSleep, wStress, wFatigue & wMuscle Soreness well-being were monitored daily using the Hooper index. Results: As a result of the analysis, it was found that there is a moderate relationship (r = 0.51, p = .003) between ACWR and w mean load (A.U.) and a high relationship (r = 0.81, p < .001) between monotony and strain. Conclusion: All variables other than ACWR, w mean load, strain, and monotony presented small and statistically insignificant relationships. These results provide coaches and practitioners with new insights into perceived loads and health changes during a season at the elite youth level.

On-field rehabilitation in football: current practice and perceptions. A survey of the English Premier League and Football League

INTRODUCTION

Return to play related research is increasing rapidly, with two recent competency-based frameworks offering conceptualised support for on-field rehabilitation (OFR) decision-making. It is still unknown, however, who is responsible for OFR and how they typically select, monitor, and progress OFR processes.

AIMS

The purpose of this study was to investigate current OFR practice within English professional football to support practitioners with decision-making and highlight opportunities for future research related to the design, monitoring, and progression of OFR.

METHODS

Sixty-nine practitioners responsible for the design and implementation of OFR at 69 clubs (75% of the English Premier League and Football League) responded to a survey containing 30 questions (14 open and 16 closed).

RESULTS

The main findings were that therapists (physiotherapists/sports therapists) have the largest influence on OFR, followed by physical performance coaches (sports scientists/strength and conditioning coaches), technical coaches and medical doctors. There was more agreement for the ordering of specific OFR drills earlier in the process when activities are easier to control. The most frequently reported objective monitoring tool was global positioning systems (GPS), with functional/clinical experience/expertise remaining subjectively vital. GPS outputs (e.g., sprint metrics and accelerations/decelerations) were most used for between session decision-making, with verbal communication being key for within session decision-making.

CONCLUSION

Future research should use evidence of current practice, such as drill design and monitoring techniques, to explore drill-level analysis and give practitioners greater insights into which stage of current OFR frameworks specific drills fall, and how they might be more objectively progressed/regressed.

Epidemiology of bone injuries in elite athletics: A prospective 9-year cohort study

OBJECTIVES

To describe bone injury patterns in elite track and field athletes. To investigate relationships between bone injury and athlete characteristics to inform future injury prevention strategies.

DESIGN

Descriptive epidemiology study.

SETTING

Elite athletics training centres across the United Kingdom and internationally, observed between 2012 and 2020.

PARTICIPANTS

207 Olympic programme senior track and field athletes.

MAIN OUTCOME MEASURES

Injury number, Incidence, Severity, Burden, Time Loss.

RESULTS

There were 78 fractures during the study period. Gradual repetitive bone injuries were the most common type of injury mode. The foot, pelvis and the lumbar spine were the regions with the highest number of bone stress injuries. Stress fractures had a higher burden overall compared to stress reactions. Average return to full training was 67.4 days (±73.1) for stress reactions and 199 (±205.2) days for stress fractures. There was no relationship between bone injury type and age, sex, ethnicity, side dominance or event group.

CONCLUSION

Bone stress injuries in athletics have a high severity and burden warranting continued efforts to prevent their occurrence and optimize management. Age, sex, ethnicity, side dominance and event region do not have any relationship with bone injury occurrence and are therefore unlikely to increase risk in this cohort.

Workload Comparison of Contemporary Interval Throwing Programs and a Novel Optimized Program for Baseball Pitchers

Background

In the rehabilitation of injured baseball pitchers, there is lack of consensus on how to guide a player back to pitching. It is unknown how different contemporary interval throwing programs (ITPs) progress in the amount of throwing workload.

Purposes

To 1) evaluate three prominent ITPs commonly employed in baseball pitcher rehabilitation and assess whether these ITPs produce training loads that increase in a controlled, graduated manner and 2) devise an ITP that produced training loads which increased steadily over time.

Study Design

Cross-sectional study.

Methods

Three publicly available ITPs from prominent sports medicine institutions were analyzed. Elbow varus torque per throw was calculated from a 2nd order polynomial regression based upon a relationship between recorded torque measurements and throwing distance measured from a database of 111,196 throws. The relative rate of workload increase was measured as an acute:chronic workload ratio (ACWR). For each ITP, throw counts, daily/acute/chronic workloads, and ACWR were calculated and plotted over time. Finally, an original ITP was devised based upon a computational model that gradually increases ACWR over time and finished with an optimal chronic workload.

Results

Each ITP exhibited a unique progression of throwing distances, quantities, and days to create different workload profiles. The three ITPs had throwing schedules ranging from 136 days to 187 days, ACWR spiked above or fell below a literature-defined "safe" range (i.e. 0.7 - 1.3) 19, 21, and 23 times. A novel ITP, predicated on a 146-day schedule and with a final chronic workload of 14.2, was designed to have no spikes outside of the safe range.

Conclusion

Existing ITPs widely utilized for rehabilitation of baseball pitchers exhibit significantly inconsistent variation in the rate of throwing load progression. Computational modeling may facilitate more incremental workload progression in ITPs, thereby reducing injury during rehabilitation and more efficiently condition a pitcher for return to competition.

Level of Evidence

3b.

Up Front and Open? Shrouded in Secrecy? Or Somewhere in Between? A Meta-Research Systematic Review of Open Science Practices in Sport Medicine Research

OBJECTIVE: To investigate open science practices in research published in the top 5 sports medicine journals from May 1, 2022, and October 1, 2022. DESIGN: A meta-research systematic review. LITERATURE SEARCH: Open science practices were searched in MEDLINE. STUDY SELECTION CRITERIA: We included original scientific research published in one of the identified top 5 sports medicine journals in 2022 as ranked by Clarivate: (1) British Journal of Sports Medicine, (2) Journal of Sport and Health Science, (3) American Journal of Sports Medicine, (4) Medicine and Science in Sports and Exercise, and (5) Sports Medicine-Open. Studies were excluded if they were systematic reviews, qualitative research, gray literature, or animal or cadaver models. DATA SYNTHESIS: Open science practices were extracted in accordance with the Transparency and Openness Promotion guidelines and patient and public involvement. RESULTS: Two hundred forty-three studies were included. The median number of open science practices in each study was 2, out of a maximum of 12 (range: 0-8; interquartile range: 2). Two hundred thirty-four studies (96%, 95% confidence interval [CI]: 94%-99%) provided an author conflict-of-interest statement and 163 (67%, 95% CI: 62%-73%) reported funding. Twenty-one studies (9%, 95% CI: 5%-12%) provided open-access data. Fifty-four studies (22%, 95% CI: 17%-27%) included a data availability statement and 3 (1%, 95% CI: 0%-3%) made code available. Seventy-six studies (32%, 95% CI: 25%-37%) had transparent materials and 30 (12%, 95% CI: 8%-16%) used a reporting guideline. Twenty-eight studies (12%, 95% CI: 8%-16%) were preregistered. Six studies (3%, 95% CI: 1%-4%) published a protocol. Four studies (2%, 95% CI: 0%-3%) reported an analysis plan a priori. Seven studies (3%, 95% CI: 1%-5%) reported patient and public involvement. CONCLUSION: Open science practices in the sports medicine field are extremely limited. The least followed practices were sharing code, data, and analysis plans. J Orthop Sports Phys Ther 2023;53(12):1-13. Epub 20 October 2023. doi:10.2519/jospt.2023.12016.

The Trade Secret Taboo: Open Science Methods are Required to Improve Prediction Models in Sports Medicine and Performance

Clinical prediction models in sports medicine that utilize regression or machine learning techniques have become more widely published, used, and disseminated. However, these models are typically characterized by poor methodology and incomplete reporting, and an inadequate evaluation of performance, leading to unreliable predictions and weak clinical utility within their intended sport population. Before implementation in practice, models require a thorough evaluation. Strong replicable methods and transparency reporting allow practitioners and researchers to make independent judgments as to the model's validity, performance, clinical usefulness, and confidence it will do no harm. However, this is not reflected in the sports medicine literature. As shown in a recent systematic review of models for predicting sports injury models, most were typically characterized by poor methodology, incomplete reporting, and inadequate performance evaluation. Because of constraints imposed by data from individual teams, the development of accurate, reliable, and useful models is highly reliant on external validation. However, a barrier to collaboration is a desire to maintain a competitive advantage; a team's proprietary information is often perceived as high value, and so these 'trade secrets' are frequently guarded. These 'trade secrets' also apply to commercially available models, as developers are unwilling to share proprietary (and potentially profitable) development and validation information. In this Current Opinion, we: (1) argue that open science is essential for improving sport prediction models and (2) critically examine sport prediction models for open science practices.

Individualizing the Throwing Progression Following Injury in Baseball Pitchers: the Past, Present, and Future

PURPOSE OF REVIEW

A critical component of any rehabilitation program following injury is a graduated exposure of pathologic or vulnerable tissue to sport-specific stressors. A foundational aspect in the return to sport process following an injury in baseball athletes is the development of an interval throwing program. A shift has occurred in recent years from generic programs to individualized progressions. The current review explores the evolution of interval throwing program construction and discusses the possibilities of the future with advancements in technology and understanding.

RECENT FINDINGS

Early interval throwing programs relied primarily on pre-determined throwing distance and volume to estimate total training load while following a fixed throwing schedule. Currently, clinicians have begun to utilize available technology in attempts to determine training prescription and obtain more accurate estimates of stresses placed upon the body. Thus, interval throwing programs have become more individualized and flexible to account for each athlete's individual differences and biological response to training. Future development may be able to predict specific internal response to stressors and proactively adjust training load to maximize positive adaptations while minimizing any maladaptive events. As with all concepts and principles within the realm of athlete rehabilitation, clinicians must continue to adapt how they conceptualize and develop individualized interval throwing programs for the overhead throwing athlete. We will continue to see a shift away from a responsive approach to a proactive one, where clinicians can utilize modern technologies to precisely prescribe a throwing dosage based upon expected tissue response within the athlete.

Automatic detection of passing and shooting in water polo using machine learning: a feasibility study

There is currently no efficient way to quantify overhead throwing volume in water polo. Therefore, this study aimed to test the feasibility of a method to detect passes and shots in water polo automatically using inertial measurement units (IMU) and machine-learning algorithms. Eight water polo players wore one IMU sensor on the wrist (dominant hand) and one on the sacrum during six practices each. Sessions were filmed with a video camera and manually tagged for individual shots or passes. Data were synchronised between video tagging and IMU sensors using a cross-correlation approach. Support vector machine (SVM) and artificial neural networks (ANN) were compared based on sensitivity and specificity for identifying shots and passes. A total of 7294 actions were identified during the training sessions, including 945 shots and 5361 passes. Using SVM, passes and shots together were identified with 94.4% (95%CI = 91.8-96.4) sensitivity and 93.6% (95%CI = 91.4-95.4) specificity. Using ANN yielded similar sensitivity (93.0% [95%CI = 90.1-95.1]) and specificity (93.4% [95%CI = 91.1 = 95.2]). The results suggest that this method of identifying overhead throwing motions with IMU has potential for future field applications. A set-up with one single sensor at the wrist can suffice to measure these activities in water polo.

In-Season Internal Load and Wellness Variations in Professional Women Soccer Players: Comparisons between Playing Positions and Status

The internal intensity monitoring in soccer has been used more in recent years in men's football; however, in women's soccer, the existing literature is still scarce. The aims of this study were threefold: (a) to describe the weekly variations of training monotony, training strain and acute: chronic workload ratio through session Rated Perceived Exertion (s-RPE); (b) to describe weekly variations of Hooper Index [stress, fatigue, Delayed Onset Muscle Soreness (DOMS) and sleep]; and (c) to compare those variations between playing positions and player status. Nineteen players (24.1 ± 2.7 years) from a Portuguese BPI League professional team participated in this study. All variables were collected in a 10-week in-season period with three training sessions and one match per week during the 2019/20 season. Considering the overall team, the results showed that there were some associations between Hooper Index categories and s-RPE like stress or fatigue (0.693, p < 0.01), stress or DOMS (0.593, p < 0.01), stress or s-RPE (-0.516, p < 0.05) and fatigue or DOMS (0.688, p < 0.01). There were no differences between all parameters in playing positions or player status. In conclusion, the study revealed that higher levels of fatigue and DOMS occur concurrently with better nights of sleep. Moreover, any in-season variations concerning internal load and perceived wellness seems independent of position or status in outfield players. The data also showed that the higher the players' reported stress, the lower the observed s-RPE, thus possibly indicating a mutual interference of experienced stress levels on the assimilation of training intensity by elite women soccer players.

Monitoring work and training load in military settings - what's in the toolbox?

Military personnel are required to complete physically demanding tasks when performing work and training, which may be quantified through the physical stress imposed (external load) or the resultant physiological strain (internal load). The aim of this narrative review is to provide an overview of the techniques used to monitor work and training load in military settings, summarise key findings, and discuss important practical, analytical, and conceptual considerations. Most investigations have focused upon measuring external and internal load in military training environments; however, limited data exist in operational settings. Accelerometry has been the primary tool used to estimate external load, with heart rate commonly used to quantify internal load. Supplemental to heart rate, psychophysiological and biochemical measures have also been investigated to elucidate aspects of internal load. Broadly, investigations have revealed that military training requires personnel to perform relatively large volumes of physical activity (e.g. averaging ∼15,000 steps·day^-1) of typically low-moderate intensity activity (<6 MET), although considerable temporal and inter-individual variability is observed from these gross mean estimates. There are limitations associated with these measures and, at best, estimates of external and internal load can only be inferred. These limitations are particularly pertinent for military tasks such as load carriage and manual material handling, which often involve complex activities performed individually or in teams, in a range of operational environments, with multiple layers of protection, over a protracted duration. Comprehensively quantifying external and internal loads during these functional activities poses substantial practical and analytical challenges.

A Systems Analysis Critique of Sport-Science Research

PURPOSE

The broad aim of sport-science research is to enhance the performance of coaches and athletes. Despite decades of such research, it is well documented that sport-science research lacks empirical evidence, and critics have questioned its scientific methods. Moreover, many have pointed to a research-practice gap, whereby the work undertaken by researchers is not readily applied by practitioners. The aim of this study was to use a systems thinking analysis method, causal loop diagrams, to understand the systemic issues that interact to influence the quality of sport-science research.

METHODS

A group model-building process was utilized to develop the causal loop diagram based on data obtained from relevant peer-reviewed literature and subject-matter experts.

RESULTS

The findings demonstrate the panoply of systemic influences associated with sport-science research, including the existence of silos, a focus on quantitative research, archaic practices, and an academic system that is incongruous with what it actually purports to achieve.

CONCLUSIONS

The emergent outcome of the interacting components is the creation of an underperforming sport-science research system, as indicated by a lack of ecological validity, translation to practice, and, ultimately, a research-practice gap.

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.

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.

Focused Issue on Workload and Injury to Share Practical Advice With Clinicians, Athletes, and Coaches

Anyone who works with athletes of any age and ability knows the best way for the athlete to avoid injury is to avoid playing sports. Anyone who works with athletes also knows that athletes want to play sports above almost all else. Understanding the relationship between how much sports activity an athlete participates in (ie, workload) and injury will help clinicians, athletes, and coaches know what to do to keep athletes healthy (injury free) and performing their best. In the October 2020 focused issue of JOSPT, we tackle workload and sports injury. J Orthop Sports Phys Ther 2020;50(10):536-537. doi:10.2519/jospt.2020.0108.

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.