UNIVERISTY OF CALGARY. Identifying the Impact of Injury Definition and Training Load on the Study of Jumper s Knee. Kerry James MacDonald A THESIS

Transcription

1 UNIVERISTY OF CALGARY Identifying the Impact of Injury Definition and Training Load on the Study of Jumper s Knee by Kerry James MacDonald A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN KINESIOLOGY CALGARY, ALBERTA OCTOBER, 2016 Kerry James MacDonald 2016

2 Abstract With a growing body of research into volleyball injuries we are beginning to understand potential risk factors for the most prevalent injuries. Volleyball has been found to have more overuse than acute injuries, yet the majority of research to date has failed to utilize an injury definition sensitive enough to capture the true frequency and burden of overuse problems. Furthermore, the mechanism of overuse injuries is believed to be a chronic overloading of tissue, in combination with an incomplete healing process. With advancements in technology, it is now possible to accurately and efficiently measure these loads which, in turn, could have significant impact on injury prevention. Previously identified risk factors were assessed with the purpose of developing a sport-specific screening program. The impact of injury definition on the data collection for overuse injuries was also examined. This analysis evaluation confirmed the need to use specific overuse injury definitions, with an improved sensitivity for the capture of overuse injury frequency and burden compared to more conventional time-loss definitions. An assessment of known risk factors, including a measure of jumping load, was completed with the more sensitive overuse injury capture. Although no risk factor was found to significantly predict injury outcome, several methodological challenges were identified. This research demonstrates that traditional assessment techniques that have been used for time-loss injuries are not sufficient for overuse injury capture and analyses. The contribution of this dissertation to the literature is the demonstration that the methods presented can more accurately capture the injury burden and record the specific load metrics for that injury. However, further advancements in statistical analysis for prevalence measures of injury are required to assess dynamic risk factors, including measures of load, for overuse injuries.

3 Table of Contents Abstract... i Table of Contents... ii List of Tables... v List of Figures... vi List of Abbreviations... vii Chapter 1: Introduction Background Research Purpose Research Rationale Primary and Secondary Objectives Summary of thesis format Author Contributions... 5 Chapter 2 - Periodic Health Exam / Pre-Participation Exam for Volleyball Purpose/Introduction Cardiovascular Assessment Non-Cardiac Assessment Musculoskeletal Assessment Previous Injury Ankle Injuries Knee Injuries Shoulder Injuries Lower Back Injuries Summary... 8 Chapter 3 - Jumper s knee in elite volleyball the effect of injury definition and surveillance methodology on measures of injury occurrence and burden Abstract Background Methods Participants Time-loss Injury Report Overuse Injury Questionnaire Weekly Exposure Statistical Analysis Results Participant Characteristics Injury Report Form Time-loss Injuries Modified Overuse Injury Questionnaire Substantial Problems Comparative Injury Rates Discussion ii

4 3.6 Conclusion Funding Competing Interests Chapter 4 - Jumper s knee: A prospective evaluation of risk factors in volleyball players using a novel measure of injury Abstract Background Methods Participants Risk Factor Evaluation Vertical Jumping Ability Ankle Dorsiflexion Range Dynamic Balance Dynamic Knee Alignment Injury Capture Statistical Analyses Results Participant Characteristics Pre-Participation Questionnaire Injury Data Intra-rater Reliability Descriptive Results Regression Analysis Discussion Conclusion Funding Competing Interests Chapter 5 - Title of Article: Validation of an Inertial Measurement Unit for the Measurement of Jump Count and Height Abstract Introduction Methods Participants Inertial Measurement Unit Jump Count Jump Height Statistical Analysis Results Participant Characteristics Jump Count Jump Height Discussion Conclusion Conflict of Interest Ethical Approval iii

5 Chapter 6 - The interactive effect of training load and injuries in volleyball Abstract Background Methods Participants Measures of Injury Measures of Training Load Estimations of Training Load Statistical Analysis Results Data Cleaning & Imputation Participant Characteristics Injuries Captured Discussion Funding Competing Interests Chapter 7 - Conclusions and Future Research Directions Summary of findings Chapter 2 - A Periodic Health Exam for the Volleyball Athlete Chapter 3 - Jumper s knee and elite volleyball the effect of injury definition and surveillance methodology Chapter 4 - A prospective evaluation of risk factors using a novel measure of injury Chapter 5 - Validation of an inertial measurement unit for the collection of jump frequency and magnitude Chapter 6 - : The interactive effect of jump load and jumper s knee Future Research Directions Overuse Injury Classification Risk Factor Assessment A Repeated Measures Design and Complexity Science approach Internal Measures of Load Conclusion Bibliography Appendix A Individual Injury Report Form Appendix B Modified Overuse Injury Questionnaire Appendix C Pre-Participation Questionnaire Appendix D Weekly Exposure Sheets iv

6 List of Tables Table Volleyball Specific Musculoskeletal Assessment Concerns Table Time-loss injury proportion and duration by body region Table Injury type and medical attention proportions Table Comparison of knee injury diagnosis between reporting mechanisms Table Comparison of time-loss injuries between reporting mechanism Table Substantial knee problems and knee injury history by position Table Analysis of risk factor measures and substantial knee problems Table Regression Analysis of risk factors for substantial problems Table A comparison of jump counts between the IMU and visual inspection during stuctured practice by skill. Table Summary of missing jump data from each cohort. Table Injury Incidence Rate (IIR) for first substantial knee problem and first overuse time-loss knee injury Table Regression Analysis of risk factors for first substantial knee problems v

7 List of Figures Figure A dynamic, recursive model of etiology in sport injury. Figure Star Excursion Balance test Figure Landing phase of Vertical Drop Jump Figure Flowchart of moiq question sequencing Figure The 4 key questions to determination if a knee problem is present Figure Prevalence of overuse knee problems Figure Prevalence of overuse knee problems across three teams Figure IMU jump height vs. 3D jump height by jump type Figure Jump Count, Jump Height and Exposure Hours vs. Knee Injury Severity for one participant Figure Jump Count & Injury Severity for 6 random subjects in one cohort. vi

8 List of Abbreviations 2-D - two dimensional 3-D - three dimensional ACL - anterior cruciate ligament ACWR Acute chronic workload ratios CI confidence interval cm centimeter CV ME coefficient of variation of the method error ECG - electrocardiogram FPS - frames per second IIRF - individual injury report form IMU - inertial measurement unit IOC - International Olympic Committee IRR - injury incidence rates Kg - kilograms LOA - limits of agreement ME method error moiq - modified overuse injury questionnaire MRI - magnetic resonance imaging OIQ - overuse injury questionnaire OR odds ratio PHE - periodic health evaluations PPE pre-participation exam PPQ - pre-participation questionnaire SCD - sudden cardiac death SEBT - star excursion balance test SLS - single leg squat SMS - short message service VDJ - vertical drop jump WES - weekly exposure sheet vii

9 Chapter 1: Introduction 1.1 Background It has been noted that sport participation and health have a paradoxical relationship. Although participation reduces morbidity it can increase risk to injury and limit further participation in physical activity. 1 Mitigation of injury risk should therefore be undertaken to maximize sport participation benefits. van Mechlen (1992) 2 outlined a model in which injury surveillance is highlighted as the initial step in the development of an injury prevention strategy. Recent work has suggested that the definition of injury should match the injury type, in order to accurately and systematically define, monitor, record and categorize injury. 3-6 The impact of different injury definitions on the incidence, prevalence and severity of injury in specific sport populations has not been well studied. Furthermore, the impact of various injury definitions on the second stage of the van Mechlen model, risk factor identification, is unknown. It is plausible that the risk factors identified for injuries captured using one injury definition vary when assessed with injuries captured using a different injury definition. This variation would therefore have a direct effect on the subsequent steps of injury prevention strategy development and implementation. Meeuwisse, et al. 7 was the first to describe the dynamic recursive nature of injury in sport (Figure 1.1). This model identifies that both intrinsic and extrinsic risk factors should be assessed in the evaluation of an athlete at risk. Intrinsic risk factors are those that are internal and therefore specific to the individual, these can be items such as strength or injury history.

10 Extrinsic risk factor variables are specific to the environment and can include playing surface or equipment. The dynamic recursive model recognizes that intrinsic risk factor variables will change over time with exposure to the extrinsic risk factors and participation in sport, regardless of the outcome of injury. 8 Figure A dynamic, recursive model of etiology in sport injury. (reproduced with permission from the Clinical Journal of Sports Medicine). One of the key risk factors that is gaining more attention, in combination with an increase in technological advancements, is the measure of workload. 9 Workload is often quantified as measure of external load, or a subjective assessment of the internal load, that the athlete endures throughout their training and competition and is interchangeably referred to as training load or player load In the dynamic recursive model, workload may be seen as an 2

11 event or inciting event and could theoretically either impact the intrinsic risk factors or may provide a mechanism of injury. In an acute injury situation (defined as occurring from a specific event), it is easy to recognize that an increased exposure to inciting events, or an increase in the magnitude (frequency and/or intensity) of events, may lead to an increased risk of injury. The effect that an increase in workload has on the risk of overuse injury is perhaps slightly more complex. Overuse injury is believed to be a repeatedly failed healing process from exposure to a workload above the specific tissue load capacity, that leads to an overuse injury such as jumper s knee 13. To thoroughly assess the interaction of workload and injury it is necessary to quantify both workload and injury variables in an individual, sensitive and timely fashion. 9 As overuse injuries tend to present with an insidious onset, early detection of signs and symptom may be difficult. 14 A clearer understanding of the workloads that trigger the initial sign and symptoms of overuse injury could lead to primary prevention initiatives. Volleyball has been found to have a relatively low rate of time-loss injuries. 15 Conversely, volleyball athletes have been found to have the highest prevalence of overuse knee injuries when compared to several other Olympic sports. 16 Further research has identified that the burden of overuse injury within a volleyball population may be more significant than the burden of acute injuries. 14 For this reason, it is imperative that more aspects of injury prevention research in a volleyball population target the prevention of overuse injuries. 3

12 1.2 Research Purpose The purpose of the following research was three fold: 1. To identify current risk factors associated with volleyball overuse injuries and develop recommendations for a periodic health exam to medically screen volleyball athletes. 2. To assess the impact that injury definition has on measures of knee injury frequency, severity and associated assessment risk factors. 3. To validate an instrument for the measure of jump load in volleyball and assess the association between jump load and overuse knee injuries. 1.3 Research Rationale The sport of volleyball has been found to have a relatively low acute injury incidence rate but a high prevalence of overuse problems. Although a new method of injury capture has been found to more accurately capture overuse knee injuries in volleyball, no study has attempted to assess risk factor measures for this new injury outcome measure. 1.4 Primary and Secondary Objectives The primary objective of this research was to assess jump load as a risk factor for the development of overuse knee injuries in elite male volleyball players. The secondary objectives were to (1) assess measures of injury frequency and severity using two different injury capture methods, employing two different definitions of injury, and then (2) assess the effect of the different definitions on injury risk factors. 4

13 1.5 Summary of thesis format The chapters to follow are laid out in a publication style as a collection of manuscripts that have either been accepted, submitted, or will be submitted for peer review publication. 1.6 Author Contributions The main author took the lead role on the creation of all chapters within this dissertation. The research direction was developed by the lead author and the vast majority of the data collection, analysis and manuscript writing was completed by the lead author. A detailed breakdown of the specific contributions that the author provided in each chapter are described below: Chapter 1 - Introduction o Writing of all original material o Gaining of reproduction permission for provided figure Chapter 2 - A Periodic Health Exam for the Volleyball Athlete o Writing of textbook chapter o Review of the literature for all provided references o Creation of all figures and tables o Acceptance for publication after completion of all requested revisions. Chapter 3 - Jumper s knee and elite volleyball the effect of injury definition and surveillance methodology o Successful completion of ethics applications from the three required ethics 5

14 review boards o Recruitment of the study cohort from 5 different teams o Establishment of short message service (SMS) agreement with Danish provider for the collection overuse injury data capture o Creation, printing, distribution and collection of all injury report forms and weekly exposure sheets. o All data cleaning and the majority of analysis o Writing of manuscript including the creation of all original tables and figures Chapter 4 - Jumper s knee: A prospective evaluation of risk factors using a novel measure of injury o Successful completion of ethics applications from the three required ethics review boards o Recruitment of all study participants o Collection, cleaning and analysis of all risk factor variables o Writing of original manuscript including creation of original tables and figures Chapter 5 - Validation of an inertial measurement unit for the collection of jump frequency and magnitude o Acquisition of donated inertial measurement units from the manufacturer o Successful completion of ethics application o Recruitment of all study participants o Collection, cleaning and analysis of all data, with the exception of the 3-D kinematic data 6

15 o Writing of original manuscript, including creation of original tables and figures o Submission for publication Chapter 6 - The interactive effect of jump load and jumper s knee o Successful completion of ethics application o Recruitment of all study participants o Cleaning and analysis of injury, jump and exposure data o Completion of the analysis plan o Writing of all original materials including creation of original tables and figures Chapter 7 Conclusion & Future Research Direction o Writing of all original material 7

16 Chapter 2 - Periodic Health Exam / Pre-Participation Exam for Volleyball Authors: Kerry MacDonald, Willem H. Meeuwisse Status: In Press Journal/Text: Chapter 6 Periodic Health Exam. International Olympic Committee Volleyball Handbook of Sports Medicine and Science 2 nd Edition. 8

17 2.1 Purpose/Introduction Historically, the role of the medical professional working within a sport specific context has focused on the diagnosis and treatment of sport related injuries. In the past decade, a methodological shift towards injury prevention has been identified as an important future direction. One of the primary tools for medical professionals to address injury prevention is through the implementation of periodic health evaluations (PHE). As with any health screen, the intention of the PHE is to determine any pathological condition early, allowing for an effective intervention and hopefully a reduction in long-term morbidity (or mortality). Although the primary goal of any PHE is to identify those athletes that are at an increased risk of injury or illness, it also presents an opportunity to assess the management of current health problems and establish a relationship between the medical practitioner and the athlete. An improved relationship between the athlete and their physician will hopefully reduce the frequency of athlete s attempting to self-manage injuries and illness. To further enhance the physician athlete relationship, it is crucial that the PHE be conducted in the primary interest of the athlete, allowing for an assessment of their health in relationship to their sport participation and only after receiving their informed consent. The principles of a good PHE are set out in detail in the International Olympic Committee (IOC) Consensus Statement on Periodic Health Evaluation of Elite Athletes. 17 A PHE should ideally begin with a detailed personal and family medical history, followed by a thorough physical exam. Based on the information gathered in these subsequent steps, further investigations such as blood, urine, electrocardiogram (ECG), etc. may be warranted. A PHE 9

18 should be completed by a sport medicine physician, in a medical setting that optimizes the accuracy of the examination through access to medical records and necessary equipment. This setting should also assure the privacy of the athletes personal information. Ideally the PHE is initially completed in the athletes off season, allowing for the management of identified concerns well before the start of the season or any significant competitions. Additional follow-up evaluation throughout the season would then allow for an assessment of the athletes health adaptions compared to preseason levels. An understanding of the common injuries and the dayto-day physiological demands of volleyball, can aid a sport medicine physician in the completion of a thorough PHE. It is therefore ideal that the sport medicine physician possesses a history of involvement in the sport and frequent interactions with the team and coaching staff in both training and competition settings. The delivery of a PHE for the primary purpose of clearance for participation in a particular sport or event is often referred to as a pre-participation exam (PPE). It is becoming increasingly common for elite level sport participation to require the successful completion of a PPE prior to any engagement with the sport team, league or competition. If the PPE is being completed to allow participation, it should be explicitly clear to the athlete, prior to the examination, whom the physician represents, what the physicians responsibilities are to the team and what the potential ramifications of a failed examination could be. Furthermore, the exam results that are given to any third party should only disclose personal information that is specifically authorized by the athlete. Disclosure should be limited to a dichotomous yes or no response to the question of whether the athlete in question is currently fit to participate in the specific event or 10

19 competition, unless the circumstances require otherwise. Although the PPE provides a onetime clearance for involvement, ideally the use of an ongoing PHE can be established to capture the dynamic health changes associated with sport involvement. Any evidence of serious medical risk that is identified during a PPE or PHE should be reported to the athlete and future participation should be strongly discouraged until the necessary medical steps have been completed. The following PHE recommendations are based on the current scientific evidence specific to volleyball. Moderately strong evidence is available for the distribution of specific injuries within an adult volleyball population. The determinants of common volleyball injuries vary greatly by injury type. Finally, specific focus was given to the use of diagnostic tests with strong positive and negative predictive values when possible. 2.2 Cardiovascular Assessment The strongest scientific evidence for the completion of a PHE comes from the potential detection of risk associated with sudden cardiac death (SCD). The combination of cardiovascular disease and concentrated physical activity can result in cardiac arrest. Although physical activity is not the cause of SCD, it acts as the triggering mechanism in the presence of underlying cardiovascular disease. 18 Furthermore, SCD in athletes can occur without prior symptoms, placing great significance on the PHE as a method to detect known risk factors. The screening for cardiovascular disease should begin with a questionnaire of personal and family cardiovascular medical history and a physical examination

20 Inclusion of a 12-lead ECG examination in the PHE has been debated by numerous international groups An ECG assessment has been shown to be abnormal in up to 90% of individuals with hypertrophic cardiomyopathy and up to 80% of individuals with arrhythmogenic right ventricular dysplasia/cardiomyopathy. The development of an ECG criteria tool for the categorizing of ECG changes has shown to reduce the false positive rate to 4.2%, while improving the sensitivity to 91% and the specificity to 94% among athletes. Although making a 12-lead ECG mandatory within a volleyball specific PHE is beyond the scope of this chapter, the IOC Consensus includes the 12- lead ECG as part of the elite athlete PHE. Of particular cardiologic concern, due to its increased prevalence in a volleyball population, is the assessment for Marfan syndrome. Several of the signs for Marfan syndrome are common among volleyball athletes. These include tall thin stature, long arms, long legs, and long fingers. Athletes with Marfan syndrome often experience an enlarged aorta and are therefore at an increased risk of aortic dissection. The inclusion of echocardiography as part of the PPE may be warranted in individuals with this body habitus. The management of identified cardiovascular concerns should then follow the accepted protocols such as those outlined by the Bethesda Conference #36 and European Society of Cardiology recommendations. 21 This may include further evaluation, education of risk and informed participation, or exclusion from participation. It is of prime importance in the cardiac assessment that the administering physician refer any detected abnormality that they are not comfortable acting on to a cardiac specialist for further assessment. 12

21 2.3 Non-Cardiac Assessment Non-injury related medical conditions effecting systems other than the cardiovascular system occur frequently in elite athletes; whether pulmonary, gastrointestinal, hematological, dermatological, urological, immunological, endocrinological, or ophthalmological. These conditions can occur at varying times throughout the season and are often transient in nature. Early detection can result in effective treatment, minimizing the burden of the condition. The use of the IOC recommended PHE questionnaire and physical exam guide provides a systematic method to aid in early detection of non-cardiac conditions Musculoskeletal Assessment The IOC consensus paper on PHE s outlines one method by which the PHE exam can be tailored to the sport in question, focusing on the most prevalent musculoskeletal injury types and their corresponding risk factors. 17 Volleyball specific areas of focus are discussed below and summarized in Table

22 Table 2.1. Volleyball Specific Musculoskeletal Assessment Concerns Body Position Concern Diagnostic Test Score Ankle Dynamic balance Modified Star Excursion Balance Test Knee Dynamic knee valgus Vertical Drop Jump Poor = bilateral difference in anterior direction > 4cm Subjective visual assessment of valgus at lowest moment from frontal angle Knee Shoulder Ankle dorsiflexion range of motion Scapular malposition and dyskinesis Weighted Lunge Poor = dorsiflexion angle > 36.5 degrees SICK Poor = overall score > 3 Lower Back Thoracic mobility Seated Thoracic Rotation Poor = visually evident bilateral differences or <45 degrees from frontal plane The most common injuries in volleyball are acute injuries of fingers and ankles, and overuse injuries of the knee, shoulder and lower back. The burden of injuries in volleyball is significant, with overuse injuries being more common and resulting in as much athletic impairment as acute injuries. Compared to other Olympic sporting events, volleyball has a relatively low incidence of time loss injuries. 15 Recent research that captured all medical complaints showed that volleyball has a high prevalence of overuse conditions, resulting in self-management without full withdrawal from participation. 16 For this reason, it is crucial that the musculoskeletal assessment within the PHE capture the current health status and is sensitive enough to identify potential injuries that have previously gone unreported. The identification of such conditions within the competitive season may provide the athlete with

23 better management techniques. However, the ultimate goal should be to address any issues in the offseason, allowing for recovery and modification of selected risk factors, with the ultimate aim of limited recurrence Previous Injury. It has been consistently demonstrated across multiple sports that the greatest predictor of future injury is previous injury. 17 For example, a strong predictor of future ankle sprains in volleyball is having previously sprained an ankle. 28 However, there is evidence that full rehabilitation can return the athlete to their baseline (pre- injury) level of risk. 29 This evidence underscores the importance of a thorough assessment of medical history responses from previous injury history questions within the PHE. Preseason identification of residual injury effects may provide an opportunity for targeted rehabilitation. All previous injuries should be assessed to determine current state and if any adaptive/protective responses have occurred (i.e., reduced range of motion). The assessment can include assessments of joint laxity or range of motion, muscular strength and/or functional ability. The assessment is often conducted with the use of the uninjured limb or joint as the control, presenting great difficulty with head, neck and trunk assessments., or in cases of bilateral injury. The use of a control limb is also confounded when large bilateral differences are expected, such as shoulder assessments of volleyball players and when the control limb has had to make large adaptions to injury in the opposing limb. 2

24 2.4.2 Ankle Injuries Ankle injuries are the most common acute injury affecting volleyball players Studies have frequently reported that ankle sprains account for up to half of all reported volleyball injuries. They commonly occur during the execution of the attacking or blocking actions, with contact with another player being frequently reported. 30 Interestingly, recurrent ankle sprains have been found to be more frequent than first time sprains and that risk is heightened in the first 12 months post sprain. 28 To help reduce the rate of injury recurrence athletes should be instructed to complete a neuromuscular rehabilitation program following initial injury Additionally, it is advised that athletes use bracing for 6-12 months post injury. There are vast differences in the types of braces available, however for any inversion or eversion ankle sprains it is recommended that a brace that limits inversion/eversion, without restricting ankle plantar or dorsiflexion, should be used. The specific reason for this will be discussed later when looking at the role of ankle dorsiflexion range of motion in overuse knee injuries. In addition to previous injury, the other common risk factor for ankle injury is poor dynamic balance. 32 A good functional assessment tool for dynamic functional stability is the modified star excursion balance test (Figure 1). The modified version of the original 8-point test assesses balance in three planes (anterior, posteromedial, and posterolateral) for both ankles with strong reliability (ICC ). Outcome scores that show bilateral differences greater than 4cm in the anterior direction should be considered at risk for subsequent sprains. 32 These athletes should also be provided with a neuromuscular and proprioceptive balance program. 3

25 Figure 2.1 Star Excursion Balance test Knee Injuries Knee injuries in volleyball can be divided into two primary categories of acute and overuse. Anterior cruciate ligament (ACL) injuries amongst female athletes accounts for the majority of acute volleyball related knee injuries Meanwhile jumper s knee is the most common overuse knee diagnosis and it effects male athletes disproportionately more than female athletes. 34 This is theorized to be due to an increased jumping ability and therefore greater load on the extensor mechanisms of the knee. 35 ACL injury rates for female NCAA volleyball players have been found to be 0.09 injuries per 1000 player exposure hours. Although this is not high compared to other sports (women s soccer = 1.3/1000hrs, women s basketball = 1.15/1000hrs), the burden of ACL injuries is significant with 4

26 long lasting consequences Research has shown that athletes with higher ground reaction forces and larger valgus angles when performing a vertical drop jump (VDJ) are at a higher risk of ACL injury. 37 Although an assessment of ground reaction forces is beyond the scope of a standard PHE, an assessment of dynamic knee alignment is possible. Dynamic knee alignment is also considered a risk factor for ligamentous knee injuries. 37 A VDJ test for the functional assessment of dynamic knee angle is recommended for all female athletes or any athletes with a history of knee injury. The assessment of knee valgus should occur at the lowest moment of the landing phase of the VDJ (Figure 2). The video capabilities of a smartphone or tablet device can be employed to enhance visual inspection (especially if slow motion is used), and also provide an opportunity for feedback to the athlete. An athlete that is determined to have visually obvious valgus angles during this assessment should seek further assistance to develop stronger knee stability and proper landing techniques. Figure 2.2 Landing phase of well executed Vertical Drop Jump landing 5

27 The most common overuse knee injury diagnosis amongst volleyball players is jumper s knee. 15 The prevalence of jumper s knee has been found to be 45% in an elite male volleyball population. 34 Male volleyball players have been found to have twice the odds of developing jumper s knee as females. 40 The causal mechanism is believed to be a repeatedly failed healing process following chronic overload of the knee joint. 13 It is therefore imperative that previous history of knee pain be identified and appropriate loading be incorporated in any decisions on practice and game participation. Athletes will frequently attempt to self-manage without a reduction in training load or volume. The establishment of a pain free training volume should be targeted prior to any increase in sport participation. Furthermore, athlete s experiencing jumper s knee should be prescribed an active rehabilitation protocol including an eccentric loading protocol. Eccentric loading has been found to be successful in the treatment of jumper s knee. 41 The preseason period is an opportune time to detect subclinical or active jumper s knee and to institute these measures. Another modifiable risk factor is reduced ankle dorsiflexion range. It is theorized that athletes with a greater ankle range of motion will use a softer landing technique, therefore reducing the eccentric load on the tendon during the landing phase of a jump A simple weight bearing lunge measure of ankle dorsiflexion should be incorporated in the PHE. This test has been found to have high inter (ICC = 0.97) and intra-rater reliability (ICC = 0.97). 44 Athletes found to have an ankle dorsiflexion angle measure less than 36.5 degrees from the vertical should be considered poor range of motion and provided with an intervention to address the limited range of motion. 45 Ankle braces that restrict ankle inversion/eversion without reducing dorsiflexion are 6

28 recommended. Such braces allow for some protection from lateral and medial ankle sprains, while permitting the soft landing techniques that are encouraged for the prevention of overuse knee injuries Shoulder Injuries Shoulder injuries amongst volleyball players are predominately overuse in nature and have been found to effect up to 32% of British and 24% of American elite volleyball players. Similar to other overhead throwing sports, volleyball athletes with overuse shoulder complaints have been found to have significant bilateral range of motion and strength differences Volleyball athletes playing positions associated with a high frequency of attacking (e.g. outside hitters and middle blockers) are at a greater risk than setters or liberos. 15 The most common specific diagnosis of shoulder problem amongst volleyball athletes is subacromial or rotator cuff impingement. 50 A strong predictor of shoulder injury is the SICK scapular score that accounts for scapular malposition, inferior medial border prominence, coracoid pain and malposition and dyskynesis of scapular motion. 48 Specifically, a SICK scapular score greater than 3 should be considered poor and those athletes should be considered at high risk for future overuse shoulder problems. 48 Athletes found to have a poor SICK score should be provided rehabilitation exercises to address the specific limitations of their current assessment. A reduction in current training volume may be required to allow for shoulder adaption to the prescribed exercises to occur. 7

29 2.4.5 Lower Back Injuries A recent review article reported that trunk and back injuries effect 17% of volleyball players, with professional athletes having higher injury prevalence than recreational volleyball players. 50 The most commonly reported injury is lower back muscle strain, an overuse condition caused by repetitive overload of the lower back musculature. 50 Similar to overuse shoulder injuries, positions associated with a high frequency of attacking (e.g. outside hitters and middle blockers) are at a greater risk. Potentially, the best way to reduce stress in the lumbar spine musculature is through the adjustment of volleyball spiking technique. When attacking and serving volleyball athletes perform extension and rotation of the lumbar and thoracic spine. Athletes with lumbar discomfort should look to reduce their extension while increasing their thoracic rotational range. For this to be possible, rotational range of the thoracic spine is required and should be assessed during the PHE. A simple seated rotation technique can be employed to assess range of motion and bilateral differences with good reliability (intrarater ICC range = ). 51 Visually evident bilateral differences or rotational ranges less than 45 degrees from the frontal plane should be considered poor and warrant additional exercises in an attempt to improve thoracic range of motion. 52 The review of spiking technique in athletes with low back pain is one example of how the PHE provides an opportunity to review injury related technical aspects with the coaches, especially at the elite level. 2.5 Summary While completing a volleyball specific PHE, specific concern to the musculoskeletal conditions outlined in this chapter should be completed. To summarize, specific assessments are highlighted 8

30 in Table 2.1. It is important to recognize that the assessment methods selected in this chapter are based on the current body of knowledge. As further assessment methods are developed and validated they should be incorporated, with specific emphasis on tests with strong predictive values. The significant impact that a cardiovascular screen can have on mortality warrants inclusion. Finally, it is important to see the PHE as more than a simple screening procedure, but rather as an opportunity to establish a relationship with the athletes and identify concerns for both injury and performance. Ideally the PHE should be conducted with the athlete s long term wellbeing as the primary focus. 9

31 Chapter 3 - Jumper s knee in elite volleyball the effect of injury definition and surveillance methodology on measures of injury occurrence and burden. Authors: Kerry MacDonald, Luz Palacios-Derflingher, Carolyn Emery, Willem H. Meeuwisse Status: In Preparation Journal/Text: American Journal of Sports Medicine 10

32 3.1 Abstract Jumper s knee in elite volleyball the effect of injury definition and surveillance methodology on measures of injury occurrence and burden. Objectives: To determine the effect that injury definition has on measures of jumper s knee incidence, prevalence and severity among elite level volleyball players. Background: A time-loss injury definition continues to be the most widely used injury definition despite evidence that it fails to accurately capture overuse injuries. An overuse injury definition has been created to address the limitation of a time-loss definition. To date there is a paucity of research comparing the impact that two definitions would have on the capture and analysis of injuries. Methods: Seventy-two male volleyball players from collegiate, national and club levels were prospectively followed over a 32-week time period. Time-loss injuries were captured by team medical staff using an individual injury report form (IIRF). Study participants received a modified version of an overuse injury questionnaire (moiq) via a weekly short message service (SMS). Results: The IIRF captured 15 time-loss knee injuries in 72 study participants (20%) (incidence rate = 0.91/1000 athlete exposure hours). Based on the moiq, 84.7% of participants reported having a knee problem and 66.7% sustained a substantial knee problem. All IIRF knee injuries captured were also registered by the moiq. Agreement on the specific diagnosis occurred for 66.7% of injuries resulting in a moderate Kappa score of Conclusion: An overuse injury definition provided a greater understanding of the magnitude and burden of knee injuries in this population. Despite the lack of a specific injury diagnosis, 11

33 this definition must be employed in future injury surveillance studies aiming to capture overuse injuries. 12

34 3.2 Background Current injury consensus statements suggest that three primary injury definitions be utilized in research: time-loss, medical attention, or all complaints The medical attention definition is described to include all injuries in which the athlete seeks medical attention from a certified medical professional. The time-loss definition of injury is employed to capture any injury resulting in an athlete being unable to fully participate in a subsequent match or training session. 16 The all complaints definition describes a situation in which any medical problem is recorded regardless of time-loss or medical attention being sought. Although this third definition is likely to capture the greatest number of injuries, it comes with an array of financial, human and logistic barriers. Fuller, et al. 3 predicted that the definitions of all complaints or medical attention are unlikely to be utilized due to the high financial and human resource costs, which is why most injury surveillance studies to date use the time-loss definition. The time-loss injury definition continues to be the most widely used, as the medical attention or all complaints definitions have only been utilized for short duration special events under tightly controlled conditions, such as the Olympic Games While time-loss is likely to capture the fewest injuries, it likely provides the most reliable measure of injury. 5 An athlete s participation in a game or practice is objectively identifiable and can be verified through additional sources such as game logs. This approach allows for a comparison of injury rates within teams, between teams and across seasons. Furthermore, without specific medical personnel to record injuries, injury occurrence can still be captured, allowing for greater use with non-elite or adolescent populations. The major limitation of a time-loss definition is that it fails to capture 13

35 those athletes who continue to train or play while injured. 4 Athletes will often attempt numerous self-management techniques, such as nonsteroidal anti-inflammatory drug use, bracing or taping, prior to an adjustment in their participation level. 14 This is a major concern for overuse injuries that often present with a gradual onset, resulting in athletes modifying their training prior to discontinuing participation Although the recording of a time-loss injury can be conducted by non-medical personnel, a follow-up phone call or examination by medical personnel is recommended in order to ascertain a specific injury diagnosis. This multi-staged registration process places greater time and human resources on the injury reporting regime and therefore results in an increased need for financial resources. Additionally, if an athlete fears that the reporting of a medical condition may result in removal from practice or games they may decide to not report the condition. Although it is a primary concern with using the medical attention definition, Clarsen et al outlined how both medical attention and time-loss definitions of injury reporting preferentially capture acute injuries. An acute injury mechanism is typically associated with a specific identifiable incident, while an overuse injury is the result of repetitive micro-trauma. 14 Overuse injury symptoms tend to present gradually and medical attention or withdrawal from training or competition often only occurs after repeatedly failed attempts at self-management. 16 This creates great difficulty for a researcher seeking to accurately capture and report all overuse injuries. 14

36 It is common practice in sport injury epidemiology to report injury incidence rates (IIR). An IIR is defined as the frequency of new injuries within a given time frame. The IIR is well suited for the registration of acute injuries with their definable moments. The presentation of overuse injuries is more appropriately reported using a measure of prevalence due to the fluctuating state of remission and exacerbation. 25 A measure of prevalence allows for the capture of the total population proportion that is affected by injury at a single point in time (i.e. point prevalence) or during a given time frame (i.e. period prevalence). An injury surveillance methodology that captures injuries not resulting in time loss by allowing the athlete to report directly, could address the many limitations of the time-loss definition. The Oslo Sport Trauma Research Center developed and validated an overuse injury questionnaire (OIQ) for the capture of overuse injuries in a multitude of elite sport settings. The injury definition used is a problem to a specific anatomical area that has an effect on participation, training volume, performance and pain in the subsequent week. 16 This definition will be referred to as an overuse injury definition. Clarsen et al found this overuse injury definition to capture ten times the number of injuries when compared to a time-loss injury report for cross-country skiing, floorball, handball, road cycling and volleyball injuries. With this method, the athletes complete an online questionnaire comprised of four questions to capture the four components of the injury definition (Figure 3.1). All completed forms are directly submitted to the researcher. Direct reporting helps to mitigate the possible culture of fear and avoidance that may be present with direct reporting of injuries to medical personnel or a team designate. However, with direct reporting, a specific diagnosis cannot be made 15

37 without follow-up from medical personnel. A limitation of this injury surveillance methodology is that the definition of what is a recordable problem could have a variety of interpretations. Additionally, the validity of the data is reliant on a high response rate from each individual athlete throughout the course of a study. Continuous monitoring of athlete response rates and follow-up for missing data is essential and can be resource intensive. With the emergence of simple message service (SMS), or text messaging as a data collection tool this recording methodology may provide a stronger response rate than online questionnaires. 55 Injury definitions could have a significant impact on the assessment of risk factors, injury management and prevention planning. The purpose of this study was to determine the effect that different injury definitions have on measures of injury incidence, prevalence and severity, focused on the problem of Jumper s Knee in a volleyball population. Jumper s Knee is an ideal injury to use for the assessment of an overuse definition because it is known to have high prevalence, frequent exacerbation and remission of symptoms and numerous attempts at selfmanagement prior to time-loss from sport We hypothesized that the overuse definition would capture significantly more injuries and a greater injury burden. Furthermore, we wanted to assess the utility of SMS as a data collection tool for overuse injuries and determine if injury diagnosis and other time-loss injuries can be accurately collected using an athlete direct reporting method. 16

38 3.2 Methods Participants A cohort study was conducted including 72 male volleyball players who were successfully recruited from an inclusive sample of five elite teams in two geographic locations. Participants were recruited from local collegiate volleyball teams, Volleyball Canada s National Training Centre and a local volleyball club at the commencement of their 2015/2016 seasons. Inclusion criteria required all participants to be registered members of the respective cohorts and able to provide consent and assent as required. Follow-up time varied between teams with collegiate and National Training Centre athletes being followed for 27 weeks while youth club athletes were followed for 14 weeks. This accounted for 100% of collegiate season, 87% of the National Training Centre annual schedule and 61% of the club season Time-loss Injury Report Each team involved in the study had a student athletic therapist attend all training sessions. The athletic therapist was responsible for completing an individual injury report form (IIRF) for any injury matching Fuller s (2006) time-loss definition: any injury that resulted in a player being unable to complete a session/match or fully participate in future training or match play. 3 All IIRFs were transcribed to an online database for further analysis Overuse Injury Questionnaire SMS Track (SMS Track Apps, Denmark) was utilized to collect and categorize all responses to a modified version of the overuse injury questionnaire (moiq) for Knee Problems (Figure 3.1). ). 17

39 The modified version of the moiq began with the four core questions of the original OIQ (Figure 3.2). These questions assessed if the respondent had reduced participation, reduced training volume, and/or reduced performance or any pain due to a knee problem in the previous week. Any respondent who indicated presence of a knee problem was asked additional questions to understand if the injury was new, continuous, or a re-injury and if they had sought medical treatment for the problem. If medical treatment had been sought, a diagnosis was requested. These subsequent questions allowed for a more detailed injury categorization. The final two questions asked all participants if they had any other injury or illness that has resulted in being unable to fully participate in game or practice. If so, a diagnosis of the injury or illness and total number of days lost was collected. By asking the athlete to record their diagnosis and days lost, the ability of the moiq to capture time-loss injuries and illnesses could be assessed. 18

40 Figure 3.1. Flowchart of the modified overuse injury questionnaire (moiq) question sequencing 19

41 Figure 3.2. The four key questions to determine if a knee problem is present Athletes received SMS messages weekly. An automatic reminder message was sent to all nonresponders four hours after the initial message and again 24 hours later if no response had yet been received. Forty-eight hours after the initial SMS message, all non-responders to the initial two reminder messages received an individualized SMS message from the lead author. Overuse knee injuries captured via the moiq were categorized as: any problem, substantial problem and time-loss problem. The category any knee problem was assigned to an athlete each week in which they reported a response greater than one for any of the moiq questions. Substantial knee problems were classified as those knee problems resulting in moderate or severe reductions in training volume or performance or an inability to participate in any training. 16 Operationally this was categorized as a response of 3, 4 or 5 to Questions 2 or 3 (Figure 20

42 3.2). Individual responses to the overuse questions allowed for the measurement of a weekly prevalence, and severity score, for each athlete. Injury burden was assessed using an injury severity score from the sum of answers to the four key questions following protocol outlined by Clarsen et al (2013) Weekly Exposure The team s athletic therapists were also responsible for the completion of a weekly exposure sheet for each week in which the cohort was in the study. This form collected attendance, duration and other descriptive information for each team session each week. Based on the session attendance and duration, weekly athlete exposure hours for each study participant were calculated Statistical Analysis Data were analyzed using the statistical software STATA (v12.1, Collage Station, Texas, USA) with the significance level set at alpha= Time-loss injuries from the IIRF Frequency and incidence rates were calculated for all time-loss injuries by region, diagnosis and burden (duration of time-loss) of injury. Crude injury incidence rates were estimated for each region of injury (#injuries/1000 athlete exposure hours). 21

43 Overuse Injuries from the moiq Weekly prevalence of overuse knee problems was estimated by dividing the number of athletes that reported a problem by the number of questionnaire respondents that week. A similar weekly problem severity estimation was made for the number of athletes who reported problems leading to reductions in training volume, sports performance, or ability to participate in sport. 16 The median severity score was also reported based on the scores of all athletes that reported a problem. A list of knee injury types, diagnoses, and all additional time-loss injuries captured with the moiq was reported. Weeks in which no SMS response was available resulted in the removal of that athlete week from the moiq dataset. Overall response rates were calculated and assessed visually for systematic errors Injury Definition Comparison Comparison of the IIRF and moiq systems was first completed by descriptively comparing the injuries collected through the two systems. Any response from the moiq questions regarding no participation (question 1, 2 or 3, responses 4) was classified as a time-loss knee injury and assessed against all knee injuries captured by the time-loss injury recording form. Visual inspection of moiq responses allowed for the differentiation of new injuries from continuous injuries by assessing week-to-week reporting and description of injury diagnosis. Continuous weeks in which the same diagnosis was provided was classified as a single injury while breaks in injury reporting indicated return to play and subsequent injuries were reported as recurrent injuries. Kappa scores were used to assess differences in reported injury diagnoses and any observable systematic errors presented. 22

44 3.4 Results Participant Characteristics The 72 male participants had a median (range) age of 21 years (17 to 25), median (range) height 193 cm (175 to 219), median (range) weight of 88.4 kg (73 to 118) and median (range) of 8 (2 to 16) years of organized volleyball participation Individual Injury Report Form- Time-loss Injuries A total of 58 time-loss injuries, 26 overuse injuries and 32 acute injuries in 37 participants, were captured using the IIRF (incidence proportion = 51.4 injuries/100 athletes) in one season. The incidence rate for time-loss injuries was 3.53 per 1000 athlete exposure hours. Knee injuries were the most prevalent (0.91), followed by shoulder (0.67), ankle (0.55), back (0.43) and fingers (0.30) (Table 3.1). The duration of time-loss, an indicator of injury burden, was estimated for each injury region. Lower leg, finger and acute knee injuries presented the greatest time loss (Table 3.1). Knee injuries were reported by 12 participants. Diagnoses included 8 cases of Jumper s Knee, 4 acute ligament or meniscal damage injuries, 2 cases of bursitis and 1 undiagnosed acute injury. Acute knee injury presented a greater burden of time loss (median 27.5 days) than overuse injuries (median 6). 23

45 Table 3.1. Time-loss injury incidence proportion and duration by body region Injury Location Injury Frequency Injury Proportion (%) Median days time-loss (range) Injury Incidence Rate (# injuries/1000 athlete exposure hours) Knee (1-94) 0.91 Overuse (1-94) 0.67 Acute (1-73) 0.24 Shoulder (2-40) 0.67 Ankle (5-22) 0.55 Back (2-9) 0.43 Fingers (1-71) 0.30 Head (4-11) 0.18 Upper Leg (3-5) 0.18 Lower Leg (19-234) 0.12 Hand Toes Hip Total N/A Modified Overuse Injury Questionnaire Substantial Problems SMS response was received for 96.9% of all player weeks and weekly exposure forms were completed for 100% of player weeks. In total, 61 of 72 participants (84.7%) reported having a knee problem at some point while in the study and 48 of 72 (66.7%) reported having sustained a substantial knee problem. Knee problems affected a median of 35.4% of participants each week (range; 19.6% %) while substantial knee problems affected a median of 7.5% of participants (range; 1.7% to 19.0%) (Figure 3.3). Participants reported having knee problems for a median of 7 weeks or 28% of their time while in the study [range; 3.7% (1 week) to 100% (27 weeks)]. Median (range) individual severity scores for those reporting any knee problem was 8 (6 to 74.5) and a substantial problem was 41 (25 to 92). Significant variability in all knee 24

46 problem proportions and substantial knee problem proportions was observed between teams and across weeks (Figures 3.3 & 3.4). Knee Problem Proportions % Sample Size Week # 0 Any Problem Substantial Problem Sample Size Figure 3.3 Prevalence of overuse knee problems for each study week The additional questions on the moiq regarding knee injury type and diagnosis resulted in the following findings summative findings. Continuous injuries (same injury as previous week) were the most frequently reported (83.8%), while injury exacerbations (7.7%) and newly reported injuries (8.5%) were infrequently reported (Table 3.2). Table 3.2. Injury type and medical attention proportions Proportions (95% CI) Continuous Injury 83.8% (80.6 to 86.6) Injury Exacerbations 7.7% (5.8 to 8.7) New Injury 8.5% (6.5 to 11.0) Sought Medical Attention 38.4% (34.5 to 42.4) 25

47 3.4.4 Comparative Injury Rates All 15 time-loss knee injuries captured using the IIRF were also registered within the SMS as a knee problem with a median severity score of 37 and a range of 14 to 100. The criteria for a substantial injury was only achieved for 4 of the 15 time-loss injuries (26.7%), while a response on the moiq (Question 1) indicating reduced or non-participation captured 12 of 15 time-loss injuries (80%). Total duration of time-loss knee injuries captured with the IIRF s was 349 days or weeks while athletes reported 591 total weeks of having a knee problem and 116 total weeks of substantial problems through the moiq. Questionnaire responses provided a knee injury diagnosis for 14 of 15 time-loss injuries and agreement on the specific diagnosis occurred for 10 of 15 time-loss injuries (Table 3.3) resulting in 66.7% agreement and a moderate Kappa score of Athlete direct self-reporting of all other time-loss injuries captured 64 non-knee injuries while the IIRF captured 43 (Table 3.4). 26

48 Table 3.3 Comparison of knee injury diagnosis between reporting mechanisms Time-loss Time-loss Injury Agreement/ SMS Injury Diagnosis Injury # Diagnosis Disagreement 1 Bursitis Jumper s Knee Disagreement 2 Bursitis Meniscus Injury Disagreement 3 Meniscus Injury Meniscus Injury Agreement 4 Unknown Unknown Agreement 5 Meniscus Injury Patellar Femoral Pain Disagreement 6 Ligament Injury Leg cramp Disagreement 7 Ligament Injury Ligament Injury Agreement 8 Jumper s Knee Jumper s Knee Agreement 9 Jumper s Knee Jumper s Knee Agreement 10 Jumper s Knee Jumper s Knee Agreement 11 Jumper s Knee Jumper s Knee Agreement 12 Jumper s Knee Jumper s Knee Agreement 13 Jumper s Knee Jumper s Knee Agreement 14 Jumper s Knee Jumper s Knee Agreement 15 Jumper s Knee No Injury Reported Disagreement 66.7% Agreement Table 3.4 Comparison of time-loss injuries between reporting mechanism Injury Location IIRF Timeloss Injuries loss Injuries OIQ Time- Shoulder Ankle 9 10 Back 7 16 Fingers 5 3 Head 3 4 Upper Leg 3 1 Lower Leg 2 7 Abdomen 0 2 Hand 1 1 Toes 1 1 Hip 1 1 Elbow 0 1 Total

49 % Knee Injury Proportions Any Problem Substantial Problem Sample Size % Sample Size % Week # Sample Size Figure 3.4 Prevalence of overuse knee problems across three teams 28

50 3.5 Discussion The accurate capture of injury frequency and severity is of primary importance in evaluating injury surveillance. It is therefore important to understand the impact of injury definition or injury collection methodology may have on injury capture. This study clearly highlights the inability of a time-loss injury definition to capture overuse injuries. The use of a time-loss injury definition resulted in a total of 15 knee injuries affecting 16.7% of participants. In contrast, the moiq found that knee problems affected 84.7% of participants and that 66.7% experienced substantial problems. As athletes continue to train through injury, there is likely limited capacity for injury surveillance to capture knee injuries without a time-loss definition. Surprisingly however, the moiq also managed to capture more time-loss non-knee injuries (64) than the IIRF (43). Because the injury definition was the same for both capture methods, it provides evidence that the difference may be due to the process of injury capture. The SMS athlete direct reporting may be addressing a potential fear of disclosing all injuries that exists in injury recording methods that utilize a team designate. Athletes may be avoiding participation due to injury and masking the true cause of time-loss to avoid an intervention from team medical staff. Alternatively, the team medical staff may be failing to capture all time-loss injuries for reasons unknown. Another possible explanation may be that athletes are over reporting their time-loss injuries and failing to utilize the same criteria of reporting as team medical staff. The true sources of the reported differences are unknown. 29

51 The measure of incidence rates based on a time-loss injury definition provides a picture of knee injuries occurring less than once every 1000 athlete hours with an injury incidence rate of Alternatively, based on the moiq, a median weekly prevalence of 35.4% for any knee problem, (range; 20.0% to 76.9%) was reported. Additionally, substantial knee problems had weekly median prevalence of 7.5% and a range from 1.7% to 19%. The vast difference in injury risk that can be gleaned from these results is likely the result of the remission and exacerbation of symptoms that is experienced with overuse injuries and not captured with a time-loss definition. Clearly these are two different measures of injury that provide radically different interpretations to the scale of problem. The burden of overuse knee injuries, as captured with the IIRF was minimal, with a median (range) of 6 (1-94) days. In contrast, the moiq found that median (range) of total weeks for reporting a knee problem was 7 (1-27) weeks per study participant. Moreover, the moiq provided a measure of burden that captured the functional limitations beyond time-loss by incorporating the use of a severity score. This severity score showed great fluctuations in knee injury burden week to week and between teams; a value unavailable from the time-loss injury capture. The use of SMS for the collection of injury data proved to be a very effective injury surveillance methodology with a response rate of 96.9%. The majority of non-respondents occurred during the winter vacation period when many athletes were out of the country and therefore not able to reply. One of the challenges with SMS use is the quantity of questions that can be asked 30

52 without causing respondent fatigue. Due to a lag in the receipt of subsequent questions following a question response (varying from a few seconds to a minute based on mobile phone carrier and signal strength), asking too many questions may result in a lack of response later in the survey sequence. This study employed up to nine questions per week and only targeted one specific region for overuse injury capture. This number would have to increase dramatically to capture multiple body regions. Future research should look at the use of smart phone based applications that could allow for quick responses to multiple questions while maintaining the convenience of being completed on a mobile phone. A limitation of athlete direct injury reporting is the inability to capture an accurate diagnosis for reported knee injury problems. It was the intent of the moiq to address this via the selfreporting of a diagnosis only after seeking medical attention. A comparison of diagnosis from the moiq and the diagnosis given for the 15 time-loss injuries does present concern with agreement only being reached on 67% of the injuries, with a moderate kappa score of agreement. Due to the frequent difficulties in diagnosing knee injuries, and the fact that many time-loss injury diagnoses were completed by student athlete therapists, this study likely lacked a stable referent group for the assessment of self-report diagnostic accuracy. Further research and methodological consideration should be given to determine a potential way to minimize this limitation. 31

53 3.6 Conclusion For sport injury epidemiology research to contribute an in depth understanding of the true magnitude and burden produced by overuse injuries, an overuse injury definition should be employed. There is evidence that athlete direct reporting may provide a more sensitive injury capture, at the cost of an accurate injury diagnosis and mechanism of injury. However, one of the greatest strengths of this methodology may be the ability to prospectively monitor change in injury prevalence and severity and make real-time adjustments to introduce interventions that impact injury. This type of information may be crucial in assessing return to play decisions and understanding how athletes are coping or adapting to changes in training loads. This study showed that injury prevalence and severity can have great fluctuations between teams. A timeloss injury definition is only capturing a small fraction of the overuse problems and may not be accounting for those with the greatest injury burden. 3.7 Funding The Sport Injury Prevention Research Centre is funded by the International Olympic Committee. 3.8 Competing Interests Authors have no competing interests or conflicts to report. 32

54 Chapter 4 - Jumper s knee: A prospective evaluation of risk factors in volleyball players using a novel measure of injury Authors: Kerry MacDonald, Luz Palacios-Derflingher, Sarah Kenny, Carolyn Emery, Willem H. Meeuwisse Status: In Preparation Journal/Text: British Journal of Sports Medicine 33

55 4.1 Abstract Jumper s knee: A prospective evaluation of risk factors in volleyball players using a novel measure of injury Objectives: To assess a multitude of potential intrinsic risk factors that may contribute to the onset of jumper s knee in volleyball players. Background: A multitude of risk factors have been reported to increase an athlete s risk of developing jumper s knee. An overuse injury definition has been cited as more sensitive in capturing knee injuries than a more standard time-loss injury definition. To date no risk factors for jumper s knee have been assessed for the prediction of developing knee problems that have been captured by an overuse injury definition. Methods: A total of 60 elite adult male volleyball players were recruited from collegiate and national team programs in Canada. Players completed a series of risk factor assessments at the start of the season including; vertical jump ability (cm), weight bearing ankle dorsiflexion range (degrees), star excursion assessment of dynamic balance (cm), dynamic knee alignment (degrees) and landing mechanics (degrees). Participants were followed prospectively for one season with all time-loss knee injuries recorded by a team therapist. Self-report of knee problems utilized an overuse injury questionnaire via short message service (SMS). Descriptive statistics and logistic regression analyses, controlling for cluster by team, were used to estimate odds ratios. Results: The prevalence of knee problems was 75.0% (95%CI: 62.2 to 84.6) and the incidence proportion for substantial injuries over the study period was 30 injuries/100 players (95% CI: 19.5 to 43.1). The SMS system of tracking overuse injuries was excellent with 98.2% 34

56 completeness. No single risk factor was found to significantly predict the future occurrence of developing a significant knee problem. The odds ratios were close to unity (range: ) with narrow confidence intervals and p>0.05. Conclusion: A more sensitive capture of overuse knee problems did not result in the identification of distinct risk factors for the development of jumper s knee. These findings highlight a lack of available methodology to accurately assess risk factors for overuse injuries. 35

57 4.2 Background Jumper s knee (patellar tendinopathy) is a common knee injury characterized by activity-related pain from the patellar or quadriceps tendon, usually accompanied by palpable tenderness of the tendon and structural changes on ultrasound or MRI imaging. 58 Volleyball has been found to have the highest prevalence of Jumper s Knee when compared with sports such as basketball, athletics, handball, ice hockey, soccer, wrestling, orienteering and cycling. 34 In sports dominated by jumping movement patterns, such as volleyball, the prevalence of jumper s knee has been found to be close to 50% Male volleyball players have been found to have twice the odds of developing Jumper s Knee as females. 60 A risk factor is a variable associated with an increased odds of sport injury and may be intrinsic or extrinsic to the athlete. 2 Meeuwisse et al explained how the presence of multiple risk factors affects an athlete s susceptibility to injury. 7 The identification of risk factors for injury is a key component in the development of an intervention program to reduce injury risk. 2 Many volleyball risk factor evaluations have been completed with an assessment of intrinsic or extrinsic variables at the same time as injury identification. 40 This cross sectional approach allows for a measure of association between the measured variable and injury, but does not allow for an assessment of a temporal relationship between the risk factor and injury. To ideally assess risk factors, they should be measured and evaluated alongside injury registration in a prospective study design. 36

58 Several studies have identified jumping ability (the ability to generate maximal height) as a risk factor across sexes and in both adult and adolescent populations An increased jumping ability arises from an increase in quadriceps contractile forces and therefore an increase in knee tendon loads. Secondly, the greater height that a subject reaches while jumping, the greater the ground reaction force during the landing phase. 43 These two factors result in an increased patellar tendon load. During the landing phase of a jump, the ankle joint moves into dorsiflexion and acts to absorb the impact force. 43 Ankle hypomobility has been theorized to lead to a reduction in force absorption at the ankle joint. 43 Similarly, low ankle dorsiflexion ranges have been found to be associated with an increase in overuse knee injuries in both basketball and volleyball A reduced force absorbing capacity at the ankle joint could result in greater force on the knee joint as that joint would be required to absorb more of the total ground reaction force. 72 An assessment of knee and ankle joint flexion during the landing phase may therefore prove to be a meaningful risk factor assessment. Plisky, et al. 32 found bilateral differences in dynamic balance, assessed using the star excursion balance test, to be predictive of lower extremity injury (OR 3.0[95%CI: 1.1, 7.7]) in male high school basketball athletes aged However, no such studies have assessed balance as a risk factor in a volleyball population, or for Jumper s Knee specifically. 37

59 Typically, a time-loss injury definition is employed to capture any injury resulting in an athlete being unable to fully participate in a subsequent match or training session. 16 While it is the most reliable measure, injuries described by time-loss typically do not capture all possible injuries. 5 An athlete s participation in a game or practice can be easily and objectively identified and verified through additional sources such as game logs. This allows for a comparison of injury data within teams, between teams and across seasons. In contrast, the Oslo Sport Trauma Research Center developed an overuse injury questionnaire (OIQ) for the capture of overuse injuries in a multitude of elite sport settings The overuse injury definition describes a problem to a specific anatomical area that has an effect on participation, training volume, performance and/or pain in the subsequent week. This definition will be referred to as an overuse injury definition. Clarsen et al found this injury definition to capture ten times the injuries when compared to a time-loss injury report for cross-country skiing, floorball, handball, road cycling and volleyball injuries. 16 A substantial problem is defined as any self-reported problem in which the participant reports moderate or severe reductions in training volume or performance or a complete inability to train. The objective of the current cohort study was to examine risk factor measures for the development of jumper s knee as captured with both time-loss and overuse injury definitions. 38

60 4.3 Methods Participants Study participants included 50 adult male volleyball players recruited from three collegiate volleyball teams in Calgary, Alberta, Canada and 10 adult male volleyball players recruited from Volleyball Canada s full time Training Centre. All participants were at least 18 years of age at the time of study enrolment and provided consent to participate. Participants were excluded if they were injured at the time of risk factor testing that restricted their ability to fully participate. Injuries were collected prospectively over the course of one complete season (26 to 30 weeks) Risk Factor Evaluation Risk factors were intentionally measured in sport-specific contexts and analyzed using software and equipment that is readily available to coaches and athletic trainers. These are requirements that would be necessary to promote large scale adoption as screening tools on a population level. The field-based risk factor measurement conducted on all study participants in the 2015 preseason included; vertical jumping ability, ankle dorsiflexion range, dynamic balance, dynamic knee alignment and landing mechanics. Additionally, all athletes completed a pre-participation questionnaire (PPQ) to determine athletes primary position played, history of knee problems, all injuries in the past year and any current injuries or medical problems. 39

61 4.3.3 Vertical Jumping Ability Vertical jumping ability was measured using a previously validated commercially available combined accelerometer gyroscope inertial measurement unit (IMU) (VERT; version 2.0, Mayfonk Inc., Fort Lauderdale, FL, USA), specifically designed for the collection of jump values. 73 Subjects wore the device for all practices and games as part of a larger cohort study. Jump data from the week of training in which risk factor testing occurred was used to determine vertical jumping ability. The mean value of the best 10 jumps from that week was used to determine jumping ability Ankle Dorsiflexion Range The measure of ankle dorsiflexion was performed using a weight-bearing lunge measure also known as a knee to wall test. The test had been shown to have strong intra-rater reliability (ICC ) in a young adult population and all measures were conducted by the same rater using previously published methods. 44 Up to 5 attempts were allowed as subjects attempt to maximize the distance of their foot from the wall. In addition to the foot distance from the wall, the ankle dorsiflexion angle was recorded using a digital inclinometer application Clinometer, Version 4.3 (Plaincode; Stephanskirchen, Germany) on an iphone 6. The recording was made by placing the long edge of the iphone along the vertical and the mid portion of the phone on the anterior border of the tibia, 15cm below the tibial tuberosity. A digital inclinometer was used due to its increased sensitivity over a mechanical inclinometer, as it provided the ability to measure angle to the nearest tenth of a degree. The application was calibrated prior to each 40

62 testing session using an application-based calibration mechanism. In alignment with previous research, the mean angle of ankle dorsiflexion from three trials was utilized for analysis Dynamic Balance The Star Excursion Balance Test (SEBT) is a functional screening tool that was used to assess dynamic balance due to its field applicability and good reliability (ICC range; ) in a healthy adult population The methodology used for this study was the previously published modified 3-point SEBT (anterior, posterior lateral, posterior medial). 32 Participants performed two trials on each leg following 1 practice trial per leg. The maximal distance reached in each direction was used for analysis and normalized by leg length. Limb length was measured from the anterior superior iliac spine to the lateral malleolus. The trial was repeated if the athlete failed to maintain balance on one leg, removed their hands from their hips, touched down with reaching foot, or failed to return their reach foot to the starting position Dynamic Knee Alignment Dynamic knee alignment was conducted using a single leg squat (SLS) test. To preset the squat depth to approximately 45 degree of knee flexion, a string was placed between two tripods in front of the subject. The specific string placement was adjusted based on knee angle flexion depth assessment using a goniometer in several practice trials to assure an approximate 45 degrees of knee flexion when the knee touched the string. Subjects performed 2 sets of 5 squats per leg touching their knee to the string. An iphone 6 recording at 240 frames per second (fps) was used to capture all video. The iphone was positioned 1.5 meters from the 41

63 subject, at a height of 55cm from the floor, and directly in line with an x on the floor that the subjects were instructed to place their heel for all trials. A still image from the lowest moment of the 2nd, 3rd and 4th squat was extracted in set 1, unless the subject had lost balance, in which case it was taken from set 2. All three still images were analyzed in ImageJ (U.S. National Institutes of Health, Bethesda, Maryland, USA) and the mean of three measurements was used for analysis. Mid ankle, mid knee and mid-thigh were used as reference points to determine the knee valgus/varus angle. All data capture for all risk factor measures and all analysis was completed by the same rater; intra-rater reliability was assessed on a sub cohort of twenty images 1 week apart as part of the analysis Landing Mechanics For the assessment of landing mechanics, a novel approach using field available equipment and sport specific movements was developed. While wearing standard volleyball equipment (shoes, braces, etc.) subjects performed a series of 6 maximal counter movement jumps with ten seconds rest between each jump. A counter movement jump was conducted by performing a rapid downward movement from a standing position immediately prior to the execution of a maximal vertical jump. All jumps were performed with subjects standing in front of a volleyball net and being instructed to simulate a sport specific stationary block jump. Specific instructions were given for the subjects to jump maximally and emphasize reaching over the net, with no guidance or instruction on how to land. These instructions were provided to minimize subjects adjusting their standard landing technique. An iphone 6 camera, recording at 240 fps, was used to capture all video recordings. The camera was positioned on a tripod 1.5 meters to the left 42

64 and right of the subject for 3 jumps each and at a height of 28cm from the floor. A still image from the initial ground contact and lowest moment of each jump was extracted. The trial that was subjectively assessed as having the best sagittal alignment with the camera was used for analysis in ImageJ. Ankle measures were taken using the angle of intersection from a line drawn from the lateral condyle of the tibia through the lateral malleolus to a line drawn along the sole of the shoe. Knee measures were taken using the lateral malleolus, mid portion of the knee and mid-thigh as reference points. Intra-rater reliability was conducted on a sample of 20 videos with measurements being completed one month apart by the same rater blinded to previous values, as part of the analysis. Ankle and knee range values were calculated as the total flexion difference from initial contact to lowest moment of the landing task. A summation of ankle and knee range values was performed to provide a total flexion angle during landing Injury Capture Using the time-loss injury definition outlined by Fuller (2006), a designate from the team s medical staff recorded any injury that resulted in a player being unable to fully participate in future training or match play. 3 Team medical staff used an injury report form for the recording of all injuries matching the injury definition. SMS Track (SMS Track Apps, Denmark) was utilized to complete the moiq for Knee Problems. Athletes received a weekly short message service (SMS) message with the OIQ for knee questions. Additional questions were asked to capture if the participant sought medical treatment and what the specific injury diagnosis was. A final question was asked to capture any 43

65 other time-loss injuries and the duration of time-loss, if applicable. Failure to respond within 24 hours resulted in a reminder message being sent. All non-responders received a personal SMS message or within 72 hours of the initial SMS message. All SMS responses were downloaded electronically for analysis from a secured server. Individual responses to the overuse questions that indicated moderate or severe reductions in training volume or performance or a complete inability to train were classified as substantial problems Statistical Analyses Data were analyzed using the statistical software STATA (v12.1, Collage Station, Texas, USA) and SPSS Version 22.0 (SPSS Inc., Chicago, IL, USA) with the significance level set at alpha=0.05. All utilized variables were visually assessed for normality using dotplots and histograms. Intrarater reliability was assessed using interclass correlation coefficients (3-1 random effects model), minimal detectible changes and limits of agreement (LOA). All continuous risk factor measures were assessed visually and descriptively using dot plots and means with 95% Confidence Intervals (CI), stratified on the outcome of developing a substantial overuse knee problem (from SMS reports). All dichotomous and categorical risk factor measures were assessed against the same outcome measure using proportions and crude odds ratios. Due to the limited number of time-loss knee injuries they were excluded as an outcome of interest for all risk factor assessments. Each risk factor measure was assessed individually using logistic regression adjusted for cluster by team for the development of at least one substantial knee problem. 44

66 4.4 Results Participant Characteristics The 60 male participants had a median (range) age of 20 (18 to 25) years, mean height cm (95% CI: to 194.7), mean weight of 88.6 kg (95% CI: 86.1 to 91.1) and a median (range) of 8.0 (2 to 16) years of organized volleyball participation. All 60 participants completed the SEBT, SLS and PPQ, one participant did not complete ankle dorsiflexion testing and nine participants did not complete the jump landing assessment due to absence on day of testing. An additional two participants did not complete the jump landing assessment due to injury at the time of testing. Data analysis only occurred for those who completed all specific risk factor assessments Pre-Participation Questionnaire All 60 participants completed the pre-participation questionnaire. In total, 45/60 [75.0% (95%CI: 62.2 to 84.6)] had a history of knee problems and 32/60 [53.3% (95%CI: 40.4 to 65.8)] reported persistent knee problems at study commencement. Of the subjects that reported a history of knee problems, 31/45 [70.5% (95%CI: 54.9 to 82.4)] had persistent problems with knee pain, 17/45 [38.6% (95%CI: 25.1 to 54.2)] reported their knee problems affecting performance and 7/45 [13.6% (95%CI: 6.1 to 27.9)] reported knee problems affecting participation. 45

67 4.4.3 Injury Data SMS injury reporting resulted in a total response rate of 98.2% (95% CI: 97.2 to 99.0). Response rates varied by player with a range of 81% to 100% and 27 of 60 participants having perfect compliance (100% response rate). Throughout the study period 18/60 participants [30.0% (95% CI: 19.5 to 43.1)] reported a substantial problem, 42/60 participants [70.0% (95% CI: 57.0 to 80.5)] reported any knee problem, and 5 participants [8.3% (95% CI: 0.3 to 18.9)] sustained a time-loss knee injury. Knee pain was reported at baseline for 12/60 participants [20% (95% CI: 11.5 to 32.4)] with 8 of those eventually developing a substantial knee problem. No participant reported a substantial problem at the time of baseline testing. All 18 substantial problems reported during the study period were classified as being consistent with a diagnosis of Jumper s Knee as confirmed via self-report, while 5 cases were further confirmed via time-loss injury report forms from team therapists. Differences were observed by primary playing position on the reporting of both substantial knee injuries and a history of ever sustained a knee injury. Absolute values and proportions with exact confidence intervals are presented in Table 4.1. Middle blockers had the highest proportion of substantial problems (41.2%) and knee problem history while liberos had the lowest (12.5%). 46

68 Table 4.1. Counts and proportions of study participants who sustained a substantial knee problem while in the study and of those who had a previous history of knee injuries, stratified by position Substantial Knee Problems Previous Knee Injury History Position Sample Yes No Proportion (95% CI) Yes No Proportion (95% CI) Size Outside (55.2 to 88.0) (17.2 to 51.9) Attacker Libero (1.4 to 58.4) (18.1 to 81.9) Middle (61.4 to 97.3) (20.2 to 65.9) Blocker Setter (1.5 to 63.2) (29.1 to 93.8) Total Intra-rater Reliability Angle measures assessed in the single leg squat had a mean difference of 2.21 (95% CI: 1.45 to 2.97) degrees, LOA of to 3.53 and MDC of 1.8 degrees. Intra-rater reliability assessment found an ICC (3,3) of 0.96 (95%CI: 0.87 to 0.97). Similarly, agreement of the landing mechanics test was strong with a mean difference of 0.93 (95% CI: 0.56 to 1.30) degrees, a MDC 1.8 degrees and and LOA of -3.8 to 5.7 degrees. Intra-rater reliability was good with an ICC (3,3) of 0.93 (95%CI: 0.87 to 0.99). These values offer support in their use as field-based measures while also providing an understanding of their limitations Descriptive Results Descriptive analyses, including means and 95% confidence intervals (CI) for all risk factor measures are presented in Table 4.2. No risk factor found a significant difference between those who did and did not sustain a substantial knee problem, with all mean values presenting 47

69 overlapping confidence intervals. In total 16 of 45 (35.6%) participants who had a history of knee problems sustained a substantial problem, while 2 of 15 (13.3%) who didn t have a history of knee problems sustained a substantial problem, resulting in a crude odds ratio of 3.6 (95%CI:0.6, 36.0). Table 4.2. Analysis of risk factor measures and substantial knee problems Substantial Problem Sample Size No (n=42) Yes (n=18) BMI (kg/m 2 ) (23.3 to 24.3) 24.1 (22.9 to 25.2) Indoor volleyball experience (years) (7.4 to 8.9) 7.8 (6.3 to 9.3) Maximal Jumping Ability (cm) (76.4 to 81.7) 78.5 (73.6 to 83.5) Ankle Dorsiflexion Total Angle (degrees) (80.4 to 86.0) 83.3 (78.1 to 88.5) Star Excursion Normalized (493.6 to 60 total reach (cm) 515.6) (494.9 to 523.9) SLS total knee angle (degrees) (-10.8 to -4.1) (-13.0 to -4.1) Total knee & ankle flexion (246.4 to 49 during landing (degrees) 261.4) (235.3 to 262.8) Values represent means (Fishers exact 95% CI) Regression Analysis Logistic regression analysis, using risk factor measures as continuous variables and adjusted for cluster by team, found no individual risk factor to significantly predict the outcome of developing a substantial knee problem (Table 4.3). All risk factor variables resulted in an odds ratio that had confidence intervals crossing one and p-values greater than the a priori significance level of

70 Table 4.3 Regression Analysis of risk factors for substantial problems Substantial Problem Risk Factor Sample Size Odds Ratio (95% CI)* P-value Maximal Jumping Ability (cm) (0.91 to 1.07) 0.75 Total Ankle Dorsiflexion (degrees) (0.93 to 1.08) 0.97 Star Excursion Total Normalized Reach 60 Distance (cm) 1.00 (0.99 to 1.02) 0.49 Single Leg Squat Total Knee Angle 60 (degrees) 1.00 (0.96 to 1.04) 0.89 Total Ankle and Knee Flexion during 49 Landing (degrees) 0.99 (0.96 to 1.02) 0.59 *Odds Ratios are separate, unadjusted, accounting for cluster by team. 4.5 Discussion The purpose of this study was to exam if field based risk factor measures could predict which subjects were at a higher risk of developing jumper s knee throughout the course of a single season. The methodology of overuse injury capture employed in this study found that many athletes developed a substantial knee problem without experiencing time-loss. Although this more sensitive capture of overuse injury was employed, no baseline risk factor significantly predicted the outcome of injury. Very little differences were measured between all risk factor measures and those who did and did not sustain a substantial overuse injury. Although the study sample was not large, the point estimates for risk factors were close to unity with a narrow confidence interval. However, the limited sample size in this study 49

71 resulted in an inability to thoroughly assess for the effects of confounding or modification by player position, previous knee injury or any other potential modifying or confounding covariate. A limited sample size also prevented the assessment of the interaction of multiple risk factors. While a larger sample size may yield statistical significance, it would likely yield a difference that is not clinically relevant. The video methodology employed in this study provides a proof of concept that an iphone 6 recording 240 fps could provide high quality video files that were capable of stop-frame analysis. Although the use of 2-D video analysis for measuring dynamic knee alignment in single leg squats and vertical drop jump tasks in the frontal plane has been validated against 3- D motion capture techniques, the assessment of landing mechanics from the sagittal plane has not Furthermore, the landing mechanics assessment failed to capture hip flexion, considered a key component in the absorption of landing impact forces. 37 With the collection of the risk factor variables prior to the injury outcome, it is possible that the measurement error of all risk factors is random in nature and not associated with the outcome of injury, resulting in a bias towards the null. Due to the ebb and flow of overuse injury symptom presentation, a measure of prevalence should be utilized that more accurately captures the frequency of overuse injuries. 14 A measure of prevalence however presents several issues when trying to determine if a specific assessment or variable is a risk factor for overuse injury. Historically, injury risk factor assessment has relied on dichotomizing count of injury as the outcome of interest. Although 50

72 this study utilized substantial knee problems as the incident injury, this dichotomization on a pre-selected severity score does not capture those less severe cases that may present with an issue for a greater duration of time. It is a combination of both knee problem severity and total duration of symptom presentation that accurately assesses the burden of an overuse injuries. Secondly, there is a great challenge in determining the impact of overuse injury presentation at the time of baseline testing. Previous research excludes those with injury at the time of testing due to the confounding influence of injury on the screening outcome measures. 78 However, in a population with high injury prevalence, doing so would exclude a meaningful proportion of a study population. This study found that 20% of the population reported some knee symptoms at the time of baseline testing. It may be best to control knee injury at the time of testing by removing these subjects from the analysis. However, it is unclear if this would also remove those that didn t report symptoms the week of testing but did the week before or the week after testing. How the specific timing of symptom presentation affects the outcome measures of the screening process is unknown. Clearly, there is a need for future research to address the issue of assessing risk factor variables against a constantly changing state of overuse injury from both the perspective of an outcome variable and as a confounding factor within in the screening process. The current approaches for risk factor assessment in time-loss injuries may not be appropriate for overuse injuries. 4.6 Conclusion Overall, this study demonstrated a high prevalence (pre-season) and high incidence (in season) of knee pain consistent with Jumper s Knee. Secondly, the SMS messaging system used to 51

73 collect overuse injury data provided excellent compliance with 98.2% data completeness. However, this study failed to identify any intrinsic risk factor for the development of Jumper s Knee. Although a larger sample size may have produced statistically significant results, it is probable that those differences would have been clinically irrelevant. Furthermore, the sample size used was much larger than most real world contexts of athlete screening, which tend to be team-centric. This study rationalizes the need for future research to address the methodological challenges of risk factor assessment for overuse injuries. The utilization of traditional risk factor assessment methodology that utilizes the incidence of time-loss injuries as the outcome variable is inappropriate for overuse injuries that are more accurately captured with a measure of prevalence. 16 The solution to this problem is likely statistically complex, however it must be addressed and utilized to re-examine what we currently believe to be risk factors for overuse injuries. 4.7 Funding This research was made possible due to funding provided to the Sport Injury Prevention Research Centre by the International Olympic Committee. 4.8 Competing Interests Authors have no competing interests or conflicts to report 52

74 Chapter 5 - Title of Article: Validation of an Inertial Measurement Unit for the Measurement of Jump Count and Height Authors: Kerry MacDonald, Roald Bahr, Jennifer Baltich, Jackie L. Whittaker, Willem H. Meeuwisse Status: In Review Journal/Text: Physical Therapy in Sport 53

75 5.1 Abstract Validation of an Inertial Measurement Unit for the Measurement of Jump Count and Height Objectives: To validate the use of an inertial measurement unit (IMU) for the collection of total jump count and assess the validity of an IMU for the measurement of jump height against 3-D motion analysis. Design: Cross sectional validation study. Setting: 3D motion-capture laboratory and field based settings Participants: Thirteen elite adolescent volleyball players. Independent variables: Participants performed structured drills, played a four set volleyball match and performed twelve counter movement jumps. Main Outcome Measures: Jump counts from structured drills and match play were validated against visual count from recorded video. Jump height during the counter movement jumps was validated against concurrent 3-D motion-capture data. Results: The IMU device captured more total jumps (1032) than visual inspection (977) during match play. During structured practice, device jump count sensitivity was strong (96.8%) while specificity was perfect (100%). The IMU underestimated jump height compared to 3D motioncapture with mean differences for maximal and submaximal jumps of 2.5cm (95%CI: 1.3 to 3.8) and 4.1cm (3.1 to 5.1), respectively. Conclusion: The IMU offers a valid measuring tool for jump count. Although the IMU underestimates maximal and submaximal jump height, our findings demonstrate its practical utility for field-based measurement of jump load. 54

76 Keywords: Training Load, Jump Load, Wearable Technology, Injury Prevention Highlights: The IMU is sensitive and specific enough to capture jumping movements. The IMU can collect accurate jump height in real time. The IMU is capable of collecting jump load in field-based settings. 55

77 5.2 Introduction There is a growing body of literature surrounding the use of microtechnology for the detection of sport specific movements Wearable sensors can include accelerometers, magnetometers and gyroscopes, with several commercially available inertial measurements units (IMU s) being comprised of a combination of sensors. IMU s allow for the measurement of movement in three dimensions in real-time. The quantification of sport movements permits sport staff to improve injury prevention, physical preparation and technical and tactical analysis within their sport. Although there has been an increase in the use and availability of IMU s there is a paucity of research surrounding their validity and reliability in sport specific contexts. Recent research has identified that jump frequency, measured as the number of jumps per hour of training or match play, differs substantially between volleyball players (regardless of similarity of court positions). 83 This finding suggests that exposure hours or minutes are an unreliable indicator of jump load, defined as a measure of jump volume and intensity. It is therefore important that an individual-based, precise measure of jump load be established. A potential alternative indicator of jump load is visual jump count, however this approach is time consuming, fails to provide a measure of height and lacks utility in sports in which several players may jump at the same time. For example Bahr & Bahr report that 12 hours of jump count analysis was required for two hours of volleyball match play. 83 An additional disadvantage of visual inspection is that jump height (an important component of jump load) cannot be accurately quantified visually. 56

78 Due to limitations with athlete exposure hours and visual inspection as a means to quantify jump load it would be beneficial to have a valid method for the quantification of jump load. Jarning et al. attempted to use accelerometers to count volleyball jump load however, their validation study found that the device had poor specificity as it failed to differentiate jumping from other volleyball specific movements, such as diving. 84 Recently, IMU s have been developed to track jump load in real word contexts, however, to date no IMU device has been validated for the assessment of jump load. 79 If such a device could accurately capture both jump frequency and jump height it could provide a field measure of individualized jump load, which would have significant implications for injury prevention and strength and conditioning. The primary objective of this study was to validate a combined accelerometer gyroscope IMU (VERT; version 2.0, Mayfonk Inc., Fort Lauderdale, FL, USA) for total jump count against visual inspection in a structured practice and game-specific context. A second objective was to validate the device for jump height against the gold standard of 3-D motion analysis. 5.3 Methods Participants Study participants included 13 male adolescent volleyball players recruited from an elite club volleyball team in Calgary, Alberta, Canada. All participants provided consent and assent to participant. Potential participants were excluded if they possessed an injury at the time of the study that restricted their ability to fully participate in match play. 57

79 5.3.2 Inertial Measurement Unit Participants completed all activities while wearing a commercially available IMU device (VERT; version 2.0, Mayfonk Inc., Fort Lauderdale, FL, USA) on an elastic waistband. The waistband was positioned in-line line with the subject s naval, placing the IMU on their lower back in the approximate location of their L3 or L4 vertebrae. The VERT contains a 3-axis accelerometer and 3-axis gyroscope that classifies movements as jumps and quantifies vertical displacement of each jump through the use of a proprietary algorithm Jump Count With maximal effort and while wearing the IMU, participants performed a sequence of predetermined structured volleyball movement patterns, similar to those used by Jarning et al. 84 The predetermined movements included six jumping activities (spike attack, stationary block, lateral moving block, jump float serve, jump spin serve and jump set) performed 10 times each and six non-jumping activities (9-meter sprint, 9-meter sprint with dive, 9-meter lateral shuffle, forward dive, lateral dive and standing set) performed five times each. Additionally, four sets of a volleyball match (each set played first to 25 points) were completed with participants wearing the IMU. All activities were captured with a high definition video camera (HDR-CX430V, SONY, Tokyo, Japan) and later reviewed for visual jump count. The video camera was situated at the end of the volleyball court to assure that all movements were captured. A single research coordinator (KM), with 15 years of volleyball coaching experience, completed all visual jump count assessments, blinded from the IMU results, by reviewing the recorded video. A jump was counted for any vertical jump that was subjectively assessed as being greater 58

80 than 15 cm. This allowed for direct comparison with that of the IMU device, which has a preset minimal vertical displacement of cm before it records a vertical movement as a jump Jump Height Jump height validation was conducted at the University of Calgary s Sport Injury Prevention Research Centre and Human Performance Lab by comparing the IMU device to simultaneously collected kinematic (3-D motion capture) data. A single rater (JB), with extensive experience in biomechanical assessment and 3-D motion analysis, conducted all 3-D measures, blinded to the recording of the IMU. Specifically, participants performed four different countermovement jump techniques with three repetitions each. These included (in order); a maximal jump with 1- hand reach (1-max) to a Vertec (Sports Imports; Columbus, Ohio, USA), maximal jump with 2- hand reach to a Vertec (2-max), submaximal jump with 1-hand reach to Vertec (1-submax) and submaximal jump with 2-hand reach to a Vertec (2-submax). For maximal jumps,participants were instructed to jump as high as they could and reach to touch the Vertec. Submaximal jumps were conducted by presetting the lowest rung on the Vertec to 15.24cm (six inches) below the participant s maximal Vertec jump height and asking participants to only jump high enough to touch the lowest rung. The IMU device provided vertical jump height (to the nearest 0.01 cm) data in real time to an Apple i-pad via Bluetooth 4.0 technology. The specific calculation of the IMU s vertical displacement is completed via a proprietary algorithm analyzing the output of the device s accelerometer and gyroscope data. Kinematic data was collected using four retro-reflective markers placed on the pelvis of each participant to measure vertical displacement of the pelvis 59

81 with an eight-camera, 240 Hertz motion capture system (Motion Analysis, CA, USA). Retroreflective markers were placed bilaterally on the anterior superior and posterior superior iliac spines. Marker trajectory data from the four countermovement jumps were tracked using Cortex software (Version 5.5, Motion Analysis, CA, USA) then filtered with a low pass fourth order Butterworth filter using a cutoff frequency of 12 Hertz. Jump height was identified as the peak vertical displacement of the pelvis (the average vertical location of the four pelvis markers) minus the neutral standing pelvis height Statistical Analysis Data were analyzed using the statistical software STATA (v12.1, Collage Station, Texas, USA) and SPSS Version 22.0 (SPSS Inc, Chicago, IL, USA) with the significance level set at alpha=0.05. For jump count the IMU was assessed against visual observation from recorded video for both structured practice and match play. Limits of agreement (LOA) were calculated as the mean difference between assessment methods ±2 standard deviations, while method error (ME) was calculated as the standard deviation of the mean difference divided by square root of 2, providing a measure of the amount of variation in the difference scores between two measurement techniques. Method error was utilized due to its resistance to being under or over inflated by data variability, a common limitation of intraclass correlation coefficients. 85 The coefficient of variation of the method error was completed to provide the percentage of variation between measurement techniques. 60

82 For jump height, all jumps from the four jumping tasks (1-max, 2-max, 1-submax and 2-submax) were calculated and utilized for all analyses comparing the two measurement techniques. Maximal and submaximal values were then analyzed separately. Mean differences (95%CI), LOA and ME were calculated and used to assess jump height values from the VERT versus the reference standard of 3D motion analysis. For the structured practice, sensitivity, specificity, positive predictive value and negative predictive values were calculated based on the correct or incorrect classification of jumping and non-jumping activities with the VERT, using the actual jumps (from structured practice) or video observation as the reference standard. A single set of the match was visually counted twice, one week apart, to determine intra-rater reliability. 5.4 Results Participant Characteristics Participants had a median age of 16.0 years (range; 15, 17), median height cm (range; 178.4, 199.0) and median mass of 75.5 kg (range; 63.4, 94.4). All 13 male participants completed the jump height data collection, while only 12 (two teams of six players) completed the volleyball match and controlled practice data collection Jump Count Although participants were instructed to perform exactly 60 jumping activities, upon video review it was discovered that some performed additional jumps. These additional jumps were utilized in the analysis. 61

83 In the structured practice setting the IMU device correctly identified 96.8% (705/728) of jumps and 100% (360/360) of non-jumping activities. Further, the device did not classify any nonjumping activities as jumps, however 23 jumps were not identified. This resulted in a specificity and positive predictive value of 1.0, a sensitivity of 0.97 and a negative predictive value of The mean difference between the visual count and the IMU was -2.0 (95%CI -4.2, 0.2) jumps with LOA of -9.0, 5.0 jumps. Stationary block jumps accounted for 14 of the 23 (60.9%) missed jumps (Table 5.1). During match play the IMU device recorded a total of 1032 jumps although only 977 jumps were identified by visual inspection. The mean difference was 5 (95%CI 0.7, 8.5) jumps with LOA of -8 to 17 jumps. There was strong agreement between the two methods within the structured practice setting with a mean difference of -0.2 jumps (95% CI -0.8, 0.4), ME (CV ME ) of 0.7 (0.1%) jumps and LOA of -2.3 to 1.8 jumps. 62

84 Table 5.1: A comparison of jump counts between the IMU and visual inspection during stuctured practice by skill. Activity Visual IMU Difference Jumping activities Attack Block - stationary Block - lateral Jump float Jump spike Jump set Total jumps Non-jumping activities 9-m sprint Sprint + dive Forward dive Lateral dive Standing set Total non-jumps Jump Height The IMU underestimated vertical displacement when compared against 3-D motion analysis, especially for submaximal jumps (Figure 5.1). The mean differences for maximal and submaximal jumps were 2.5 cm (95% CI -4.7, 9.7) and 4.1 cm (95% CI -2.9, 11.1), respectively. The ME (CV ME ) was 2.6 cm (4.4%) for maximal jumps and 2.5 cm (4.8%) for submaximal jumps. LOA were -6.1 to 9.8 cm for maximal jumps and -3.0 to 11.2 cm for submaximal jumps. 63

85 Figure 5.1: IMU jump height vs. 3D jump height by jump type 5.5 Discussion This is the first study to assess the validity of a novel IMU device, which combines an accelerometer with a gyroscope, for the collection of jump count and jump height. During structured practice, the IMU performed perfectly capturing only jumping activities, which has been a limitation with previous accelerometer only devices. 84 Further, the device demonstrated a sensitivity of 97% suggesting it is sufficiently accurate for use as a field-based measure of jump frequency. 64

86 With respect to jump height the IMU systematically underestimated vertical displacement when compared to the reference standard of 3-D motion analysis. The magnitude of error, approximately 4.2% for maximal jumps and 5.5% for submaximal jumps, may represent a concern for some applications that require precise measures of jump height, such as jump testing to assess the effect of a conditioning program. Random error was less pronounced and estimated at approximately 3.7% for maximal and 3.4% for submaximal jumps. One of the study limitations is the likely source of measurement error that exists in the visual review from the video of match play. As previously mentioned, the IMU has a preset minimal vertical displacement of approximately 15 cm (6 inches) before it considers a vertical movement to be classified as a jump. This threshold is difficult to replicate with visual review and represents a source of measurement error. It is likely that small jumps, close to the preset threshold of the IMU, are not captured in video review, resulting in poorer sensitivity than the IMU method. The lower sensitivity of visual review may explain why visual review underestimated jump frequency compared to IMU values during the match play analysis. This strengthens the argument that the VERT IMU is the current referent criterion for the classification of jump count in volleyball match play or unstructured practice settings. Considering the jump count accuracy and small magnitude of error for jump height, the VERT IMU device appears to be an acceptable field-based tool that can be used to monitor jump load in real world settings. Further, the structured practice test protocol provided a strong methodological assessment of the device s ability to differentiate specific movements that can 65

87 easily be confirmed from video. A final advantage of this device is that it can be worn by all players on a team enabling real-time monitoring of multiple athletes by a single rater. These findings suggest that the VERT IMU could be used in future research aimed at prospectively understanding the relationship between jump load and overuse injuries such as jumper s knee. The IMU has the potential of providing a better understanding of what jump loads precede the initial onset of injury or are correlated with symptomatic flares in the condition. A greater understanding of the load injury relationship would contribute to the development of both primary and secondary injury prevention strategies. Further from a clinical perspective, rehabilitation professional and strength and conditioning coaches could use the VERT IMU to accurately and efficiently quantify and monitor jump load in graduated return to play protocols, a possibility that to date has not existed. Finally, the VERT IMU could prove to be a powerful device in the quantification of jump demands in both training and competition settings. Providing support staff with a strong understanding of the physical demands of the sport may improve athlete preparation methodologies. Also, an understanding of how the athlete s jump performance changes over time could allow for the early identification of fatigue and the current capacity that the athlete can withstand prior to fatiguing. 5.6 Conclusion In conclusion, this is the first study to demonstrate that an IMU device is capable of accurately measuring jump load in a practical setting. The resulting information collected by this device 66

88 will allow for novel approaches in the prevention of overuse injuries and the maximization of performance. Using an IMU that can accurately capture jump data provides a tremendous opportunity to further the scientific understanding of the sport specific movements in a multitude of jumping dominated sports. 5.7 Conflict of Interest The authors have no competing interests or conflicts to report. 5.8 Ethical Approval Ethical approval was provided by the Conjoint Health Research Ethics Board. Consent and assent to participate was collected from all participants. 67

89 Chapter 6 - The interactive effect of training load and injuries in volleyball Authors: Kerry MacDonald, Tracy Blake, Luz Palacios-Derflingher, Carolyn Emery, Willem H. Meeuwisse MD Status: To be submitted Journal: British Journal of Sports Medicine 68

90 6.1 Abstract Objectives: The objective of this study is to examine the feasibility of assessing the individual measures of training load as risk factors for the development of jumper s knee. Background: Jumper s knee is a highly prevalent condition among volleyball players and encompassing of tendinopathy of the patellar or quadriceps tendon. Until recently it was not possible to capture an individual measure of jump load in the field. An understanding of the jump loads that precede the onset of jumper s knee could lead to more effective primary prevention initiatives. Methods: A cohort of 65 elite level volleyball players from five teams were prospectively followed over one season (i.e., 32-weeks). Study participants wore an inertial measure unit for all on-court session to capture measures of jump load (jump count, height jumped) in real time. Team designates collected all time-loss injuries, while short message service was used for weekly athlete completion of a modified overuse injury questionnaire. Results: A total of 12 participants sustained a time-loss knee injury (incidence proportion = 13.8 injuries/100 athletes) and 28 participants reported having a substantial overuse knee problem (incidence proportion = 38.5 injuries/100 athletes). No measure of load was found to be predictive of injury with logistic regression yielding odds ratios close to 1 and p-values>0.05. Conclusion: Despite using the most accurate and sensitive field based measures of jump load and overuse injury capture available, no association between load was observed. The lack of - observed association could be due to methodologic limitations associated with the overuse injury measurement methodology and operationalization of load. 69

91 6.2 Background Jumper s knee is a medical diagnosis of an overuse injury specifically effecting the patellar or quadriceps tendon. The condition is characterized by palpation tenderness of either tendon and usually accompanied by visual changes on ultrasound or magnetic resonance imaging (MRI). 58 Jumper s knee is inclusive of such diagnoses as patellar or quadriceps tendinopathy and the prevalence is highest in jumping dominated sports such as volleyball and basketball. Cook et al. developed a continuum model of tendinopathy that suggests that there are three stages: reactive, disrepair and degenerative. 13 Overload of a healthy tendon can cause the tendon to become reactive. A repeatedly failed healing process can then lead to degenerative tendinopathy This theory explains how chronic repetitive damage to tendons could accumulate over time resulting in a diagnosis of jumper s knee. 87 Volleyball has the highest prevalence of jumper s knee with reported prevalence as high as 50% These reported values are likely underestimated due to the injury definition utilized in most injury surveillance studies. 16 The majority of injury surveillance research to date utilizes a time-loss definition of injury, which captures any injury resulting in an athlete being unable to complete the current session and/or fully participate in a subsequent match or training session. 3 An overuse injury is believed to be caused by repeated micro-traumas rather than a single event. Further, overuse injury symptoms tend to present gradually with withdrawal from training or competition only occurring after repeatedly failed attempts at self-management. This etiology is a significant challenge for researchers to accurately and comprehensively capture and report all overuse injuries. The Oslo Sport Trauma Research Centre developed an 70

92 overuse injury questionnaire (OIQ) specifically design to capture the prevalence and severity of overuse injuries in a sport setting. 16 The OIQ asks questions regarding the impact that a problem to a specific anatomical area has on participation, training volume, performance and/or pain in the subsequent week. Clarsen et al found this injury definition to capture ten times the injuries when compared to a time-loss injury report for cross-country skiing, floorball, handball, road cycling and volleyball injuries. 16 In a 4 year prospective study of jumper s knee in adolescent volleyball players, Visnes et al found high training and match load to be predictive of the development of jumper s knee. 35 This study classified training and match load based on a measure of exposure hours; subsequent research uncovered dramatic inter-individual differences in jump frequency within an exposed hour. 83 These findings warrant the need for further research on the assessment of individual load for the prevention and treatment of tendon specific injuries. 86 Recently, an inertial measurement unit (IMU) device was validated to collect jump count that can differentiate jumping from other sport specific movements in volleyball, such as diving, a failure of a previous device This IMU device provides an unbiased, individualized, direct measure for jump load that is associated with the outcome of interest, jumper s knee. Therefore, a measure of jump load is now available to be assessed as a risk factor for jumper s knee. Training load is a measure of both the duration and intensity of training. A specific measure of load that is of interest for an injury such as jumper s knee may be jump count or cumulative 71

93 height jumped. Recent research on assessing load and injury has found that absolute load may not be the primary concern but rather it may be dramatic changes in load that increase injury risk Therefore, the prevention of jumper s knee may not be as simple as avoiding high absolute jump loads. The key factor may be a gradual development of tendon capacity to withstand the load demands of the sport, and then regulation of the loads to not surpass the tendon s capacity. As a result of these recent findings some have proposed that the term overuse injury be replaced with term training load error injury. 89 The objective of this study was to assess the individual measures of load as a risk factor for the development of jumper s knee, as registered with both an overuse and time-loss injury definition, in an elite male volleyball cohort. It was hypothesized that acute (1-week) increases in jump load above the chronic load levels (4-weeks) would result in an increase in the incidence of self-reported jumper s knee severity. 6.3 Methods This study was a cohort design with repeated measures of training loads and injuries captured prospectively over the duration of one season in a cohort of five elite male volleyball teams Participants A total of 72 male elite volleyball players were successfully recruited from an inclusive sample of five elite teams in two geographic locations. These teams included three collegiate teams, 72

94 one national team training group and one local youth club volleyball team (18 year old or younger). All athletes provided consent to participate and assent when under 18 years of age upon study entry. Additionally, all participants completed a pre-participation questionnaire (PPQ) at study commencement for the collection of injury history, participation history, position played, and basic anthropometric values. Inclusion in the study and collection of load and injury data began on the first week of the respective teams season and continued until the season was completed, or the athlete withdrew from the program. All censored subjects provided verbal agreement for their data to remain in the study. Subjects who indicated their primary position as libero were excluded from the analysis. This was completed due to the specific demands on the position. As a defensive specialist, a libero is not permitted to attack the ball and must only play in the backcourt, resulting in a minimal amount of jumping activity Measures of Injury Time-loss Injuries Time-loss injuries were collected using an individual injury report form (IIRF) by an athletic therapist or an athletic therapy student assigned to each team. The form defined an injury as any medical complaint that resulted in the individual being unable to complete the current session or fully participate in a subsequent session. 3 All IIRF forms were later transcribed to an online database for further analyses. First reported time-loss injury was identified and further stratified as being an overuse or acute time-loss injury based on mechanism of injury and injury diagnosis. Only time-loss injuries that were classified as being overuse in origin, and consistent with a diagnosis of jumper s knee, were utilized for analysis. 73

95 Overuse Injuries Overuse injuries were also collected using a modified version of the Oslo Sport Trauma s Research Centres Overuse Injury Questionnaire (moiq). 90 The specific modifications included the addition of an additional question of injury diagnosis and any other time-loss injuries. The moiq was distributed weekly via the use of a short message system (SMS) company SMS Track (SMS Track Apps, Denmark). Study subjects received the moiq every Sunday with reminder messages being sent 4, 24 and 48 hours after a failed response. Individualized responses to the moiq allowed for a calculation of weekly knee problem prevalence and severity. Substantial knee problems were identified as those responses that indicated a moderate or severe reduction in training volume or performance as a result of a knee problem. Substantial problems were further identified as being a first time substantial problem or a subsequent substantial problem. Self-reported diagnosis and/or an IIRF diagnosis was used to determine if all reported substantial problems were consistent with a diagnosis of jumper s knee or not. Only those first-time substantial knee problems, with a diagnosis consistent with that of jumper s knee, was included in the analyses Measures of Training Load Weekly Exposure Weekly athlete exposure minutes were collected by a team designate using a standardized weekly exposure sheet (WES). The WES collected attendance, session duration and all IIRF qualified injuries for each team member for every session each week. 74

96 Inertial measurement Unit A previously validated 3-axis accelerometer and 3-axis gyroscope inertial measurement unit (IMU) (VERT; version 2.0, Mayfonk Inc., Fort Lauderdale, FL, USA), was utilized for collection of daily jump count and daily cumulative jump. 73 Subjects were requested to wear the IMU during all training and competition events throughout the 2015/2016 season. Data from the devices was transmitted to an ipad device in real time. Data from the ipad was subsequently uploaded to a secured online server and downloaded at a later time for analysis Estimations of Training Load Weekly total hours of exposure, total jump count and total height jumped (cumulative jump height) were utilized as 3 different measures of external load. Acute:chronic workload ratios (ACWR) were calculated by dividing the 1-week load (acute) by the 4-week rolling average (chronic) load. 81 A measure of ACWR was only calculated for weeks in which acute data was available for all four chronic weeks. Any ACWR calculation missing a week of data was removed from the analysis. Missing data was identified based on WES attendance in combination with time-stamped IMU jump data. Subjects not participating in a session, due to an injury or for any other reason, were recorded as acquiring 0 load and were not considered missing. ACWR s were assessed for weeks of injury reporting and for the week immediately prior to the injury being reported to address the possibility of delayed symptom reporting. 75

97 Based on coach opinions, a jump count average of 100 jumps per session in a week was selected as a cut point for a high a jump load week and assessed as an exposure of interest for the outcome of both time-loss injuries and overuse knee problems Statistical Analysis Data were analyzed using the statistical software STATA (v12.1, Collage Station, Texas, USA) with the significance level of alpha=0.05. Normality of all variables was assessed using histograms and dotplots and appropriate measures of central tendency utilized. Athlete weeks in which more than 25% of jump data was missing were removed. Jump data for athlete weeks in which 25% or less was missing was imputed. Jump frequency for all sessions that week with completed jump data was calculated by dividing the total jump count by the total duration of all sessions. The resulting frequency was then multiplied by the duration of the session in which jump data was unavailable, providing a jump count for missing sessions. Finally, the resulting jump count variable was multiplied by the average jump height for that week for a final calculation of cumulative jump height. Incidence rates (# injuries per 1000 athlete exposure hours to time of injury) and incidence proportions (# injured athletes per 100 athletes) were calculated for both first reported timeloss knee injuries and first reported overuse knee problems, as reported from the IIRF and moiq. The utilization of only the first injury was chosen to address the lack of consensus on the appropriate way to identify discrete, unique overuse injuries. ACWR measures of exposure 76

98 hours, jump count and cumulative jump height were independently assessed, due to sample size limitations, using logistic regression clustered by team. The first reported substantial overuse knee problem was assessed as the outcome of interest. All other reported substantial problems were not assessed due to difficulty in determining independent injuries and ways to address the confounding influence of the previous substantial problem. Individual measures of knee injury severity from the moiq and all three exposure values were plotted over time. This allowed for a visual assessment of impact that changes in load had on injury severity for each subject. 6.4 Results Data Cleaning & Imputation Data completeness varied by program with National team and Youth collecting jump data for 90.3% (95% CI: 87.1 to 93.5) and 89.5% (95% CI: 86.6 to 92.5) of all sessions respectively. The collegiate teams collected a lower proportion of sessions with 78.8% (95% CI: 75.5 to 82.1), 68.3% (95% CI: 65.2 to 71.3) and 66.1% (95% CI: 63.0 to 69.1) of session data collected among the three teams (Table 6.1). The data imputation technique employed resulted in the imputation of 27,085 of the 393,242 (6.9%) jumps used in the final analyses. Time-loss knee injuries were excluded as an outcome for evaluation with ACWR due to the limited number of injuries available for analysis with a corresponding ACWR value. A sensitivity analyses of the impact of imputed data was not possible due to the infrequency of perfectly 77

99 complete data sets over a 4-week time period. Without imputed data ACWR jump load values were only available for three reported substantial knee problems and no time-loss knee injuries. Table 6.1 Summary of missing jump data from each cohort. Total Player Sessions Missing Player Sessions Number of Players Follow-up Duration (weeks) Proportion of Missing Data (95% CI) (%) College # (32.76%) (30.9 to 37.0) College # (33.12%) (28.7 to 34.8) College # (17.76%) (17.9 to 24.5) National (9.23%) (6.5 to 12.9) Youth (10.18%) (7.5 to 13.4) Participant Characteristics In total 72 participants were involved in the study. Upon removal of those whose primary position was libero, 65 participants remained for analysis [ median (range) age of 20 (16 to 25) years, mean height cm (95% CI: to 195.5), mean weight of 87.9 kg (95% CI: 85.6 to 90.1) and a median (range) of 8.0 (2 to 16) years of organised volleyball participation as collected from the PPQ]. The study duration was 32 weeks with teams start and end points differing due to variance in respective seasonal schedules (Table 6.1) Injuries Captured A total of 15 unique time-loss knee injuries were captured from the IIRF affecting 12 study participants (incidence proportion = 16.7 injuries/100 athletes), and 12 of the 15 time-loss 78

100 injuries (80%) were deemed to be overuse knee injuries affecting nine study participants (incidence proportion = 12.5 injuries/100 athletes). Of the nine first time overuse time-loss knee injuries, ACWR jump data was only available for three injuries. The moiq was successfully completed for 1466 of 1507 (97.3%) player weeks with missing weeks removed from the analysis. The moiq identified 28 unique substantial overuse knee problems affecting 25 participants (incidence proportion = 38.5 injuries/100 athletes). Injury incidence rates for first time substantial knee problems were higher than for first time time-loss injuries 13.6 (95% CI: 9.1 to 20.6) compared to 4.8 (2.5 to 9.2) injuries per 1000 exposure hours (Table 6.2). Table 6.2 Injury Incidence Rate (IIR) for first substantial knee problem and first overuse timeloss knee injury First Substantial Knee Problem First Time-loss Knee Injury Cohort Injury Count # injuries/1000 hours (95% CI) Injury Count # injuries/1000 hours (95% CI) College # (3.9 to 27.8) (0.3 to 16.5) College # (13.0 to 57.4) (5.9 to 41.8) College # (6.4 to 37.0) (1.2 to 20.6) National (0.7 to 34.3) (0.7 to 34.5) Youth (6.4 to 36.7) (0.4 to 18.8) Overall (9.1 to 20.6) (2.5 to 9.2) When assessing the ACWR for the week in which the substantial knee problem was first reported, or looking at the week prior to the injury being reported, no significant association was identified for any of the three load measures. (Tables 6.3 & 6.4). 79

101 Table 6.3 Logistic Regression Analysis of ACRW measures from week of first substantial knee problems Injury Count Odds Ratio (95% CI)* p-value ACWR Jump Count (0.85 to 1.02) 0.14 ACWR Jump Height (0.84 to 1.24) 0.85 ACWR Exposure Hours (0.90 to 2.11) 0.14 *Odds Ratios are separate, unadjusted, accounting for cluster by team. Table 6.4 Regression Analysis of ACWR measures from week prior to first substantial knee problems Injury Count Odds Ratio (95% CI)* p-value ACWR Jump Count (0.29 to 1.30) 0.20 ACWR Jump Height (0.31 to 1.53) 0.36 ACWR Exposure Hours (0.93 to 2.40) 0.10 *Odds Ratios are separate, unadjusted, accounting for cluster by team. A jump count per session average of 100 was selected as a high jump count for each athlete each week. In total 17.1% (95% CI: 15.3 to 19.1) of all athlete weeks were above the 100 jump threshold. Odds ratio estimations using logistic regression and clustered by team for a 100 jump exposure week were not significant for outcomes of time-loss or substantial overuse problems in the week of the injury or the week prior to the injury capture (Table 6.5). Table 6.5 Regression Analysis for a weekly jump count average over 100 Injury Count Injuries with jump count>100 Odds Ratio (95% CI)* p-value 80

102 Week of Substantial (0.43 to 1.63) 0.59 problem Week before (0.34 to 2.06) 0.70 Substantial Problem Week of time-loss (0.09 to 4.14) 0.60 Injury Week before time-loss (0.14 to 4.60) 0.81 injury *Odds Ratios are separate, unadjusted, accounting for cluster by team. A graphical assessment of the individual measures of knee injury severity and all three exposure values, plotted over time, showed no distinctive pattern across all participants. It was unclear if an increase or decrease in any load measure resulted in an increase or decrease in injury severity, examples are provided in Figure 6.1 &

103 Injury Severity Cummulative Jump Height vs. Injury Severity Severity Jump Height Weeks Jump Height Injury Severity Jump Count vs. Injury Severity Severity Jump Count Weeks Jump Count Injury Severity Exposure Hours vs. Injury Severity Severity Exposure Hours Weeks Exposure Hours Figure Jump Count, Jump Height and Exposure Hours vs. Knee Injury Severity for one participant. 82

104 Jump Count & Injury Severity Jump Count Week Injury Severity Jump Count Week Injury Severity Jump Count Week Injury Severity Jump Count Week Injury Severity Jump Count Week Injury Severity Jump Count Week Jump Count Injury Severity Injury Severity Figure 6.2 Jump Count & Injury Severity for 6 random subjects in one cohort. 83

105 6.5 Discussion This is the first study to assess a direct measure of external load (jump count and cumulative jump height) against overuse knee injuries. Furthermore, the studied employed an injury definition that has been shown to be very sensitive to overuse injury capture. 16 Although a measure of load is assumed to be closely linked with an overuse knee problem, such as jumper s knee, the findings from this study are equivocal. The study did show that a proxy measure of load, such as exposure hours, did not always approximate measures of external load, jump count or cumulative jump height. Graphical assessment of the multiple load values and injury severity showed no distinctive pattern across all participants. It was unclear if an increase or decrease in any load measure resulted in an increase or decrease in injury severity. (Figure 6.1 & 6.2). The low injury incidence with the National cohort, the most elite cohort and oldest cohort in this study, may be indicative of a survivor bias. The National cohort is void of those subjects who have been eliminated due to injury at earlier stages of their development and are subsequently at a lower risk of developing an injury. A limitation of this study was the completeness of data available. Due to jump data being unavailable several reported knee injuries could not be assessed for the interaction with ACWR measures. The loss of these injuries in combination with a limited sample size resulted in the inability to run a multivariable analysis and assess for confounding or modification by other covariates. It should also be noted that a potential Hawthorne effect could have influenced the 84

106 outcome of the study. As coaches within the study were assisting in the collection of jump loads they were aware of the load values. Because these values were being monitored for the purpose of injury prevention, coaches may have then altered their training loads in attempt to reduce injury rates. The impact of this effect would have been a bias towards the null. The methodology of calculating ACWR requires a minimum of 4 weeks of data, resulting in an inability to assess the impact of load on any injury that occurs within the first 3 weeks of the study. Due to the fact that study commencement began at the beginning of each team s respective seasons, it possible that this time period represents the greatest increase in training load. The limitations of this approach resulted in the removal of 6 substantial knee problems (21.4%) from the analysis. It is plausible that a failure to assess the impact of load for those injuries occurring at in the beginning of the season, when changes in load may be the greatest, resulted in a bias towards the null. Additionally, a week in which an injury occurs, that results in a reduction of training load, will result in a decreased ACWR. The magnitude of this reduction will depend on the day(s) of the week in which the injury impacts the load, with injuries early in the 1-week time frame having more significant reductions in acute load. For this reason, it is best to develop an ACWR value with a rolling weekly time-set based on the specific day of injury reporting. To assess this ACWR value against an overuse measure of injury would require a daily capture of injury prevalence and severity. The capture of overuse injuries has been shown to be most appropriate with a measure of injury prevalence. The challenge lies in the assessment of a continuous risk factor, such as jump 85

107 load, against an ever changing value of injury prevalence and severity. This study attempted to create a measure of incidence from the moiq by utilizing the classification of first substantial problems as the incident of injury. It is likely that this simplification of injury to a dichotomous injury variable failed to provide a sensitive enough outcome measure to accurately assess the impact of load. The true etiologically relevant time period in which the overuse condition began may be weeks prior to the reporting of a substantial problem and only following a failed attempt at self-management. A different analysis approach that can assess the complex interaction of the load and injury severity on an individual level and over time is needed to more thoroughly understand the association between the two variables. To conclude, this study highlights that the assessment of load and overuse injuries is complex and that several methodological challenges remain. A sensitive and accurate measure of injury with an individual and etiologically specific measure of load does not solve this issue, but rather increases the complexity of the assessment. Although this study may be the most complex assessment of the interaction of load and jumper s knee to date, future research may require an even more sensitive measure of daily changes in injury severity to identify the etiologically relevant loading patterns that occur prior to the commencement of injury symptom presentation. 6.6 Funding This research was made possible due to funding provided to the Sport Injury Prevention Research Centre by the International Olympic Committee. 86

108 6.7 Competing Interests Authors have no competing interests or conflicts to report. 87

109 Chapter 7 - Conclusions and Future Research Directions Summary of findings The following is an outline of the key findings highlight in the preceding research chapters: Chapter 2 - A Periodic Health Exam for the Volleyball Athlete This chapter explored the evidence to date for the screening of a volleyball athlete. Based on current evidence, suggested risk factors, including specific assessment techniques, were provided. With continued research into the area of athlete screening and the specific assessment of risk factors for volleyball injuries, consistent updates and revision will be warranted Chapter 3 - Jumper s knee and elite volleyball the effect of injury definition and surveillance methodology Chapter three assessed the frequency and severity of jumper s knee with an elite male volleyball cohort using two different injury definitions. This study showed that an overuse definition of injury that provides a measure of injury prevalence and severity, based on functional limitations, is more sensitive than a time-loss injury definition. As a result of these findings, future research on overuse injuries should look to employ an overuse definition across sports with potentially high prevalence. 88

110 7.1.3 Chapter 4 - A prospective evaluation of risk factors using a novel measure of injury In the fourth chapter of the thesis, several field based risk factors were evaluated with the use of an overuse injury definition as the primary outcome of interest. Although no significant risk factors were revealed, the key finding from the chapter was the methodological challenges of assessing risk factors for an overuse condition. Without possessing a simplistic binary injury value that prevails in acute injury incidence collection, an overuse injury measure of prevalence creates a statistical dilemma. This study selected a specific threshold for the dichotomization of injury in order to utilize methods for time-loss injury collection. For several reasons, this approach may be inappropriate and future research is warranted to further explore this topic Chapter 5 - Validation of an inertial measurement unit for the collection of jump frequency and magnitude Overuse injury mechanism is believed to be a repeated overload of specific tissue beyond its capacity, followed by an inadequate healing process. Therefore, the assessment of jumper s knee requires an accurate and specific measure of knee load to assess the causal mechanism of the injury. Several inertial measurement units are commercially available but none was validated for the specific capture of jump load. This chapter outlined the validation process and confirmed that an IMU can differentiate jumping from non-jumping activities in a sensitive manner, while providing a reasonably accurate measure of jump height for each jump recorded. This study established the first validated inertial measurement unit capable of capturing jump load in a field based setting. 89

111 7.1.5 Chapter 6 : The interactive effect of jump load and jumper s knee The final research chapter of the thesis attempted to evaluate individual measures of load as risk factors for the onset of overuse knee injuries in an elite male volleyball cohort. The findings of this chapter are equivocal and uncovered further methodological challenges. Although the collection of injuries using an overuse injury definition is more appropriate than a time-loss definition, it presents further challenges in determining timing of injury onset and, therefore, the etiologically relevant time period for the assessment of load. Further research is required to determine the methodological approach required to assess training load as a risk factor for overuse injuries. 7.2 Future Research Directions As identified throughout the preceding chapters, there is a substantial methodological limitation that exist and must be addressed to begin to understand overuse injuries and their corresponding risk factors. It is the intent of the following to identify potential strategies to tackle some of these limitations Overuse Injury Classification One of the primary issues discussed in this thesis revolved around the definition that is used for the capture of overuse injuries. Although the current overuse definition provides a more accurate measure of the burden of injury in a given population, further methodological processes are required to use this measure in the assessment of risk factors for overuse injury. 90

112 One of the methodological shortfalls that was identified is the inability to assess a continuous risk factor variable (jump load) against a fluctuating level of injury severity. It is possible that a form of mixed modeling that accounts for repeated measures of a continuous outcome measure, and provides the ability to assess other covariates, could be able to address this issue and warrants further analysis. A secondary issue with the overuse injury definition arose from the limitation of a weekly measure of injury to pinpoint initial symptom onset. If a daily measure of injury severity was feasible, it would provide the specific day of initial injury symptom onset and then allow one to conclude the training load values that immediately preceded the injury. Future research should assess the feasibility of daily measures of overuse injury Risk Factor Assessment A Repeated Measures Design and Complexity Science approach One of the core issues with the assessment of overuse injuries stems from the complex interaction that intrinsic and extrinsic risk factors play in the etiology of injury onset. As highlighted by Meeuwisse s Dynamic Recursive Model, it is the combination of both intrinsic and extrinsic risk factors that contribute to the development of the susceptible athlete. 7 Current statistical approaches for risk factor assessment have been unable to assess how a multitude of risk factors may interact to effect the likelihood of an injury outcome. Drawing from mathematical approaches in statistical physics, information theory and non-linear dynamics, a complexity science approach could begin to shed light on how the relationship 91

113 between multiple risk factors gives rise to an injury outcome. 91 It is also acknowledged that intrinsic factors will change over time. Yet limited research to date has attempted to address this with a repeated measure design of risk factor assessment. An understanding of the variability of a risk factor throughout the course of the season could also provide a greater insight into its impact on injury risk. This emerging strategy might be particularly relevant to overuse injuries in a sport like volleyball Internal Measures of Load Training load can be measured in a multitude of ways that fall under two primary categories; external and internal measure of load. 10 External load measures come from devices such as global position systems (GPS), accelerometers or other inertial measurement units and provide the ability to track measures such as meters ran, jumps performed, or tackles encountered. Meanwhile internal measures of load begin to capture the inter-individual variations that external loads have on each individual specifically. Although internal measures of load can take the form of specific bio-markers or heart rate, it is a low-tech, session specific, rating of perceived exertion (srpe) questionnaire that may provide the greatest understanding of the training loads that an athlete has endured relative to their ability to tolerate the load. 9 The simplicity of collection for srpe may allow for the large scale population level collection of training load that would be required to adequately power a study on the assessment of load and injury. How internal measures of loads correlate with external measures and what influence internal measures have on overuse injury onset and severity deserves further assessment. 92

114 7.3 Conclusion Although the research presented here utilized volleyball as the sport of interest, a multitude of Olympic and non-olympic sports likely have a high prevalence of overuse injuries. Initial work on addressing the definition of injury will allow us to gain a more thorough understanding of the extent of the problem across sport. However, more work is required to tackle the methodological complexities of using this new definition of injury outcome for the identification of injury risk factors. It is then, through the identification of injury risk factors, that intervention initiatives can be developed to prevent overuse injuries. 93

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122 Appendix A Individual Injury Report Form Individual Injury Report Form Volleyball Injury ID#: Please complete this form for any injury that results in an athlete being unable to fully participate in game or practice. 1. Athlete ID#: 2. Date of Injury (MM / DD): / 3. Date Reported (MM / DD): / 4. Injury Status: New injury (no previous history of this injury) Re-injury (same injury previously occurred but was healed) Exacerbation (worsening state of previous unhealed injury) 5. Did athlete return to play the same game or practice? No Yes N/A or Other: 6. Was bracing or taping used on the injured area or limb at the time of injury? No Unknown N/A Yes If yes, what type?: 7. Position Played when Injured: Setter Libero Middle Power Rightside NA Unknown Describe Events Surrounding Injury (including exact mechanism of injury if possible): Unknown Known: Remarks: (Subjective report of cause; e.g. overtraining, unsafe action,, etc.) Assessment: Side (Right/Left/Both) Body Region (Structure) Type of Injury ("Diagnosis") e.g. Right shoulder A/C joint 3 sprain Therapist's Name (print): 8. Normal Position Played: Setter Libero Middle Power Rightside 9. This Injury Involved (check all that apply): Sudden onset & contact with: Player Ball Pole Other Sudden onset & NO contact with another person or object Gradual Onset/Overuse Unknown Other: 10. Injury Occurred During: Game Warm-up 1st Set 2nd Set 3rd Set 4th Set 5th Set Practice Warm-up 1st Half 2nd Half Other Gradual Onset Weight Training Other Conditioning Other Sport Non-Sport Unknown ONLY Complete this section once the athlete has fully returned to play AND has completed all injury related care Date of return to play (full participation) (MM / DD): / Confirmed Diagnosis: Who confirmed the diagnosis: Physician Athletic Therapist Student Athletic Therapist Physiotherapist Other: Name of person who confirmed diagnosis: Who provided clearance to return to play? Physician Athletic Therapist Student Athletic Therapist Physiotherapist Other: 101