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2020
Making Football Safer: Optimizing the efficacy and implementation of the 11+ Program
Matthew Whalan
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Making Football Safer: Optimizing the efficacy and implementation of the 11+ Program
Matthew Whalan Master of Physiotherapy Bachelor of Exercise Science & Rehabilitation (Hons)
Supervisors:
Dr. John Sampson, Associate Professor Ric Lovell, and Senior Professor Julie Steele
This thesis is presented as part of the requirement for the conferral of the degree:
Doctor of Philosophy
University of Wollongong School of Medicine Faculty of Science, Medicine and Health
February 2020
Abstract
Introduction: Although football (soccer) has the highest participation of any sport worldwide, the potential for injury is high due to its intense nature. In the elite setting, injury may impact on immediate and future playing capacity, however in the sub-elite setting, injury may also impact on employment outside of football. To consistently evaluate the prevalence and aetiology of injuries in football, a consensus method was developed to allow for ongoing injury data collection. Despite a number of injury studies in the elite setting, there has been little research performed in the sub-elite setting that complies with the football consensus, and no injury research performed in Australia.
The 11+ program was designed as a football specific surrogate warm-up that included specific exercises to reduce injury risk in sub-elite football. Despite extensive research showing the injury prevention capacity of the program when players perform the program a minimum of 2 × per week, there has been low uptake of the 11+ program. Issues related to: (i) program duration; (ii) player and coach support; and (iii) potential fatigue related to some of the exercises; are all established reasons for the poor uptake. Consequently, the aims of this thesis were: (i) determine the types, frequency and severity of injury observed as per the football injury consensus statement in sub-elite football in Australia, (ii) assess the prevalence and impact of non-time loss injury and associated time loss injury risk in sub-elite football, (iii) investigate the attitudes, beliefs and behaviours of coaches, players and medical staff towards injury prevention strategies and find potential options to overcome barriers to injury prevention in sub-elite football, (iv) investigate the effect of a novel 11+ program delivery method on player compliance and overall program efficacy.
Methods: (i) To determine the prevalence and aetiology of injuries, a season long injury surveillance study of 1049 players was performed with injury and exposure data collected as per the football consensus statement. (ii) Whilst conducting this season of injury surveillance,
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an additional self-reported injury surveillance method was included with a sub-group of 218 players. The Oslo Sports Trauma Research Centre (OSTRC) Questionnaire on Health Problems was delivered weekly for the entire season. (iii) A survey-based questionnaire was delivered to coaches, players and medical staff of sub-elite clubs. The survey contained several sections related to: current practices and beliefs regarding injury risk and prevention; attitudes towards the 11+ program and potential barriers to injury prevention practice. (iv) Finally, an investigation including 806 players determined the effect of performing Parts 1 and 3 of the
11+ program only during the warm-up whilst rescheduling Part 2 of the 11+ program to the end of training (P2Post; n = 408 players). This was compared with performing the standard 11+ program (Standard-11+; n = 398 players).
Results: (i) A total of 1041 injuries were recorded resulting in an injury incidence of 20 injuries/1000 hours of exposure with the burden being 228 days lost/1000 hours of exposure.
Muscle (41%) and ligament (26%) injuries were the most prevalent, whilst the most common injury locations were; thigh (22%) and ankle (17%). Recurrent injuries accounted for 20% of all injuries while mild injuries (days lost = 1 to 3 days) were the most prevalent (35%). (ii)
The prevalence of non-time loss injuries was shown to be 2.3 × greater than time loss injuries in sub-elite football. The presence of a non-time loss injury was associated with a 3.6-6.9 × higher risk of sustaining a time loss injury in the 7 days following the report. (iii) Coaches, players and medical staff were all supportive of injury prevention programs and perceive them as important to reduce injuries. All stakeholders were equally supportive of performing two
10-minute injury prevention components delivered both before and after training, whilst the ideal duration for a warm-up was between 16 to 19 minutes. (iv) There was no significant difference in injury incidence between groups (P2post vs Standand-11+ = 11.8 vs 12.3 injuries/1000 hours of exposure). Severe injuries (33 vs 58 injuries) and total days lost to injury
(4303 vs 5815 days lost) were significantly lower in the P2post group compared with the
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Standand-11+ group. Both versions of the 11+ program each reduced injury incidence compared to the previous season (Standard-11+ = 38% reduction; P2post = 40% reduction).
Players in the P2post group had a significantly higher dose exposure to the 11+ program (29.1 doses vs 18.9 doses) compared with the Standard-11+ group, thereby increasing player compliance by 35%.
Discussion: Sub-elite football has an injury issue that requires immediate attention. With injury incidence and burden in Australia twice that observed in elite football, the implementation of injury prevention strategies and programs such as the 11+ program is of great importance and urgency. The present results also indicate that the collection of non-time loss injury data not only improves the insight into injury in sub-elite football but may also serve as an effective secondary injury prevention strategy to identify players at increased risk of obtaining a more severe injury.
Key stakeholders consider programs like the 11+ as important to reduce injury risk, however strategies to increase program adoption and implementation are required. The findings from this thesis indicate that the simple act of rescheduling Part 2 of the 11+ program to the end of training not only maintains the efficacy of the standard program, but increases player compliance and reduces injury burden when compared to the standard 11+ program delivery format.
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Acknowledgments
The original concept for this thesis was a simple one – to make football safer. A simple idea grew into a much bigger project that has now been the centre of my universe for the past 5 years. To achieve what has been done requires a great deal of support and I have been very fortunate to work with some fantastic people during this process.
Firstly, to my supervisory team, Dr John Sampson, Dr Ric Lovell and Senior Professor Julie
Steele: you have all been first class and fantastic to work with. “Thank you” does not do justice to the work, time, encouragement and guidance you have provided. You have instilled a great sense of academic rigor and pride in everything that was produced and helped me achieve things I did not think I was capable of doing. On many levels, I am very proud of our collaboration to ensure the original research idea achieved such high academic quality and outcomes. I must also acknowledge the invaluable assistance of Dr Robert McCunn and Dr
Sean Williams for their assistance and guidance regarding the logistical and statistical methods employed in this thesis.
To all the players, coaches, medical staff, fellow researchers, students and associations that participated in this project: your faith and belief in what was proposed to you all is a major reason that such a large scale project was successful and I cannot thank you all enough. A special mention must go to physiotherapists – Michael Gabriel, Kieran Rooney and Steve
Felsher – whose support was invaluable to the outcome of this project.
To my parents: you have always inspired and encouraged me to work hard and be the best I can possibly be. This project would not have been possible without the qualities you have instilled in me over my life and I sincerely thank you.
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Finally, to my wife, Laura, and children, Darcey and Flynn: you have sacrificed as much, if not more, than I in the completion of this thesis. Your belief in my ability to complete this project has been unwavering and the outcomes would not have been possible without your immense love, support and patience - I am eternally grateful and love you all very much.
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Certification
I, Matthew Whalan, declare that this thesis, submitted in fulfilment of the requirements for the conferral of the degree Doctor of Philosophy, from the University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. This document has not been submitted for qualifications at any other academic institution.
Matthew Whalan 11th February 2020
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Publications
This thesis includes chapters that have been written as the following journal articles:
Chapter 2: Whalan M, Lovell R, McCunn R, Sampson JA. The incidence and burden of time loss injury in Australian men’s sub-elite football (soccer): a single season prospective cohort study. J Sci Med Sport 2019;22(1):42-47.
Chapter 3: Whalan M, Lovell R, Sampson JA. Do Niggles Matter? – Increased injury risk following physical complaints in football (soccer). Science and Medicine in Football 2019; doi.org/10.1080/24733938.2019.1705996.
Chapter 4: Whalan M, Lovell R, Siegler JC, Marshall PW, Sampson JA. What do players, coaches and physiotherapists in men’s sub-elite football think of injury prevention and the 11+ program? Science and Medicine in Football (submitted for publication February, 2020).
Chapter 5: Whalan M, Lovell R, Steele JR, Sampson JA. Rescheduling Part 2 of the 11+ program reduces injury burden and increases compliance in semi-professional football Scand
J Sci Med Sport 2019;29(12):1941-1951.
In order to ensure consistency throughout this thesis, some minor modifications may have been made to the published text.
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As the primary supervisor, I, Dr John Sampson, declare that the greater part of the work in each article listed above is attributed to the candidate, Matthew Whalan. In each of the above manuscripts, Matthew contributed to the study design, recruited participants, was solely responsible for overseeing the data collection and data analysis, and was largely responsible for statistical analysis and data interpretation. The first draft of each manuscript was written by the candidate and Matthew was then responsible for responding to the editing suggestions of his co-authors. The co-authors listed on each manuscript were responsible for assisting in study design, data interpretation and editing the manuscripts. Matthew has been solely responsible for submitting each manuscript for publication to the relevant journals, and he has been primarily in charge of responding to reviewer’s comments, with assistance from his co-authors.
Matthew Whalan John Sampson Date: 11/02/2020 Date: 11/02/2020
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Abbreviations
ACL Anterior cruciate ligament
ACLR Anterior cruciate ligament rupture
AUC Area under the curve
CI Confidence interval
FFA Football Federation of Australia
FIFA Federation Internationale de Football Association
GEE Generalised estimating equation
IPP Injury Prevention Program
NHE Nordic hamstring exercise
Non-TL Non-time loss
NSO National Sporting Organisation
NSW New South Wales
P2post Part 2 of the 11+ performed at the end of training
PDC Primary Data Collector
RE-AIM Reach Effectiveness Adoption Implementation Maintenance
RE-AIM SSM RE-AIM Sport Setting Matrix
RR Relative risk
ROC Receiver operating characteristics
Standard-11+ Normal 11+ program
TL Time loss
TRIPP Translating Research into Injury Prevention Practice Framework
OSICS Orchard Sports Injury Classification System
OSTRC Oslo Sports Trauma Research Centre
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Table of Contents
Contents Page
Abstract ...... 1
Acknowledgments ...... 4
Certification ...... 6
Publications ...... 7
Abbreviations ...... 9
Table of Contents ...... 10
List of Tables ...... 15
List of Figures ...... 17
Chapter 1 – The Problem ...... 18
1. Introduction ...... 18
1.1 Injury Surveillance (TRIPP Stages 1, 2 and 6) ...... 20
1.1.1 Elite versus Sub-elite Cohort Injury Research ...... 20
1.1.2 Issues and Potential Solutions to Injury Research in Sub-Elite Football ...... 22
1.2 Development of the Injury Prevention Program (TRIPP Stages 3 to 5) ...... 26
1.2.1 The 11+ Program (TRIPP Stages 3 and 4) ...... 26
1.2.2 Addressing Intervention and Adoption Issues (TRIPP Stage 5) ...... 26
1.3 Statement of the Problem ...... 28
1.4. Thesis Schematic Framework ...... 29
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Chapter 2 - The Incidence and Burden of Time Loss Injury in Australian Men’s Sub-Elite
Football: A Single Season Prospective Cohort Study ...... 40
2.1 Introduction ...... 42
2.2 Methods ...... 43
2.2.1 Participant Recruitment ...... 43
2.2.2 Data Collection Definitions and Procedures ...... 44
2.2.3 Statistical Analysis ...... 45
2.3 Results ...... 45
2.4 Discussion ...... 51
2.4.1 Injury Incidence and Burden ...... 51
2.4.2 Muscle Injuries ...... 53
2.4.3 Ligament Injuries ...... 54
2.4.4 Injury Mechanism ...... 54
2.4.5 Limitations ...... 55
2.5 Conclusion ...... 56
2.6 Practical Implication ...... 57
2.7 References ...... 58
Chapter 3 - Do Niggles Matter? Increased Injury Risk Following Physical Complaints in
Football ...... 62
3.1 Preface ...... 62
3.2 Introduction ...... 64
3.3 Methods ...... 65
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3.3.1 Participants ...... 65
3.3.2 Time Loss Injury Data Collection...... 66
3.3.3 Non-Time Loss Injury Data Collection...... 66
3.3.4 Statistical Analysis ...... 67
3.4 Results ...... 69
3.4.1 Relative Risk and Time-loss Injury Prediction ...... 69
3.4.2 Sub-group Relative Risk and Time-loss Injury Prediction ...... 73
3.4.3 Sub-group Weekly Injury Prevalence ...... 75
3.5 Discussion ...... 77
3.5.1 Importance of Non-Time Loss Injuries ...... 77
3.5.2 Another Tool in the Injury Reduction Box? ...... 79
3.5.3 Football Consensus Method vs OSTRC Questionnaire on Health Problems ...... 80
3.5.4 Limitations ...... 81
3.6 Conclusion ...... 82
3.7 Practical Implications ...... 83
3.8 References ...... 85
Chapter 4 - How Can We Get Players To Do The 11+ Program? - Stakeholder Perceptions on
Injury, Prevention and Potential Solutions ...... 90
4. 1 Preface ...... 90
4.2 Introduction ...... 92
4.3 Methods ...... 93
4.3.1 Survey Design ...... 93
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4.3.2 Statistical Analysis ...... 94
4.4 Results ...... 95
4.4.1 Stakeholder Attitudes, Perceptions, Practices and Barriers Regarding Injury Risk
Factors and Prevention Strategies ...... 95
4.5 Discussion ...... 102
4.5.1 Injury risk factors...... 102
4.5.2 Injury Prevention Program Perceptions and Practices ...... 103
4.5.3 The 11+ Program – Awareness and Barriers ...... 104
4.5.4 Potential Solutions to the 11+ Program Adoption Problem ...... 104
4.5.5 Limitations ...... 105
4.6 Conclusion ...... 106
4.7 Practical Implications ...... 107
4.8 References ...... 108
Chapter 5 - Rescheduling Part 2 of the 11+ Program Reduces Injury Burden and Increases
Compliance in Sub-Elite Football ...... 113
5.1 Preface ...... 113
5.2 Introduction ...... 115
5.3 Methods ...... 117
5.3.1 Participant Recruitment ...... 117
5.3.2 Training to Implement the 11+ Program ...... 120
5.3.3 Program Compliance & Injury Data Collection ...... 120
5.3.4 Statistical Analysis ...... 121
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5.4 Results ...... 122
5.5 Discussion ...... 128
5.5.1 Effect on 11+ Program Efficacy ...... 128
5.5.2 The Potential Role of Rescheduling on 11+ Program Compliance ...... 131
5.5.3 Limitations ...... 132
5.6 Conclusion ...... 134
5.7 Practical Implications ...... 134
5.8 References ...... 136
Chapter 6 - Summary, Recommendations for Future Research, and Practical Implications ... 142
6.1 Summary ...... 142
6.2 Recommendations for Future Research ...... 146
6.2.1 Cohort Specific Injury Surveillance ...... 146
6.2.2 Increased use of Self-Report Measures in Primary and Secondary Prevention ...... 146
6.2.3 Updating the “11+ Program” and its “concept” ...... 148
6.3 Practical Implications ...... 149
6.3.1 Translation to Practice ...... 151
6.4 References ...... 157
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List of Tables
Table 1.1 The Translating Research into Injury Prevention Practice Framework (TRIPP)
Framework ……………………………………………………………………....19
Table 1.2 Definitions for frequently used terms in football injury surveillance research ….20
Table 1.3 Examples of the various injury surveillance methods used in sub-elite football
research…………………………………………………………………………..25
Table 2.1 Injury incidence pattern including location, type and mechanism ………………47
Table 2.2 Muscle and ligament injury incidence pattern, incidence and burden……………48
Table 2.3 Injury burden of time loss injuries (injury incidence × mean absence per injury) .50
Table 3.1 Associated injury risk and injury prediction using the OSTRC Questionnaire on
Health Problems for time loss injury for entire cohort and sub-group ……………71
Table 3.2 Diagnostic accuracy assessment for OSTRC Questionnaire on Health Problems for
each sub-category drawn from entire cohort and sub-group ……………………72
Table 3.3 Sub-Group time-loss injury reports and associated relative risk following a
previous physical complaint. Data presented according to location using third party
(Football Consensus) and self-reporting method (OSTRC Questionnaire on Health
Problems) ………………………………………………………………………..74
Table 4.1 Perceived injury risk factors in sub-elite football ………………………………..96
Table 4.2 Stakeholders Beliefs and Attitudes to Injury Prevention Practices ………………97
Table 4.3 Location specific injury prevention practices from coaches, players and
physiotherapists …………………………………………………………………99
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Table 4.4 Perceived stakeholder barriers key stakeholders to the implementation of injury
prevention programs …………………………………………………………...100
Table 5.1 Player exposure, compliance, injury count and severity for participants in the
Standard-11+ and P2post group …………………………………………………123
Table 5.2 Injury pattern, incidence rate and rate ratios for participants in the Standard-11+
and P2post Groups ………………………………………………………………125
Table 5.3 Injury burden and days lost to injury for participants in Standard-11+ and P2post
Groups………………………………………………………………………….126
Table 5.4: Muscle and ligament injury pattern, incidence and burden for participants in the
Standard-11+ and P2post groups ………………………………………………..127
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List of Figures
Figure 1.1 Schematic of thesis structure, and how each component complies with the TRIPP
framework, addressing the overall thesis aim……………………………………30
Figure 3.1 Prevalence of all injuries (dark grey) and non-time loss only injuries (light grey)
recorded by the weekly self-reported injury OSTRC Questionnaire on Health
Problems (A); Combining both injury surveillance methods – Self-reported and
third party (B)…………………… ………………………………………………76
Figure 4.1 Percentage of players that recorded “Neither agree nor disagree” for statements
regarding the 11+ program……………………………………………………...101
Figure 5.1 Consolidated Standards of Reporting Trials (CONSORT) diagram of the flow of
participants in the study………………………………………………………...119
Figure 6.1 Stakeholder specific guidelines for reducing injury incidence and risk in sub-elite
football ………………………………………………………...... 152
Figure 6.2 Guidelines for practice for National, State and Local sporting organisations to
reduce injury incidence and risk in sub-elite football…………………………..153
Figure 6.3 Guidelines for practice for coaches to reduce injury incidence and risk in sub-elite
football ………………………………………………………...... 154
Figure 6.4 Guidelines for practice for players to reduce injury incidence and risk in sub-elite
football ………………………………………………………...... 155
Figure 6.5 Guidelines for practice for medical and performance staff to reduce injury
incidence and risk in sub-elite football…………………………………………156
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Chapter 1
Chapter 1 – The Problem
1. Introduction
In Australia an estimated 4.7 million people over the age of 15 years1 and 1.7 million children aged between 5 to 14 years participate in organised sporting activities.2 Participating in leisure time sporting activities can result in a range of health-related benefits3 with recreational football
(soccer) repeatedly shown to positively impact the cardiovascular, metabolic and skeletal systems of both men and women.4-9 The health benefits associated with participating in sport are however potentially offset by the risk of injury.10 This risk is magnified in sports like football, due to the characteristics of the sport involving high intensity activity, changes of direction and contact.11-13, 14 Unfortunately, injury often results in discontinued sporting participation,15 can lead to longer term disability16 and substantial medical costs.17 Notably, in
Australia the annual cost of sporting injuries has been reported to exceed $2 billion.18 In the sub-elite setting there is also the additional impact of injuries on missed days of employment, which can result in a substantial economic cost to employers.19, 20
FootballƗ is the most popular sport in Australia, with 1.8 million participants,21 most of whom participate on a sub-elite basis (amateur and semi-professional). It is therefore important to investigate avenues to reduce the risk of injury associated with football activities at the sub- elite level. To ensure that the correct injury risks are addressed, it is vital to accurately identify the nature of injuries that occur in football and complete a period of injury surveillance to effectively evaluate an ensuing injury prevention program (IPP).22, 23 Van Mechelen et al.22 developed a four-stage injury prevention framework model to: (i) identify the extent of the problem, (ii) identify the aetiology and mechanisms of injury, (iii) introduce preventative measures and (iv) assess the effectiveness of the preventative measures by repeated step (i).
Ɨ In Australia, several sporting codes use the label “football”. The focus of this thesis is what is often referred to as soccer. From this point onwards, the term football will be used.
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Chapter 1
Almost two decades later, van Mechelen’s framework22 was further developed into the
Translating Research into Injury Prevention Practice Framework (TRIPP) 23, 24 (Table 1.1) in order to try and improve the success of implementing IPPs.
TABLE 1.1. The Translating Research into Injury Prevention Practice Framework (TRIPP) Framework.
Model Stage Translating Research into Injury Prevention Practice
1 Injury Surveillance
2 Establish aetiology and mechanisms of injury
3 Develop preventative measures
4 “Ideal conditions”/scientific evaluation
5 Describe intervention context to inform implementation strategies
6 Evaluate effectiveness of preventative measures in implementation context
The TRIPP framework provides researchers with a robust methodological structure to conduct injury prevention research and address ‘real world’ barriers to implementing an injury prevention program. In Australia, several injury surveillance studies have been performed in
Australian Rules Football,25-27 the rugby codes28-30 and cricket.31, 32 However, despite football’s popularity, no published studies have investigated the injury profile of elite or sub-elite football players in Australia. It is therefore imperative that literature relative to Stages 1 to 6 of the
TRIPP framework are explored in relation to football in order to identify current knowledge and gaps that warrant investigation.
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Chapter 1
1.1 Injury Surveillance (TRIPP Stages 1, 2 and 6)
1.1.1 Elite versus Sub-elite Cohort Injury Research
The first and last stages of injury prevention are reliant on consistent injury surveillance. In
football, a consensus statement on injury data collection definitions and methodology was
developed to guide this process.33 A list of the most frequently used terms in football injury
surveillance research is presented in Table 1.2. 33, 34
TABLE 1.2. Definitions for frequently used terms in football injury surveillance research.
Term Definition
Injury Any physical complaint sustained by a player that results from a football match or football training.
Time Loss Injury Any injury that results in a player being unable to fully participate in matches or training, including an injury where a player ceases training or matches due to injury.
Injury Severity The number of days from the date of the injury to the date of the player’s return to full participation in training or availability for match selection. The day of injury is Day 0 and severity is classified by the number of days that the player is unavailable for full participation. The severity is reported in the subcategories: Slight – 0 days; Minimal – 1-3 days; Mild – 4-7 days; Moderate – 8-28 days; Severe – >28 days.
Time Exposure Exposure, in hours, to football specific training and match play is recorded. All sessions conducted by club coaching and fitness staff are recorded. Extra sessions external to the club are not included.
Recurrent Injury Injury of the same type and the same site which occurs after a player’s return to full participation from the previous injury.
Trauma Injury Injury with sudden onset and known cause.
Overuse Injury Injury with insidious onset and no known cause.
Injury Incidence Number of injuries per 1000 player hours.
Injury Burden Number of days lost due to injury per 1000 player hours – (injury incidence × mean absence (days) per injury).
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Chapter 1
Over the past 10 years, most studies investigating injury incidence and injury patterns in football that adhered to the guidelines presented in the consensus statement, have focused on the elite level of competition.35-40 Comparisons of injuries incurred by sub-elite and elite football players have shown a higher overall risk and rate of injury in elite football,41 with higher risks during elite matches but lower risks at training.40, 42, 43 However, only one of the aforementioned studies of injury in sub-elite football40 adhered to the football consensus method for recording injuries in football.33 In this study, the frequency of injuries relative to the effected body locations were almost identical between playing levels, with the only exceptions observed being a higher number of knee and overuse injuries in the professional cohort, and higher number of ankle injuries in the semi-professional cohort.40 The higher number of overuse injuries in professional players is likely to be associated with higher intensity training, increased training frequency and immediate access to medical staff for diagnosis and assessment.40, 44, 45 Sub-elite players, however, reported more recurrent injuries, which is consistent with research showing that recurrence rates are inversely proportional to playing level.40, 45 When the severity of the injuries were examined, higher level players suffered more “minimal” severity injuries, whereas lower level players reported more “severe” injuries.40 Proposed reasons for this difference include a lack of medical staff and supervision at lower level clubs, which may result in delayed or non-reporting of minor injuries, as well as a reduced squad size in lower league teams, potentially resulting in more urgency for players to return to training or a match before fully recovering from injury.40, 45, 46
Although these previous studies provide important information, discrepancies are apparent in the injury reporting and recording methods across the literature investigating sub- elite players, making it difficult to infer broader associations. 47 This variability in injury recording is not surprising given that there are difficulties in adhering to the consensus methods for injury recording in sub-elite football. 47
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Chapter 1
1.1.2 Issues and Potential Solutions to Injury Research in Sub-Elite Football
The methods outlined in the football consensus method33 were designed to be used in all football injury research, both elite and sub-elite. However, there are many potential issues that may limit the application of injury recording methods that adhere to the football consensus statement guidelines33 in sub-elite levels of football.47 Limited medical supervision and resources are available to non-professional football clubs and, as such, individuals with varied levels of medical training have been used to collect injury and exposure data. In a sub-elite setting, researchers have used several different sources to collect football injury data, including coaches,48, 49 players,50-53 parents,54, 55 medical staff 56-61 and academics.45, 62, 63 Such variation can lead to inconsistencies in data collection and interpretation of injury incidents when comparing the information presented across the literature.47 Examples of the various injury recording methods within the injury surveillance literature is contained in Table 1.3 and highlights the large variation that exists. Furthermore, in studies in which non-medical stakeholders are used to collect injury data, it is often not possible to comply with the consensus injury collection methods.47 Yet research in sub-elite football that has claimed to follow the football consensus methods has not acknowledged or explained how any of the aforementioned data collection issues were addressed (Table 1.3).53, 59, 61, 64
There are several ways research performed in sub-elite football settings could comply with the consensus injury recording methods.47 Firstly, ensuring medical and data collection coverage in sub-elite football occurs at training sessions and matches is important in injury research to maximise injury capture.65 The injury consensus statement also advises that a minimum level of medical knowledge is required to collect injury data.33 In sub-elite football, standardised data collection may be achieved by individuals with a sports trainer’s qualification in which an advanced first aid qualification, in addition to a basic first aid qualification, is obtained. This qualification includes education on specific modules on anatomy, injury
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Chapter 1 mechanisms and injury reporting methodology. Indeed, previous research has shown that sports trainers at community level sporting clubs can collect valid injury data and information of adequate quality to provide an understanding of injury profiles.66, 67 Although it must also be acknowledged that an underestimation of approximately 20% in injury rates has been reported within injury data collected by sports trainers,66 these results are consistent with injuries recorded for elite football players when injuries were recorded by team medical staff.68
In order to understand the true nature and extent of injuries in sub-elite football, the issue of underreporting and “missing” injuries needs to be addressed. When injuries are missed and not recorded it can result in the misclassification of injury severity (days lost) due to under reporting of the initial injury occurrence. Unfortunately, the lack of resources and nature of part-time participation in sub-elite football, often results in a lack of contact between club staff and players. This can result in a scenario whereby a player sustains a minor injury which may resolve between scheduled training/match days, yet the player may not have been able to participate in a football training session during the days immediately after the event. In this instance, the minor time loss injury would not be recorded during the data collection process.
As a consequence, many minor injuries might not be recorded in a sub-elite football environment, impacting on the recorded total injury incidence and the under reporting of injuries. For example, as most injuries occur during a match, in the sub-elite setting it is not uncommon for at least 48-72 hours (Saturday match until a Tuesday evening training session) to pass until the next training session. This issue can be further compounded by “missed” football sessions caused by non-football related issues (e.g. work or personal commitments).
Finally, as sub-elite players do not have instant access to a diagnosis from a medical professional, a medical review of injured players is not often possible. Alternative methods, including phone consultations with injured players,54 weekly visits from allocated medical professionals69 and player self-reports providing an injury description from which a diagnosis
23
Chapter 1 can be established,50-52 may offer viable methods to obtain a valid diagnosis.47
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Chapter 1
Table 1.3 – Examples of the various injury surveillance methods used in sub-elite football injury research
Study Method Used to Record Injuries Cohort Total Injuries (n) Total Exposure Injury Incidence Compliance with and Exposure (h) or (AE) (injuries/1000h)* Football Consensus Methods van Beijsterveldt et al 40 Professional = Medical staff Professional (n=217); Professional = 286 Professional = 46194 h Professional = 6.2 (5.5 to 7.0) Yes Amateur = Sports Trainer amateur (n=456) Amateur = 424 Amateur = 44252 h Amateur = 9.6 (8.7 to 10.5) Hagglund et al 45 Top-level and elite = medical staff Top-level (n=6956); Top-level = 11581 Top-level = 232 Top-level = 7.2 (7.0 to 7.3) Yes Amateur = coaches elite (n=2014); Elite = 3836 h/player Elite = 7.4 (7.1 to 7.6) amateur (n=241) Amateur = 134 Elite = 259 h/player Amateur = 5.2 (4.4 to 6.1) Amateur = 107 h/player Froholdt et al 49 Coaches Amateurs – girls 200 94175 h 2.2 (1.8 to 2.6) Yes (n=591) and boys (n=1288) - 6 to 12 years old Hammes et al 51 Coaches and/or Players Amateur (n=265) Intervention = 51 Intervention = 4172 h Intervention = 12.2 (8.9 to Yes Control = 37 Control = 2937 h 15.6) Control = 12.6 (8.5 to 16.7) Emery et al 55 Coach and/or Parent Amateur (n=317) 78 13965 h 5.59 (4.42 to 6.97) No
Herrero et al 56 Medical Staff Amateur – country 15246 Estimated - 1 match Training = 0.49 No wide competition (90 mins) and 2 training Matches = 1.15 sessions (60 mins) per week per player Brito et al 59 Medical Staff and Coaches Amateur (n=674) 199 161850h Total = 1.2 (0.8 to 1.6) Yes
Silvers-Granelli 61 Athletic Trainers Amateur (n=1525) Control = 665 Control = 44212 h Control = 15.04/1000 AEs No Intervention = 285 Intervention = 35226 h Intervention = 8.09/1000 AEs McNoe et al 62 Research assistants contacting Amateur (n=880) Matches = 677 Matches = 13483 h Matches = 50.2 (46.6 to 54.1) No players who self-reported injuries Training = 145 Training = 16031 h Training = 9.0 (7.7 to 10.6) Soligard et al 64 Coaches Amateur (n=1892) Control = 215 Control = 45428 h 4.7 Yes Intervention = 161 Intervention = 49899 h 3.2
* 95% Confidence Intervals presented where found; h = hours of exposure; AE = Athletic Exposures.
25
Chapter 1
1.2 Development of the Injury Prevention Program (TRIPP Stages 3 to 5)
1.2.1 The 11+ Program (TRIPP Stages 3 and 4)
The injury data collected during the first two stages of the TRIPP framework provides the evidence for an injury prevention program to be developed to address the most common and problematic injuries in a sport (Stage 3). In football, the 11+ program was designed, funded and supported by the medical department of the world governing body for football, the
Federation Internationale de Football Association (FIFA). The 11+ program, which is described in further detail in Chapters 4 and 5, was designed as a surrogate warm-up that is simple to implement and to be performed at training at least twice per week without any specialised gym or exercise equipment.70 Importantly, the 11+ program has been shown to reduce injury incidence in both male61, 71 and female64, 72 sub-elite football players, with several systematic reviews showing a 40% reduction of injury incidence after football players have followed the program (Stage 4 of the TRIPP model).73-76
Despite these reductions in injury incidence, there has been poor adoption of the 11+ program. Several factors, including: (i) negative perceptions of the key stakeholders
(associations, coaches and players),23, 70, 77-79 (ii) issues regarding time taken to perform the program,77, 80 (iii) concerns regarding fatigue and soreness77, 80 and (iv) boredom with the program77, 80 appear to contribute to the lack of program adoption. Despite the evidence supporting use of the 11+ program to reduce injuries and knowledge of the barriers to implementing the 11+ program, adoption issues remain. 78 Stage 5 of the TRIPP framework acknowledges this problem and highlights the need to explore methods to overcome the established barriers to a program.
1.2.2 Addressing Intervention and Adoption Issues (TRIPP Stage 5)
To address Stage 5 of the TRIPP framework, it is important to explore the views of key stakeholders associated with implementing injury prevention programs. A method to achieve
26
Chapter 1 this is to employ the RE-AIM model, which provides five dimensions to consider when designing and developing an injury prevention program. The initial model81 acknowledged that multiple stakeholders are involved in the process of implementing injury prevention programs including: (i) the individual, (ii) the organisation, and (iii) the community. This model evolved and was re-named as the RE-AIM Sports Setting Matrix (RE-AIM SSM) to acknowledge hierarchical stakeholder levels that exist within sport including: (i) national sporting organisations (NSO), (ii) state federations, (iii) community organisations, (iv) coaches and clubs and (v) players.23 The importance of stakeholder buy-in has been recognized in reference to adopting and implementing the 11+ program.78 A framework called the “Eleven steps to implement the FIFA 11+” outlined how NSO’s could implement the 11+ program throughout the community.78 This framework included NSO endorsement and resulted in successful implementation of a nationwide dissemination of the similar “11” program in Switzerland, with sports physical therapists training coaches to deliver the program.82 Furthermore, researchers in New Zealand have shown, via implementation of the multi-sport SportsSmart program
(based on the 11+ program), that success can be achieved in terms of both reducing injury and financial burden when the government is included in the framework.83 Therefore, implementing any injury prevention program should engage with as many key stakeholder levels as possible, with the RE-AIM SSM23 and the “Eleven Steps”,78 providing clear frameworks to achieve this.
Despite such clear frameworks, no published study was located in which an injury prevention program was successfully implemented following these frameworks.
27
Chapter 1
1.3 Statement of the Problem
Despite the success of the 11+ program in reducing injury incidence in controlled experimental conditions, issues involving implementation of the 11+ program on a larger scale remain. The overall aim of this thesis was therefore to explore the effects of modifying the 11+ program delivery on injuries incurred by sub-elite football players. In order to determine the best approach to improve 11+ program implementation, the results of injury surveillance (Chapters
2 and 3) and potential options and barriers to 11+ program delivery (Chapter 4) were considered prior to the development of a new strategy (Chapter 5). Therefore, to achieve the aim of this thesis, a series of studies were conducted to systematically address gaps in our knowledge related to injury and injury prevention in sub-elite football:
(i) Confirm the types, mechanisms, frequency and burden of injury observed and
determine the associated severity of injury in sub-elite football in Australia.
(ii) Using validated self-reported methods, assess the prevalence and impact of non-time
loss injury and the association with time-loss injury risk in sub-elite football.
(iii) Determine the attitudes, beliefs and behaviours of coaches, players and medical staff
towards injury risk and prevention strategies in sub-elite football.
(iv) Using a cluster randomised control design, determine the effect of rescheduling Part 2
of the 11+ on injury incidence and program compliance compared with the standard
program delivery, in sub-elite football.
28
Chapter 1
1.4. Thesis Schematic Framework
Consistent with the stages of the TRIPP framework, a 1-year period of injury surveillance was first performed throughout the entire 2016 football season to identify the aetiology and mechanisms of injury in sub-elite football in Australia (Chapter 2; TRIPP Stages 1 and 2). This was extended to determine the true nature of injuries in sub-elite football using self-reporting methods to provide additional data for the analysis of non-time loss injuries in sub-elite football
(Chapter 3; TRIPP Stages 1 and 2). The 11+ program was selected as the injury prevention program for Stages 3 and 4 of the TRIPP framework based on research supporting the efficacy and implementation of this program for injury prevention in sub-elite football.74 Considering the information gathered in Chapters 2 and 3, a survey of key stakeholders and end users – coaches, players and physiotherapists – was conducted to determine attitudes and perceptions on injury, injury prevention practices, the 11+ program and potential options for overcoming barriers to injury prevention program adoption. (Chapter 4; TRIPP Stages 3, 4 and 5). Finally, the 11+ program was implemented but modified (i.e. rescheduling components of the 11+ program) to explore strategies to improve program compliance (Chapter 5) and injuries incurred by the players throughout the entire 2017 football season were recorded using the same methods employed in Chapter 2. To determine the effect of rescheduling components on the efficacy of the 11+ program, injury data collected during Chapter 5 for the different intervention groups were also compared to baseline data (Chapter 2). As the study in Chapter
5 was performed as a randomized controlled trial rather than a “real world implementation” study, this chapter complies with Stage 4 of the TRIPP framework. Figure 1.1 outlines the framework for this project.
29
Chapter 1
Thesis aim To optimize the delivery and efficacy of the 11+ program delivery in sub-elite football TRIPP Stage
Chapter 2 Chapter 3 The incidence and burden of time loss Do niggles matter? Increased injury injury in Australian men’s sub-elite risk following physical complaints in Stage 1 & 2 football (soccer): a single season football (soccer) prospective cohort study
Stage 3 & 4* 11+ program selected due to established efficacy of the program
(*Already established)
Chapter 4 What do players, coaches and physiotherapists in men’s sub-elite football think of injury Stage 5 prevention and the 11+ program?
Chapter 5 Rescheduling Part 2 of the 11+ reduces injury burden and increases compliance in semi- professional football Stage 4
Thesis Outcomes Description of injury patterns and mechanism in sub-elite football and how to implement the 11+ program to reduce injury burden and increase compliance in semi-professional football
Figure 1.1. Schematic of thesis structure and how each component complies with the TRIPP framework, addressing the overall thesis aim.
30
Chapter 1
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professional football level than at national and amateur levels: does sports medicine and
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52. Hammes D, aus der Fünten K, Kaiser S et al Injuries of Veteran Football (Soccer)
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Benin City, Nigeria. Br J Sports Med 2009;43(5):382-386.
54. Emery CA, Meeuwisse WH. Risk Factors for Injury in Indoor Compared With Outdoor
Adolescent Soccer. Am J Sports Med 2006;34(10):1636-1642.
55. Emery CA, Meeuwisse WH, Hartmann SE. Evaluation of Risk Factors for Injury in
Adolescent Soccer: Implementation and Validation of an Injury Surveillance System.
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56. Herrero H, Salinero JJ, Del Coso J. Injuries Among Spanish Male Amateur Soccer
Players: A Retrospective Population Study. Am J Sports Med 2014;42(1):78-85.
57. Junge A, Rösch D, Peterson L et al. Prevention of Soccer Injuries: A Prospective
Intervention Study in Youth Amateur Players. Am J Sports Med 2002;30(5):652-659.
58. Peterson L, Junge A, Chomiak J et al. Incidence of football injuries and complaints in
different age groups and skill-level groups. Am J Sports Med 2000;28(S5):S51-7.
59. Brito J, Malina RM, Seabra A et al. Injuries in Portuguese Youth Soccer Players During
Training and Match Play. J Athl Train 2012;47(2):191-197.
60. Gilchrist J, Mandelbaum BR, Melancon H et al. A Randomized Controlled Trial to
Prevent Noncontact Anterior Cruciate Ligament Injury in Female Collegiate Soccer
Players. Am J Sports Med 2008;36(8):1476-1483.
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61. Silvers-Granelli H, Mandelbaum BR, Adeniji O et al. Efficacy of the FIFA 11+ Injury
Prevention Program in the Collegiate Male Soccer Player. Am J Sports Med
2015;43(11):2628-2637.
62. McNoe BM, Chalmers DJ. Injury in Community-Level Soccer: Development of an
Injury Surveillance System. Am J Sports Med 2010;38(12):2542-2551.
63. Schmikli SL, de Vries WR, Inklaar H, Backx FJ. Injury prevention target groups in
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Sci Med Sport 2011;14(3):199-203.
64. Soligard T, Myklebust G, Steffen K et al. Comprehensive warm-up program to prevent
injuries in young female footballers: cluster randomised controlled trial. BMJ
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65. Wik EH, Materne O, Chamari K et al. Involving research-invested clinicians in data
collection affects injury incidence in youth football. Scand J Sci Med Sports
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66. Ekegren CL, Gabbe BJ, Finch CF. Injury surveillance in community sport: Can we
obtain valid data from sports trainers? Scand J Sci Med Sports 2015;25(3):315-322.
67. Ekegren CL, Gabbe BJ, Donaldson A et al. Injuries in community-level Australian
football: Results from a club-based injury surveillance system. J Sci Med Sport
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68. Bjørneboe J, Flørenes TW, Bahr R, Andersen TE. Injury surveillance in male
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70. Bizzini M, Dvorak J. FIFA 11+: an effective program to prevent football injuries in
various player groups worldwide—a narrative review. Br J Sports Med 2015;49(9):577-
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72. Steffen K, Emery CA, Romiti M et al. High adherence to a neuromuscular injury
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73. Fernandes AdA, da Silva CD, da Costa It, Marins JCB. The “FIFA 11+” warm-up
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74. Thorborg K, Krommes KK, Esteve E et al. Effect of specific exercise-based football
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Programs for Soccer Players? A Systematic Review and Meta-Analysis. Sports Med
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77. O'Brien J, Finch CF. Injury prevention exercise programs in professional youth soccer:
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program: How to approach and convince the Football associations to invest in
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39 Chapter 2
Chapter 2 - The Incidence and Burden of Time Loss Injury in Australian Men’s
Sub-Elite Football: A Single Season Prospective Cohort Study
This chapter is an amended version of the published manuscript: Whalan M, Lovell R, McCunn
R, Sampson JA. The incidence and burden of time loss injury in Australian men’s sub-elite football (soccer): a single season prospective cohort study. J Sci Med Sport 2019;22(1):42-47.
The citations and references contained herein apply to this chapter only. The citations related to the reference list within this section only and not to the reference list included at the end of this thesis.
40 Chapter 2
Abstract
Objectives: This study aimed to conduct the first injury surveillance study in sub-elite football in Australia, using methods from the international football consensus statement.
Methods: 1049 sub-elite football players were recruited during the 2016 season. Injury and exposure data were collected by trained Primary Data Collectors (PDCs) who attended every training session and match.
Results: There were 1041 time loss injuries recorded during 52127 h of exposure resulting in an injury incidence rate of 20 injuries/1000 h (95% Confidence Interval [CI]: 15.9-23.3). The injury burden (days lost to injury relative to exposure) was 228 days lost/1000 h. Muscle and ligament injuries were the most prevalent (41% and 26%) and incurred the highest injury burden (83 and 80 days lost/1000 h, respectively). The most common injuries were observed at the thigh (22%) and ankle (17%), with hamstring (13%) the highest reported muscle injury.
The profile of injury severity was: mild – 35%; minor – 29%; moderate – 28% and severe –
8%. Recurrent injuries accounted for 20% of all injuries.
Conclusion: By addressing issues identified with injury recording in sub-elite football, this study found that the injury incidence was twice that observed in previous research in elite and sub-elite football cohorts. Injury burden was also twice that of the elite setting, with similar injuries associated with the highest burden. The results highlight the need for investment into medical provision, facilities, coach education and injury prevention programs to reduce healthcare costs to sub-elite players in Australia.
41 Chapter 2
2.1 Introduction
Football is Australia’s most popular sport with over 1.1 million participants.1 Below the only professional league (A-League; <1% of all Australian football participants), both National and regional league competitions include high level sub-elite (semi-professional and amateur) players who participate in three to four scheduled football sessions (training and competition) per week. In addition, sub-elite players are typically committed to other occupational employment or full-time education commitments, which can introduce additional stressors and strains.2 Despite the high participation rates and player participation profile, there has been no injury surveillance research performed in sub-elite football in Australia. Injury is often the reason a player discontinues sporting participation and can lead to long term disability and substantial medical costs3 and economic cost associated with employment absences.4 In alignment with Van Mechelen’s injury prevention model,5 accurate cohort specific surveillance is necessary to inform bespoke injury prevention programs. Thus, whilst injury prevention programs can reduce injuries in football by up to 39%,6 without cohort specific injury surveillance, the effectiveness and efficacy of injury prevention programs cannot be accurately determined.7
In 2006 a football consensus statement8 was developed to guide injury research and since publication, the majority of elite football injury surveillance studies have employed the methods as proposed within this statement.9-11 A number of injury surveillance studies in sub- elite football have stated that the methods used are consistent with the football consensus statement. However, there is often: (i) a lack of detail regarding what injury details are recorded and who collects the data,12 (ii) inconsistencies in the way playing/training exposure is recorded
13 and (iii) inconsistent injury definitions used.14 Meanwhile, due to a lack of resources in the sub-elite setting, studies that have strictly applied the consensus statement methods report difficulties when attempting to record minor (<7 day training/match absence) injuries.11, 15
42 Chapter 2
Additionally, despite research establishing the importance and value of recording injury burden in the elite setting,16 injury burden has is yet to be examined in the sub-elite setting.
Consequently, the inconsistences and methodological limitations in sub-elite injury surveillance studies make it difficult to compare the incidence and patterns of injury between sub-elite studies and elite cohorts.12, 17 Therefore translation of current elite injury prevention practices into sub-elite populations is somewhat limited.7
This study aimed to: (i) conduct the first injury surveillance study in sub-elite football in Australia, using methods that allow strict adherence to the international football consensus statement 8, 16 and, (ii) document injury burden16 in sub-elite football, which has implications for injury prevention strategies and practices.
2.2 Methods
2.2.1 Participant Recruitment
A prospective cohort study of 1049 players (age: 24.3 ± 6.2 years; stature: 178.6 ± 6.9 cm; body mass: 75.2 ± 11.2 kg) from 25 male sub-elite football clubs (each comprising ~ 2-3 teams) in New South Wales (Australia) was conducted over the 2016 season. The clubs consisted of four Tier 2 (National Premier League) and twenty-one Tier 3 (Regional League) clubs in which all players received financial incentive to play and were contracted to their club. The players participated in competitions that were the level directly below the full-time professional
Australian competition. With almost over 1.1 million players participating in football in
Australia,1 and the professional league (The A League) only having 11 teams, the performance level and quality of the sub-elite player is often quite high. Players all participated in a minimum of 3 scheduled team sessions/week (including 2 training sessions + match). Clubs and players were recruited via a number of methods including: direct contact with team medical staff; presentations to club officials and coaches; engagement with the Regional Association and contact with State and National Federations. Injury records were obtained during all
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training sessions (2-3 per week) and matches including preseason, in-season and finals (28-34 weeks). Prior to data collection, all players were fully informed of the study and provided signed consent. All procedures were approved by the University of Wollongong’s Ethics
Committee (reference number: 15/340).
2.2.2 Data Collection Definitions and Procedures
The football consensus statements’8 injury definitions and data collection procedures
(Appendix 1) were applied in this study. An injury was defined as “any physical complaint sustained by a player that results from a football match or football training”, whilst time loss injuries were defined as an “injury that results in a player being unable to fully participate in matches or training.” As per the football consensus statement, only time loss injuries were included for analysis. Players were deemed to have recovered from injury once they had returned to full training/match participation or were considered eligible for team selection. 8
A Primary Data Collector (PDC) at each club attended all training and match sessions to record football exposure and injury data via a standardised collection form (Appendix 2).8
Injury and exposure records were shared with the primary researcher on a weekly basis via a customised online data management platform. The use of a Primary Data Collector (PDC) at each club attempted to address the issues identified in performing injury surveillance in sub- elite football.17 The PDC was designated as the only person collecting injury and exposure data; they attended every training session and were present on match day to facilitate the capture of all injuries. Each PDC was required to obtain a Sports Trainers Level 1 certification, which is considered the national minimum medical qualification in Australia. Sports trainers have been used as PDCs in sub-elite Australian Rules Football injury surveillance18 and completed additional training with the lead researcher (an accredited physiotherapist) detailing how exposure (minutes) and injury details were to be recorded to comply with the football consensus.8 The PDC was educated on injury definitions and the process for recording detailed
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injury descriptions and, as per previous surveillance work,19 from the injury description, an injury diagnosis was later determined by an accredited physiotherapist using the Orchard
Sports Injury Classification System (OSICS-10.1).20 Additional groin pain subcategories of abdominal, adductor and iliopsoas related origin were added to provide a more in depth analysis of hip/groin pain presentation and to broaden the scope of the injury surveillance, allowing for comparison with recent literature. 21 Injuries that occurred late in the season were followed up by the PDC in order to determine a full recovery date.
2.2.3 Statistical Analysis
Injury incidence rate (± 95% Confidence Intervals [CI]) was calculated (total injuries / total exposure (hours) x 1000 hr), and the mean number of days lost per injury was recorded. Injury burden was calculated as the average number of days lost per injury relative to exposure.16 The frequency of injuries categorised by type, mechanism and location, are presented as absolute and relative values (percentage of total injuries). If players ceased participation, their individual exposure and injury was still included. Thus, no player data were lost because the injury data were normalised relative to exposure.
2.3 Results
A total of 1041 time loss injuries were recorded during 52127 hours (h) of exposure (training
= 40327 h and matches = 11800 h), resulting in a total injury incidence of 20 injuries/1000 h
(95% CI: 15.9 to 23.3). Matches incurred a 5-fold greater incidence of injuries (54 injuries/1000 h; 95% CI: 51.2 to 57.8) versus training (10 injuries/1000 h; 95% CI: 8.2 to 11.8). Individual player exposure for matches (11 h) and training (39 h) over the season resulted in a training exposure-to-match ratio of 3.6:1. Minimal (7 injuries/1000 h; 95% CI: 4.0 to 8.6), mild (5.8 injuries/1000 h; 95% CI: 4.2 to 7.1) and moderate injury (5.5 injuries/1000 h; 95% CI: 4.7 t0
6.8) severity classification were evenly distributed, and severe injuries (1.7 injuries/1000 h;
95% CI: 1.3 to 2.4) were relatively uncommon (Table 2.1). Injuries affecting the lower limb
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accounted for 86% of all injuries (Table 2.1), with the most common locations observed at the thigh (22%) and ankle (18%). The majority (82%; 16 injuries/1000 h) of injuries occurred as a result of a specific incident (i.e. trauma) and hamstring injuries (13%) were the most common muscle injury (Table 2.2).
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TABLE 2.1. Injury incidence pattern including location, type and mechanism. Total Minimal Mild Moderate (8- Severe (1-3 Days) (4-7 Days) 28 Days) (>28 days) Injury location Head/face 33 (3) 16 (4) 8 (3) 7 (2) 2 (2) Neck/cervical spine 10 (1) 3 2 4 (1) 1 (1) Shoulder/clavicle 21 (2) 3 7 (2) 6 (2) 5 (6) Sternum/ribs/upper back 18 (2) 8 (2) 5 (1) 4 (1) 1 (1) Abdomen 7 2 1 3 (1) 1 (1) Low back/sacrum/pelvis 34 (3) 19 (5) 9 (3) 5 (2) 1 (1) Hand/finger/thumb 17 (1) 6 7 (2) 4 (1) 0 Hip/groin 126 (12) 43 (12) 39 (13) 37 (13) 7 (8) Thigh 231 (22) 62 (17) 68 (22) 79 (27) 22 (25) Hamstrings 145 (14) 32 (9) 34 (11) 60 (20) 19 (22) Quadriceps 86 (8) 30 (8) 34 (11) 19 (7) 3 (3) Knee 167 (16) 57 (16) 46 (15) 45 (16) 19 (22) Lower leg/Achilles tendon 134 (13) 67 (18) 34 (11) 22 (8) 11 (13) Ankle 192 (18) 55 (15) 64 (21) 59 (20) 14 (16) Foot/toe 43 (4) 21 (6) 8 (3) 12 (4) 2 (2)
Injury type Fracture 21 (2) 3 2 6 (2) 10 (12) Other bone injury 12 (1) 4 4 (1) 4 (1) 0 Dislocation/subluxation 19 (2) 2 3 7(2) 6 (7) Sprain/ligament injury 270 (26) 80 (22) 79 (26) 80 (28) 31 (36) Meniscus/cartilage 27 (3) 6 (2) 13 (4) 7 (2) 1 (1) Muscle injury/strain 429 (41) 140 (38) 119 (39) 136 (47) 34 (39) Tendon injury 54 (5) 21 (6) 20 (7) 12 (4) 1 Haematoma/contusion 160 (15) 86 (24) 45 (15) 25 (9) 4 (5) Abrasion 6 4 (1) 2 0 0 Laceration 10 (1) 6 (2) 4 (1) 0 0 Concussion 15 (1) 5 (1) 3 (1) 6 (2) 1 (1) Other injury 20 (2) 5 (1) 9 (3) 5 (5) 1 (1)
Injury mechanism Non-contact 599 (58) 184 (31) 179 (30) 184 (31) 52 (8) Contact 442 (42) 180 (41) 123 (28) 104 (23) 35 (8) Recurrent 211 (20) 61 (29) 67 (32) 66 (31) 17 (8) Trauma 853 (82) 283 (33) 236 (28) 250 (30) 84 (9) Overuse 188 (18) 81 (43) 66 (35) 38 (20) 3 (2) Total injuries 1041 364 (35) 302 (29) 288 (28) 87 (8) Values within brackets show percentage of total values (below 1% not shown) Injury locations and types with <5 injuries are not shown
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TABLE 2.2. Muscle* and ligament injury incidence pattern, incidence and burden. Total Incidence 95% CI Injury Burden Average Days (/1000 h) (Days lost/1000 h) Lost/Injury Muscle Injury Hamstring muscle strain 138 (13) 3 2.4 to 3.4 38 14 Quadriceps muscle strain 43 (4) 1 0.8 to 1.2 8 9 Calf muscle strain 72 (7) 1.4 1.2 to 1.6 12 9 Hip/Groin Pain 102 (10) 2 1.7 to 2.3 21 11 Adductor Related 64 (6) 1.2 1.0 to 1.4 13 11 Iliopsoas Related 32 (3) 0.6 0.5 to 0.7 4 7 Abdominal Related 6 (1) 0.1 0.08 to 0.12 4 32 Recurrent muscle injury 81 (8) 1.6 1.5 to 1.7 20 13 Ligament Sprain Knee ligament sprain 82 (8) 1.6 1.4 to 1.8 39 25 ACL sprain 8 (1) 0.13 0.1 to 0.16 17 127 MCL sprain 43 (4) 0.8 0.6 to 0.1 15 18
Ankle ligament sprain 142 (14) 2.8 2.6 to 3.0 33 12
*Muscle injuries only include structural and functional injuries - exclude contusions, haematoma, tendon related injuries. Values within brackets show percentage of total all injuries (n=1041)
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An injury burden of 228 days lost/1000 h with an average of 11 days lost/injury was observed (Table 2.3). Muscle and ligament injuries resulted in the highest injury burden (83 and 80 days lost/1000 h, respectively), with the knee and thigh (53 and 48 days lost/1000 h, respectively) the most common locations. Injuries during match exposure resulted in a greater injury burden (160 days lost/1000 h) and mean time lost to injury (13 days) when compared to injuries associated with training exposure (68 days lost/1000 h; 9 days).
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TABLE 2.3. Injury burden of time loss injuries (injury incidence × mean absence per injury). Days Lost per 1000 hours Days Lost per Injury Injury location Head/face 5 8 Shoulder/clavicle 9 23 Sternum/ribs/upper back 3 8 Low back/sacrum/pelvis 4 6 Hip/groin 25 10 Thigh 48 10 Hamstring 36 13 Quadriceps 12 7 Knee 53 17 Lower leg/Achilles tendon 21 8 Ankle 43 11 Foot/toe 7 8 Injury type Fracture 15 37 Sprain/ligament injury 80 16 Meniscus/cartilage 5 10 Muscle injury/strain 83 10 Tendon injury 9 9 Haematoma/contusion 17 6 Concussion 3 11 Dislocation 8 29 Injury mechanism Non-contact 136 12 Contact 92 11 Recurrent 51 13 Trauma 203 13 Overuse 25 8 Injury event Match 160 13 Training 68 9
Total 228 11
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Non-contact injuries (136 days lost/1000 h) resulted in a greater injury burden compared to contact injuries (92 days lost/1000 h). Despite a relatively low injury incidence, knee ligament injuries resulted in a similarly high injury burden (39 days lost/1000 h) versus hamstring muscle (38 days lost/1000 h) and lateral ankle sprain (33 days lost/1000 h) injuries.
Recurrent injuries resulted in an injury burden of 50 days lost/1000 h and a time lost average of 13 days per injury.
2.4 Discussion
In this study, the incidence of injury (20 injuries/1000 h) was more than twice that previously reported in elite (8 injuries/1000 h)9 and sub-elite (9.6 injuries/1000 h)11 cohorts. Strict adherence to the consensus statement methods within this study captured a larger percentage of “mild” and “minimal” severity (<7 days’ time lost) injuries compared to previous sub-elite studies,11, 15 although the relative distribution of injury severity, types, mechanisms and locations were all similar to elite studies.9, 16 This study was the first to add injury burden to sub-elite injury surveillance. Injury burden was almost twice that seen in research conducted in the elite setting,16 albeit the same injuries (anterior cruciate ligament rupture, hamstring muscle strains, ankle sprains and muscle contusions) were associated with the highest injury burden.
2.4.1 Injury Incidence and Burden
In contrast to previous investigations,11 the injury incidence in this study was two times greater than that observed in the elite setting,9 whilst injury burden in the sub-elite setting was almost twice that observed in the elite setting.16 Indeed, there are a number of reasons why one might expect differences between sub-elite and elite cohorts that would result in a higher injury incidence and burden. Firstly, a lower training exposure (39 h/player) and training to match exposure ratio (3.6:1) was observed versus elite populations (213 h/player and 5.2:1,
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respectively)9, with matches yielding a higher intensity22 and injury incidence compared with training sessions.9, 11 Furthermore, whilst only field-based football exposure is included in the football consensus statement, elite teams often perform additional injury prevention and strength and conditioning (S&C) programs to complement on-field work.23 As such, the lower training-to-game ratio, reduced training exposure and a lack of injury prevention and S&C programs may not provide adequate physical readiness for match intensities in sub-elite football.24 Therefore, programs, such as the 11+ program, that have strong evidence for reducing injury risk in football 6 and can be delivered in the sub-elite setting, may have an important role in addressing these issues.
Secondly, lower player skill levels can present an increased injury risk25 as these players are less adept at avoiding injury scenarios involving direct contact that commonly result in contusion/haematoma injuries.26 Indeed, whilst time lost from direct impact injuries in this study was similar to elite football (≤7 days’ time loss),27 an incidence of 3 injuries/1000 h for contusion/haematomas was almost three times higher than previously observed in an elite setting (1.3 injuries/1000 h ).9 It is thus suggested that the methods adopted in this study, which resulted in a high capture of minor injuries, highlight a potential issue associated with low skill level in sub-elite football. Compounding this, sub-elite teams often play on surfaces with substantial signs of wear and tear, which can exacerbate the lower skill level,25 and potentially increase impact injuries and sprains. With respect to the cohort examined within this study, an increased risk of non-contact traumatic injury may also have been observed due to the warmer climate and firmer playing surface characteristics compared with European based sub-elite and elite cohorts.11,26, 28
Thirdly, a lack of access to medical staff (e.g. medical doctors, physiotherapists) in sub- elite football likely results in inadequate rehabilitation and return to play decisions that are solely coach and/or player driven, potentially leading to uninformed decisions on safe return
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to play. The lack of medical staff at training also typically reduces the ability to complete accurate injury reporting.18 However, the presence of a Sports Trainer at training and on match days to record injury in this study appears to have addressed this issue with a larger capture of injury data compared with previous sub-elite research. It is important to note that, in sub-elite football, it is common for a number of days to pass between scheduled sessions with no player- medical staff contact. Correspondingly, the methods utilised in this study may have overestimated time loss for minimal and mild injuries and presented an inflated incidence.17
As players were presumed injured until they were able to fully participate in training or a match, in some cases it is possible that there were 3 to 4 days between player-medical contacts, and may have increased time loss periods by 2 to 3 days. However, the effect of any overestimation is difficult to evaluate as an underreporting of injuries has been noted in previous research.12
2.4.2 Muscle Injuries
Despite the high injury incidence observed in this study, there were similarities in the injury patterns observed when compared with elite cohorts, with muscle injuries incurring the highest injury incidence and injury burden.9 The time loss (14 days) and relative occurrence (13% of all injuries) of hamstring injury was also similar to elite populations.29 The impact of hamstring injuries was further highlighted in this study by a burden three and four times higher than calf and quadriceps muscle injuries, respectively. Hip and groin injuries also presented at a similarly high incidence, burden and time loss per injury as the hamstring. The incidence of groin pain was twice that previously reported in elite30 and two to four times that in sub-elite11,21 populations. Hip/groin injuries were sub-group classified21 with a resultant incidence of adductor-related groin pain two times higher than iliopsoas-related, and ten times higher than abdominal-related groin pain, and a similar distribution to existing elite30 and sub-elite research.21 Adductor-related injury burden (13 days lost/1000 h) was similar to a recent elite cohort study30 despite a twofold higher groin injury incidence in this study. Whilst it has been
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suggested that higher level players are at more risk of hip and groin pain,30 the results of this study indicate that the prevalence of adductor-related groin pain at both sub-elite and elite levels is similar. These findings reaffirm that thigh and groin muscle injuries represent an injury challenge in both elite and sub-elite football, and suggest that in addition to a focus on thigh and ankle exercises, specific groin related exercises should also be included in injury prevention programs at the sub-elite level.
2.4.3 Ligament Injuries
Knee and ankle ligament injuries were the most common ligament injuries observed in this study and is consistent with previous research conducted in the elite setting.9 Knee ligament sprains were associated with player time loss more than twice that of a muscle injury, contributing to a ligament injury burden similar to muscle injury (80 and 83 days lost/1000 h) despite a lower injury incidence. The incidence and burden of ligament injury was also much higher in this cohort of sub-elite footballers when compared to reports in an elite setting. Lateral ankle sprain incidence was five times higher and injury burden 50% greater10 whilst incidence of anterior cruciate and medial collateral ligament (MCL) was two to three times greater than that observed in an elite setting.31
2.4.4 Injury Mechanism
Typically, the cause of all muscle and ligament injuries (82%; 15 injuries/1000 h) observed in this study were the result of a specific event (trauma). Trauma was the major cause (69%) of all non-contact injuries and resulted in a higher injury burden (136 days lost/1000 h) compared with contact injuries (92 days lost/1000 h). Indeed, trauma has been reported as the most common injury mechanism in previous research of sub-elite football.11 In contrast, overuse injuries appear more common in the elite setting.9 It should be considered, however, that higher football exposure/player in elite football9 may result in elite players being more susceptible to overuse injury and better access to medical services may facilitate overuse injury recording.11
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In this current study, recurrent injuries resulted in an injury burden twice that of overuse injuries, despite a similar injury incidence, with the mean days lost similar to that of non- contact and contact injuries. Interestingly, the incidence of recurrent injuries was two-four times higher than previous elite9 and sub-elite research, 11, 15 which we attribute to the increased number of minor (time loss <7 days) injuries captured. Indeed, most injuries (64%) in this study were classified as minor, substantially increasing the number of ‘initial’ injury events that may be defined as recurrent. Injury recurrence was also 50% higher in this study compared to “top level” Union of European Football Associations (UEFA) European elite cohorts, but similar to that seen in “high level” (Swedish Premier Division) teams.15 This difference is likely explained by improved medical resources and larger squad sizes at the “top level”.9, 16 Based on the prevalence and burden of recurrent injuries in sub-elite football, strategies to improve return to play policies are thus required, with the importance of minor injury data capture highlighted in this study.
2.4.5 Limitations
This study has shown a high injury incidence in sub-elite football; however, when considering the results, the limitations of this study should be acknowledged. Firstly, multiple PDCs at multiple clubs collecting the data may have presented a degree of extraneous variability. By conducting extensive training of the PDC cohort however, we aimed to minimise potential reporting differences and this ‘interclub’ variation would also be equally prevalent in any injury surveillance research involving multiple practitioners.12
Secondly, although the football consensus statement defines an injury as “any physical complaint”, only injuries that resulted in an inability to participate in training or matches are typically included for analysis.8 The accumulative nature of overuse injuries though, often leads to players with physical complaints continuing to fully participate in football, suggesting it is likely that overuse injuries account for a much larger injury prevalence than reported in
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this study.32 Furthermore, accumulated fatigue and injury from participation in other sports, recreational pursuits and work outside of football is not typically included in elite and sub-elite injury surveillance research, yet may impact on potential injury risk and incidence. Future research should therefore seek to incorporate methods to improve the capture of overuse injuries and non-football related workloads.
Thirdly, the individual player exposure to matches and trainings was 11 and 39 h, respectively. Over the course of a 28-34 week season this exposure is potentially quite low and indicates that many players may have had poor training attendance or left during the season for various reasons. As such it is possible that this poor exposure over-inflated the injury incidence observed in this chapter, however a lack of adequate training exposure may also suggest a potential mechanism for higher injury risk in the sub-elite population.
2.5 Conclusion
In this study a two-fold higher injury incidence and injury burden, and four-fold higher recurrence, was observed when compared to research in the elite and sub-elite football setting, yet the location, severity and mechanisms of injury were similar. Conseqeuently, adherence to the procedures outlined in the football consensus statement appears to improve injury surveillance in sub-elite football and should be adopted in future football injury research. The high injury incidence may be related to a number of factors including individual skill level, training availability and access to medical expertise in sub-elite cohorts. Potentially, improved coach education on ensuring physical readiness and safe return to play and improved access to medical resources, in addition to the implementation of injury prevention programs, may all be possible avenues to reduce injury incidence in sub-elite football. Overcoming barriers to, and improving, the implementation of injury prevention and rehabilitation programs is thus paramount to reducing the incidence and burden of injury in sub-elite football.
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2.6 Practical Implication
• The addition of a PDC to injury data collection in sub-elite football increases capture of
less severe injuries and improves injury surveillance.
• The pattern and severity distribution of injury is similar in elite and sub-elite football.
• The high incidence and burden of injuries emphasises the need to include programs, such
as the 11+ program, in sub-elite football.
• Particular focus should be applied to the prevention of knee, ankle and hamstring related
injuries due to their associated high injury burden.
• Additional coach education via the coaching curriculum to develop: (i) strategies to ensure
adequate player preparation, (ii) delivery of injury prevention programs, and (iii) return to
play policies, are warranted.
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2.7 References
1. FFA, Football Federation of Australia (FFA) National Audit. 2015.
2. Arlinghaus A, Lombardi DA, Willetts JL et al. A Structural Equation Modeling
Approach to Fatigue-related Risk Factors for Occupational Injury. Am J Epidem 2012;
176(7):597-607.
3. Andrew N, Gabbe BJ, Wolfe R et al. The impact of serious sport and active recreation
injuries on physical activity levels. Br J Sports Med 2011;45(4):335.
4. Schneider S, Seither B, Tönges S et al. Sports injuries: population based representative
data on incidence, diagnosis, sequelae, and high risk groups. Br J Sports Med
2006;40(4):334-339.
5. van Mechelen W, Hlobil H, Kemper H. Incidence, Severity, Aetiology and Prevention
of Sports Injuries: A Review of Concepts. Sports Med 1992;14(2):82-99.
6. Thorborg K, Krommes KK, Esteve E et al. Effect of specific exercise-based football
injury prevention programs on the overall injury rate in football: a systematic review
and meta-analysis of the FIFA 11 and 11+ programs. Br J Sports Med 2017;51(7):562-
571.
7. Finch, C. A new framework for research leading to sports injury prevention. J Sci Med
Sport 2006;9(1):3-9.
8. Fuller CW, Ekstrand J, Junge A. et al. Consensus statement on injury definitions and
data collection procedures in studies of football (soccer) injuries. Br J Sports Med
2006;40(3):193-201.
9. Ekstrand J, Hägglund M, Waldén M. Injury incidence and injury patterns in
professional football: the UEFA injury study. Br J Sports Med 2011;45(7):553-558.
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10. Ekstrand J, Hägglund M, Kristenson K et al. Fewer ligament injuries but no preventive
effect on muscle injuries and severe injuries: an 11-year follow-up of the UEFA
Champions League injury study. Br J Sports Med 2013;47(12):732-737.
11. van Beijsterveldt A, Stubbe J, Schmikli S et al. Differences in injury risk and
characteristics between Dutch amateur and professional soccer players. J Sci Med Sport
2015;18(2):145-149.
12. Hägglund M. Data collection procedures for football injuries in lower leagues: Is there
a need for an updated consensus statement? Science and Medicine in Football 2016;
1:1-2.
13. Silvers-Granelli H, Mandelbaum B, Adeniji O et al. Efficacy of the FIFA 11+ Injury
Prevention Program in the Collegiate Male Soccer Player. Am J Sports Med
2015;43(11):2628-2637.
14. Grooms DR, Palmer T, Onate JA et al. Soccer-specific warm-up and lower extremity
injury rates in collegiate male soccer players. J Athletic Training 2013;48(6):782-789.
15. Hägglund M, Waldén M, Ekstrand J. Injury recurrence is lower at the highest
professional football level than at national and amateur levels: does sports medicine
and sports physiotherapy deliver? Br J Sports Med 2016;50(12):751-758.
16. Hägglund M, Waldén M, Magnusson H et al. Injuries affect team performance
negatively in professional football: an 11-year follow-up of the UEFA Champions
League injury study. Br J Sports Med 2013;47(12):738-742.
17. McCunn R, Sampson JA, Whalan M et al. Data collection procedures for football
injuries in lower leagues: Is there a need for an updated consensus statement? Science
and Medicine in Football 2017;1(1):86-88.
18. Finch C, Lloyd D, Elliot B. The Preventing Australian Football Injuries with Exercise
(PAFIX) Study: a group randomised controlled trial. Inj Prev 2009;15(3):e1.
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19. Hammes D, Aus Der Fünten K, Kaiser S et al. Injuries of Veteran Football (Soccer)
Players in Germany. Research Sports Med 2015;23(2):215-226.
20. Orchard J, Rae K, Brooks J et al. Revision, uptake and coding issues related to the open
access Orchard Sports Injury Classification System (OSICS) versions 8, 9 and 10.1.
Open Access J Sports Med 2010;1:207-214.
21. Hölmich P, Thorborg K, Dehlendorff C et al. Incidence and clinical presentation of
groin injuries in sub-elite male soccer. Br J Sports Med 2014;48(16):1245-1250.
22. Thorpe RT, Strudwick AJ, Buchheit M et al. The tracking of morning fatigue status
across in-season training weeks in elite soccer players. Int J Sports Physiol Perform
2016;11(7):947-952.
23. McCall A, Carling C, Nedelec M et al. Risk factors, testing and preventative strategies
for non-contact injuries in professional football: current perceptions and practices of 44
teams from various premier leagues. Br J Sports Med 2015:49(9);583-589.
24. Stølen T, Chamari K, Castagna C et al. Physiology of Soccer: An Update. Sports Med
2005;35(6):501-536.
25. Murphy D, Connolly D, Beynnon B. Risk factors for lower extremity injury: a review
of the literature. Br J Sports Med 2003;37(1):13-29.
26. Azubuike SO, Okojie OH. An epidemiological study of football (soccer) injuries in
Benin City, Nigeria. Br J Sports Med 2009;43(5):382-386.
27. Ueblacker P, Müller-Wohlfahrt H-W, Ekstrand J. Epidemiological and clinical
outcome comparison of indirect (‘strain’) versus direct (‘contusion’) anterior and
posterior thigh muscle injuries in male elite football players: UEFA Elite League study
of 2287 thigh injuries (2001–2013). Br J Sports Med 2015;49(22):1461-1465.
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28. Orchard JW, Waldén M, Hägglund M et al. Comparison of injury incidences between
football teams playing in different climatic regions. Open Access J Sports Med
2013;4:251-260.
29. Ekstrand J, Hägglund M, Waldén M. Epidemiology of muscle injuries in professional
football (soccer). Am J Sports Med 2011;39(6):1226-1232.
30. Mosler AB, Weir A, Eirale C et al. Epidemiology of time loss groin injuries in a men’s
professional football league: a 2-year prospective study of 17 clubs and 606 players. Br
J Sports Med 2018;52(5):292-297.
31. Lundblad M, Waldén M, Magnusson H et al. The UEFA injury study: 11-year data
concerning 346 MCL injuries and time to return to play. Br J Sports Med
2013;47(12):759-762.
32. Clarsen B. Current severity measures are insufficient for overuse injuries. Science and
Medicine in Football 2017;1:1-2.
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Chapter 3 - Do Niggles Matter? Increased Injury Risk Following Physical
Complaints in Football
3.1 Preface
The results of Chapter 2 highlight the high time loss injury incidence and burden in sub-elite football, however to obtain a “true” injury overview the collection of non-time loss injuries is considered necessary.4 The prevalence and nature of overuse, non-TL injuries6 may provide further insight into the high injury incidence observed in Chapter 2. To achieve this at the sub- elite level, limitations to injury surveillance such as a lack of medical staff and recording resources9 must be addressed. Self-reported methods of injury surveillance offer a potentially effective solution.10 As yet, no research has investigated the non-TL injury profile in sub-elite football over an entire season. Therefore, given the importance of Stages 1 and 2 of the TRIPP model for the development of injury prevention strategies, the addition of non-time loss injury surveillance, in addition to the traditional time loss method, may prove to be of importance and enhance injury program design. Furthermore, investigating the link between non-TL injury as a potential risk factor for the development of a TL injury is a unique feature of the analysis.
Evidence of any association may provide practitioners with another tool to identify players at increased risk of injury.
This chapter is an amended version of the published manuscript: Whalan M, Lovell R,
Sampson JA. Do Niggles Matter? – Increased injury risk following physical complaints in football (soccer). Science and Medicine in Football 2019; doi.org/10.1080/24733938.2019.1705996.
The citations and references contained herein apply to this chapter only. The citations related to the reference list within this section only and not to the reference list included at the end of this thesis.
62 Chapter 3
Abstract
Objective: To determine the prevalence and impact of non-time loss injuries in sub-elite football.
Methods: 218 players completed the Oslo Sports Trauma Research Centre (OSTRC)
Questionnaire on Health Problems weekly during the 2016 season (35 weeks), recording the prevalence and impact of time loss (TL) and non-time loss (non-TL) injuries. TL injury and exposure were also collected by a third party as per the football consensus statement. The relative risk (RR) of a TL injury within 7 days of a self-reported non-TL injury was determined, with associated predictive power calculated.
Results: The risk of a TL injury was 3.6 to 6.9 higher when preceded by ‘minor’ and
‘moderate’ non-TL complaints, respectively, and good predictive power (22.0 – 41.8%) was observed (AUC range = 0.73 to 0.83). Compliant responders (80% of completed OSTRC questionnaires) showed a mean self-reported weekly injury prevalence (TL and non-TL combined) of 33% (95% CI – 31.4% to 34.6%) with 28% (CI - 26.4% to 29.6%) attributed to non-TL injury.
Conclusion: Over a quarter of players, on average, report a physical complaint each week that does not prevent them from participating in training or match play. A non-TL injury was shown to be useful in identifying individual players at an increased risk of a TL injury.
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3.2 Introduction
Accurate injury surveillance underpins effective injury prevention programs.1 However, in football injury research, whilst an injury is defined as “any physical complaint”,2 only time loss
(TL) injuries resulting in a failure to fully participate in training or matches are used to determine injury incidence and severity.3 It is acknowledged that excluding physical complaints that do not result in a TL injury may underestimate the true injury profile in football.4 The complex nature of injury suggests that as many contributing factors as possible should be considered during surveillance to improve the effectiveness of injury risk reduction strategies.5 Notably in overuse injuries, tissue failure may already be present before the development of pain and performance deficits, with dysfunction in a local area potentially impacting on pathology in neighbouring regions.6 As such, injury surveillance methods that capture all “physical complaints” may improve the sensitivity of injury surveillance7 and allow practitioners to consider the magnitude of the symptoms suffered alongside the burden associated with time loss injury.8
Such methods may be achieved in an elite setting where clubs have access to full-time medical staff and resources that allow thorough player monitoring and accurate injury surveillance. In the sub-elite setting however, there is often a lack of medical staff and recording protocols may need to be more adaptable.9 Self-reported data collection methods can improve injury data collection,10 increasing capture of physical complaints that do not result in training or match play absences (a non-TL injury), versus more commonly used TL only methods.11-14 However, little is known about the prevalence and impact non-TL injuries in football may have on more serious TL injury risk. This information may have particular importance in sub-elite, semi-professional environments, where the players’ primary source of income may be from non-football occupations, and the long term cost of injury can affect both the player’s health15 and financial status.16 Indeed, injuries in non-professional settings, such
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as a college, high school or university, are associated with a significant financial cost.17 The increasing costs associated with sporting injury has led to suggestions that the risk of injury may negate the positive health benefits associated with physical activity.18 It is therefore of paramount importance that practitioners continue to search for effective and easily implementable methods to reduce injury incidence.19
The current study therefore compared the prevalence and impact of “all physical complaints” in sub-elite, semi-professional football between self-reported and third party injury surveillance recording methods and further aimed to: (i) determine the relative risk of sustaining a TL injury within 7 days of reporting the presence (vs absence) of a reported non-
TL injury; and (ii) examine whether the presence of a non-TL injury, in isolation, is linked to injury occurrence. The null hypotheses were: (i) that the number of injuries reported with a self-reported questionnaire would be similar to the number recorded by a third party, and (ii) the relative risk of suffering a TL injury would be similar regardless of the presence or absence of a preceding self-reported non-TL injury.
3.3 Methods
3.3.1 Participants
Twenty-five teams from ten semi-professional football clubs volunteered to participate in the study during the 2016 season. Clubs were recruited from the NSW National Premier League and Illawarra Premier League in Australia (2nd and 3rd tiers of participation, respectively). All players participated in a minimum of three football-based sessions per week (training and match). Prior to data collection, all players were informed of the study and provided written informed consent. All procedures were approved by the University of Wollongong’s Ethics
Committee (reference number: 15/340).
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3.3.2 Time Loss Injury Data Collection.
Time loss injury data and individual exposure minutes (training and match) were collected in accordance with the methods outlined in Chapter 2, with injury defined as “any physical complaint”, and TL injury defined as an “inability to fully participate in football training or matches”.2 As in Chapter 2, to comply with the consensus methods, each club was assigned a
Primary Data Collector (PDC) holding a minimum medical qualification (Sports Trainer Level
1), a method that has been previously shown to be a valid and reliable means of collecting injury data.12, 20 The PDC attended all training and match sessions to record injury and exposure via standardised data collection forms (Appendix 2) and were provided with additional tuition by a qualified physiotherapist detailing injury description, definitions and recording exposure to comply with the Fuller et al. 21 consensus statement. No exposure data was recorded for players performing modified training or rehabilitation exercises at training. Players were considered no longer injured on their return to full training and deemed available for match selection.
3.3.3 Non-Time Loss Injury Data Collection.
The presence and impact of physical complaints on training/match participation, performance, volume and severity was assessed weekly (35 weeks) using the OSTRC Questionnaire on
Health Problems.22 The OSTRC Questionnaire was only used to record injury occurrence, an accumulated “injury score” was not calculated. A survey link was emailed to each player at the start of each week (www.surveymonkey.com) with instructions to complete prior to the first training session of the same week. Due to the “participation” focus in the Fuller et al.2 consensus statement for injury definition, the “participation” category of the OSTRC
Questionnaire was selected to be the primary category for analysis. A TL injury was recorded via the OSTRC Questionnaire when a report of “Cannot participate due to injury” was recorded. A non-TL injury was recorded when a player self-reported “full participation but
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with health problems” (minor) and “reduced participation due to health problems” (moderate) complaints. The impact of any non-TL injury reported was further assessed by its affect (minor or moderate) on performance, volume of training and perceived severity. Players reporting the presence of any injury (TL or non-TL) were required to record the location as per the Fuller et al.2 football consensus statement. Illnesses were also recorded by the OSTRC Questionnaire but were not included in the analysis for this study. All PDC’s, clubs and coaches were blinded to self-report responses.
To facilitate compliance, the questionnaire reminder was emailed the day after each weekly game and resent daily up until the first training session of the following week to any players that had not yet completed the questionnaire. The primary investigator then sent each
PDC a list of players who had not yet completed the questionnaire and they were asked to encourage players to complete the questionnaire online prior to the start of training.
3.3.4 Statistical Analysis
During analysis, PDC reported TL injuries were compared with self-reported questionnaire responses. Weekly non-TL or self-reported “complaints” from players fully participating in training were included in the analysis. Self-reports submitted by players engaged in modified training or rehabilitation were excluded from the relative risk (RR) analysis, but retained within prevalence calculations. In these cases, the player would be considered to be “injured” under the TL injury definition as they have an “inability to fully participate in football training or matches”,2 and the self-reported injury would relate to a pre-existing TL injury. Similarly, if a
PDC TL injury report was present in the absence of a player self-report in the preceding week, the TL injury was excluded from the relative risk (RR) analysis but included in the overall seasonal total for prevalence calculations.
The ‘normal’ risk of injury was determined by calculating the risk of a TL injury within
7 days of a self-report indicating “no physical complaints”. The RR of a TL injury occurring
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within 7 days of a non-TL ‘minor’ or ‘moderate’ complaint was calculated relative to the
‘normal’ injury risk. The risk of sustaining a TL injury at a specific location was also determined relative to the specific location of the self-reported non-TL complaint. To account for within-subject variance due to the repeated measures and potential unbalanced nature of the data set (differences in number of survey responses by players), a generalized estimating equation (GEE) analysis (SPSS v24, IBM, USA) was used to examine associations between
OSTRC questionnaire injury reports for each category and occurrence of time loss injury within
7-days. Specifically, a binary logistic regression model (link function) was used, including a robust estimator with an autoregressive working correlations matrix and an independent model category. The predictor variable was the OSTRC value for that week, which was coded as an ordinal variable and included in the model as a Factor. That is, for the participation category, full training with no health problems = 1, full training but with health problems = 2; reduced participation due to health problems = 3; Cannot participate due to health problems = 4. ‘Full training with no health problems’ was used as the reference category. The response/dependent variable was the injury indicator represented ordinally (0 = no TL injury within 7 days/1 = TL within 7 days), modelled as a Binary logistic. Exponential parameter estimates were included to calculate odds ratio values to determine the relative effects of reporting a 2 or 3 (compared to reporting a 1) on the OSTRC health questionnaire on the risk of sustaining a subsequent time-loss injury (within 7 days). In the event of a missing questionnaire response, this week was excluded from analysis regardless of whether or not a TL injury was recorded in the following 7-day period. Where significance was observed, sub-category analysis with RR
(95% CI) were calculated and resultant p values used to calculate the likelihood of a harmful effect statistic, accompanied by relevant probabilistic terms to describe the clinical inference ranging from “most unlikely to be harmful <0.5%” to “most likely to be harmful >99.5%”.23
The predictive power of a non-TL complaint on the occurrence of a TL injury was examined
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using receiver operating characteristic (ROC) curves. The area under the curve (AUC) was used to determine discriminatory power, with values < 0.5, > 0.7, and 1.0 considered as poor, good, and perfect, respectively.24 Diagnostic accuracy and predictive power (95% CI) were also determined via sensitivity and specificity analysis of minor and moderate complaint sub- categories of the OSTRC Questionnaire.
OSTRC questionnaire response rates of 80% have previously been observed in athletic groups.22, 25 To accurately assess the effects of minor and moderate injury reports, a sub-group analysis of players with >80% response rates across the season was performed. Initially, the results of the GEE, RR and predictive characteristics of the sub-group and entire cohort were compared. In the event that both groups were statistically similar, an absence of bias was assumed and further analysis of the sub-group performed to assess the frequency of injury and reported weekly injury locations relative to PDC reports. Data are presented as absolute and relative values. Weekly injury prevalence was determined by calculating the percentage of injury reports relative to the total number of players participating that week.
3.4 Results
3.4.1 Relative Risk and Time-loss Injury Prediction
A total of 218 players (age: 24.1 ± 4.3 years; height: 177.1 ± 5.2 cm; weight: 74.9 ± 6.2 kg) participated in the study. A total of 3430 questionnaires were completed over the 35-week period (45% overall compliance, mean = 98 [95% CI – 88.1 to 110.2] completed questionnaires each week). The risk of sustaining a TL injury within 7-days of self-reported “no health problems” was 6%. OSTRC Questionnaire perceived minor and moderate effects on participation, performance, volume and severity were each associated (P<0.05) with an increased relative risk of TL injury within 7-days (Table 3.1). The power of a reported non-TL injury to predict the incidence of a TL injury within 7-days was good across all OSTRC categories (Table 3.1). Sensitivity, specificity and positive predictive power values are
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displayed in Table 3.2. A cohort of 73 (33%) players completed >80% of the weekly questionnaires (mean = 28.5 [CI: 26.2 to 31.3] each week) to form the sub-group. In this sub- group of players, the risk of TL injury within 7-days of “no health problems” was 9%. The associated injury risk and prediction results for the sub-group are also reported (Tables 3.1 and
3.2).
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TABLE 3.1. Associated injury risk and injury prediction using the OSTRC Questionnaire on Health Problems22 for time loss injury for entire cohort and sub-group. Entire Cohort (n=218) Association Prediction OSTRC Category P level Relative Risk (RR)* Clinical Inference23 Area Under the Curve Ɨ Participation <0.0001 0.79 (CI: 0.76 to 0.82) Full Participation with Problems 3.3 (CI: 2.0 to 5.8) 93.5% - likely harmful 0.75 (CI: 0.70 to 0.80) Reduced Participation Due to Health 6.5 (CI: 3.7 to 8.9) 100% - most likely harmful 0.79 (CI: 0.74 to 0.84) Problems Performance <0.0001 0.79 (CI: 0.75 to 0.83) To a minor extent 4.0 (CI: 1.9 to 9.3) 93.1% - likely harmful 0.77 (CI: 0.72 to 0.83) To a moderate extent 5.5 (CI: 3.2 to 9.4) 100% - most likely harmful 0.80 ( CI: 0.75 to 0.84) Volume <0.0001 0.77 (CI: 0.74 to 0.80) To a minor extent 4.4 (CI: 1.9 to 5.7) 100% - very likely harmful 0.75 (CI: 0.71 to 0.79) To a moderate extent 6.9 (CI: 3.2 to 10.1) 100% - very likely harmful 0.74 (CI: 0.70 to 0.78) Severity <0.0001 0.73 (CI: 0.69 to 0.76) To a minor extent 4.7 (CI: 0.01 to 11.7) 63.4% - possibly harmful 0.69 (CI: 0.65 to 0.74) To a moderate extent 4.8 (CI: 1.1 to 15.0) 99.2% - likely harmful 0.72 (CI: 0.67 to 0.76) Sub Group** (n=73) Participation <0.0001 0.83 (CI: 0.80 to 0.86) Full Participation with Problems 2.8 (CI: 1.01 to 7.8) 95.2% - likely harmful 0.79 (CI: 0.73 to 0.84) Reduced Participation Due to Health 5.2 (CI: 2.7 to 9.9) 100% - most likely harmful 0.83 (CI: 0.78 to 0.88) Problems Performance <0.0001 0.82 (CI: 0.79 to 0.85) To a minor extent 3.2 (CI: 1.01 to 10.3) 94.6% - likely harmful 0.80 (CI: 0.76 to 0.84) To a moderate extent 5.4 (CI: 2.78 to 10.4) 100% - most likely harmful 0.83 (CI: 0.79 to 0.87) Volume <0.0001 0.78 (CI: 0.75 to 0.82) To a minor extent 3.5 (CI: 1.9 to 6.7) 99.9% - very likely harmful 0.75 (CI: 0.70 to 0.80) To a moderate extent 5.9 (CI: 3.6 to 9.4) 100% - most likely harmful 0.72 (CI: 0.66 to 0.77) Severity <0.0001 0.78 (CI: 0.75 to 0.82) To a minor extent 3.6 (CI: 0.01 to 10.7) 64.3% - possibly harmful 0.68 (CI: 0.62 to 0.75) To a moderate extent 5.2 (CI: 1.82 to 15.0) 99.5% - very likely harmful 0.77 (CI: 0.73 to 0.81) *RR of a 3rd party reported TL injury within 7-days of the non-TL injury report within each category (95% confidence intervals) **Sub-group inclusion determined by >80% completion of OSTRC Questionnaire surveys during the season. Ɨ Area under the curve based on ROC curve analysis for each category for prediction of a time loss in 7-days following a physical complaint (95 % confidence interval).
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TABLE 3.2. Diagnostic accuracy assessment for OSTRC Questionnaire on Health Problems22 for each sub-category drawn from entire cohort and sub-group. OSTRC Questionnaire True False False True Sensitivity (%) with 95% Specificity (%) with 95% Positive Predictive Value Category Positive Positive Negative Negative CI CI (%) with 95% CI (n) (n) (n) (n) Entire Cohort (n=218) Participation Full participation with problems 67 237 0 14 100.0 (100) 5.6 (2.2 to 7.1) 22.0 (19.4 to 24.8) Reduced participation due to health problems 82 156 0 2 100.0 (100) 1.3 (0.2 to 3.1) 34.5 (31.6 to 39.3) Performance To a minor extent 93 277 0 15 100.0 (100) 5.1 (2.8 to 7.3) 25.1 (21.9 to 30.0) To a moderate extent 56 102 0 4 100.0 (100) 3.8 (2.1 to 7.9) 35.4 (30.3 to 40.9) Volume To a minor extent 74 203 0 8 100.0 (100) 3.8 (1.9 to 4.9) 26.7 (21.2 to 31.9) To a moderate extent 48 72 0 10 100.0 (100) 2.9 (1.8 to 4.1) 35.5 (30.2 to 41.8) Severity To a minor extent 101 253 0 15 100.0 (100) 5.6 (2.1 to 7.3) 28.5 (23.7 to 31.5) To a moderate extent 51 128 0 4 100.0 (100) 3.0 (1.1 to 5.1) 28.5 (25.9 to 30.2) Sub-Group (n=73) Participation Full participation with problems 64 196 0 36 100.0 (100) 15.5 (10.9 to 20.2) 24.6 (19.4 to 29.8) Reduced participation due to 75 120 0 25 100.0 (100) 17.2 (11.1 to 23.4) 38.5 (31.6 to 45.3) health problems Performance To a minor extent 85 219 1 51 98.8 (96.6 to 100) 18.9 (14.2 to 23.6) 28.0 (22.9 to 33.0) To a moderate extent 51 81 0 14 100.0 (100) 14.7 (7.6 to 21.9) 38.6 (30.3 to 46.9) Volume To a minor extent 70 163 0 37 100.0 (100) 18.5 (13.1 to 23.9) 30.0 (24.2 to 35.9) To a moderate extent 48 72 0 10 100.0 (100) 12.2 (5.1 to 19.2) 40.0 (31.2 to 48.8) Severity To a minor extent 92 203 1 54 98.9 (96.8 to 100) 21.0 (16.0 to 26.0) 31.2 (25.9 to 36.5) To a moderate extent 50 85 0 26 100.0 (100) 23.4 (15.5 to 31.3) 37.0 (28.9 to 45.2)
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3.4.2 Sub-group Relative Risk and Time-loss Injury Prediction
The magnitude of the increase in risk (RR) and predictive capacity for future TL injury were similar for the sub-group and entire cohort (Table 3.2). The total number of reported “physical complaints” was 2.3 times greater when comparing self-reported versus PDC methods (n=604 versus 265). Within the self-reports, non-TL injuries were 13.2 times (516 versus 39) higher, however, TL injuries were 2.6 times lower (88 versus 226) when compared to PDC data (Table
3.3). The proportion and distribution of injuries were similar between methods, with 87%
(PDC) and 83% (self-reported) of all injuries affecting the lower limb. The most common locations were the hamstring muscles (17% - PDC; 16% - self report) and knee (19% - PDC;
17% - self report; Table 3.3.3). Overall, 68% of all TL injuries were preceded by a non-TL report, with 94% of knee and 90% of hamstring TL injuries preceded by a non-TL complaint in the same location. The greatest risks were observed in the ankle and lower leg (RR=6.8 and
6.3, respectively; Table 3.3). As players were able to report multiple locations per survey, there were more injury locations than injury reports recorded via the OSTRC Questionnaire (Table
3.3).
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TABLE 3.3. Sub-group time-loss injury reports and associated relative risk following a previous physical complaint. Data are presented according to location using third party (Football Consensus) 2 and self-reporting method (OSTRC Questionnaire on Health Problems). 22 Football Consensus OSTRC Participation Category Injury Location Time Loss – 3rd Party Total – Self Non-Time Relative Risk (RR)* Clinical Inference23 Factor – Non- Method Report Loss – Self Time Report Loss/Time Loss** Head/face 6 (3) 4 2 - Neck/cervical spine 2 11 (1) 11 (1) - Shoulder/clavicle 3 (1) 18 (2) 14 (2) - Sternum/ribs/upper back 3 (1) 27 (3) 23 (3) - Hand/finger/thumb 4 (2) 16 (2) 15 (2) - Wrist 1 0 0 - Low back/sacrum/pelvis 11 (5) 76 (9) 69 (9) 1.9 (CI: 0.2 to 19.5) 64.8% - possibly harmful 6.3 Hip/groin 26 (12) 138 (16) 128 (17) 3.5 (CI: 2.4 to 5.2) 100% - most likely harmful 4.9 Thigh 64 (28) 189 (22) 163 (21) 5.2 (CI: 2.2 to 12.5) 99.8% - most likely harmful 2.5 Hamstring 39 (17) 136 (16) 116 (15) 4.7 (CI: 2.0 to 11.0) 99.7% - most likely harmful 3.0 Quadriceps 25 (11) 58 (7) 52 (7) 5.8 (CI: 1.4 to 24.9) 96.9% - most likely harmful 2.1 Knee 43 (19) 149 (17) 122 (16) 3.6 (CI: 2 to 6.1) 100% - most likely harmful 2.8 Lower leg/Achilles tendon 28 (12) 89 (10) 78 (10) 6.3 (CI: 0.1 to 375.8) 75.7% - likely harmful 2.8 Ankle 22 (10) 59 (7) 52 (7) 6.8 (CI: 0.1 to 376.0) 77.1% - likely harmful 2.4 Foot/toe 10 (4) 38 (4) 36 (5) 1.3 (CI: 1.1 to 1.5) 96.2% - very likely harmful 3.6 Total Injury Reports 226 604 516 2.3 Total Injury Locations 226 871 771 *RR - of a third party reported time loss injury occurring within 7 days following a self-reported non-time loss injury (determined on injuries with prevalence ≥5%; 95% confidence intervals. Normal risk = 10%) ** Factor = Total Non-time loss injury via OSTRC Questionnaire/Total Time Loss via Football Consensus (only locations with >10 time loss injuries included). Values within brackets show percentage of total injury locations (below 1% not shown)
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3.4.3 Sub-group Weekly Injury Prevalence
Self-reports highlighted 33% (95% CI – 31.4% to 34.6%) of all players recorded an injury
(comprising TL and non-TL injuries) each week with non-TL complaints accounting for 28%
(95% CI - 26.4% to 29.6%) of all weekly injuries (Figure 3.1A). Combining self-reported non-
TL and PDC recorded TL injury reports indicated that 49% (95% CI – 47.0% to 51.0%) of players were affected by injury each week (Figure 3.1B).
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Figure 3.1. Prevalence of all injuries (dark grey) and non-TL only injuries (light grey) recorded by the weekly self-reported injury OSTRC Questionnaire on Health Problems22 (A); and combining both injury surveillance methods – Self-reported and Third Party (B).
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3.5 Discussion
To our knowledge, this is the first study to investigate the impact and prevalence of non-TL injuries in semi-professional men’s football. Across the cohort of 218 players, the TL injury risk within 7 days of a self-reported minor or moderate non-TL injury (complaint) affecting performance, participation, volume or perceived severity was three to seven times greater compared to the absence of any complaint. Uniquely, a non-TL report across all four categories presented “good” injury prediction capacities of sustaining a TL injury within the subsequent
7-days. A comparison of PDC and self-reports in the compliant group indicated a total injury prevalence more than two times higher within the self-reports. As similar injury risks and predictive capacities were observed in compliant and non-compliant groups, to facilitate a detailed analysis of the results, the discussion relates to the findings of the compliant sub-group
(n=73). Based on the findings in this study, both null hypotheses are rejected.
3.5.1 Importance of Non-Time Loss Injuries
In this study, most (85%) recorded OSTRC Questionnaire complaints were non-TL and did not prevent participation. Our results thus highlight that including non-TL injuries substantially increases the prevalence of “slight” (0-1 day TL) injuries (‘physical complaints’) in semi- professional football.26 Previously, congested match fixtures have been associated with a third of players reporting groin pain on a weekly basis.25 However, to our knowledge, our study is the first prospective study in semi-professional football to be conducted over an entire season and record all injury locations. Therefore, given the duration of the TL and non-TL injury capture, our findings highlight a more comprehensive injury profile in semi-professional football than previously reported.
Previously, the need to record non-TL injuries has been questioned due to concerns over obtaining accurate and useful data.27 However, the results of the current study in semi- professional football, show a non-TL physical complaint to be associated with a 2.8-5.9 fold
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increase in the risk of sustaining a TL injury risk within the subsequent 7 days. Determining why this increased risk exists is likely to be multifactorial and dependent on the origin of the player’s pain and physical discomfort.15, 28 The presence and perceived impairment (minor or moderate) resulting from a complaint, is likely to reflect the presence of perceived pain.
Importantly, the risk of a TL injury within 7 days of a reported complaint increased with elevated perception of “pain” severity. The presence of pain alters motor patterns and muscle recruitment behavior,29 which may affect performance capacity and contribute to the more serious injury risk we observed. Pain that leads to a “physical complaint” may originate from a number of pathological issues30 and the high prevalence observed in this study reveals the pain-related issues that players in semi-professional football experience on a weekly basis.
Issues associated with pain, long term medication use and the development of chronic pain conditions in elite athletes15 have been identified, with the long term health of ex-professional football players impacted by osteoarthritis-related pain.31 When interpreting our results it is, however, important to consider that pain is often associated with sporting injury,32 may be present in the absence of physiological or biomechanical pathology and can continue after damaged tissue has healed.30 Furthermore, athletes are known to have a greater capacity to perform and participate despite pain compared with non-athletes,33 and pain may be a by- product of the normal process of a physiological overload stimulus and ensuing fatigue.34
Regardless of the pathology, mechanism or origin of pain, this study highlights that the presence of a non-TL injury clearly increased the risk of a subsequent TL injury and suggests that reporting non-TL injuries may be an important consideration for coaches, players, and medical and performance staff in semi-professional football.
Our findings thus support research that suggests the complexity of injury should be considered when describing the injury “problem” and the multifactorial aetiology of incidence.5, 28 In this study, self-reports increased the detail of an injury occurrence and
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encapsulated symptom severity and provided insight into the physical state of a player preceding a more severe injury resulting in TL. Therefore, our findings demonstrate a simple method to enhance the first stage of the injury prevention cycle illustrated by van Mechelen.1
3.5.2 Another Tool in the Injury Reduction Box?
The complex and multifactorial nature of injury28 challenges practitioners and researchers to search for tools that identify players at increased risk of injury, and to implement methods to mitigate this risk.35 The results of this study suggest that the OSTRC Questionnaire may assist in identifying high risk players in semi-professional football. Indeed, improving communication between key stakeholders within a club can reduce injury incidence and sustain player availability.36
Uniquely, the presence of a non-TL injury in this study displayed “good” predictive power for future injury, suggesting that non-TL injuries or “complaints” can classify “high risk” players who may require an injury risk reduction intervention.37 The strong associations observed between non-TL reports preceding a TL injury in the same location (Table 3.3), suggest it may also be possible to identify location specific injury risks. However, the current research does not allow us to accurately determine whether the TL injury suffered was a direct result of a worsening of an issue in the same location or related to a separate issue in a different location. Notably, all OSTRC questions were associated with identifying at risk players to similar degrees, suggesting that a single question could be equally effective. Reducing questionnaire burden may also facilitate compliance. The positive predictive values of 24.6 to
40% (increasing as reported symptom severity increased) associated with the risk of injury was substantially greater than the 1.8 to 3.8% workload-related risks observed in professional football.38 However, whilst good at capturing players at increased risk (high sensitivity), considering the presence of non-TL injury for the prediction of a TL injury resulted in a high number of false positive results (low specificity). Considering non-TL injury reports in
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isolation to predict injury is not recommended; however, using the OSTRC Questionnaire as an early identification tool to prevent minor injuries progressing to more significant ones, i.e. a secondary prevention tool, may be beneficial. As such, a non-TL complaint may be considered as a ‘flag’ to open player-coach/medical staff communication and assist in injury risk reduction.
3.5.3 Football Consensus Method vs OSTRC Questionnaire on Health Problems
Despite the lower capture of TL injury data, 2.3 times more total physical complaints were captured using the OSTRC Questionnaire, with a third of players reporting a physical complaint of varying severity each week. Our findings thus suggest that the Football Consensus method of injury surveillance underestimates the number of “slight” (0-1 day TL) injuries sustained in semi-professional football and is consistent with previous research.25 This result is likely a consequence of methods that rely on players reporting injuries to a medical staff member.2 In professional sport, reporting medical complaints is perceived to be an issue,39 and is likely exacerbated in semi-professional sport due to decreased medical access.26 The increased prevalence of self-reported non-TL injuries observed in this study was thus a likely consequence of providing the opportunity to report complaints indirectly.13
Despite the increased prevalence of non-TL injuries observed within self-reports recorded, PDC’s in this study recorded >2.5 times the number of TL injuries compared with self-reports. The consistent capture of this TL injury data is essential to determine severity profiles and burden associated with injury8 and our results thus also highlight the importance of third-party injury surveillance methods. There are a number of possible explanations for the observed TL report discrepancy: (i) an injured player who did not attend at training that week may have failed to complete the survey; (ii) players may have perceived TL injury disclosure may affect their eligibility for selection40 and (iii) player and PDC definitions of time-loss may have differed e.g. a player in modified training may perceive they have returned to play, yet
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the PDC worked under a definition of returning to full training.39 The third party method of TL injury recording outlined in the football consensus2 thus better facilitates thorough TL injury recording with a consistent injury definition and addresses the limitations associated with questionnaire compliance. Overall, this study indicates that the recording method, self-reported or third party, can have an impact on the results recorded. As such, a combination of both methods may be necessary to ensure complete injury data capture.
3.5.4 Limitations
Despite the clear association between non-TL injuries and occurrence of a TL injury in this study, a number of limitations should be acknowledged. The low compliance rate of players
(33%) completing the weekly survey in this study highlights a potential barrier for the use of the OSTRC Questionnaire for both injury surveillance and as a potential risk identification tool.
This issue has also been observed in other athletes with survey compliance over 12 weeks reported as 52% (24/46 players).13 Given the similarity of the results we observed between the entire cohort and the sub-group, we do not believe that there is an issue in generalising our results on a larger scale. However, methods to improve buy-in to self-reported player monitoring methods are required. Adopting smartphone technology may improve compliance13, 25 and allow sessional or daily application of the survey.
The delivery design of the OSTRC Questionnaire presents a limitation to the use of the questionnaire for injury “prediction” with multiple injury locations able to be recorded each week. Whilst 90% of all TL hamstring injuries in this study were preceded by a non-TL hamstring complaint, 33% of these preceding complaints included more than one location, and it has been suggested that pain at locations distal to a TL injury site may impact on future injury risk.6 As such, it is not possible to conclusively determine whether the subsequent TL hamstring injury was always a progression of the reported non-TL hamstring injury, or was related to the non-TL injury in a different location. To further evaluate the efficacy of using
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the OSTRC Questionnaire for injury prediction, more frequent application is necessary.
We also acknowledge that differences in: (i) coaching styles,41 (ii) previous injury history and physical fitness levels35 and (iii) workloads preceding a TL injury38 were each uncontrolled extraneous variables that may have impacted upon TL injury risk and non-TL injury prevalence that were not considered in the analysis. Additionally, the translation of the findings from this study to the professional setting may be limited. In the professional setting, players are likely to be monitored more closely than in semi-professional football. However, the results may suggest that the use of changes in pain reports commonly collected in daily monitoring in the professional setting,42 may have potential in secondary injury prevention strategies and requires further investigation. Finally, the treatment received by players for non-
TL injuries or TL injuries was not monitored and it is possible that players may have had access to differing medical provision. Furthermore, players who received treatment may have “self- reduced” their injury risk by addressing non-TL complaints.
There are limitations to a direct comparison between the two injury recording methods used in this chapter. For example, a non-TL injury that results in a self-reported “reduced participation” in training should be considered as a TL injury according to the football consensus statement. In this cohort of sub-elite, semi-professional players, it is possible that players may have self-reduced their involvement at training, for example, not completing all running drills, but participated in all other activities. As they would have been on the training field and “involved” they may have be classified as “fully participating” by the PDC if this modification to training was not reported to them by the coach or player.
3.6 Conclusion
In this study, the OSTRC Questionnaire combined with Football Consensus third party methods substantially improved injury surveillance, which may assist in injury risk reduction program design. Weekly non-time loss physical complaints were high in semi-professional
82 Chapter 3
football with 49% of all players affected by a physical complaint of varying severity (TL or non-TL) each week. TL injury risk was 3 to 6 times higher when preceded (<7days) by self- reported non-TL physical complaints that had minor and moderate impacts on participation, performance, training volume or perceived severity. Importantly, the presence of a non-TL injury had good injury prediction capacity for the incidence of a TL injury within the following week.
The findings in this chapter further adds to the knowledge obtained in Chapter 2 regarding the injury profile in sub-elite football. Importantly, the findings in this chapter not only provide a more comprehensive injury profile than that in Chapter 2 but also identifies a potential secondary prevention measure to identify players at increased risk of injury in this population. Given the high TL injury incidence observed in Chapter 2, the findings in this chapter suggest that the inclusion of non-TL injury surveillance serves as a very useful tool in sub-elite football.
3.7 Practical Implications
• Different injury data collection methods result in different information being collected.
As such, the combination of third party and self-report injury reporting methods greatly
increases the capture of injury data in semi-professional football.
• The presence of a non-TL injury is associated with an increased risk of a TL injury and
good predictive power relative to a future TL injury occurrence.
• The OSTRC Questionnaire on Health Problems, in addition to improving injury
surveillance, is a useful tool for secondary injury prevention, as an early identification
tool to prevent minor injuries progressing to more significant ones.
• The similar results observed across each of the four OSTRC Questionnaire categories
suggests that a single question may sufficiently identify high risk players, a strategy
83 Chapter 3
that might facilitate player compliance.
84 Chapter 3
3.8 References
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of Sports Injuries: A Review of Concepts. Sports Med 1992;14(2): 82-99.
2. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury definitions and
data collection procedures in studies of football injuries. Br J Sports Med
2006;40(3):193-201.
3. Ekstrand J, Hägglund M, Waldén M. Injury incidence and injury patterns in
professional football: the UEFA injury study. Br J Sports Med 2011;45(7):553-558.
4. Clarsen B. Current severity measures are insufficient for overuse injuries. Science and
Medicine in Football 2017;1(1):91-92.
5. Bolling C, van Mechelen W, Pasman HR, Verhagen E. Context Matters: Revisiting the
First Step of the ‘Sequence of Prevention’ of Sports Injuries. Sports Med
2018;48(10):2227-2234.
6. Wilke J, Vleeming A, Wearing S. Overuse Injury: The Result fo Pathologically Altered
Myofascial Force Transmission? Exerc Sport Sci Rev 2019 47(4): 230-236.
7. Clarsen B, Bahr R. Matching the choice of injury/illness definition to study setting,
purpose and design: one size does not fit all! Br J Sports Med 2014;48(7):510-512.
8. Bahr R, Clarsen B, Ekstrand J. Why we should focus on the burden of injuries and
illnesses, not just their incidence. Br J Sports Med 2018;52(16):1018-1021.
9. Finch CF. Injury data collection in lower leagues needs to be targeted specifically to
those settings. Science and Medicine in Football 2017;1(1):89-90.
10. Gallagher J, Needleman I, Ashley P, Sanchez RG, Lumsden R. Self-Reported Outcome
Measures of the Impact of Injury and Illness on Athlete Performance: A Systematic
Review. Sports Med 2017;47(7):1335-1348.
85 Chapter 3
11. Clarsen B, Myklebust G, Bahr R. Development and validation of a new method for the
registration of overuse injuries in sports injury epidemiology: the Oslo Sports Trauma
Research Centre (OSTRC) Overuse Injury Questionnaire. Br J Sports Med
2013;47(8):495-502.
12. Ekegren CL, Gabbe BJ, Finch CF. Injury surveillance in community sport: Can we
obtain valid data from sports trainers? Scand J Med Sci Sports 2015;25(3):315-322.
13. Møller M, Wedderkopp N, Myklebust G, et al. Validity of the SMS, Phone, and medical
staff Examination sports injury surveillance system for time-loss and medical attention
injuries in sports. Scand J Med Sci Sports 2017;28(1):252-259.
14. Langhout R, Weir A, Litjes W, et al. Hip and groin injury is the most common non-
time-loss injury in female amateur football. Knee Surg Sports Traumatol Arthrosc
[Internet] 2018 [cited 2 June 2018] doi: 10.1007/s00167-018-4996-1
15. Hainline B, Derman W, Vernec A, et al. International Olympic Committee consensus
statement on pain management in elite athletes. Br J Sports Med 2017;51(17): 1245-
1258.
16. Lee AJ, Garraway WM. Epidemiological comparison of injuries in school and senior
club rugby. Br J Sports Med 1996;30(3):213-217.
17. Fair RC, Champa C. Estimated Costs of Contact in College and High School Male
Sports. J Sports Econom [Internet] 2018 [cited 25 September 2018] doi:
10.1177/1527002518798681.
18. Conn J, Annest JL, Gilchrist J. Sports and recreation related injury episodes in the US
population, 1997–99. Inj Prev 2003;9(2):117-123.
19. Marshall SW, Guskiewicz KM. Sports and recreational injury: the hidden cost of a
healthy lifestyle. Inj Prev 2003;9(2):100-102.
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20. McCunn R, Sampson JA, Whalan M, Myer T. Data collection procedures for football
injuries in lower leagues: Is there a need for an updated consensus statement? Science
and Medicine in Football 2017;1(1):86-88
21. Whalan M, Lovell R, McCunn R, Sampson JA. The incidence and burden of time loss
injury in Australian men’s sub-elite football: a single season prospective cohort study.
J Sci Med Sport 2019;22(1):42-47.
22. Clarsen B, Rønsen O, Myklebust G, Flørenes TW, Bahr R. The Oslo Sports Trauma
Research Center questionnaire on health problems: a new approach to prospective
monitoring of illness and injury in elite athletes. Br J Sports Med 2014;48:754-760.
23. Hopkins WG. A Spreadsheet for Deriving a Confidence Interval, Mechanistic Inference
and Clinical Inference from a P Value. Sportscience 2007;11:16-20.
24. Crowcroft S, McCleave E, Slattery K, Coutts AJ. Assessing the Measurement
Sensitivity and Diagnostic Characteristics of Athlete-Monitoring Tools in National
Swimmers. Int J Sports Physiol Perform 2016;12(Suppl 2):S2-95-S2-100.
25. Harøy J, Clarsen B, Thorborg K, Hölmich P, Bahr R, Andersen TE. Groin Problems
in Male Soccer Players Are More Common Than Previously Reported. Am J Sports
Med 2017;45(6):1304-1308.
26. van Beijsterveldt A, Stubbe J, Schmikli S, van de Port IGL, Backx FJG. Differences in
injury risk and characteristics between Dutch amateur and professional soccer players.
J Sci Med Sport 2015; 18(2):145-149.
27. Orchard J, Hoskins W. For debate: consensus injury definitions in team sports should
focus on missed playing time. Clin J Sport Med 2007;17(3):192-196.
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28. Bittencourt NFN, Meeuwisse WH, Mendonça LD, Nettel-Aguirre A, Ocarino JM,
Fonseca ST. Complex systems approach for sports injuries: moving from risk factor
identification to injury pattern recogition – narrative review and new concept. Br J
Sports Med 2016;50(20):1309-1314.
29. Hodges PW, Tsao H, Sims K. Gain of postural responses increases in response to real
and anticipated pain. Exp Brain Res 2015;233(9):2745-2752.
30. Hainline B, Turner JA, Caneiro JP, Stewart M, Moseley GL. Pain in elite athletes—
neurophysiological, biomechanical and psychosocial considerations: a narrative
review. Br J Sports Med 2017;51(17):1259-1264.
31. Arliani GG, Astur DC, Yamada RKF, et al. Professional football can be considered a
healthy sport? Knee Surg Sports Traumatol Arthrosc 2016;24(12):3907-3911.
32. Meyers MC, Bourgeois AE, LeUnes A. Pain coping response of collegiate athletes
involved in high contact, high injury-potential sport. Int J Sport Psychol 2001;32(1):29-
42.
33. Tesarz J, Schuster AK, Hartmann M, Gerhardt A, Eich W. Pain perception in athletes
compared to normally active controls: A systematic review with meta-analysis. Pain
2012;153(6):1253-1262.
34. O’Sullivan K, O’Sullivan PB, Gabbett TJ. Pain and fatigue in sport: are they so
different? Br J Sports Med 2018;52:555-556.
35. Windt J, Gabbett TJ. How do training and competition workloads relate to injury? The
workload—injury aetiology model. Br J Sports Med 2017;51(5):428-435.
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36. Ekstrand J, Lundqvist D, Davison M, D’Hooghe M, Pensgaard AM, Communication
quality between the medical team and the head coach/manager is associated with injury
burden and player availability in elite football clubs. Br J Sports Med 2019;53(5):304-
308.
37. McCall A, Fanchini M, Coutts AJ. Prediction: The Modern-Day Sport-Science and
Sports-Medicine "Quest for the Holy Grail". Int J Sports Physiol Perform
2017;12(5):704-706.
38. McCall A, Dupont G, Ekstrand J. Internal workload and non-contact injury: a one-
season study of five teams from the UEFA Elite Club Injury Study. Br J Sports Med
2018;52(23):1517-1522.
39. Bjørneboe J, Flørenes TW, Bahr R, Andersen TE. Injury surveillance in male
professional football; is medical staff reporting complete and accurate? Scand J Med
Sci Sports 2011;21(5):713-720.
40. Ekegren CL, Donaldson A, Gabbe BJ, Finch CF. Implementing injury surveillance
systems alongside injury prevention programs: evaluation of an online surveillance
system in a community setting. Inj Epidemiol 2014;1(1):19.
41. Ekstrand J, Lundqvist D, Lagerbäck L, et al. Is there a correlation between coaches’
leadership styles and injuries in elite football teams? A study of 36 elite teams in 17
countries. Br J Sports Med 2018;52:527-531.
42. Thorpe RT, Atkinson G, Drust B et al., Monitoring Fatigue Status in Elite Team-Sport
Athletes: Implications for Practice. Int J Sport Physiol 2017;12(Suppl 2):1-25.
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Chapter 4 - How Can We Get Players To Do The 11+ Program? -
Stakeholder Perceptions on Injury, Prevention and Potential Solutions
4. 1 Preface
Chapters 2 and 3 of this thesis identify the injury profile and pattern in sub-elite football in
Australia as per Stages 1 and 2 of the TRIPP model. Based on the high injury incidence and prevalence observed, we can confidently conclude injuries are problematic in sub-elite football in Australia. Therefore, exploring strategies to improve the implementation of effective injury prevention strategies, such as the 11+ program is important. Despite the acknowledged efficacy of the 11+ program, adoption is poor20 with issues regarding program duration and potential fatigue often reported. 23, 24 As per Stage 5 of the TRIPP model, knowledge of stakeholder perceptions and barriers to adoption of IPPs is an important step. However, while barriers to implementation of injury prevention programs have been explored in youth football,23, 26, 28 the barriers to implementation of IPPs in sub-elite men’s football are not fully understood. It is also important to engage with stakeholders to overcome barriers to implementation of IPPs, however we are unaware of any research that has posed this question.
This chapter is an amended version of a manuscript under review: Whalan M, Lovell R, Siegler
JC, Marshall PW, Sampson JA. Improving 11+ Program Compliance – Stakeholder
Perceptions on Injury, Prevention and Delivery Science and Medicine in Football (submitted for publication February, 2020).
The citations and references contained herein apply to this chapter only. The citations related to the reference list within this section only and not to the reference list included at the end of this thesis.
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Abstract
Objective: Despite its known effectiveness, compliance to the 11+ program is low. Identifying strategies that are supported by stakeholders is important to overcome these barriers.
Methods: A survey was administered to coaches, players and physiotherapists at sub-elite football clubs. The survey included questions regarding: injury risk factors; injury prevention
(IP) practices; beliefs regarding IP programs (IPPs) and the 11+ program specifically.
Results: 145 players, 35 coaches and 16 physiotherapists completed the survey. All stakeholders considered IPPs important to reduce injuries and believed the 11+ program was effective and easy to implement. However, the duration of IPP’s and stakeholder (coach and player) buy-in were reported barriers to implementation with the ideal warm-up duration reported as <20 minutes for all groups (coaches = 16.3 min; players = 17.7 min; physiotherapists = 19.8 mins. All stakeholders supported splitting an IPP into smaller components to be performed at the start and end of training.
Conclusions: Stakeholders are supportive of IPPs and the 11+ program in sub-elite football.
However, buy-in and program duration appear to be primary barriers. Alternative delivery modes that involve “splitting” the components of an IPP into its sub-components may remove these barriers and present a viable alternative to enhance adherence.
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4.2 Introduction
Football is the number one participation sport with over 270 million worldwide participants1 and, as it is a contact, high intensity sport, carries an inherent risk of injury.2 Unfortunately, as identified in Chapter 2, the incidence and burden of injury in sub-elite football is greater than that of the elite cohort.3 Injury often results in discontinued sporting participation,4 can lead to longer term disability5 and present substantial medical costs.6 In a sub-elite setting, injuries can also impact on employment, resulting in a substantial economic cost to individuals and employers.7, 8 As such, the implementation of an effective injury prevention program (IPP) in sub-elite football is a priority.
The 11+ program, first released in 2006, was specifically designed as a surrogate warm- up to overcome some of the barriers to IPP implementation in sub-elite football.9 However, despite the 11+ program being successful in reducing injury incidence,10-12 larger scale “real world” adoption has been poor, with few (~10%) national federations implementing the program.13 Convincing key stakeholders to adopt prevention practices remains problematic in both elite14 and sub-elite football,15 with a number of barriers, including: (i) a lack of support from coaches and players; 13, 15, 16 (ii) the duration of the program16, 17 and (iii) reports of fatigue and soreness caused by the exercises within the program16-19 previously identified. Current knowledge of key stakeholder views has been derived from coaches and medical staff regarding their practices and attitudes to IPPs.15, 16, 19 Yet, little is known about the players’ perception towards IPPs and practices, an insight which may contribute to successful program implementation.20
Furthermore, whilst implementation barriers in youth football are reported, 16, 19, 21 the issues facing implementation of the 11+ program in a sub-elite adult cohort are unknown.
Herein, no research has posed possible solutions, or asked stakeholders for their opinions on options to overcome identified barriers to IPP implementation. Proposing options to
92 Chapter 4 stakeholders that may address implementation issues, such as 11+ program duration,16, 17 will provide greater insight into barriers to implementation and provide evidence for ways to improve 11+ program adoption. Furthermore, investigating delivery method perceptions of stakeholders, may provide further insight into issues regarding player and coach buy-in.13, 15,16
This study therefore investigated: (i) the injury and injury prevention perceptions; (ii) current injury prevention practices and (iii) options to overcome barriers to the implementation of the
11+ program of coaches, players and physiotherapists involved in men’s sub-elite football. The null hypotheses for this study were: (i) perceptions of injury and injury prevention practices and (ii) barriers to implementation, would be not be different for all stakeholders.
4.3 Methods
Initial contact was made via email, with an anonymous web link to the survey disseminated to the club secretaries of 24 Tier two and 12 Tier one football clubs in New South Wales, Australia in the period between the end of the 2016 season and start of the 2017 seasons. The club secretary was asked to distribute the survey web link to all senior coaches, players and physiotherapist at the club. Questionnaire responses were anonymous and informed consent was included on the first page. All procedures were approved by the University of
Wollongong’s Ethics Committee (reference number: 15/340).
4.3.1 Survey Design
The survey was developed following guidelines of the Reach Effectiveness Adoption
Implementation Maintenance (RE-AIM) framework.22 A mixture of closed and open questions were used throughout the survey with multiple choice and 5-point Likert scale responses required. The first section of the survey recorded descriptive data including role (coach, player or physiotherapist), age, years of experience, level of participation/involvement (professional, semi-professional or amateur), and coaching qualifications (where relevant). The second section surveyed stakeholder perceptions regarding injury risk factors and perceptions
93 Chapter 4 regarding preventable injury types. Stakeholders were asked to rate the importance of 17 different football injury risk factors from “very important” to “not important”. The risk factors selected were taken from previous survey-based research on risk factors in elite football. 23 The third section documented current injury prevention practices and proposed potential solutions to address established IPP implementation barriers.16-19 Solutions to address established IPP implementation barriers included preferred methods of incorporating an IPP (defined in the survey as strengthening, plyometrics and balance exercises) into a training session – “a 20-25 running and injury prevention program prior to training”; “a 20-25 minute running and injury prevention program after training” or “a 10-15 minute running program prior to training and a
10-15 minute injury prevention program after training”. Stakeholders were also requested to identify any injury prevention practices they implement for specific body locations. The fourth section questioned stakeholder awareness of the 11+ program, and rated attitudes and beliefs towards the program from “strongly agree” to “strongly disagree” amongst those who indicated awareness. The final section (available to all stakeholders) queried barriers for IPP implementation for players and then coaches.
Risk factor importance was calculated by allocating points on a Likert scale with a final score accumulated across all responses.23 Risk factors perceived as “very important” were awarded 3 points, “important” = 2 points, “somewhat important”=1 point, and “not important”= 0.23 Only fully completed surveys were included in the analysis.
4.3.2 Statistical Analysis
The accumulated scores were ranked highest to lowest in order of importance. To determine differences between stakeholder groups (coaches, players and physiotherapists), a Kruskal-
Wallis ANOVA was performed on risk factor importance scores and on ideal duration
(minutes) for a warm-up. A post-hoc Mann-Whitney U test was performed to determine the source of any difference observed. Significance level was set at p<0.05 with results displayed
94 Chapter 4 as means and 95% confidence intervals.
4.4 Results
A total of 196 complete surveys were returned from 145 players (age: 23.9 ± 5.8 years), 35 coaches (age: 40.8 ± 13.1 years) and 16 physiotherapists (age: 33.3 ± 8.7 years). The majority of players played at semi-professional (n=96) followed by amateur (n=49) level. Coaches were split between semi-professional (n=19) and amateur (n=16) categories, n=10 held a FFA “B”, n=11 a “C” Senior coaching license, n= 6 a FFA “A” Senior (n=6), n=4 a FFA “C” Youth and n=4 and n=4 a standard Senior Coaching (n=4) qualifications. Mean years involved in football at all levels was: players = 17.0 ± 5.6 years; coaches = 15.8 ± 14.1 years; and physiotherapists
= 9.1 ± 6.1 years.
4.4.1 Stakeholder Attitudes, Perceptions, Practices and Barriers Regarding Injury
Risk Factors and Prevention Strategies
An open question revealed ideal warm up durations of 16.3 mins (CI:14.7 to 18.0), 17.7 mins,
(CI: 16.8 to 18.6) and 19.8 mins (CI: 16.8 to 22.7) from coaches, players and physiotherapists, respectively. Perceived stakeholder injury risk factors in sub-elite football are outlined in Table
4.1. Attitudes and perceptions of injury prevention practices are outlined in Table 4.2.
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TABLE 4.1. Perceived injury risk factors in sub-elite football.
Ranked Importance Risk Factor Accumulated Points Points/Participant Players (n=145) Maximum = 435 1 Inadequate warm-up prior to training or a game 373 2.57 2 Poor strength endurance (i.e. fatigue resistance) 365 2.52 3 Previous Injury 363 2.50* 4 Fatigue throughout a season 348 2.40 Coaches (n=35) Maximum = 105 1 Poor strength endurance (i.e. fatigue resistance) 96 2.74 2 Previous Injury 95 2.71* 3 High training intensity and volume 89 2.54 4 Inadequate warm-up prior to training or a game 88 2.51 Physiotherapists (n=16) Maximum = 42 1 Previous Injury 42 3.00* 2 Game Scheduling (multiple games per week) 39 2.79# 3 Inadequate warm-up prior to training or a game 38 2.71 4 Poor Strength Endurance (i.e. fatigue resistance) 38 2.71 *significant ranking order difference between stakeholder groups (p=0.002) #significantly higher ranking order by physiotherapists compared to players and coaches (p=0.014)
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TABLE 4.2. Stakeholders’ beliefs and attitudes to injury prevention practices.
Concept Players (n=145) Coaches (n=35) Physiotherapists (n=16) % % % Belief on IPPs 98 97 93 1. Think IPP are important to reduce injuries 2. The team will be more successful with less injuries 95 94 93
3. Supportive of a 10-15 minute injury prevention 88 97 86 program including strengthening exercises 2x/week at training 4. Supportive of a 10-15 minute running program including 77 86 86 jumping and bounding prior to training
Scheduling of an IPP – Which way is best to incorporate IPP into a session? 1. A 20-25 minute program that includes a running 44 48 65 program & injury prevention program prior to training
2. A 10-15 minute running warm-up prior to training and a 50 46 35 10-15 minute injury prevention program after training
3. A 20-25 minute program that includes a running 4 0 0 program & injury prevention program after training
4. None of the above are suitable 2 6 0
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Current IP practices are contained in Table 4.3. All physiotherapists (n=16) and 83% of coaches (n=29) and 38% (n=55) of players were aware of the 11+ program, with 35% of physiotherapists (n=5), 69% of coaches (n=20) and 21% of players (n=12) currently performing the program in their respective teams. Most considered the program: (i) effective in reducing injuries in football (coaches = 79.3%; players = 60.8%; physiotherapists = 85.7%);
(ii) easy to implement (coaches = 75.8%; players = 77.3%; physiotherapists = 85.7%); (iii) football specific (coaches = 96.5%; players = 75.6%; physiotherapists = 100%); (iv) reduced injury incidence (coaches = 63.2%; players = 53.7%; physiotherapists = 64.3%); (v) suitable
(coaches = 68.9%; players = 53.7%; physiotherapists = 100%); (vi) necessary in adult male sub-elite football (coaches = 72.4%; players = 59.3%; physiotherapists = 92.9%); and worthy of recommendation (coaches = 69%; players = 57%; physiotherapists = 100%). Several barriers were however identified (Table 4.4). A lack of knowledge regarding the 11+ program was also demonstrated by the number of players who responded “unsure” to barriers associated with the
11+ program, or reported “neither agree nor disagree” (range = 22.2% to 55.6%) to questions within the survey (Figure 4.1).
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TABLE 4.3. Location specific injury prevention practices from coaches, players and physiotherapists.
I don't do anything Strength Training Balance/Proprioception "Core" or Flexibility Plyometric Exercises specific for this area (including gym based) Trunk (including (including bounding) Exercises stretches) % % % % % % Player (n=145) Hamstring 8 49 18 36 80 32 Groin/Adductor 15 28 17 29 76 23 Knee 35 38 31 18 40 30 Ankle 41 24 32 12 29 25 Calf 14 45 18 17 78 30 Quadriceps 12 54 18 25 77 28 Lower Back 15 42 16 51 65 13
Coach (n=35) Hamstring 6 36 25 39 78 67 Groin/Adductor 6 19 25 44 78 53 Knee 22 19 44 25 42 36 Ankle 25 19 44 25 42 36 Calf 8 31 25 25 81 61 Quadriceps 8 36 28 22 81 53 Lower Back 17 17 17 64 67 31
Physiotherapist (n=16) Hamstring 6 75 50 75 81 50 Groin/Adductor 6 69 44 75 75 44 Knee 19 69 75 56 44 69 Ankle 19 63 81 25 56 63 Calf 6 69 63 37 81 56 Quadriceps 13 69 50 50 63 56 Lower Back 6 50 38 81 81 31
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TABLE 4.4. Perceived stakeholder barriers by key stakeholders to the implementation of injury prevention programs
Players (n=145) Coaches (n=35) Physiotherapists (n=16) % % % Barriers For Players for IPP Implementation Players are not convinced that the exercises will prevent injuries 58 63 75 Players concerned about experiencing muscle soreness from exercises 28 17 19 Players concerned that some exercises may increase their risk of injury 20 20 6 Players are concerned that they will experience “heavy legs”(fatigue) during the match 41 20 44 Players are not interested in IPPs 60 63 50 Players are not educated about what injuries occur in football 45 77 44
Barriers For Coaches for IPP Implementation Coaches not convinced that the exercises will prevent injuries 28 46 75 Coaches do not have enough time to run an IPP 58 60 81 Coaches do not have the knowledge or expertise to conduct an IPP 63 71 75 There is not enough space on the training field to conduct an IPP 6 9 12 The IPPs take too long to perform 40 49 50 The coaches believe that the players may experience fatigue after the IPP 21 11 44 Coaches are unaware of the common injuries in football 17 31 25
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Players Indecision Regarding the 11+
Would you recommend the FIFA11+ Causes too much muscle soreness Causes too much fatigue to be a warm up Not necessary in Lower League Football Not suitable for adult male footballers Not able to be implemented for an entire season Lacking the use of a ball Beneficial but needs modification Lacking variation and progression Too boring Too long for a warm up Football specific Easy to implement Effective in reducing injuries in football
0 10 20 30 40 50 60 % of respondants (n=55)
Figure 4.1. Percentage of players that recorded “Neither agree nor disagree” for statements regarding the 11+ program.
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4.5 Discussion
This study investigated perceived injury risk factors, attitudes, perceptions and IPP practices of coaches, players and physiotherapists in men’s sub-elite football in Australia. The findings highlight that coaches, players and physiotherapists have similar and consistent perceptions and attitudes towards injury and IPP in sub-elite football, thereby rejecting the null hypothese.
All groups identified common risk factors, barriers to implementation of IPPs and a preferred warm-up duration of less than 20 minutes. Uniquely, questions posed to determine acceptability of alternative delivery modes, indicate support for options to split IPP components across the start and end of training.
4.5.1 Injury risk factors
Whilst the order was different, coaches, players and physiotherapists all perceived “previous injury”, “poor strength endurance (fatigue resistance)” and “inadequate warm-up” as three of the top four most important injury risk factors (Table 4.1). Whilst previous injury is considered non-modifiable, “fatigue” and “inadequate warm up” are modifiable in nature and may be addressed to potentially reduce injury risk.24 “Previous injury” was ranked significantly differently across stakeholder groups, with physiotherapists high ranking perhaps reflective of their education and industry experience.23
Fatigue, a known injury risk factor15, 23, 25 and barrier to IPP compliance,19 was a reported concern associated with exercises within the 11+ program in almost half of players in the current study (40%) that were aware of the 11+ program. Such concerns are perhaps warranted, with the Nordic Hamstring Exercise (NHE), performed in Part 2 of the 11+ program, shown to result in reductions of up to 17% in eccentric hamstring torque.18 Additionally, accumulated fatigue throughout a season was outlined as a concern for injury by players and is likely associated with general concerns from stakeholders around high training intensities
(coaches) and game scheduling (physiotherapists). However, of the stakeholders that were
102 Chapter 4
aware of the 11+, none considered that the exercises in the 11+ program lead to soreness and stakeholders did not think the exercises were efficacious in terms of reducing injury incidence.
4.5.2 Injury Prevention Program Perceptions and Practices
Team success is inversely related to injury incidence,26 and IPPs such as the 11+ program are effective in reducing injury incidence in sub-elite football.10, 11 The evidence therefore supports the views given by most coaches (98%), players (97%) and physiotherapists (93%), who each considered IPPs to reduce injuries in football, and subsequently increase a team’s chances of success (Table 4.2). Exercises that focused on increasing flexibility were the most commonly used by all stakeholders, whereas the knee and ankle were associated with the highest percentage of stakeholders reporting “not doing anything specific” for IP (Table 4.3). Of note, over a third of players reported no knee or ankle IP practice, which is concerning given that these are two of the most common injury locations identified in sub-elite3 and elite27 football.
Furthermore, despite the burden of muscle (in particular hamstring and groin) injuries in football,3, 28 and evidence supporting strength-based interventions for muscle injury prevention,10, 29-31 less than 50% of players reported any specific muscle strength exercises of these muscle groups (Table 4.3). Such a lack of specific muscle strengthening exercise may, to some extent, explain the high muscle injury incidence in sub-elite football. 3 Strength-based exercises were, however, well supported as an important component of an IPP by physiotherapists (Table 4.3). Interestingly the most commonly reported injury prevention practice by all stakeholders in this study was stretching (Table 4.3) and whilst stretching is often included in warm-up programs,32 there is limited evidence that stretching in a warm-up reduces injury risk33 or improves performance.34
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4.5.3 The 11+ Program – Awareness and Barriers
All physiotherapists and, in contrast to previous research in elite and sub-elite youth football,16,
21 the vast majority of coaches in the current study were aware of the 11+ program. However, less than 40% of the players in this study were aware of the 11+ program. Considering the high degree of program awareness in coaches, it is possible that players have been exposed to exercises contained within the 11+ program without knowing. It is also possible that unbeknown to players, the exercises prescribed may have been modified by coaches and physiotherapists.19 A lack of support from coaches and players has been previously identified as a barrier to implementation of the 11+ program.9, 13, 15, 16, 22 Yet, our results show that all three stakeholder groups consider the 11+ program effective and easy to implement.
Interestingly, coaches believed players, and reciprocally players believed coaches, were not interested in IPPs, despite all stakeholders reporting that IPPs are important and effective.
In this study, the time taken to perform an IPP like the 11+ program was a reported barrier to adoption. This is not a novel finding,16, 17, 21 with reported barriers of “coaches not having enough time” and “IPPs taking too long to perform” two of the most common barriers to implementation across all three stakeholder groups. Considering the known time barrier, we also posed an open ended question to all stakeholders to identify their preferred warm up duration, with all stakeholders reporting a preferred warm-up duration of less than 20 minutes.
These results indicate, despite its proven utility, 10 that the 11+ program is considered too long for a warm-up.
4.5.4 Potential Solutions to the 11+ Program Adoption Problem
Despite the exercises in the 11+ program potentially improving “fatigue resistance” (a reported injury risk factor), by increasing strength and stability,35 only half of coaches and players were supportive of a 20-25 minute warm-up and there were concerns regarding fatigue resulting from these exercises. Physiotherapists reported preference for performing IPPs prior to training
104 Chapter 4
(Table 4.2), a finding which may relate to their greater knowledge of the program (100%). Of interest however, stakeholders were as supportive of 2 × shorter 10-15 minute IPPs delivery periods split between the warm-up and cool down, as the traditional method of delivering the
11+ program as a warm-up. Such an approach may combat known barriers of duration16, 17 and fatigue16-19 that were similarly identified concerns in the current study. Given the perceived injury risk associated with an inadequate warm-up reported in this study and the known effectiveness of warm-ups to reduce injury risk, 32 any manipulation of the 11+ program should ensure that the effectiveness of the program as a warm-up is maintained. 36 Herein, performing just Parts 1 and 3 (and this excluding Part 2: strength and plyometric exercises) of the 11+ program has been shown to increase muscle temperature and acute muscle function,37 suggesting that these two parts in combination do indeed offer an appropriate “warm up”.
Combining Part 1 and 3 would offer a warm-up duration of approximately 10 minutes, well under the ideal times reported by all stakeholders which may address negative perceptions regarding IPP duration. Integrating the strength and plyometric exercises within Part 2 of the
11+ program to the end of training may also make better use of this cool down period.38
Notably, the exercises within Part 2 include those known to result in fatigue,18 and as such, fatigue accumulated prior to training is likely reduced, and perceptions of fatigue-related concerns when performing all exercises prior to training removed. Importantly, moving exercises contained in Part 2 to the end of training may also improve their effectiveness,39, 40 and increase player compliance to the exercises.41
4.5.5 Limitations
Several limitations must be acknowledged when interpreting the results of this study. Firstly, we acknowledge, that the stakeholders in the current study were adult sub-elite (semi- professional and amateur) players, and as such the outcomes may not be generalisable to the broader (Youth, Female and Elite) playing population. Nevertheless, it was our intention, as
105 Chapter 4
this population was the original target group for the development of the 11+ program, to examine barriers and solutions to implementation within this specific population. The sample size of the coaches and physiotherapists was much smaller than the player group. This was, however, a consequence of a real-world setting with many more players registered compared to other staff and as such our results may be representative of these groups. Although the sample size of coaches was small the findings of our study were similar to larger scale research15 and to those observed in the elite cohort.23 Due to the small sample and indifferent size, we did not however have sufficient power to examine within group differences.
Additionally, delivering the survey via a web link meant that it was not possible to calculate the response rate compared to the number of people that received the survey. As the link was publicly available, stakeholders were free to share with colleagues and peers. Unfortunately, this may have resulted in a reduced capacity to generalize the findings due to potential bias of respondents.
Finally, the addition of other alternative delivery methods of the 11+ exercises would also potentially provide further options for practitioners. For example, exploring spreading the exercises throughout the session rather than at the beginning or end of training may further increase stakeholder support.
4.6 Conclusion
This study adds further context to the attitudes, perceptions and behaviours of key stakeholders in men’s sub-elite football. Interestingly, coaches, players and physiotherapists all support the use of IPPs and believe they will be more successful with less injuries. Coach awareness of the
11+ program was high, yet players were predominantly unaware of the program. A lack of time to implement an IPP in addition to a perceived lack of interest in IPPs were the main barrier outlined in this research and are similar to those previously reported. Importantly, all stakeholders are equally supportive of performing injury prevention exercises either before or
106 Chapter 4
after training.
4.7 Practical Implications
• Coaches, player and physiotherapists had similar attitudes and perceptions of injury,
IPPs and barriers to implementation.
• Support was evident from all stakeholders for a proposed alternative mode of IPP
delivery. As such proposing to split IPP delivery into shorter components delivered in
the warm-up and cool down periods of training may address identified barriers to 11+
program implementation.
• A split delivery may remove time and fatigue barriers associated with the 11+ program
and perceived injury risk. As Part 2 contains the most fatiguing exercises, this
component is perhaps the most appropriate component to be delivered after training.
• Education and 11+ program awareness targeting players may present an important
avenue to increase compliance given their apparent lower levels of knowledge, yet
strong beliefs regarding IPP effectiveness. Despite a perceived lack of interest between
stakeholder groups, all stakeholders consider IPPs to be important and effective in
reducing injuries. Based on these findings, further promotion and education strategies
should include stakeholder-specific awareness initiatives.
107 Chapter 4
4.8 References
1. Kunz M. Big Count. FIFA Magazine 2007
2. Nedelec M, McCall A, Carling C, et al. The Influence of Soccer Playing Actions on the
Recovery Kinetics After a Soccer Match. J Strength Cond Res 2014;28(6):1517-23.
3. Whalan M, Lovell R, McCunn R, et al. The incidence and burden of time loss injury in
Australian men’s sub-elite football (soccer): a single season prospective cohort study.
J Sci Med Sport 2019;22(1):42-47.
4. Arliani GG, Astur DC, Yamada RKF, Yamada AF et al. Professional football can be
considered a healthy sport? Knee Surg Sport Tr A 2016;24(12):3907-3911.
5. Kuijt MT, Inklaar H, Gouttebarge V, Frings-Dresen MH. Knee and ankle osteoarthritis
in former elite soccer players: A systematic review of the recent literature. J Sci Med
Sport 2012;15(6):480-487.
6. Andrew N, Gabbe BJ, Wolfe R, et al. The impact of serious sport and active recreation
injuries on physical activity levels. Br J Sports Med 2011;45(4):335.
7. Lee AJ, Garraway WM. Epidemiological comparison of injuries in school and senior
club rugby. Br J Sports Med 1996;30(3):213-217.
8. Schneider S, Seither B, Tonges S, Schmitt H. Sports injuries: population based
representative data on incidence, diagnosis, sequelae, and high risk groups. Br J Sports
Med 2006;40(4):334-339.
9. Bizzini M, Dvorak J. FIFA 11+: an effective program to prevent football injuries in
various player groups worldwide—a narrative review. Br J Sports Med
2015;49(9):577-579.
108 Chapter 4
10. Thorborg K, Krommes KK, Esteve E et al. Effect of specific exercise-based football
injury prevention programs on the overall injury rate in football: a systematic review
and meta-analysis of the FIFA 11 and 11+ programs. Br J Sports Med 2017;51(7):562-
571.
11. Silvers-Granelli H, Mandelbaum B, Adeniji O et al. Efficacy of the FIFA 11+ Injury
Prevention Program in the Collegiate Male Soccer Player. Am J Sports Med 2015;
43(11):2628-2637.
12. Owoeye OB, Akinbo SR, Tella BA, Olawale OA. Efficacy of the FIFA 11+ warm-up
program in male youth football: a cluster randomised controlled trial. J Sports Sci Med
2014;13(2):321-8.
13. Bizzini M, Junge A, Dvorak J. Implementation of the FIFA 11+ football warm up
program: How to approach and convince the Football associations to invest in
prevention. Br J Sports Med 2013;47(12):803-806.
14. Bahr R, Thorborg K, Ekstrand J Evidence-based hamstring injury prevention is not
adopted by the majority of Champions League or Norwegian Premier League football
teams: the Nordic Hamstring survey. Br J Sports Med 2015:49(22):1466-1471.
15. Klein C, Henke T, Luig P, Platen P. Leaving injury prevention theoretical? Ask the
coach!—A survey of 1012 football coaches in Germany. German Journal of Exercise
and Sport Research 2018;48(4):489-497.
16. O'Brien J, Finch CF. Injury prevention exercise programs in professional youth soccer:
understanding the perceptions of program deliverers. BMJ Open Sport Exerc Med
2016;2(1):e000075.
17. O'Brien J, Finch CF. The Implementation of Musculoskeletal Injury-Prevention
Exercise Programs in Team Ball Sports: A Systematic Review Employing the RE-AIM
Framework. Sports Med 2014;44(9):1305-1318.
109 Chapter 4
18. Marshall PW, Lovell R, Knox MF et al. Hamstring fatigue and muscle activation
changes during six sets of Nordic hamstring exercise in amateur soccer players. J
Strength Cond Res 2015;29(11):3124-33.
19. O'Brien J, Young W, Finch CF. The use and modification of injury prevention exercises
by professional youth soccer teams. Scand J Med Sci Sports 2017;27(11): 1337-1346.
20. Finch CF, Doyle TLA, Dempsey AR et al. What do community football players think
about different exercise-training programs? Implications for the delivery of lower limb
injury prevention programs. Br J Sports Med 2014;48(8):702-707.
21. Donaldson A, Callaghan A, Bizzini M, et al. A concept mapping approach to
identifying the barriers to implementing an evidence-based sports injury prevention
program. Inj Prev Published Online First: 20 Jan 2018. doi:10.1136/injuryprev-2017-
042639.
22. Finch CF, Donaldson A. A sports setting matrix for understanding the implementation
context for community sport. Br J Sports Med 2010;44(13):973-978.
23. McCall A, Carling C, Nedelec M et al. Risk factors, testing and preventative strategies
for non-contact injuries in professional football: current perceptions and practices of 44
teams from various premier leagues. Br J Sports Med 2014;48(18):1352-7.
24. Meeuwisse WH, Tyreman H, Hagel B, Emery C. A dynamic model of etiology in sport
injury: the recursive nature of risk and causation. Clin J Sport Med 2007;17(3):215-
219.
25. McCall A, Davison M, Andersen TE et al. Injury prevention strategies at the FIFA 2014
World Cup: perceptions and practices of the physicians from the 32 participating
national teams. Br J Sports Med 2015;49(9):603-608.
110 Chapter 4
26. Hägglund M, Waldén M, Magnusson H et al. Injuries affect team performance
negatively in professional football: an 11-year follow-up of the UEFA Champions
League injury study. Br J Sports Med 2013;47(12):738-742.
27. Ekstrand J, Hägglund M, Waldén M. Injury incidence and injury patterns in
professional football: the UEFA injury study. Br J Sports Med 2011;45(7):553-558.
28. Ekstrand J, Hägglund M, Waldén M. Epidemiology of muscle injuries in professional
football (soccer). Am J Sports Med 2011;39(6):1226-1232.
29. Harøy J, Clarsen B, Wiger EG et al. The Adductor Strengthening Program prevents
groin problems among male football players: a cluster-randomised controlled trial. Br
J Sports Med 2019;53:150-157.
30. Petersen J, Thorborg K, Nielsen MB et al. Preventive Effect of Eccentric Training on
Acute Hamstring Injuries in Men’s Soccer: A Cluster-Randomized Controlled Trial.
Am J Sports Med 2011;39(11):2296-2303.
31. van der Horst N, Smits DW, Petersen et al. The Preventive Effect of the Nordic
Hamstring Exercise on Hamstring Injuries in Amateur Soccer Players: A Randomized
Controlled Trial. Am J Sports Med 2015;43(6):1316-23.
32. Woods K, Bishop P, Jones E. Warm-Up and Stretching in the Prevention of Muscular
Injury. Sports Med 2007;37(12):1089-1099.
33. Lauersen JB, Bertelsen DM, Andersen LB. The effectiveness of exercise interventions
to prevent sports injuries: a systematic review and meta-analysis of randomised
controlled trials. Br J Sports Med 2014;48(11):871-877.
34. Blazevich AJ, Gill ND, Kvorning T et al. No Effect of Muscle Stretching within a Full,
Dynamic Warm-up on Athletic Performance. Med Sci Sports Exerc 2018;50(6):1258-
1266.
111 Chapter 4
35. Impellizzeri FM, Bizzini M, Dvorak J et al, Physiological and performance responses
to the FIFA 11+ (part 2): a randomised controlled trial on the training effects. J Sports
Sci 2013;31(13):1491-1502.
36. Bizzini M, Impellizzeri FM, Dvorak J et al. Physiological and performance responses
to the "FIFA 11+" (part 1): is it an appropriate warm-up? J Sports Sci
2013;31(13):1481-1490.
37. Marshall PW, Cross R, Lovell R. Passive heating following the prematch warm‐up in
soccer: examining the time‐course of changes in muscle temperature and contractile
function. Physiol Rep 2015;3(12):e12635.
38. Van Hooren B, Peake JM. Do we need a cool-down after exercise? A narrative review
of the psychophysiological effects and the effects on performance, injuries and the long-
term adaptive response. Sports Med 2018;48(7):1575-1595.
39. Gioftsidow A, Malliou P, Pafis G, et al. The effects of soccer training and timing of
balance training on balance ability. Eur J Appl Physiol 2006;96(6):659-664.
40. Lovell R, Siegler JC, Knox M et al. Acute Neuromuscular and performance responses
to Nordic hamstring exercises completed before or after football training. J Sports Sci
2016;34(24):2286-2294.
41. Lovell R, Knox M, Weston M, et al. Hamstring injury prevention in soccer: Before or
after training? Scand J Med Sci Sports 2018;28(2):658-666.
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Chapter 5 Chapter 5 - Rescheduling Part 2 of the 11+ Program Reduces Injury
Burden and Increases Compliance in Sub-Elite Football
5.1 Preface
As outlined in Chapter 1, the TRIPP model allows for a methodological approach to develop and evaluate the efficacy of an injury prevention program. Chapters 2 and 3 provide insight into the injury profile in sub-elite football in Australia to ensure that any intervention addresses issues identified within this population. Given the evidence, the 11+ program is a suitable intervention to combat the most common injuries identified in these chapters.11 However, despite the efficacy of the 11+ program, 11 low adoption and compliance may limit the success of the program.16-18 Chapter 4 addressed Stage 5 of the TRIPP model, exploring and identifying perceptions related to injury prevention programs in general and the 11+ program specifically.
Importantly, the outcomes of Chapter 4 indicate that a proposed method to overcome barriers to the implementation of the 11+ program via the simple rescheduling of components of the
11+ program to the end of training were supported. As the study was conducted under “ideal conditions” this study addresses Stage 4 of the TRIPP model, evaluating the efficacy of rescheduling components of the 11+ program. The following chapter evaluates the effects of rescheduling Parts 1 and 3 of the 11+ program at the beginning of training and Part 2 at the end of training, on program efficacy, using injury surveillance methods employed in Chapter 2.
This chapter is an amended version of the published manuscript: Whalan M, Lovell R, Steele
JR, Sampson JA. Rescheduling Part 2 of the 11+ reduces injury burden and increases compliance in semi-professional football Scand J Sci Med Sport 2019;29(12):1941-1951.
The citations and references contained herein apply to this chapter only. The citations related to the reference list within this section only and not to the reference list included at the end of this thesis.
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Chapter 5 Abstract
Objectives: Although the 11+ program has been shown to reduce injuries in sub-elite football, program compliance is typically poor, suggesting that strategies to optimise delivery are necessary. This study investigated the effect of rescheduling Part 2 of the three-part 11+ program on the efficacy of the 11+ program.
Methods: Twenty-five semi-professional football clubs were randomly allocated to either a
Standard-11+ (n=398 players) or P2post group (n=408 players). Both groups performed the 11+ program at least twice a week throughout the 2017 football season. The Standard-11+ group performed the entire 11+ program before training activities commenced, whereas the P2post group performed Parts 1 and 3 of the 11+ program before and Part 2 after training. Injuries, exposure and individual player 11+ dose were monitored throughout the season.
Results: No significant between group difference in injury incidence rate (P2post vs Standard-
11+ = 11.8 vs 12.3 injuries/1000 h) was observed. Severe time loss injuries >28 days (33 vs 58 injuries; p<0.002) and total days lost to injury (4303 vs 5815 days; p<0.001) were lower in the
P2post group. A higher 11+ program dose was observed in the P2post (29.1 doses; 95% CI 27.9–
30.1) versus Standard-11+ group (18.9 doses; 95% CI 17.6 –20.2; p<0.001).
Conclusions: In semi-professional football, rescheduling Part 2 of the 11+ program to the end of training maintained the efficacy of the original 11+ program to reduce injury incidence.
Importantly, rescheduling Part 2 improved player compliance and reduced the number of severe injuries and total injury burden thereby enhancing the efficacy of the 11+ program.
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Chapter 5 5.2 Introduction
Football is a contact sport characterised by periods of high intensity activity, which carries an inherent risk of injury.1-3 Whilst participation in football is associated with improved health,4 injury is often the reason players discontinue participating in the sport, leading to longer term disability and substantial medical costs.5 The high injury incidence and burden observed in sub-elite football6 suggests there is a need to develop injury prevention strategies. Importantly, injury prevention strategies may not only help maintain long term player participation but also reduce health costs associated with sporting injury,5 a finding that has been specifically observed following implementation of the 11+ program in amateur football.7, 8
The 11+ program was developed and disseminated by Fédération Internationale de
Football Association (FIFA) to reduce football injuries. The program consists of three parts;
Parts 1 and 3 focus on running-based activity including dynamic actions and accelerations, whereas Part 2 focuses on strengthening and neuromuscular control exercises. The 11+ program was designed to be delivered as a 20-25 minute “warm-up” before commencing other training activities, without the need for specialised expertise or equipment. This is important for sub-elite sports where resources are typically scarce with limited access to staff6, 9 and, as a result, injury prevention programs are usually coach led.10 Previous research has shown that injury rates can be reduced by 40% when players complete the 11+ program at least twice per week,11 with higher program compliance and dose exposure associated with increased program effectiveness.12 However, despite the proven effectiveness of the 11+ program, only 10% of
FIFA’s member associations have endorsed the program and several studies highlight low 11+ program compliance.13-15
Poor adoption and compliance rates of the 11+ program have been explained by: (i) the time required to complete and boredom associated with the program,10, 16 (ii) fatigue and soreness caused by exercises contained in Part 210, 15-17 and (iii) a lack of awareness and
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Chapter 5 knowledge of how to perform the program.16, 18 These barriers are similar to those identified in
Chapter 4 with a lack of coach and player buy-in, program duration and concerns regarding fatigue reported as key concerns for stakeholders working in men’s sub-elite football.
Furthermore, given the importance of strengthening exercises in reducing injury risk,19 it is concerning that research has shown that the strengthening exercises performed in Part 2 of the
11+ program, are often modified or not performed.15 Potential fatigue caused by the exercises in Part 2 may contribute to why compliance to the full 11+ program is poor,15 with fatigue considered by practitioners to be a primary injury risk factor in football.20, 21 Interestingly, it has been found that performing an exercise in Part 2, the Nordic Hamstring Exercise (NHE), prior to football activity exacerbates eccentric hamstring fatigue,22, 23 although administering these exercises after training did not affect the exercise stimulus. Furthermore, rescheduling the NHE to the end of training not only maintained the efficacy of the NHE in terms of improving eccentric hamstring strength24 and reducing hamstring muscle injury incidence,22 but was also associated with enhanced compliance to the intervention.24, 25 These findings from one exercise, in addition to the conclusion from Chapter 4, suggest rescheduling Part 2 of the
11+ program after training as a practical alternative to address identified barriers to implementation, such as program duration, exercise difficulty/fatigue and boredom.
Exploring ways to ensure that all three components of the 11+ program (Part 1, 2 and
3) are performed, including the strengthening exercises in Part 2, could therefore improve the efficacy of the program, although research is required to confirm or refute this notion.
Therefore, the aim of this study was to determine whether rescheduling the 11+ program, such that Parts 1 and 3 are performed at the beginning, and Part 2 at the end of training, improved the efficacy of the 11+ program, compared to the standard 11+ program performed in its entirety at the beginning of training. The null hypothesises that rescheduling Part 2 of the 11+ program to the end of training would have no effect on: (i) injury incidence, (ii) injury severity
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Chapter 5 profile and (iii) compliance to the 11+ program, in sub-elite football was posed. A secondary aim is to assess the impact of the implementation of the 11+ program comparing injury data from 2016 to 2017. The null hypotheses for this secondary aim is that performing the 11+ program would: (i) not reduce injury incidence in sub-elite football and (ii) have no effect on the injury severity profile in sub-elite football.
5.3 Methods
5.3.1 Participant Recruitment
Twenty-five sub-elite football clubs, each comprising 2-3 teams, volunteered to participate in the study during the 2017 season. The clubs consisted of 4 Tier 2 (National Premier League) and 21 Tier 3 (Regional League) clubs in which all players received payment to play. Club and player recruitment and engagement was performed according to the Sports Setting Matrix,26 which was developed to help identify key stakeholders and “levels” of engagement required for successful implementation of an injury prevention program.26 In this study, this involved gaining approval from the National and State Federations, engaging with regional associations and presenting to club officials, coaching staff and players about the study. Before data collection, all players provided signed informed consent. All procedures were approved by the
University of Wollongong Human Research Ethics Committee (15/340).
Clubs were randomly allocated to either: (i) a Standard-11+ or (ii) a P2post group. Both groups were instructed to complete the full 11+ program a minimum of twice per week at training, and Parts 1 and 3 before matches (Figure 5.1). The Standard-11+ group performed all three parts of the 11+ program at the start of training as a warm-up, whereas the P2post group were instructed to perform Parts 1 and 3 at the start of training as a warm-up, and Part 2 of the
11+ program at the end of training during the cool down period. Coaches and players were permitted to include additional exercises, including those involving a ball, into the warm-up and cool down once the 11+ exercises were completed. Sample size calculation was based on
117
Chapter 5 the frequency of injury in football being ~1.8 injuries per player per season.27 Therefore a total of 652 injuries must be recorded to determine small effects with 95% confidence (p<0.05) and a sample of 362 players per group was required (G-Power).
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Chapter 5
Figure 5.1. Consolidated Standards of Reporting Trials (CONSORT) diagram of the flow of participants in the study.
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Chapter 5 5.3.2 Training to Implement the 11+ Program
Before implementing the 11+ program, the chief investigator (MW) presented information to coaches, club officials and medical staff about: (i) the rate and burden of injury in sub-elite football, (ii) the 11+ program and its effectiveness, (iii) barriers affecting uptake of the 11+ program, (iv) coach education regarding the importance of their role in 11+ program adoption,8,
28 (v) when to progress the 11+ exercises and (vi) the role of the Primary Data Collector (PDC) in program delivery. Coaches and medical staff were also shown videos of all exercises in the
11+ program, given explanations for the purpose and required technique for each exercise in the program, instructed on the process and criteria for stage progress in Part 2 and informed of the positive impact coach delivery has upon the efficacy of the program.29 The 11+ program instructions allow players to progress through the three stages of Part 2 as they felt comfortable, on the grounds that the coach and/or PDC were satisfied with their exercise technique.
However, we applied progression restrictions in accordance with previous research,30 whereby players remained at Level 1 of Part 2 for a minimum of 2 weeks initially, and progressed to
Level 3 after a minimum of 6 weeks. In the event a player missed a week of training due to injury, they were required to return to a lower level of Part 2 for a minimum of 1 week. At the information sessions for club officials and coaches, it was made clear that the PDC would be trained in implementing the 11+ program and would attend training sessions to coordinate the program. Coaches were not required to deliver the program, but were encouraged to support its implementation. Paper and digital copies of the 11+ program poster and field set up cards were also provided (Appendix 4).
5.3.3 Program Compliance & Injury Data Collection
To determine the efficacy of rescheduling Part 2 of the 11+ program, individual player exposure to the 11+ program was monitored. Given the cluster randomised controlled experimental design adopted, in which players were instructed to complete a specific set of
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Chapter 5 exercises, the term “compliance” was used to assess player dose exposure and was used as a continuous predictor for analysis.31 A player was deemed to have performed the 11+ program only when they completed all components of the program during that session. Data pertaining to program compliance and player injuries for each participating team were collected by an allocated onsite primary data collector (PDC), a qualified sports trainer, who attended all training sessions and matches.32, 33 All PDCs completed at least 6 hours of training including, how to record program compliance, injury and exposure data recording, injury definitions and details regarding the correct delivery of the 11+ program (see Appendix 1 and 2 for operational definitions and injury recording sheet, respectively).6 Training included scenario-based examples and the primary researcher (MW) was in weekly contact with PDCs during the season to review data collected. As per the methods employed in Chapter 2, a time loss injury was defined as an “injury that results in a player being unable to fully participate in matches or training.”32 Players were deemed to have recovered from injury once they had returned to full training/match participation or were considered eligible for team selection.32 Injury records were obtained during all training sessions (2-3 per week) and matches, including preseason, in- season and finals (28-34 weeks).
The primary outcome variables for this study included program compliance, represented by the total 11+ dose per player, and the efficacy of the program to reduce injury.
Program efficacy was represented by: injury count (total number of injuries), injury severity, injury incidence (total number of injuries/total football exposure (h) × 1000 h), the number of days lost to injury, and injury type, locations and mechanisms. Injury burden was then calculated (injury incidence × mean absence (days) per injury).34
5.3.4 Statistical Analysis
To account for the potential club cluster effect on outcomes, a Generalised Estimated Equation
(GEE) was performed with Poisson distribution used to assess between group differences in
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Chapter 5 injury count, injury severity and days lost to injury, with participant group, 11+ dose and total soccer exposure (h) entered as predictor variables. A second GEE was performed to determine significant differences between the two groups (Standard-11+ and P2post) for 11+ dose exposure with participant group and exposure imputed as predictor variables. A Mann-Whitney U test was used to assess differences between 11+ doses for each group (SPSS v25, IBM, USA).
Injury incidence rate (IIR) ratios (±95% confidence intervals [CI]) were calculated to compare injury locations and types between the groups. In addition, IIRs were also determined for a subset of players (Standard-11+, n=185 and P2post, n=226) who participated in a previous surveillance season (2016; Chapter 2), in which no club implemented the 11+ program or any other known injury prevention program.6 Therefore, the data collected in 2016, which was conducted by the same research team and collection procedures, served as baseline, pre- intervention data pertaining to injury incidence. All IIR ratio analysis was performed via
Hopkin’s ‘compare and combine’ analysis to determine clinical inference ranging from “most unlikely to be beneficial <0.5%” to “most likely to be beneficial >99.5%”.35
5.4 Results
A total of 806 male players consented to participate in this study with 398 players in the
Standard-11+ group and 408 players in P2post (Table 5.1). Player football exposure, compliance and injury incidence and severity for participants in the Standard-11+ and P2post groups are presented in Table 5.1. A total of 657 time-loss injuries were recorded during 54604 hours of football exposure (training and matches combined) across both groups. A similar number of time loss injuries were observed in both groups. However, significantly higher 11+ dose, a lower number of severe injuries and correspondingly lower total number of days lost to injury were observed in the P2post group compared to the Standard-11+ group (Table 5.1).
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Chapter 5
TABLE 5.1. Player exposure, compliance, injury count and severity for participants in the Standard-11+ and P2post group.
Variable Standard-11+ Group P2post Group P value (n = 398) (n = 408) Player Characteristics & Positions (mean [95% CI]) (mean [95% CI]) Age (years) 24.8 [24.0,25.6] 23.8 [23.0,24.7] 0.218 Height (cm) 176.9 [176.2,177.6] 178.3 [177.5,179.1] 0.061 Weight (Kg) 79.3 [78.9,79.7] 78.3 [77.9,78.7] 0.120 Goalkeepers (%) 10.1 9.9 Defenders (%) 32.2 32.3 Midfielders (%) 32.7 31.2 Strikers (%) 25.0 26.6 Player Exposure & Compliance (mean [95% CI]) (mean [95% CI]) Total football exposure (h) 26062.1 28541.4 0.972 Total training sessions (n) 51.6 [50.3,52.9] 49.7 [48.6, 50.9] 0.721 Total 11+ player doses (n) 7625 11871 0.004* Total 11+ player dose (sessions) 18.9 [17.6, 20.2] 29.1 [27.9, 30.1] <0.001* 11+ player dose/training Session (%) 32.7 [31.1, 34.3] 57.7 [56.2, 59.2] - 11+ Player dose/Exposure (h) 0.27 [0.26, 0.28] 0.42 [0.41, 0.43] - Injury Count n (% total) n (% total) Total Injuries (n) 320 (48.7) 337 (51.3) 0.825 Days Lost to Injury (n) 5815* 4303* 0.026*
Injury Severity n (% total) n (% total) Minimal: 1-3 days lost 60 (19) 95 (28) 0.335 Mild: 4-7 days lost 93 (29) 104 (31) 0.832 Moderate: 8-28 days lost 108 (34) 105 (31) 0.881 Severe: >28 days lost 59 (18) 33 (10) 0.012*
* indicates a significant difference between the Standard-11+ and P2post groups
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Chapter 5 The injury location differed between participant groups, with a significantly lower incidence of ankle and recurrent injuries in the P2post group, whereas the incidence of quadriceps muscle and contusion injury was lower in the Standard-11+ group (Table 5.2). Total injury burden was also lower in the P2post group, with lower time lost (days) associated with non-contact, recurrent and hamstring muscle injuries compared to the Standard-11+ group
(Table 5.3 and 5.4). There was also a significantly lower incidence of non-contact ankle injury injuries in the P2post (Table 5.4).
Comparing the subset of the current data (Total combined IIR = 12.5 injuries/1000 h;
Standard-11+ IIR = 12.3 injuries/1000 h, total injuries = 206; P2post group IIR = 12.9 injuries/1000 h, total injuries = 171) to the 2016 baseline injury incidence data (IIR = 19.9
6 injuries/1000 h, total injuries = 558) showed that both the Standard-11+ and P2post groups displayed reduced injury rates of 38% and 40%, respectively, compared to the 2016 injury incidence (IRR=0.61; 95% CI – 0.48–0.68; clinical inference– very likely beneficial; 99.3%).
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TABLE 5.2. Injury pattern, incidence rate and rate ratios for participants in the Standard-11+ and P2post groups.
Standard-11+ Group P2post Group No. of Injuries IR per 1000 h No. of Injuries IR per 1000 h IRR P value Clinical Inference [95% CI] [95% CI] [95% CI] Ɨ (No. of Injuries) - IRR ƗƗ Injury location Thigh 68 2.6 [2.4,2.7] 79 2.8 [2.5, 3.0] 1.1 [0.8, 1.5] 0.806 Unclear Hamstrings 51 2.0 [1.8,2.2] 45 1.6 [1.3,1.8] 0.8 [0.5, 1.2] 0.370 Possibly beneficial Quadriceps 17 0.7 [0.5,0.9] 34 1.2 [0.9,1.4] 1.8 [1.0, 3.7] 0.098 Possibly harmful Knee 59 2.3 [2.1,2.5] 60 2.1 [1.9, 2.4] 0.9 [0.7, 1.3] 0.857 Likely trivial effect Ankle 55 2.1 [1.9,2.4] 39 1.4 [1.1,1.6] 0.7 [0.4, 0.9] 0.132 Possibly beneficial Hip/groin 41 1.6 [1.4,1.7] 50 1.8 [1.6,2.1] 1.1 [0.7, 1.7] 0.618 Likely trivial effect
Lower leg/Achilles 40 1.5 [1.1,1.9] 47 1.6 [1.1,2.1] 0.745 Possibly trivial effect tendon 1.1 [0.7, 1.6] Injury type Muscle injury/strain 135 5.2 [4.7,5.4] 139 4.9 [4.4,5.3] 0.9 [0.7, 1.2] 0.882 Very likely trivial Sprain/ligament injury 85 3.3 [3.0,3.7] 77 2.7 [2.5,3.0] 0.8 [0.6 to 1.1] 0.812 Possibly beneficial Haematoma/contusion 38 1.5 [1.2,1.8] 64 2.2 [1.9,2.5] 1.5 [1.0 to 2.3] 0.116 Likely harmful Fracture 13 0.5 [0.2,0.8] 10 0.4 [0.2,0.9] 0.7 [0.3, 1.6] 0.832 Unclear Other bone injury 10 0.4 [0.1,0.9] 9 0.3 [0.1,0.6] 1.0 [0.4, 2.5] 0.891 Unclear Meniscus/cartilage 10 0.4 [0.1,0.8] 7 0.2 [0.08,0.5] 0.6 [0.2, 1.7] 0.765 Unclear Tendon injury 9 0.3 [0.1,0.7] 12 0.4 [0.1,0.8] 1.2 [0.5, 2.9] 0.832 Unclear Injury mechanism Non-contact 189 7.3 [7.0,7.5] 177 6.2 [5.8,6.6] 0.9 [0.7, 1.1] 0.367 Possibly beneficial Contact 132 5.1 [4.7,5.5] 161 5.6 [5.2,5.9] 1.1 [0.9, 1.4] 0.332 Very likely trivial Recurrent 67 2.6 [2.1,2.9] 48 1.7 [1.4,2.1] 0.7 [0.5, 0.9] 0.242 Likely beneficial Total injuries 320 12.3 [10.4, 14.1] 337 11.8 [10.1, 13.9] 1.0 [0.8 to 1.1] 0.579 Likely trivial
Ɨ IRR – incidence rate ratio for injury incidence (P2post group: Standard-11+ group), ƗƗ clinical inference of P2post is more beneficial/harmful than the Standard-11+ determined from IRR via Hopkins ‘combine and compare’ analysis.35
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TABLE 5.3. Injury burden and days lost to injury for participants in Standard-11+ and P2post groups.
Standard-11+ group P2post group Days Lost per 1000 h Total Days Lost Days Lost per 1000 h Total Days Lost P value (Total Days Lost) Injury location Thigh 45.7 1133 28.5 843 0.058 Hamstrings 39.3 1001 19.6 559 0.006* Quadriceps 6.2 162 8.9 254 0.464 Knee 60.7 1622 41.7 1190 0.203 Ankle 30.4 797 17.2 490 0.300 Hip/groin 20.8 535 19.2 547 0.867 Lower leg/Achilles tendon 26.4 697 13.6 371 0.127 Injury type Muscle injury/strain 75.6 1970 48.7 1390 0.080 Sprain/ligament injury 66.0 1720 53.9 1538 0.121 Haematoma/contusion 11.1 290 13.6 385 0.277 Fracture 26.2 682 15.8 450 0.812 Other bone injury 5.8 151 3.4 96 0.572 Meniscus/cartilage 7.1 185 5.1 146 0.652 Tendon injury 12.6 329 4.9 140 0.865 Injury mechanism Non-contact 128.3 3377 72.5 2099 0.010* Contact 94.9 2472 78.2 2166 0.564 Recurrent 55.4 1445 18.2 519 0.009* Total 223.1 5815 150.8 4303 0.026*
* statistically significant difference between the Standard-11+ and P2post groups.
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TABLE 5.4. Musclea and ligament injury pattern, incidence and burden for participants in the Standard-11+ and P2post groups.
Standard 11+ group P2post group
No. of IR per 1000 h Days Lost Total Days No. of IR per 1000 h Days Lost Total Days IRR Ɨ Clinical Inference ƗƗ P value P value Injuries [95% CI] per 1000 Lost Injuries [95% CI] per 1000 h Lost [95% CI] - IRR (No. (Total Days h Injuries) Lost)
Non-contact muscle
Thigh 56 2.3 [1.7,2.7] 22.1 1092 56 1.8 [1.4,2.2] 20.1 672 0.8 [0.5, 1.1] Possibly beneficial 0.395 0.010*
Hamstrings 49 1.9 [1.3,2.5] 35.8 937 44 1.4 [1.0,2.0] 17.0 552 0.7 [0.5, 1.1] Possibly beneficial 0.285 0.005*
Quadriceps 10 0.4 [0.1,0.9] 4.6 121 11 0.4 [0.1,1.1] 3.2 116 1.0 [0.4, 2.4] Unclear 0.999 0.580
Hip/groin 34 1.2 [0.7,1.9] 15.3 456 38 1.3 [0.9,1.8] 13.6 404 1.1 [0.7, 1.8] Possibly trivial 0.678 0.882
Lower leg 27 1.0 [0.6,1.5] 11.0 286 23 0.8 [0.4,1.4] 5.2 151 0.8 [0.4, 1.5] Unclear 0.556 0.231
Non-contact Ligament
Ankle 45 1.7 [1.1,2.5] 25.3 659 31 1.1 [0.7, 1.7] 15.5 441 0.6 [0.3, 0.9] Likely beneficial 0.131 0.449
Anterior Cruciate Unclear 0.238 0.237 8 0.15 [0.01, 0.4] 22.3 3 0.06 [0.01, 0.2] 9.1 Ligament Rupture 1280 474 0.4 [0.1, 0.6]
a Muscle injuries only included structural and functional injuries (i.e. muscle injuries excluded contusions, haematoma and tendon related injuries). *statistically significant difference between the Standard-11+ and P2post groups, Ɨ IRR – incidence rate ratio for injury incidence (P2post group: Standard-11+ group) ƗƗ clinical inference determined from IRR via Hopkins ‘combine and compare’ analysis.35
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5.5 Discussion
This is the first study to evaluate whether manipulating delivery of the 11+ program can enhance program efficacy and compliance. Simply rescheduling, such that Parts 1 and 3 are performed at the beginning and Part 2 of the 11+ program at the end of training, reduced the severity and burden associated with the most common injuries observed in football, whilst increasing individual player 11+ dose. Based on the findings in this study all null hypotheses are rejected. The specific effects of rescheduling the 11+ program are discussed below.
5.5.1 Effect on 11+ Program Efficacy
Irrespective of how the 11+ program was scheduled, the injury incidence rate was reduced
(Standard-11+ = 38% reduction; P2post = 40% reduction compared with 2016 [Chapter 2] baseline) in this study. These reductions were consistent with previous research,6, 11 and our results show that the 11+ program is equally as effective in reducing injury incidence in football, whether performing all three parts collectively at the start of training or with Part 2 rescheduled until the end of training. There were, however, significantly lower total number of severe injuries and days lost to injury observed in the P2post group in this study. Players in the
P2post group performed the 11+ program more frequently than the Standard-11+ group, which may have resulted in greater physiological adaptions to the 11+ program in the P2post group.
The 11+ program has been shown to result in both acute and chronic performance benefits, including speed and agility, in addition to potential injury reduction effects, such as improving strength, balance, muscle activity and core stability.30, 36, 37 It is therefore plausible that the benefits observed in the P2post group are related to a dose effect, rather than any physiological changes in response to the scheduling of exercises.
Performing the exercises contained in Part 2 of the 11+ program before training is the source of most concern for practitioners and is the most modified component of the 11+ program.15 As such, investigating methods to improve compliance and efficacy of exercises in
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Part 2 of the 11+ program such as the Nordic Hamstring Exercise (NHE), which is known to reduce the risk of hamstring injuries,38 is important for improving adoption.39 Previous research has suggested that the scheduling of the NHE has no impact upon chronic strength gains, albeit the muscle architectural mechanism seems to differ.24 In the current study, however, the incidence of hamstring injury was similar in the Standard-11+ and P2post groups, and collectively 50% lower than our previous research,6 suggesting that scheduling of the NHE does not impact efficacy. Performing NHEs prior to training can, however, transiently reduce eccentric hamstring strength, which can in turn increase injury risk.22 This can contribute to negative perceptions of the 11+ program because fatigue and soreness from the NHE are a reported barrier to 11+ program adoption.10, 16, 17 Performing NHEs at the start of training in the Standard-11+ group did not increase training-related hamstring injury risk with most hamstring injuries occurring during matches. Interestingly, however, a significantly lower time lost, and subsequently severity, of hamstring injury was observed in the P2post group. This finding was in contrast to previous research in which the inclusion of the NHE was not associated with a reduction in hamstring injury severity.25 Considering our finding and research that has shown hamstring eccentric strength decreases as a match progresses,40 performing the
NHE, as a component of a larger injury prevention program, after training might be an effective strategy for reducing hamstring injury incidence and burden.
A significantly lower incidence of ankle injuries was also observed in the P2post group relative to their Standard-11+ counterparts. Ankle sprains most commonly occur in the later stages of matches,41 with ankle function changing under fatigue.42 Exercises that focus on improving balance have been shown to more effective when performed after football training,43 and therefore suggests that performing the ankle stability exercises in Part 244 at the end of training, in addition to the higher dose exposure, are likely to have improved the efficacy of this component of the 11+ program. However, the P2post group incurred a significantly higher
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quadriceps injury incidence compared to the Standard-11+ group. The higher quadriceps injury incidence was a consequence of a significantly higher number of anterior thigh contusion injuries incurred by the P2post (23 versus 7 injuries), whereas non-contact quadriceps muscle strains were similar between groups. The 11+ program is designed to reduce non-contact
45 injuries. Therefore, the higher quadriceps injury incidence in the P2post group is unlikely the result of the program rescheduling.
Recurrent injuries are problematic in sub-elite football with inadequate recovery, poor physical conditioning on return to play and a lack of access to medical care believed to contribute to the high incidence rate.6, 9, 46 Interestingly, recurrent injury incidence and time lost to recurrent injury was significantly lower in the P2post group compared to the Standard-11+, and both groups had lower injury incidence when compared to the 2016 cohort.6 Previously research has shown that increased compliance to strength programs is associated with reduced injury incidence.12, 19 Our results additionally suggest that rescheduling the exercises in Part 2 so that they are performed more regularly, reduces ankle injury incidence, hamstring injury severity and injury recurrence. We speculate that by significantly reducing the number of severe injuries and reducing time lost to injury, players in the P2post group returned to training earlier, increased their exposure to the 11+ program as well as to football training and, in turn, reduced the injury risk caused by de-training for the most common injuries in football.6, 27, 30,
46, 48
To our knowledge, this study is the first to analyse the injury burden associated with the 11+ program, allowing for an examination beyond injury incidence.34 A 33% lower injury burden was observed in the P2post group compared with both the Standard-11+ group and to the 2016 baseline,6 with the greatest burden reductions associated with the most common injuries (ankle sprains, hamstring and calf muscle strains) in football.6, 34 Lower time lost for hamstring, quadriceps and calf injuries and lower injury incidence for ankle sprains account
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for the lower injury burden observed in the P2post group compared with the Standard-11+ group.
Interestingly, the Standard-11+ showed a reduction in injury burden compared to the 2016 baseline,6 which is likely to be the result of a significantly higher number of severe injuries in the baseline season. Additionally, injury burden associated with anterior cruciate ligament rupture (ACLR) in the P2post group was lower compared to both the Standard 11+ group and
6 2016 data, with ACLR incidence 2.5 times lower in the P2post compared to the Standard-11+ group, and half that of 2016 baseline.6 Furthermore, it is noteworthy that six of the eight ACLR in the Standard-11+ group were non-contact injuries, whilst all ACLR in the P2post group involved contact with another player. Previous 11+ program research found a similar dose related effect to ACLR incidence48 and our findings present encouraging data that may help reduce non-contact ACLR in sub-elite football.
5.5.2 The Potential Role of Rescheduling on 11+ Program Compliance
The findings in Chapter 4 indicated that coaches and players were equally supportive of performing IPP at the start or the end of training. Interestingly, in this study, rescheduling Part
2 of the 11+ program to the end of training significantly increased program compliance with a
20% higher number of 11+ doses observed in the P2post compared to the Standard-11+ group.
When considering the percentage of 11+ doses relative to training sessions completed, the
P2post group individual player dose (57.7%) was higher than has previously reported (47%) in
11+ program research in youth football,49 whereas the Standard-11+ group was lower (32.7%).
However, compliance in both groups in the current study would be categorised as “low” and
“moderate”12 or “low”50 relative to previous research. This result was despite “best practice” strategies to encourage program compliance, including extensive coach and staff education50 and engagement with stakeholders.26 The previous 11+ studies, however, did not record or state whether all components of the 11+ program were completed for an exposure to be recorded.12,
50 The apparently low compliance in this study might have been a consequence of the strict
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compliance criteria we applied, as only “doses” in which players completed all three components of the 11+ program were included in the analysis. Regardless of the method of delivery, improving compliance to Part 2 of the 11+ requires further investigation and potentially other strategies. Based on the findings in Chapter 4, addressing coach knowledge regarding the importance and delivery of the 11+ program may be another strategy that requires attention. Coach knowledge was a perceived barrier to implementation for all stakeholders and despite an education session being performed prior to the study, inclusion into coach education programs may help “normalize” the 11+ program, thereby improving compliance.
5.5.3 Limitations
Performing large scale injury research across numerous clubs can result in several methodological limitations that must be acknowledged. We acknowledge potential issues that may arise from performing multiple sub-classification hypothesis testing on the same data set.
Initial power calculations for participant inclusion were based on evaluating total injury incidence and burden. Once the overall effect was determined, we performed sub-classification analysis on different injury locations and types, which will reduce the power size of the sample analysed. To overcome the potential impact of obtaining a false positive or false negative result, we determined clinical inferences35 to allow for practical implications to be drawn from the findings. Although caution may need to be applied to the sub-class findings, the number of injuries recorded for specific injuries, such as hamstring muscle injuries, in our study was larger compared to other published research.25, 38
Attempts were made to control the delivery of 11+ exercises for both groups to allow for the efficacy of the scheduling change to be correctly determined, and compliance accurately assessed. A limitation to the application of the “compliance” assessment when evaluating the
11+ program is the progression of stages in Part 2. There is not a specific progression of Part 2
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exercises within the program and, apart from the restrictions applied at the initial stages, standardised progression through these stages for players is not possible. We attempted to address this issue by only “allowing” players to progress through a stage in Part 2 once the
PDC or coach was satisfied with the technique and performance of the exercise and, as such, maintained control over the prescription of exercises for the players. Although this limitation may be indicative of a pragmatic issue associated with real world program coordination, we applied the more rigorous compliance definition to ensure the true effect of rescheduling Part
2 was evaluated.
Notably, whilst a PDC was present to coordinate the 11+ program, the quality of how well the exercises were performed was not recorded. It is possible that how well the 11+ exercises were performed and extra exercises may have impacted on injury incidence outcomes. It should also be acknowledged that the presence of the PDC at training sessions may have facilitated the compliance observed in this study.
Multiple PDCs were assigned across different clubs, which might have resulted in under or over reporting of injuries.6 Moreover, variations in coaching styles,51 player fitness and physical characteristics, and previous injury history of players was not considered in the analysis.52 We attempted to standardise the knowledge base, program implementation and data collection by providing an extensive education program for coaches and PDCs before the intervention was implemented to minimise these limitations. Additionally, PDCs performed several practice injury reports before the season started to improve interclub data reporting consistency. Further research, however, is necessary to determine whether the improved 11+ program outcomes in the P2post group were due to increased dose exposure or the scheduling change, or a combination of the two elements. The long-term physiological adaptions to performing Part 2 post training also requires further investigation. Additionally, the translation of the results and conclusions from this study to other populations, such as youth and females,
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should be approached with caution. It is beyond the scope of this study and as such we do not speculate as to the impact of rescheduling Part 2 of the 11+ program would have beyond the sub-elite, semi-professional men’s cohort.
Finally, the use of PDCs to deliver the 11+ program may limit the transferability of this approach to a “coach only” delivery model. The placement of the PDC added a resource that may not be common at many sub-elite clubs and therefore may put more demands on the coach.
However, the use of sports trainers as the PDC was an integral component of this study methodology to ensure valid, accurate collection of the compliance and injury data which was vital to determining the efficacy of the study.53 Coach education regarding delivery of the 11+ program and their role as an important part of the implementation process was performed as part of the study prior to the season starting. This education process is likely to be important for future research and practical application of the study findings into the “real world” where delivery modes may vary beyond the restrictions of a randomised control design.
5.6 Conclusion
Rescheduling exercises in Part 2 of the 11+ program maintained program efficacy whilst increasing compliance, thereby combatting some of the barriers associated with uptake of the
11+ program. Our results also suggest that improving 11+ program compliance and performing
Part 2 exercises at the end of training reduces the injury burden and severity associated with the most problematic injuries in football.
5.7 Practical Implications
• The simple act of rescheduling Part 2 of the 11+ program to the end of training
significantly improves 11+ compliance whilst maintaining the overall efficacy of the
11+ program.
• Rescheduling appeared to impact directly upon severe injury incidence, reducing the
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number of days lost to injury of the most common injuries in football. The findings of this study provide a simple and practical method to potentially improve the efficacy of the 11+ program and the compliance to the 11+ program, thus may assist in improving the overall adoption of the program.
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2018;21(3): 257-262.
48. Silvers-Granelli HJ, Bizzini M, Arundale A, et al. Does the FIFA 11+ Injury Prevention
Program Reduce the Incidence of ACL Injury in Male Soccer Players? Clin Orthop
Relat Res 2017;475(10):2447-2455.
49. Soligard T, Nilstad A, Steffen K et al. Compliance with a comprehensive warm-up
program to prevent injuries in youth football. Br J Sports Med 2010;44:787-793.
50. McKay CD, Steffen K, Romiti M, et al. The effect of coach and player injury
knowledge, attitudes and beliefs on adherence to the FIFA 11+ program in female youth
soccer. Br J Sports Med 2014;48(17):1281-1286.
51. Ekstrand J, Lundqvist D, Lagerbäck L, et al. Is there a correlation between coaches’
leadership styles and injuries in elite football teams? A study of 36 elite teams in 17
countries. Br J Sports Med 2018;52:527-531.
52. Windt J, Gabbett TJ. How do training and competition workloads relate to injury? The
workload—injury aetiology model. Br J Sports Med 2017;51(5):428-435.
53. Ekegren CL, Gabbe BJ, Finch CF. Injury surveillance in community sport: Can we
obtain valid data from sports trainers? Scand J Med Sci Sports 2015;25(3):315-322.
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Chapter 6 - Summary, Recommendations for Future Research, and
Practical Implications
6.1 Summary
The overarching aim of this thesis was to systematically investigate the effects of modifying the 11+ program delivery on injuries incurred by sub-elite football players. Before the effects of 11+ program delivery could be investigated, it was imperative to first establish the injury problem in sub-elite football. In Chapter 2, the results highlight an injury incidence in sub-elite football twice that observed in previous research in elite and sub-elite football cohorts. Whilst the higher injury incidence may be a result of cohort-specific factors discussed in Chapter 2, it is more likely that the improved recording methods used in this thesis have provided more accurate injury data. Interestingly, the results of previous research1 and the results presented in
Chapter 2, indicate that the main observed increases in injury incidence reporting compared to other seasons and studies, were in the mild (1-3 days lost) injury severity category. This study was also the first to document and report the injury burden in sub-elite football, which was also found to be twice as high as that reported in the elite football setting. Of note, the results of
Chapter 3 highlighting hamstring muscle strains, hip/groin pain, lower leg contusions and ACL tears, are all associated with the highest injury burden in sub-elite football, a finding that is consistent with elite football,2 whereas ankle sprain burden was higher in sub-elite football relative to their elite counterparts. The results of this study highlights the size of the injury problem in sub-elite football with the need for investment into medical provision, facilities, coach education and injury mitigation programs to reduce healthcare costs to sub-elite football players in Australia.
In Chapter 3 the prevalence of non-time loss injuries in sub-elite football and their association with an impending (within 7 days) time-loss (TL) injury was investigated. This
142
Chapter 6 chapter further explored the surveillance data reported in Chapter 2 because non-TL injuries are known to be an underreported component of injury surveillance3 with only TL injuries typically reported in injury research. Injury surveillance included player self-reports collected via the OSTRC Questionnaire on Health Problems4 combined with football consensus5 third party methods. Self-reported methods increased the data capture of non-TL injury, whilst the
OSTRC Questionnaire was less effective at capturing accurate TL data. The third-party reporting method captured more than twice the number of TL injuries. Weekly non-TL physical complaints were high with almost half of all players affected by a physical complaint that had an impact on their participation and performance each week. Notably, the risk of a player sustaining a TL injury was three to six times higher, respectively, when preceded (<7 days) by a self-reported non-TL physical complaint resulting in a perceived minor and moderate impact on participation, performance, training volume or severity. Importantly, whilst there was low specificity, the presence of a non-TL injury was associated with good injury prediction capacity
(AUC range = 0.73 to 0.83) for the incidence of a TL injury within the following week and, therefore, may be a useful secondary prevention tool to include in an injury prevention system.
Due to the low specificity, caution and the application of applied clinical reasoning should be used before decisions to reduce training load are based on the presence of a non-TL injury alone, as this will risk needless reduction in training exposure and/or unnecessary medical intervention. Notably however, the different injury risk observed at different injury locations may further assist clinicians in their treatment and intervention process. For example, the results in Chapter 3 highlight that reporting the presence of a non-TL hamstring complaint were associated with a higher TL injury risk compared to those with a hip/groin non-TL complaint.
As such, this information may assist clinicians and coaches with decision making and risk profiling considering non-TL complaint location. The inclusion of the self-reported injury surveillance method not only improved the depth of injury surveillance, but could also be
143
Chapter 6 considered as a method to help identify players at increased risk of injury in sub-elite football.
Overall, the results observed in Chapters 2 and 3 highlighted the need to implement effective injury prevention strategies in this population. The most common injuries reported in Chapter
2 were consistent with the injuries that the 11+ program was designed to address6 and is an important consideration when looking to select any IPP. As such the 11+ program was confirmed as a potentially suitable IPP for this cohort and based on the evidence supporting its use,7, 8 satisfied Stages 3 and 4 of the TRIPP model.
In Chapter 4, Stage 5 of the TRIPP model was addressed with potential barriers and beliefs regarding IP practices across several stakeholders investigated. Coaches, players and physiotherapists all supported using IPPs and perceived that IPPs would result in less injuries.
All stakeholders considered previous injury, a lack of fatigue resistance and an inadequate warm-up as the main risk factors for injury in sub-elite football players. Contrary to previous research, coach awareness of the 11+ program was high. Players, however, were relatively unaware of the program and, as such, may present an important avenue for education involving
11+ program awareness. All stakeholders considered the 11+ program as effective in reducing injuries although the program duration was consistently identified as a barrier to implementation. A unique aspect of this survey-based study was that potential solutions to improve IPP implementation was explored with stakeholders. Given the barriers of program duration and fatigue related to some of the 11+ exercises, options to address these were posed, specifically regarding moving a component to the end of training. Subsequently, the survey results indicated that coaches and players were receptive to the concept of ‘splitting’ an IPP by delivering two shorter (10-15 minute) components before and after training, with all stakeholders reporting that the ideal warm-up duration was less than 20 minutes. The results of
Chapter 4 thus provided support to investigate the effects of rescheduling components of the
11+ program in Chapter 5.
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In Chapter 5, 25 sub-elite, semi-professional football clubs were randomly allocated to either a Standard-11+ (n=398 players) or P2post group (n=408 players). Players in the Standard-
11+ group performed the entire 11+ program before training activities commenced whereas players in the P2post group performed Parts 1 and 3 of the 11+ program before, and Part 2 after, training. Both groups reported a similar number of injuries and injury incidence rate throughout the football season, suggesting the 11+ program was equally effective in both groups.
Additional sub-group analysis also showed that rescheduling exercises in Part 2 of the 11+ program maintained program efficacy with both groups reducing injury incidence by approximately 40% compared to the previous football season. Interestingly, performing the exercises in Part 2 of the 11+ program at the end of training significantly reduced the injury burden and severity associated with the most problematic injuries in football when compared with the standard 11+ program delivery method. Days lost to hamstring muscle injuries, recurrent injury and non-contact injuries were all significantly lower when the exercises contained in Part 2 were performed after training compared to before training. These findings may have been the result of significantly increased compliance in the group performing Part 2 at the end of training. This suggests that rescheduling Part 2 not only improved efficacy of the
11+ program, but also combatted the barriers of perceived program duration and potential fatigue associated with the 11+ program.
In conclusion, by systematically applying an evidence-based framework to implement an IPP, it was possible to identify the high injury incidence and burden that exists, in addition to the prevalence and impact of non-TL injuries, in sub-elite football. Rescheduling Part 2 of the 11+ program resulted in increased compliance whilst also reducing the incidence and burden of injury incurred by sub-elite football players. Overall, the outcomes of this thesis highlight ways to make football safer.
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6.2 Recommendations for Future Research
The findings from this thesis provide practical and effective methods to reduce injury incidence and burden associated with sub-elite football. The findings from this thesis however, do facilitate the development of further research questions.
6.2.1 Cohort Specific Injury Surveillance
Future research should replicate the research methods and interventions used in this thesis in other football cohorts, such as youth, women and veterans, to gain a greater insight into the injury patterns associated with sub-elite sport. Chapters 2, 3 and 5 show that large scale injury research using methods outlined in consensus statements is possible and practical in a sub-elite cohort. The methods employed in these chapters may therefore provide a template framework for future research to be performed. Notably, future researchers are advised to engage with key stakeholders regarding IPP delivery preferences to assist with “buy in” and implementation of a proposed IPP. Additionally, the effect of rescheduling Part 2 of the 11+ program to the end of training in other populations is also important to determine whether these results observed in Chapter 5 are transferrable to other populations.
6.2.2 Increased use of Self-Report Measures in Primary and Secondary Prevention
Including the OSTRC Questionnaire on Health Problems4 to evaluate the efficacy (Stage 4 of the TRIPP model) and effectiveness of an IPP (6 of the TRIPP model) should also be explored, as only TL injury data was captured in Chapter 5. Based on the high prevalence of non-TL injuries compared with TL injuries reported in Chapter 3, evaluating the efficacy and effectiveness of the IPP in more depth by assessing the effects of an IPP on non-TL injury prevalence should also be performed. Recent research has continued to show the higher injury prevalence recorded when self-reported methods are employed, however these studies have targeted groin injuries specifically.9, 10 The benefit of the OSTRC Questionnaire on Health
Problems4 is that it allows for all injury locations to be recorded by the player and may be more
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Chapter 6 suited to larger scale IPP evaluation.
Furthermore, Chapter 3’s findings indicate that incorporating the OSTRC
Questionnaire on Health Problems4 into player monitoring systems may assist in identifying players at increased risk of injury. Such findings provide potential secondary prevention strategies to be developed in which a player that is “flagged” as being at increased risk has an intervention implemented to manage or reduce this risk. Interventions such as load management11 or physiotherapy intervention may be explored as a potential strategy for risk management with further research, including training load and its effect on non-TL injury reporting, of interest. As discussed in Chapter 3, the perception of “pain” varies between players12 and pain can be a normal by-product of training.13 As such, based on the findings in
Chapter 3, a reported non-TL injury may be indicative of that player being relatively overloaded, thereby potentially suggesting a simple way to evaluate individual responses to training. To achieve this however, future research that incorporates the OSTRC Questionnaire on Health Problems should implement the questionnaire on a more regular basis than weekly.
The results in Chapter 3 suggest using just one question from the OSTRC questionnaire is adequate and may reduce the risk of questionnaire fatigue if players are asked to complete the questionnaire more than once a week. Given the prevalence of daily monitoring that occurs in modern sport,14, 15 and its use to identify changes in player “readiness”,16 then it is possible that one category (performance, participation, severity or volume) could be incorporated into this normal practice. Athletes however often do not perceive themselves to be “injured” until performance is affected.17 The performance category OSTRC Question may therefore present the most appropriate single question, with future research required to determine its effectiveness in identifying high risk players when implemented daily.
Finally, the impact of 11+ program on non-TL injuries should also be investigated. The results in Chapter 3 indicate the high prevalence of non-TL injuries compared to TL injuries
147
Chapter 6 and also the TL injury risk associated with them. Future IPP research should include self- reported methods for injury recording to assess the impact of programs such as the 11+ program on non-TL injury prevalence and the potential impact on reducing TL injury risk.
6.2.3 Updating the “11+ Program” and its “concept”
Despite the ~40% reduction of injuries observed in Chapter 5, future research should investigate ways to further improve the efficacy of the 11+ program as an IPP. For example, adding an exercise such as the Copenhagen Adductor exercise, proven to reduce groin injury incidence18 and increase eccentric adductor strength,19 within Part 2 of the 11+ program would be a logical inclusion to specifically target hip/groin related injuries. Additionally, investigating the underlying physiological adaptions that occur when the exercises in Part 2 of the 11+ program are performed after training may also provide further insight into the factors contributing to reducing injury incidence.
Initially the 11+ program was designed to use the warm-up period to integrate specific drills and exercises to reduce injury risk, whilst also being an effective warm-up.20, 21 The findings in Chapter 5 are the first to show that expanding the 11+ program beyond the warm- up, not only maintains the efficacy of the original program, but also improves compliance and the program’s capacity to reduce injury burden. As the understanding of injury complexity continues to improve and evolve,22 incorporating other components into the “11+ program model” may be beneficial. Recent literature has highlighted that components such as adequate training load23 and exposure to high speed running24 are key components in the reduction of injury risk. It is therefore possible that the scope of the 11+ program could be expanded to include additional sections with basic conditioning drills to ensure these components are in a session. Additionally, performing exercises, such as the plank, within rest periods and between drills, while keeping the exercises that may induce immediate fatigue, such as the Nordic
Hamstring exercise,25 at the end of training, may further reduce the perceived duration of the
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Chapter 6
11+ program. Such strategies would require substantial coach involvement, as highlighted in
Chapter 4. Coaches are very interested and supportive of IP strategies and as such, future research could explore the concept of a more holistic 11+ program representing a sessional concept rather than just a warm-up.
6.3 Practical Implications
The findings of the current thesis have the following practical implications:
• The high incidence and burden of injuries in sub-elite football emphasises the need to
include programs, such as the 11+ program, in sub-elite football. Particular focus should
be applied to prevent knee, ankle and hamstring related injuries due to their associated
high injury burden.
• The injury severity profile – mild, minor, moderate and severe - is similar in elite and
sub-elite football. This suggests that injury prevention strategies and focus should be
similar across both cohorts of football players.
• The addition of a PDC to injury data collection in sub-elite football increases the capture
of less severe injuries and improves injury surveillance data.
• Combining the more commonly used third party and self-report injury reporting
methods greatly increases the capture of injury data in sub-elite football.
• The presence of a non-TL injury is associated with an increased risk of a TL injury in
sub-elite football, with good predictive power relative to a future TL injury occurrence.
As such, the OSTRC Questionnaire for Health Problems is a useful tool that can be used
to assist in player monitoring, improve communication between coaches, players and
medical staff, and to help identify injury risk in sub-elite football.
• Due to low specificity, the OSTRC Questionnaire on Health Problems is potentially a
useful tool for secondary injury prevention, as an early identification tool to prevent
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Chapter 6
minor injuries progressing to more significant ones rather than being used to predict
injury.
• The similarly predictive capacity observed across each of the four OSTRC
Questionnaire on Health Problems categories suggests that a single question may
sufficiently identify players at increased risk of TL injury.
• Players, coaches and physiotherapists all consider IPPs are effective in reducing injuries
in sub-elite football. However, player awareness of effective IPPs in sub-elite football
is low compared to coaches and physiotherapists, presenting an opportunity for player
education.
• The perceived lack of stakeholder support for IPPs and the 11+ program duration are
primary barriers for IPP implementation.
• All stakeholders believe that inadequate warm-up is a major risk factor for injury but
the acceptable duration for a warm-up is less than 20 minutes.
• Splitting an IPP, such as the 11+ program, into two shorter periods and including
exercises at the end of training, is well supported by all stakeholders.
• Rescheduling Part 2 of the 11+ program to the end of training significantly improves
11+ program compliance whilst maintaining the overall efficacy of the 11+ program.
In fact, rescheduling appeared to impact directly upon severe injury incidence, reducing
the number of days lost to injury due to the most common injuries in football.
• The findings of this study provide a simple and practical method to improve compliance
and subsequent efficacy of the 11+ program that may be implemented in sub-elite
football to assist in improving adoption of the program.
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Chapter 6
6.3.1 Translation to Practice
By employing the RE-AIM SSM framework, it is possible to identify the key stakeholders and translate the thesis findings into practice, with the key stakeholders being: National, state and local sporting organisations; coaches; players; and medical staff. The following documents are examples of stakeholder-specific handouts that have been developed, based on the findings of this thesis, to assist with translating the findings into practice. It is envisaged that implementing these recommendations will, ultimately, assist to make football safer.
151
Chapter 6
Figure 6.1 – Stakeholder specific guidelines for reducing injury incidence and risk in sub-elite football
152
Chapter 6
Figure 6.2 – Guidelines for practice for National, State and Local sporting organisations to reduce injury incidence and risk in sub-elite football
153
Chapter 6
Figure 6.3 – Guidelines for practice for coaches to reduce injury incidence and risk in sub-elite football
154
Chapter 6
Figure 6.4 – Guidelines for practice for players to reduce injury incidence and risk in sub-elite football
155
Chapter 6
Figure 6.5 – Guidelines for practice for medical and performance staff to reduce injury incidence and risk in sub-elite football
156
Chapter 6
6.4 References
1. Tabben M, Whiteley R, Wik EH et al. Methods may matter in injury surveillance:
“how” may be more inmportant than “what, when or why”. Biol Sport 2019;37(1):3-5.
2. Bahr R, Clarsen B, Ekstrand J. Why we should focus on the burden of injuries and
illnesses, not just their incidence. Br J Sports Med 2018;52(16):1018-1021.
3. Clarsen B. Current severity measures are insufficient for overuse injuries. Science and
Medicine in Football 2017;1(1):91-92.
4. Clarsen B, Rønsen O, Myklebust G et al. The Oslo Sports Trauma Research Centre
Questionnaire on Health Problems: a new approach to prospective monitoring ofillness
and injury in elite athletes. Br J Sports Med 2014;48(8):754-60.
5. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury definitions and
data collection procedures in studies of football (soccer) injuries. Br J Sports Med
2006;40(3):193-201.
6. Bizzini M, Junge A, Dvorak J. Implementation of the FIFA 11+ football warm up
program: How to approach and convince the Football associations to invest in
prevention. Br J Sports Med 2013;47(12):803-806.
7. Thorborg K, Krommes KK, Esteve E, et al. Effect of specific exercise-based football
injury prevention programs on the overall injury rate in football: a systematic review
and meta-analysis of the FIFA 11 and FIFA 11+ programs. Br J Sports Med
2017;51(7):562-571.
8. Silvers-Granelli H, Mandelbaum B, Adeniji O, et al. Efficacy of the FIFA 11+ injury
prevention program in the collegiate male soccer player. Am J Sports Med
2015;43(11):2628-2637.
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9. Wörner T, Clarsen B, Thorborg K et al. Elite Ice Hockey Goalkeepers Have a High
Prevalence of Hip and Groin Problems Associated With Decreased Sporting Function:
A Single-Season Prospective Cohort Study. Orthopaedic Journal of Sports Medicine
2019;7(12): Published online 18 Dec 2019: http://doi.org/10.1177/2325967119892586.
10. Esteve E, Clausen MB, Rathleff MS et al. Prevalence and severity of groin problems in
Spanish football: A prospective study beyond the time-loss approach. Scand J Sci Med
Sports 2019; Published online 17 Dec 2019: https://doi.org/10.1111/sms.13615.
11. Wollin M, Thorborg K, Drew M et al. A novel hamstring strain injury prevention
system: post-match strength testing for secondary prevention in football. Br J Sports
Med 2019;Published online 19 Oct 2019: https://doi.org/10.1136/bjsports-2019-
100707.
12. Hainline B, Turner JA, Caneiro JP, Stewart M, Moseley GL. Pain in elite athletes—
neurophysiological, biomechanical and psychosocial considerations: a narrative
review. Br J Sports Med 2017;51(17):1259-1264.
13. O’Sullivan K, O’Sullivan PB, Gabbett TJ. Pain and fatigue in sport: are they so
different? Br J Sports Med 2018;52:555-556.
14. McCall A, Davison M, Carling C et al. Can off-field ‘brains’ provide a competitive
advantage in professional football? Br J Sports Med 2016;50(12):710-712.
15. Thorpe RT, Atkinson G, Drust B et al., Monitoring Fatigue Status in Elite Team-Sport
Athletes: Implications for Practice. Int J Sport Physiol 2017;12(Suppl 2):1-25.
16. Thorpe RT, Strudwick AJ, Buchheit M et al. The tracking of morning fatigue status
across in-season training weeks in elite soccer players. Int J Sports Physiol Perform
2016;11(7):947-952.
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17. Bolling C, Barboza SD, van Mechelen W, Pasman HR. How elite athletes, coaches, and
physiotherapists perceive a sports injury. Transl Sports Med
2018;https://doi.org/10.1002/tsm2.53
18. Harøy J, Clarsen B, Wiger et al. The Adductor Strengthening Programme prevents
groin problems among male football players: a cluster-randomised controlled trial. Br
J Sports Med 2019;53:150-157.
19. Harøy J, Thorborg K, Serner A et al. Including the Copenhagen Adduction Exercise in
the FIFA 11+ Provides Missing Eccentric Hip Adduction Strength Effect in Male
Soccer Players: A Randomized Controlled Trial. Am J Sports Med 2017;45(13):3052-
3059.
20. Bizzini M, Impellizzeri FM, Dvorak J et al. Physiological and performance responses
to the "FIFA 11+" (part 1): is it an appropriate warm-up? J Sports Sci
2013;31(13):1481-1490.
21. Impellizzeri FM, Bizzini M, Dvorak J et al, Physiological and performance responses
to the FIFA 11+ (part 2): a randomised controlled trial on the training effects. J Sports
Sci 2013;31(13):1491-1502.
22. Bittencourt NFN, Meeuwisse WH, Mendonça LD, Nettel-Aguirre A, Ocarino JM,
Fonseca ST. Complex systems approach for sports injuries: moving from risk factor
identification to injury pattern recogition – narrative review and new concept. Br J
Sports Med 2016;50(20):1309-1314.
23. Windt J, Gabbett TJ. How do training and competition workloads relate to injury? The
workload—injury aetiology model. Br J Sports Med 2017;51(5):428-435.
24. Buckthorpe M, Wright S, Bruce-Low et al. Recommendations for hamstring injury
prevention in elite football: translating research into practice. Br J Sports Med
2019;53(7): 449-456.
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25. Marshall PW, Lovell R, Knox MF et al. Hamstring fatigue and muscle activation
changes during six sets of Nordic hamstring exercise in amateur soccer players. J
Strength Cond Res 2015;29(11):3124-33.
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Appendix 1
Definitions Used in Chapters 2, 3 and 5
Term Definition
Injury Any physical complaint sustained by a player that results from a football match or football training.
Time Loss Injury Any injury that results in a player being unable to fully participate in matches or training, including an injury where a player cease training or matches due to injury.
Injury Severity The number of days from the date of the injury to the date of the player’s return to full participation in training and availability for match selection. The day of injury is Day 0 and severity will be classified by the number of days that the player is unavailable for full participation. The severity is to be reported in the subcategories: Slight – 0 days; Minimal – 1-3 days; Mild – 4-7 days; Moderate – 8-28 days; Severe - >28 days
Time Exposure Exposure, in hours, to football specific training and match play is recorded. All sessions conducted by club coaching and fitness staff are recorded. Extra sessions external to the club are not included. Recurrent Injury Injury of the same type and the same site occurring within 2 months of the player’s return from the previous injury Trauma Injury Injury with sudden onset and known cause Overuse Injury Injury with insidious onset and no known cause
Injury Incidence Number of injuries per 1000 player hours
Injury Burden Number of days lost due to injury per 1000 player hours – (injury incidence × mean absence (days) per injury)
Muscle Injury A traumatic or overuse injury to the muscle including structural-mechanical and functional injuries such as fatigue induced cramps. Contusions, haematoma and tendinopathy are not included in specific muscle injury analysis
Sub-elite participation level Sub-elite players participate in a minimum of 3 scheduled team sessions/week (2 scheduled team training sessions + 1 match). This is inclusive of semi-professional (financial incentive) and amateur (non- financial) classifications. Players that are not training or playing in a full time, professional capacity.
161
Appendix 2
Injury Recording Template Used in Chapters 2, 3 and 5
Player:______1. Date of Injury:______2. Date of Full Return :______
3. Injured body part Head/face Hip/Groin Neck/cervical spine Thigh - Hamstrings Sternum/ribs/upper back Thigh - Quads Abdomen Knee Low Back/Sacrum/Pelvis Lower Leg/Achilles Shoulder/Clavicle Ankle Upper Arm Foot/Toe Elbow Forearm Wrist Hand/finger/thumb Upper Arm
4. Side of Injury Left Right Both Not Applicable
5. Type of Injury Concussion with or without Sprain/Ligament Injury Muscle LOC Rupture/Strain/Tear/Cramp Fracture Haematoma/contusion/bruise Abrasion Other Bone Injury Dental injury Laceration Dislocation/Subluxation Tendon Other______injury/rupture/tendinosis/bursitis 6a - Diagnosis:______6b - Description:______
6. Has the player had a previous injury of the same location and type? No Yes – Full Participation was______7. Was the injury caused by: Overuse Trauma 8. When did the injury occur? Date:______Training Match
9. Was the injury caused by contact/collision? No Yes, with another player Yes, with the ball Yes, with other object ______
162
Appendix 3
Survey Delivered Via SurveyMonkey in Chapter 4
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166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
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Appendix 4
11+ Program Used in Chapter 5
184
Appendix 5
University of Wollongong Ethics Approval Letter
185
186
Appendix 6
• Full Copies of Published Articles • •
1. Whalan M, Lovell R, McCunn R, Sampson JA. The incidence and burden of time loss
injury in Australian men’s sub-elite football (soccer): a single season prospective cohort
study. J Sci Med Sport 2019;22(1):42-47.
2. Whalan M, Lovell R, Sampson JA. Do Niggles Matter? – Increased injury risk
following physical complaints in football (soccer). Science and Medicine in Football
2019; doi.org/10.1080/24733938.2019.1705996.
3. Whalan M, Lovell R, Steele JR, Sampson JA. Rescheduling Part 2 of the 11+ program
reduces injury burden and increases compliance in semi-professional football Scand J
Sci Med Sport 2019;29(12):1941-1951.
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Journal of Science and Medicine in Sport 22 (2019) 42–47
Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport
j ournal homepage: www.elsevier.com/locate/jsams
Original research
The incidence and burden of time loss injury in Australian men’s
sub-elite football (soccer): A single season prospective cohort study
a,d,e,∗ b,d c,d,f a,d
Matthew Whalan , Ric Lovell , Robert McCunn , John A. Sampson
a
Centre for Human and Applied Physiology, School of Medicine, University of Wollongong, Australia
b
School of Science and Health, Western Sydney University, Australia
c
Institute of Sport and Preventive Medicine, Saarland University, Germany
d
NSW Football Medicine Association, Australia
e
Figtree Physiotherapy, Australia
f
Oriam: Scotland’s Sports Performance Centre, Heriot-Watt University, United Kingdom
a r t i c l e i n f o a b s t r a c t
Article history: Objectives: This study aimed to conduct the first injury surveillance study in sub-elite football in Australia,
Received 12 October 2017
using methods from the international football consensus statement.
Received in revised form 18 May 2018
Design: Descriptive epidemiological study.
Accepted 24 May 2018
Methods: 1049 sub-elite football players were recruited during the 2016 season. Injury and exposure data
Available online 31 May 2018
was collected by trained Primary Data Collectors (PDCs) who attended every training session and match.
Results: There were 1041 time loss injuries recorded during 52,127 h of exposure resulting in an injury
Keywords:
incidence rate of 20 injuries/1000 h (95% Confidence Interval [CI]: 15.9–23.3). The injury burden (days
Sports medicine
lost to injury relative to exposure) was 228 days lost/1000 h. Muscle and ligament injuries were the most
Athletic injuries
prevalent (41% and 26%) and incurred the highest injury burden (83 and 80 days lost/1000 h, respectively).
Injury surveillance
Elite football The most common injuries were observed at the thigh (22%) and ankle (17%), with hamstring (13%) the
Sub-elite football highest reported muscle injury. The profile of injury severity was: mild — 35%; minor — 29%; moderate
— 28% and severe — 8%. Recurrent injuries accounted for 20% of all injuries.
Conclusions: By addressing issues identified with injury recording in sub-elite football, this study found
that the injury incidence was twice that observed in previous research in elite and sub-elite football
cohorts. Injury burden was also twice that of the elite setting, with similar injuries associated with the
highest burden. The results highlight the need for investment into medical provision, facilities, coach
education and injury mitigation programmes to reduce healthcare costs to sub-elite players in Australia.
© 2018 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
1. Introduction in Australia. Injury is often the reason a player discontinues sporting
participation and can lead to long term disability and substantial
3
Football (soccer) is Australia’s most popular sport with over medical costs and economic cost associated with employment
1 4
1.1 million participants. Below the only professional league (A- absences. In alignment with Van Mechelen’s injury prevention
5
League; <1% of all Australian football participants), both National model, accurate cohort specific surveillance is necessary to inform
and regional league competitions include high level sub-elite bespoke injury prevention programmes. Thus, whilst injury pre-
6
(semi-professional and amateur) players who participate in three vention programmes can reduce injuries in football by up to 39%,
to four scheduled football sessions (training and competition) per without cohort specific injury surveillance, the effectiveness of
7
week. In addition, sub-elite players are typically committed to other injury prevention programmes cannot be accurately determined.
8
occupational employment or full time education committments In 2006 a football consensus statement was developed to guide
2
which can introduce additional stressors and strains. Despite the injury research and since publication, the majority of elite foot-
high participation rates and player participation profile, there has ball injury surveillance studies have employed the methods as
9–11
been no injury surveillance research performed in sub-elite football proposed within this statement. A number of injury surveil-
lance studies in sub-elite football have stated that the methods
used are consistent with the football consensus statement. How-
∗ ever, there is often: 1) a lack of detail regarding what injury details
Corresponding author.
12
are recorded and who collects the data, 2) inconsistencies in the
E-mail address: matt@figtreephysio.com.au (M. Whalan).
https://doi.org/10.1016/j.jsams.2018.05.024
1440-2440/© 2018 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
M. Whalan et al. / Journal of Science and Medicine in Sport 22 (2019) 42–47 43
13 18
way playing/training exposure is recorded and 3) inconsistent surveillance and completed additional training with the lead
14
injury definitions used. Meanwhile, due to a lack of resources researcher (an accredited physiotherapist) detailing how exposure
in the sub-elite setting, studies that have strictly applied the con- (minutes) and injury details were to be recorded to comply with
8
sensus statement methods report difficulties when attempting to the football consensus. The PDC was educated on injury defini-
11,15
record minor (<7 day training/match absence) injuries. Addi- tions and the process for recording detailed injury descriptions and,
19
tionally, despite research establishing the importance and value of as per previous surveillance work, from the injury description,
16
recording injury burden in the elite setting, injury burden has an injury diagnosis was later determined by an accredited phys-
is yet to be examined in the sub-elite setting. Consequently, the iotherapist using the Orchard Sports Injury Classification System
20
inconsistences and methodological limitations in sub-elite injury (OSICS-10.1). Additional groin pain subcategories of abdominal,
surveillance studies make it difficult to compare the incidence adductor and iliopsoas related origin were added to provide a more
and patterns of injury between sub-elite studies and with elite in depth analysis of hip/groin pain presentation and to broaden
12,17
cohorts. Therefore translation of current elite injury prevention the scope of the injury surveillance, allowing for comparison with
7 21
practices into sub-elite populations is somewhat limited. recent literature. Injuries that occurred late in the season were
This study aims to: 1) conduct the first injury surveillance study followed up by the PDC in order to determine a full recovery
in sub-elite football in Australia, using methods that allow strict date.
8,16
adherence to the international football consensus statement Injury incidence rate (±95% Confidence Intervals [CI]) was cal-
16
and, 2) document injury burden in sub-elite football which has culated (total injuries/total exposure (h) × 1000 h), and the mean
implications for injury prevention strategies and practices. number of days lost per injury was recorded. Injury burden was
calculated as the average number of days lost per injury relative to
16
exposure. The frequency of injuries categorised by type, mech-
2. Methods anism and location, are presented as absolute and relative values
(percentage of total injuries). If players ceased participation, their
A prospective cohort study of 1049 players (age: individual exposure and injury was still included. Thus, no player
± ± ±
24.3 6.2 years; stature: 178.6 6.9 cm; body mass: 75.2 11.2 kg) data was lost since the injury data was normalized relative to expo-
from 25 male sub-elite football clubs (each comprising ∼2–3 sure.
teams) in New South Wales (Australia) was conducted over the
2016 season. The clubs consisted of four Tier 2 (National Premier
League) and twenty-one Tier 3 (Regional League) clubs in which all
players received financial incentive to play. Clubs and players were
3. Results
recruited via a number methods including: direct contact with
team medical staff; presentations to club officials and coaches;
A total of 1041 time loss injuries were recorded dur-
engagement with the regional Association; and contact with State
ing 52,127 hours (h) of exposure (training = 40,327 h and
and National Federations. Only players that were considered sub-
matches = 11,800 h), resulting in a total injury incidence of
elite defined as “participating in a minimum of 3 scheduled team
20 injuries/1000 h (95% CI: 15.9–23.3). Matches incurred a 5-fold
sessions/week (including 2 training sessions + match day)” were
greater incidence of injuries (54 injuries/1000 h; 95% CI: 51.2–57.8)
included. Injury records were obtained during all training sessions
versus training (10 injuries/1000 h; 95% CI: 8.2–11.8). Individual
(2–3 per week) and matches including preseason, in-season and
player exposure for matches (11 h) and training (39 h) over the
finals (28–34 weeks). Prior to data collection, all players were
season resulted in a training exposure to match ratio of 3.6:1. Min-
fully informed of the study and provided signed consent. All
imal (7 injuries/1000 h; 95% CI: 4.0–8.6), mild (5.8 injuries/1000 h;
procedures were approved by the University of Wollongong’s
95% CI: 4.2–7.1) and moderate injury (5.5 injuries/1000 h; 95% CI:
Ethics Committee (reference number: 15/340).
8 4.7–6.8) severity classification were evenly distributed, and severe
The football consensus statement injury definitions and data
injuries (1.7 injuries/1000 h; 95% CI: 1.3–2.4) were relatively
collection procedures (Appendix A of Supplementary material)
uncommon (Table 1). Injuries affecting the lower limb accounted
were applied in this study. An injury was defined as “any phys-
for 86% of all injuries (Table 1), with the most common locations
ical complaint sustained by a player that results from a football
observed at the thigh (22%) and ankle (18%). The majority (82%;
match or football training”, whilst time loss injuries were defined
16 injuries/1000 h) of injuries occurred as a result of a specific
as “injury that results in a player being unable to fully participate
incident (i.e. trauma) and hamstring injuries (13%) were the most
in matches or training.” As per the football consensus statement,
common muscle injury (Table 2).
only time loss injuries were included for analysis. Players were
An injury burden of 228 days lost/1000 h with an average of
deemed to have recovered from injury once they had returned
11 days lost/injury was observed (Table 3). Muscle and ligament
to full training/match participation or were considered eligible for
8 injuries resulted in the highest injury burden (83 and 80 days
team selection.
lost/1000 h respectively), with the knee and thigh (53 and 48 days
A Primary Data Collector (PDC) at each club attended all train-
lost/1000 h, respectively) the most common locations. Injuries dur-
ing and match sessions to record football exposure and injury
8 ing match exposure resulted in a greater injury burden (160 days
data via a standardised collection form. Injury and exposure
lost/1000 h) and mean time lost to injury (13 days) when compared
records were shared with the primary researcher on a weekly
to injuries associated with training exposure (68 days lost/1000 h;
basis via a customised online data management platform. The
9 days).
use of a Primary Data Collector (PDC) at each club attempted to
Non-contact injuries (136 days lost/1000 h) resulted in a greater
address the issues identified in performing injury surveillance in
17 injury burden compared to contact injuries (92 days lost/1000 h).
sub-elite football. The PDC was designated as the only person
Despite a relatively low injury incidence, knee ligament injuries
collecting injury and exposure data; they attended every training
resulted in a similarly high injury burden (39 days lost/1000 h)
session and were present on match day to facilitate the cap-
versus hamstring muscle (38 days lost/1000 h) and lateral ankle
ture of all injuries. Each PDC was required to obtain a Sports
sprain (33 days lost/1000 h) injuries. Recurrent injuries resulted in
Trainers Level 1 certification, which is considered the national
an injury burden of 50 days lost/1000 h and a time lost average of
minimum medical qualification in Australia. Sports trainers have
13 days per injury.
been used as PDCs in sub-elite Australian Rules Football injury
44 M. Whalan et al. / Journal of Science and Medicine in Sport 22 (2019) 42–47
Table 1
Injury incidence pattern including location, type and mechanism.
Total Minimal (1–3 days) Mild (4–7 days) Moderate (8–28 days) Severe (>28 days)
Injury location
Head/face 33 (3) 16 (4) 8 (3) 7 (2) 2 (2)
Neck/cervical spine 10 (1) 3 2 4 (1) 1 (1)
Shoulder/clavicle 21 (2) 3 7 (2) 6 (2) 5 (6)
Sternum/ribs/upper back 18 (2) 8 (2) 5 (1) 4 (1) 1 (1)
Abdomen 7 2 1 3 (1) 1 (1)
Low back/sacrum/pelvis 34 (3) 19 (5) 9 (3) 5 (2) 1 (1)
Hand/finger/thumb 17 (1) 6 7 (2) 4 (1) 0
Hip/groin 126 (12) 43 (12) 39 (13) 37 (13) 7 (8)
Thigh 231 (22) 62 (17) 68 (22) 79 (27) 22 (25)
Hamstrings 145 (14) 32 (9) 34 (11) 60 (20) 19 (22)
Quadriceps 86 (8) 30 (8) 34 (11) 19 (7) 3 (3)
Knee 167 (16) 57 (16) 46 (15) 45 (16) 19 (22)
Lower leg/Achilles tendon 134 (13) 67 (18) 34 (11) 22 (8) 11 (13)
Ankle 192 (18) 55 (15) 64 (21) 59 (20) 14 (16)
Foot/toe 43 (4) 21 (6) 8 (3) 12 (4) 2 (2)
Injury type
Fracture 21 (2) 3 2 6 (2) 10 (12)
Other bone injury 12 (1) 4 4 (1) 4 (1) 0
Dislocation/subluxation 19 (2) 2 3 7(2) 6 (7)
Sprain/ligament injury 270 (26) 80 (22) 79 (26) 80 (28) 31 (36)
Meniscus/cartilage 27 (3) 6 (2) 13 (4) 7 (2) 1 (1)
Muscle injury/strain 429 (41) 140 (38) 119 (39) 136 (47) 34 (39)
Tendon injury 54 (5) 21 (6) 20 (7) 12 (4) 1
Haematoma/contusion 160 (15) 86 (24) 45 (15) 25 (9) 4 (5)
Abrasion 6 4 (1) 2 0 0
Laceration 10 (1) 6 (2) 4 (1) 0 0
Concussion 15 (1) 5 (1) 3 (1) 6 (2) 1 (1)
Other injury 20 (2) 5 (1) 9 (3) 5 (5) 1 (1)
Injury mechanism
Non-contact 599 (58) 184 (31) 179 (30) 184 (31) 52 (8)
Contact 442 (42) 180 (41) 123 (28) 104 (23) 35 (8)
Recurrent 211 (20) 61 (29) 67 (32) 66 (31) 17 (8)
Trauma 853 (82) 283 (33) 236 (28) 250 (30) 84 (9)
Overuse 188 (18) 81 (43) 66 (35) 38 (20) 3 (2)
Total injuries 1041 364 (35) 302 (29) 288 (28) 87 (8)
Values within brackets show percentage of total values (below 1% not shown).
Injury locations and types with <5 injuries are not shown.
Table 2
a
Muscle and ligament injury incidence pattern, incidence and burden.
Total Incidence (/1000 h) 95% CI Injury burden (days lost/1000 h) Average days lost/injury
Muscle injury
Hamstring muscle strain 138 (13) 3 2.4–3.4 38 14
Quadriceps muscle strain 43 (4) 1 0.8–1.2 8 9
Calf muscle strain 72 (7) 1.4 1.2–1.6 12 9
Hip/Groin pain 102 (10) 2 1.7–2.3 21 11
Adductor related 64 (6) 1.2 1.0–1.4 13 11
Iliopsoas related 32 (3) 0.6 0.5–0.7 4 7
Abdominal related 6 (1) 0.1 0.08–0.12 4 32
Recurrent muscle injury 81 (8) 1.6 1.5–1.7 20 13
Ligament sprain
Knee ligament sprain 82 (8) 1.6 1.4–1.8 39 25
ACL sprain 8 (1) 0.13 0.1–0.16 17 127
MCL sprain 43 (4) 0.8 0.6–0.1 15 18
Ankle ligament sprain 142 (14) 2.8 2.6–3.0 33 12
a
Muscle injuries only include structural and functional injuries — exclude contusions, haematoma, tendon related injuries. Values within brackets show percentage of
total all injuries (n = 1041).
4. Discussion surveillance. Injury burden was almost twice that of that seen in
16
research conducted in the elite setting, albeit the same injuries
In this study, the incidence of injury (20 injuries/1000 h) (anterior cruciate ligament rupture, hamstring muscle strains,
was more than twice that previously reported in elite (8 ankle sprains and muscle contusions) were associated with the
9 11
injuries/1000 h) and sub-elite (9.6 injuries/1000 h) cohorts. highest injury burden.
11
Strict adherence to the consensus statement methods within this In contrast to previous investigations, the injury incidence
study captured a larger percentage of “mild” and “minimal” sever- in this study was two times greater than that observed in the
9
ity (<7 days’ time lost) injuries compared to previous sub-elite elite setting, whilst injury burden in the sub-elite setting and was
11,15 16
studies, however the relative distribution of injury severity, almost twice that observed in the elite setting. Indeed, there are a
9,16
types, mechanisms and locations were all similar to elite studies. number of reasons why one might expect differences between sub-
This study was the first to add injury burden to sub-elite injury elite and elite cohorts that would result in a higher injury incidence
M. Whalan et al. / Journal of Science and Medicine in Sport 22 (2019) 42–47 45
Table 3
Thirdly, a lack of access to medical staff (e.g. medical doctors,
Injury burden of time loss injuries (injury incidence × mean absence per injury).
physiotherapists) in sub-elite football likely results in inadequate
Days lost per 1000 h Days lost per injury rehabilitation and return to play decisions that are solely coach
and/or player driven, potentially leading to uninformed decisions
Injury location
Head/face 5 8 on safe return to play. The lack of medical staff at training also typ-
18
Shoulder/clavicle 9 23 ically reduces the ability to complete accurate injury reporting.
Sternum/ribs/upper back 3 8
However, the presence of a Sports Trainer at training and on match
Low back/sacrum/pelvis 4 6
days to record injury in this study appears to have addressed this
Hip/groin 25 10
issue with a larger capture of injury data compared with previous
Thigh 48 10
Hamstring 36 13 sub-elite research. It is important to note that, in sub-elite foot-
Quadriceps 12 7
ball, it is common for a number of days to pass between scheduled
Knee 53 17
sessions with no player-medical staff contact. Correspondingly, the
Lower leg/Achilles tendon 21 8
methods utilised in this study may have overestimated time loss for
Ankle 43 11
17
Foot/toe 7 8 minimal and mild injuries and presented an inflated incidence.
Injury type As players were presumed injured until they were able to fully par-
Fracture 15 37
ticipate in training or a match, in some cases it is possible that there
Sprain/ligament injury 80 16
were 3 to 4 days between player-medical contacts, and may have
Meniscus/cartilage 5 10
increased time loss periods by 2 to 3 days. However, the effect of
Muscle injury/strain 83 10
Tendon injury 9 9 any overestimation is difficult to evaluate as an underreporting of
12
Haematoma/contusion 17 6
injuries has been noted in previous research.
Concussion 3 11
Despite the high injury incidence observed in this study, there
Dislocation 8 29
were similarities in the injury patterns observed when compared
Injury mechanism
Non-contact 136 12 with elite cohorts with muscle injuries incurring the highest injury
9
Contact 92 11 incidence and injury burden. The time loss (14 days) and relative
Recurrent 51 13
occurrence (13% of all injuries) of hamstring injury was also sim-
Trauma 203 13 29
ilar to elite populations. The impact of hamstring injuries was
Overuse 25 8
further highlighted in this study by a burden three and four times
Injury event
Match 160 13 higher than calf and quadriceps muscle injuries, respectively. Hip
Training 68 9
and groin injuries also presented at a similarly high incidence, bur-
Total 228 11 den and time loss per injury as the hamstring. The incidence of
30
groin pain was twice that previously reported in elite and two
11,21
to four times that in sub-elite populations. Hip/groin injuries
21
were sub-group classified with a resultant incidence of adductor-
and burden. Firstly, a lower training exposure (39 h/player) and related groin pain two times higher than iliopsoas-related, and
training to match exposure ratio (3.6:1) was observed versus elite ten times higher than abdominal-related groin pain, and a similar
9 30 21
populations (213 h/player and 5.2:1, respectively) , with matches distribution to existing elite and sub-elite research. Adductor-
22
yielding a higher intensity and injury incidence compared with related injury burden (13 days lost/1000 h) was similar to a recent
9,11 30
training sessions. Furthermore, whilst only field based foot- elite cohort study despite a twofold higher groin injury incidence
ball exposure is included in the football consensus statement, elite in this study. Whilst it has been suggested that higher level players
30
teams often perform additional injury prevention and strength and are at more risk of hip and groin pain, the results of this study
23
conditioning (S&C) programmes to complement on-field work. indicate that the prevalence of adductor-related groin pain at both
As such, the lower training to game ratio, reduced training expo- sub-elite and elite levels is similar. These findings reaffirm that
sure and a lack of injury prevention and S&C programmes may not thigh and groin muscle injuries represent an injury challenge in
provide adequate physical readiness for match intensities in sub- both elite and sub-elite football, and suggest that in addition to a
24
elite football. Therefore, programmes, such as the FIFA11+, that focus on thigh and ankle exercises, specific groin related exercises
6
have strong evidence for reducing injury risk in football and can should also be included in injury prevention programmes at the
be delivered in the sub-elite setting, may have an important role in sub-elite level.
addressing these issues. Knee and ankle ligament injuries were the most common liga-
Secondly, lower player skill levels can present an increased ment injuries observed in this study, and is consistent with previous
25 9
injury risk as these players are less adept at avoiding injury research conducted in the elite setting. Knee ligament sprains
scenarios involving direct contact that commonly result in were associated with player time loss more than twice that of a
26
contusion/haematoma injuries. Indeed, whilst time lost from muscle injury, contributing to a ligament injury burden similar to
direct impact injuries in this study was similar to elite football muscle injury (80 and 83 days lost/1000 h) despite a lower injury
≤ 27
( 7 days’ time loss), an incidence of 3 injuries/1000 h for contu- incidence. The incidence and burden of ligament injury was also
sion/haematomas was almost three times higher than previously much higher in this cohort of sub-elite footballers when compared
9
observed in an elite setting (1.3 injuries/1000 h). It is thus sug- to reports in an elite setting. Lateral ankle sprain incidence was five
10
gested that the methods adopted in this study, which resulted in times higher and injury burden 50% greater whilst incidence of
a high capture of minor injuries, highlight a potential issue associ- anterior cruciate and medial collateral ligament (MCL) was two to
31
ated with low skill level in sub-elite football. Compounding this, three times greater than that observed in an elite setting.
sub-elite teams often play on surfaces with significant signs of Typically, the cause of all muscle and ligament injuries (82%; 15
25
wear and tear which can exacerbate the lower skill level, and injuries/1000 h) observed in this study were the result of a specific
potentially increase impact injuries and sprains. With respect to the event (trauma). Trauma was the major cause (69%) of all non-
cohort examined within this study, an increased risk of non-contact contact injuries and resulted in a higher injury burden (136 days
traumatic injury may also have been observed due to the warmer lost/1000 h) compared with contact injuries (92 days lost/1000 h).
climate and firmer playing surface characteristics compared with Indeed, trauma has been reported as the most common injury
11,26,28 11
European based sub-elite and elite cohorts. mechanism in previous sub-elite research. In contrast, overuse
46 M. Whalan et al. / Journal of Science and Medicine in Sport 22 (2019) 42–47
9
appears more common in an in the elite setting. It should be Practical implications
considered, however, that higher football exposure/player in elite
9 •
football may result in elite players being more susceptible to The addition of a PDC to injury data collection in sub-elite foot-
overuse injury and better access to medical services may facilitate ball increases capture of less severe injuries and improves injury
11
overuse injury recording. In this current study, recurrent injuries surveillance.
•
resulted in an injury burden twice that of overuse injuries, despite The pattern and severity distribution of injury is similar in elite
a similar injury incidence, with the mean days lost similar to that and sub-elite football.
•
of non-contact and contact injuries. Interestingly, the incidence of The high incidence and burden of injuries emphasises the need
9
recurrent injuries was two-four times higher than previous elite to include programmes, such as the FIFA11+, in sub-elite football.
11,15
and sub-elite research which we attribute to the increased Particular focus should be applied to the prevention of knee, ankle
number of minor (time loss <7 days) injuries captured. Indeed, the and hamstring related injuries due to their associated high injury
majority of injuries (64%) in this study were classified as minor, burden.
•
substantially increasing the number of ‘initial’ injury events that Additional coach education via the coaching curriculum to
may be defined as recurrent. Injury recurrence was also 50% higher develop: i) strategies to ensure adequate player preparation, ii)
in this study compared to “top level” UEFA European elite cohorts, delivery of injury prevention programmes, and iii) return to play
but similar to that seen in “high level” (Swedish Premier Division) policies are warranted.
15
teams. This difference is likely explained by improved medical
9,16
resources and larger squad sizes at the “top level”. Based on Funding
the prevalence and burden of recurrent injuries in sub-elite foot-
ball, strategies to improve return to play policies are thus required,
Research grant from University of Wollongong.
with the importance of minor injury data capture highlighted in
this study.
Ethics approval
This study has shown a high injury incidence in sub-elite foot-
ball; however when considering the results, the limitations of this
University of Wollongong.
study should be acknowledged. Firstly, multiple PDCs at multiple
clubs collecting the data may have presented a degree of extraneous
variability. By conducting extensive training of the PDC cohort how- Acknowledgements
ever, we aimed to minimize potential reporting differences and this
‘interclub’ variation would also be equally prevalent in any injury The authors would like to thank Football South Coast and the
12
surveillance research involving multiple practitioners. Football Federation of Australia for facilitating this project and all
Secondly, the football consensus statement defines an injury as of the clubs, coaches, players and data collectors involved in this
“any physical complaint”, however only injuries which resulted study.
in an inability to participate in training or matches are typically
8
included for analysis. The accumulative nature of overuse injuries
Appendix A. Supplementary data
though, often leads to players with physical complaints continuing
to fully participate in football, suggesting it is likely that overuse
Supplementary data associated with this article can be found, in
injuries account for a much larger injury prevalence than reported
the online version, at https://doi.org/10.1016/j.jsams.2018.05.024.
32
in this study. Furthermore, accumulated fatigue and injury from
participation in other sports, recreational pursuits, and work out-
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Do Niggles Matter? - Increased injury risk following physical complaints in football (soccer)
Matthew Whalan, Ric Lovell & John A Sampson
To cite this article: Matthew Whalan, Ric Lovell & John A Sampson (2019): Do Niggles Matter? - Increased injury risk following physical complaints in football (soccer), Science and Medicine in Football, DOI: 10.1080/24733938.2019.1705996 To link to this article: https://doi.org/10.1080/24733938.2019.1705996
Accepted author version posted online: 14 Dec 2019. Published online: 23 Dec 2019.
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Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=rsmf20 SCIENCE AND MEDICINE IN FOOTBALL https://doi.org/10.1080/24733938.2019.1705996
Do Niggles Matter? - Increased injury risk following physical complaints in football (soccer) Matthew Whalan a,b,c, Ric Lovell b,d and John A Sampson a,b aCentre for Human and Applied Physiology, School of Medicine, University of Wollongong, Wollongong, Australia; bNSW Football Medicine Association; cFigtree Physiotherapy, Australia; dSchool of Science and Health, Western Sydney University, Australia
ABSTRACT ARTICLE HISTORY Objective: To determine the prevalence and impact of non-time loss injuries in semi-professional Accepted 10 December 2019 football. KEYWORS Methods: 218 players completed the Oslo Sports Trauma Research Centre (OSTRC) Questionnaire on Time loss; non-time loss; Health Problems weekly during the 2016 season (35 weeks), recording the prevalence and impact of time prevention; injury loss (TL) and non-time loss (non-TL) injuries. TL injury and exposure were also collected by a third party as surveillance per the Football Consensus statement. The relative risk (RR) of a TL injury within 7 days of a self-reported non-TL injury was determined, with associated predictive power calculated. Results: The risk of TL injury was 3.6 to 6.9 × higher when preceded by ‘minor’ and ‘moderate’ non-TL complaints, respectively, and good predictive power (22.0–41.8%) was observed (AUC range = 0.73 to 0.83). Compliant responders (80% of completed OSTRC questionnaires) showed a mean self-reported weekly injury prevalence (TL and non-TL combined) of 33% (95% CI – 31.4% to 34.6%) with 28% (CI – 26.4% to 29.6%) attributed to non-TL injury. Conclusion: Over a quarter of players on average, report a physical complaint each week that does not prevent them from participating in training or match play. A non-TL injury was shown to be useful in identifying individual players at an increased risk of a TL injury.
Introduction surveillance. In the sub-elite setting, however, there is often a lack of medical staff and recording protocols may need to be Accurate injury surveillance underpins effective injury pre- more adaptable (Finch 2017). Self-reported data collection ventionprograms(VanMechelenandHlobil1992). methods can improve injury data collection (Gallagher et al. However, in football injury research, whilst an injury is 2017), increasing capture of physical complaints that do not defined as ‘any physical complaint’ (Fuller et al. 2006), only result in training or match play absences (a non-TL injury), time loss (TL) injuries resulting in a failure to fully partici- versus more commonly used TL only methods (Clarsen et al. pate in training or matches are used to determine injury 2013; Ekegren et al. 2015; Møller et al. 2017; Langhout et al. incidence and severity (Ekstrand et al. 2011). It is acknowl- 2018). However, little is known about the prevalence and edged that excluding physical complaints that do not result impact that non-TL injuries in football may have on more in a TL injury may underestimate the true injury profile in serious TL injury risk. This information may have particular football (Clarsen 2017). The complex nature of injury sug- importance in semi-professional environments, where the gests that as many contributing factors as possible should players’ primary source of income may be from non-football be considered during surveillance to improve the effective- occupations, and the long-term cost of injury can effect both ness of injury risk reduction strategies (Bolling et al. 2018). the player’s health (Hainline et al. 2017a) and financial status Notably, in overuse injuries, tissue failure may already be (Lee and Garraway 1996). Indeed, injuries in non-professional present before the development of pain and performance settings; such as a college, high school or university, are asso- deficits, with dysfunction in a local area potentially impact- ciated with significant financial cost (Fair and Champa 2018). ing on pathology in neighbouring regions (Wilke et al. The increasing costs associated with sporting injury has led to 2019). As such, injury surveillance methods that capture all suggestions that the risk of injury, may negate the positive ‘physical complaints’ may improve the sensitivity of injury health benefits associated with physical activity (Conn et al. surveillance (Clarsen and Bahr 2014) and allow practitioners 2003). It is therefore of paramount importance that practi- to consider the magnitude of the symptoms suffered along- tioners continue to search for effective and easily implementa- side the burden associated with time loss injury (Bahr et al. ble methods to reduce injury incidence (Marshall and 2018). Guskiewicz 2003). Such methods may be achieved in an elite setting where The current study will therefore compare the prevalence and clubs have access to full-time medical staff and resources that impact of ‘all physical complaints’ in semi-professional football allow thorough player monitoring and accurate injury
CONTACT Matthew Whalan [email protected] Centre for Human and Applied Physiology, School of Medicine, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia © 2019 Informa UK Limited, trading as Taylor & Francis Group 2 M. WHALAN ET AL.
between self-reported and third party injury surveillance recording ‘Cannot participate due to injury’ was recorded. A non-TL injury methods and further aims to; 1) determine the relative risk of was recorded when a player self-reported ‘full participation but sustaining a TL injury within 7 days of reporting the presence (vs with health problems’ (minor) or ‘reduced participation due to absence) of a reported non-TL injury; 2) examine whether the health problems’ (moderate). The impact of any non-TL injury presence of a non-TL injury, in isolation, is linked injury occurrence. reported was further assessed by its affect (minor or moderate) on performance, volume of training and perceived severity. Players reporting the presence of any injury (TL or non-TL) Methods were required to record the location as per the Fuller et al. Participants (2006) football consensus statement. Illnesses were also recorded by the OSTRC Questionnaire but were not included fi Twenty- ve teams from 10 semi-professional football clubs, in the analysis for this study. All PDC’s, clubs and coaches were volunteered to participate in the study during the 2016 season. blinded to self-report responses. Clubs were recruited from the NSW National Premier League To facilitate compliance, the questionnaire reminder was nd rd and Illawarra Premier League in Australia (2 and 3 tiers of emailed the day after each weekly game and resent daily up participation, respectively). All players participated in a mini- until the first training session of the following week to any mum of three football-based sessions per week (training and players that had not yet completed the questionnaire. The match). Prior to data collection, all players were informed of the primary investigator then sent each PDC a list of players who study and provided written informed consent. All procedures had not yet completed the questionnaire and they were asked ’ were approved by the University of Wollongong s Ethics to encourage players to complete the questionnaire online Committee (reference number: 15/340). prior to the start of training.
Time loss injury data collection Statistical analysis TL injury data and individual exposure minutes (training and During analysis, PDC reported TL injuries were compared with match) were collected in accordance with the Fuller et al. self-reported questionnaire responses. Weekly non-TL or self- (2006) consensus statement on injury definitions and data collec- reported ‘complaints’ from players fully participating in the tion procedures in football, with injury defined as ‘any physical training were included in the analysis. Self-reports submitted complaint’, and TL injury defined as an ‘inability to fully partici- by players engaged in modified training or rehabilitation were pate in football training or matches’ (Fuller et al. 2006). To excluded from the relative risk (RR) analysis but retained within comply with the Consensus methods, each club was assigned a prevalence calculations. In these cases, the player would be Primary Data Collector (PDC) holding a minimum medical quali- considered to be ‘injured’ under the TL injury definition as fication (Sports Trainer Level 1), a method that has been pre- they have an ‘inability to fully participate in football training viously shown to be a valid and reliable means of collecting or matches’ (Fuller et al. 2006), and the self-reported injury injury data (Ekegren et al. 2015;McCunnetal.2017). The PDC would relate to a pre-existing TL injury. Similarly, if a PDC TL attended all training and match sessions to record injury and injury report was present in the absence of a player self-report exposure via standardised data collection forms and were pro- in the preceding week, the TL injury was excluded from the vided with additional tuition by a qualified physiotherapist relative risk (RR) analysis but included in the overall seasonal detailing injury description, definitions, and recording exposure total for prevalence calculations. to comply with the Fuller et al. (2006) Consensus statement The ‘normal’ risk of injury was determined by calculating the (Whalan et al. 2019). No exposure data was recorded for players risk of a TL injury within 7 days of a self-report indicating ‘no performing modified training or rehabilitation exercises at train- physical complaints’. The RR of a TL injury occurring within 7 ing. Players were considered no longer injured on their return to days of a non-TL ‘minor’ or ‘moderate’ complaint was calculated full training and deemed available for match selection. relative to the ‘normal’ injury risk. The risk of sustaining a TL injury at a specific location was also determined relative to the specific location of the self-reported non-TL complaint. To Non-time loss injury data collection account for within-subject variance due to the repeated mea- The presence and impact of physical complaints on training/ sures and potential unbalanced nature of the data set (differ- match participation, performance, volume and severity were ences in number of survey responses by players), a generalized assessed weekly (35 weeks) using the OSTRC Questionnaire on estimating equation (GEE) analysis (SPSS v24, IBM, USA) was Health Problems (Clarsen et al. 2014). The OSTRC Questionnaire used to examine associations between OSTRC questionnaire was only used to record injury occurrence, an accumulated injury reports for each category and occurrence of time loss ‘injury score’ was not calculated. A survey link was emailed to injury within 7-days. Specifically, a binary logistic regression each player at the start of each week (www.surveymonkey. model (link function) was used, including a robust estimator com) with instructions to complete prior to the first training with an autoregressive working correlations matrix and an inde- session of the same week. Due to the ‘participation’ focus in the pendent model category. The predictor variable was the OSTRC Fuller et al. (2006) consensus statement for injury definition, the value for that week, which was coded as an ordinal variable and ‘participation’ category of the OSTRC Questionnaire was included in the model as a Factor. That is, for the participation selected to be the primary category for analysis. A TL injury category, full training with no health problems = 1, full training was recorded via the OSTRC Questionnaire when a report of but with health problems = 2; reduced participation due to SCIENCE AND MEDICINE IN FOOTBALL 3
health problems = 3; Cannot participate due to health pro- completed >80% of the weekly questionnaires (mean = 28.5 [CI: blems = 4. ‘1 – Full training with no health problems’ was 26.2 to 31.3] completed questionnaires each week) to form the used as the reference category. The response/dependent vari- sub-group. In this sub-group of players, the risk of TL injury within able was the injury indicator represented ordinally (0 = no TL 7-days of ‘no health problems’ was 9%. The associated injury risk injury within 7 days/1 = TL within 7 days), modelled as a Binary and prediction results for the sub-group are also reported (Tables 1 logistic. Exponential parameter estimates were included to cal- and 2). culate odds ratio values to determine the relative effects of reporting a 2 or 3 (compared to reporting a 1) on the OSTRC health questionnaire on the risk of sustaining a subsequent Sub-group time-loss injury (within 7 days). In the event of a missing ques- The magnitude of the increase in risk (RR) and predictive capacity tionnaire response, this week was excluded from analysis for future TL injury was similar for the sub-group and entire cohort regardless of whether or not a TL injury was recorded in the (Table 2). The total number of reported ‘physical complaints’ was following 7 day period. Where significance was observed, sub- 2.3 times greater when comparing self-reported versus PDC meth- category analysis with RR (95% CI) was calculated and resultant ods(n=604vs265).Withintheself-reports,non-TLinjurieswere p values used to calculate the likelihood of a harmful effect 13.2 times (516 vs. 39) higher; however, TL injuries were 2.6 times statistic, accompanied by relevant probabilistic terms to lower (88 vs. 226) when compared to PDC data (Table 3). The describe the clinical inference ranging from ‘most unlikely to be proportion and distribution of injuries were similar between meth- harmful <0.5%’ to ‘most likely to be harmful >99.5%’ (Hopkins ods, with 87% (PDC) and 83% (self-reported) of all injuries affecting 2007). The predictive power of a non-TL complaint on the the lower limb. The most common locations were the hamstring occurrence of a TL injury was examined using receiver operating (17% – PDC; 16% – self report) and knee (19% – PDC; 17% – self characteristic (ROC) curves. The area under the curve (AUC) was report; Table 3). Overall, 68% of all TL injuries were preceded by a used to determine discriminatory power, with values <0.5, >0.7, non-TL report, with 94% of knee and 90% of hamstring TL injuries and 1.0 considered as poor, good, and perfect, respectively preceded by a non-TL complaint in the same location. The greatest (Crowcroft et al. 2016). Diagnostic accuracy and predictive risks were observed in the ankle and lower leg (RR = 6.8 and 6.3, power (95% CI) were also determined via sensitivity and speci- respectively; Table 3). As players were able to report multiple ficity analysis of minor and moderate complaint sub-categories locations per survey, there were more injury locations than injury of the OSTRC Questionnaire. reports recorded via the OSTRC Questionnaire (Table 3). OSTRC questionnaire response rates of 80% have previously been observed in athletic groups (Clarsen et al. 2014; Harøy et al. 2017). To accurately assess the effects of minor and Sub-group weekly injury prevalence moderate injury reports, a sub-group analysis of players with >80% response rates across the season was performed. Initially, Self-reports highlighted 33% (95% CI – 31.4% to 34.6%) of all the results of the GEE, RR and predictive characteristics of the players recorded an injury (comprising TL and non-TL injuries) sub-group and entire cohort were compared. In the event that each week with non-TL complaints accounting for 28% (95% both groups were statistically similar, an absence of bias was CI – 26.4% to 29.6%) of all weekly injuries (Figure 1A). Combining assumed and further analysis of the sub-group performed to self-reported non-TL and PDC recorded TL injury reports indicates assess the frequency of injury and reported weekly injury loca- that49%(95%CI– 47.0% to 51.0%) of players were affected by tions relative to PDC reports. Data are presented as absolute injury each week (Figure 1B). and relative values. Weekly injury prevalence was determined by calculating the percentage of injury reports relative to the total number of players participating that week. Discussion To our knowledge, this is the first study to investigate the Results impact and prevalence of non-TL injuries in semi-profes- sional men’s football. Across the cohort of 218 players, the Relative risk and time-loss injury prediction TL injury risk within 7 days of a self-reported minor or A total of 218 players (age: 24.1 ± 4.3 years; height: 177.1 ± 5.2 cm; moderate non-TL injury (complaint) effecting performance, weight: 74.9 ± 6.2 kg) participated in the study. A total of 3430 participation, volume or perceived severity was three to questionnaires were completed over the 35 week period (45% seven times greater compared to the absence of any com- overall compliance, mean = 98 [95% CI – 88.1 to 110.2] completed plaint. Uniquely, a non-TL report across all four categories questionnaires each week). The risk of sustaining a TL injury within presented ‘good’ injury prediction capacities of sustaining a 7-days of self-reported ‘no health problems’ was 6%. OSTRC TL injury within the subsequent 7-days. A comparison of Questionnaire perceived minor and moderate effects on participa- PDC and self-reports in the compliant group indicated a tion,performance,volumeandseverity were each associated (P< total injury prevalence more than 2 times higher within 0.05) with an increased relative risk of TL injury within 7-days (Table the self-reports. As similar injury risks and predictive capa- 1). The power of a reported non-TL injury to predict the incidence cities were observed in compliant and non-compliant of a TL injury within 7-days was good across all OSTRC categories groups, to facilitate a detailed analysis of the results, the (Table 1). Sensitivity, specificity and positive predictive power discussion relates to the findings of the compliant sub- values are displayed in Table 2. A cohort of 73 (33%) players group (n = 73). 4 M. WHALAN ET AL.
Table 1. Associated injury risk and injury prediction using the OSTRC Questionnaire on Health Problems (Clarsen et al. 2014) for time loss injury for the entire cohort and sub-group. Entire Cohort (n = 218) Association Prediction OSTRC Category P level Relative Risk (RR) a Clinical Inference (Hopkins 2007) Area Under the Curve Ɨ Participation <0.0001 0.79 (CI: 0.76 to 0.82) Full Participation with Problems 3.3 (CI: 2.0 to 5.8) 93.5% – likely harmful 0.75 (CI: 0.70 to 0.80) Reduced Participation Due to Health Problems 6.5 (CI: 3.7 to 8.9) 100% – most likely harmful 0.79 (CI: 0.74 to 0.84) Performance <0.0001 0.79 (CI: 0.75 to 0.83) To a minor extent 4.0 (CI: 1.9 to 9.3) 93.1% – likely harmful 0.77 (CI: 0.72 to 0.83) To a moderate extent 5.5 (CI: 3.2 to 9.4) 100% – most likely harmful 0.80 (CI: 0.75 to 0.84) Volume <0.0001 0.77 (CI: 0.74 to 0.80) To a minor extent 4.4 (CI: 1.9 to 5.7) 100% – very likely harmful 0.75 (CI: 0.71 to 0.79) To a moderate extent 6.9 (CI: 3.2 to 10.1) 100% – very likely harmful 0.74 (CI: 0.70 to 0.78) Severity <0.0001 0.73 (CI: 0.69 to 0.76) To a minor extent 4.7 (CI: 0.01 to 11.7) 63.4% – possibly harmful 0.69 (CI: 0.65 to 0.74) To a moderate extent 4.8 (CI: 1.1 to 15.0) 99.2% – likely harmful 0.72 (CI: 0.67 to 0.76) Sub Group** (n = 73) Participation <0.0001 0.83 (CI: 0.80 to 0.86) Full Participation with Problems 2.8 (CI: 1.01 to 7.8) 95.2% – likely harmful 0.79 (CI: 0.73 to 0.84) Reduced Participation Due to Health Problems 5.2 (CI: 2.7 to 9.9) 100% – most likely harmful 0.83 (CI: 0.78 to 0.88) Performance <0.0001 0.82 (CI: 0.79 to 0.85) To a minor extent 3.2 (CI: 1.01 to 10.3) 94.6% – likely harmful 0.80 (CI: 0.76 to 0.84) To a moderate extent 5.4 (CI: 2.78 to 10.4) 100% – most likely harmful 0.83 (CI: 0.79 to 0.87) Volume <0.0001 0.78 (CI: 0.75 to 0.82) To a minor extent 3.5 (CI: 1.9 to 6.7) 99.9% – very likely harmful 0.75 (CI: 0.70 to 0.80) To a moderate extent 5.9 (CI: 3.6 to 9.4) 100% – most likely harmful 0.72 (CI: 0.66 to 0.77) Severity <0.0001 0.78 (CI: 0.75 to 0.82) To a minor extent 3.6 (CI: 0.01 to 10.7) 64.3% – possibly harmful 0.68 (CI: 0.62 to 0.75) To a moderate extent 5.2 (CI: 1.82 to 15.0) 99.5% – very likely harmful 0.77 (CI: 0.73 to 0.81) aRR of a third party reported TL injury within 7-days of the non-TL injury report within each category (95% confidence intervals) **Sub-group inclusion determined by >80% completion of OSTRC Questionnaire surveys during the season. Ɨ Area under the curve based on ROC curve analysis for each category for prediction of a time loss in 7-days following a physical complaint (95% confidence interval).
Importance of non-time loss injuries et al. 2015), which may affect performance capacity and contribute to the more serious injury risk we observed. In this study, the majority (85%) of recorded OSTRC Questionnaire Pain that leads to a ‘physical complaint’ may originate complaints were non-TL and did not prevent participation. Our from a number of pathological issues (Hainline et al. results thus highlight that including non-TL injuries substantially 2017b) and the high prevalence observed in this study increases the prevalence of ‘slight’ (0–1dayTL)injuries(‘physical reveals the pain-related issues that players in semi-profes- complaints’) in semi-professional football (van Beijsterveldt et al. sional football experience on a weekly basis. Issues asso- 2015). Previously, congested match fixtures have been associated ciated with pain, long-term medication use, and the withathirdofplayersreportinggroinpainonaweeklybasis development of chronic pain conditions in elite athletes (Harøy et al. 2017). However, to our knowledge, our study is the (Hainline et al. 2017a)havebeenidentified, with the long- first prospective study in semi-professional football to be con- term health of ex-professional football players impacted by ducted over an entire season and record all injury locations. osteoarthritis related pain (Arliani et al. 2016). When inter- Therefore, given the duration of the TL and non-TL injury capture, preting our results it is, however, important to consider that our findings highlight a more comprehensive injury profile in semi- pain is often associated with sporting injury (Meyers et al. professional football than previously reported. 2001), may be present in the absence of physiological or Previously, the need to record non-TL injuries has been biomechanical pathology, and can continue after damaged questioned due to concerns over obtaining accurate and tissue has healed (Hainline et al. 2017b). Furthermore, ath- useful data (Orchard and Hoskins 2007). However, the letesareknowntohaveagreatercapacitytoperformand results of the current study in semi-professional football, participate despite pain compared with non-athletes (Tesarz show a non-TL physical complaint to be associated with a et al. 2012), and pain may be a by-product of the normal 2.8–5.9 fold increase in the risk of sustaining a TL injury risk process of a physiological overload stimulus and ensuing within the subsequent 7-days. Determining why this fatigue (O’Sullivan et al. 2018). Regardless of the pathology, increased risk exists is likely to be multifactorial and depen- mechanism, or origin of pain, this study highlights that the dent on the origin of the player’s pain and physical discom- presence of a non-TL injury clearly increased the risk of a fort (Bittencourt et al. 2016;Hainlineetal.2017a). The subsequent TL injury and suggests that reporting non-TL presence and perceived impairment (minor or moderate) injuries may be an important consideration for coaches, resulting from a complaint, are likely to reflect the presence players, medical and performance staff in semi-professional of perceived pain. Importantly, the risk of a TL injury within football. 7-days of a reported complaint increased with elevated Our findings thus support research that suggests the perception of ‘pain’ severity. The presence of pain alters complexity of injury should be considered when describing motor patterns and muscle recruitment behaviour (Hodges the injury ‘problem’ and the multifactorial aetiology of SCIENCE AND MEDICINE IN FOOTBALL 5
Table 2. Diagnostic accuracy assessment for OSTRC Questionnaire on Health Problems (Clarsen et al. 2014) for each sub-category drawn from entire cohort and sub- group. True False False True Sensitivity (%) with Specificity (%) with Positive Predictive Value (%) OSTRC Questionnaire Category Positive (n) Positive (n) Negative (n) Negative (n) 95% CI 95% CI with 95% CI Entire Cohort (n = 218) Participation Full participation with problems 67 237 0 14 100.0 (100) 5.6 (2.2 to 7.1) 22.0 (19.4 to 24.8) Reduced participation due to 82 156 0 2 100.0 (100) 1.3 (0.2 to 3.1) 34.5 (31.6 to 39.3) health problems Performance To a minor extent 93 277 0 15 100.0 (100) 5.1 (2.8 to 7.3) 25.1 (21.9 to 30.0) To a moderate extent 56 102 0 4 100.0 (100) 3.8 (2.1 to 7.9) 35.4 (30.3 to 40.9) Volume To a minor extent 74 203 0 8 100.0 (100) 3.8 (1.9 to 4.9) 26.7 (21.2 to 31.9) To a moderate extent 48 72 0 10 100.0 (100) 2.9 (1.8 to 4.1) 35.5 (30.2 to 41.8) Severity To a minor extent 101 253 0 15 100.0 (100) 5.6 (2.1 to 7.3) 28.5 (23.7 to 31.5) To a moderate extent 51 128 0 4 100.0 (100) 3.0 (1.1 to 5.1) 28.5 (25.9 to 30.2) Sub-Group (n = 73) Participation Full participation with problems 64 196 0 36 100.0 (100) 15.5 (10.9 to 20.2) 24.6 (19.4 to 29.8) Reduced participation due to 75 120 0 25 100.0 (100) 17.2 (11.1 to 23.4) 38.5 (31.6 to 45.3) health problems Performance To a minor extent 85 219 1 51 98.8 (96.6 to 100) 18.9 (14.2 to 23.6) 28.0 (22.9 to 33.0) To a moderate extent 51 81 0 14 100.0 (100) 14.7 (7.6 to 21.9) 38.6 (30.3 to 46.9) Volume To a minor extent 70 163 0 37 100.0 (100) 18.5 (13.1 to 23.9) 30.0 (24.2 to 35.9) To a moderate extent 48 72 0 10 100.0 (100) 12.2 (5.1 to 19.2) 40.0 (31.2 to 48.8) Severity To a minor extent 92 203 1 54 98.9 (96.8 to 100) 21.0 (16.0 to 26.0) 31.2 (25.9 to 36.5) To a moderate extent 50 85 0 26 100.0 (100) 23.4 (15.5 to 31.3) 37.0 (28.9 to 45.2)
Table 3. Sub-Group time-loss Injury reports and associated relative risk following a previous physical complaint. Data presented according to location using third party (Football Consensus) (Fuller et al. 2006) and self-reporting method (OSTRC Questionnaire on Health Problems) (Clarsen et al. 2014). Football Consensus OSTRC Participation Category Time Loss – 3rd Party Total – Self Non-Time Loss – Self Relative Risk Clinical Inference Factor – Non-Time Injury Location Method Report Report (RR)a (Hopkins 2007) Loss/Time Loss** Head/face 6 (3) 4 2 - Neck/cervical spine 2 11 (1) 11 (1) - Shoulder/clavicle 3 (1) 18 (2) 14 (2) - Sternum/ribs/upper 3 (1) 27 (3) 23 (3) - back Hand/finger/thumb 4 (2) 16 (2) 15 (2) - Wrist 1 0 0 - Low back/ 11 (5) 76 (9) 69 (9) 1.9 (CI: 0.2 to 64.8% – possibly harmful 6.3 sacrum/pelvis 19.5) Hip/groin 26 (12) 138 (16) 128 (17) 3.5 (CI: 2.4 to 100% – most likely 4.9 5.2) harmful Thigh 64 (28) 189 (22) 163 (21) 5.2 (CI: 2.2 to 99.8% – most likely 2.5 12.5) harmful Hamstring 39 (17) 136 (16) 116 (15) 4.7 (CI: 2.0 to 99.7% – most likely 3.0 11.0) harmful Quadriceps 25 (11) 58 (7) 52 (7) 5.8 (CI: 1.4 to 96.9% – most likely 2.1 24.9) harmful Knee 43 (19) 149 (17) 122 (16) 3.6 (CI: 2 to 6.1) 100% – most likely 2.8 harmful Lower leg/Achilles 28 (12) 89 (10) 78 (10) 6.3 (CI: 0.1 to 75.7% – likely harmful 2.8 tendon 375.8) Ankle 22 (10) 59 (7) 52 (7) 6.8 (CI: 0.1 to 77.1% – likely harmful 2.4 376.0) Foot/toe 10 (4) 38 (4) 36 (5) 1.3 (CI: 1.1 to 96.2% – very likely 3.6 1.5) harmful Total Injury Reports 226 604 516 2.3 Total Injury Locations 226 871 771 aRR – of a third party reported time loss injury occurring within 7 days following a self-reported non-time loss injury (determined on injuries with prevalence ≥5%; 95% confidence intervals. Normal risk = 10%) ** Factor = Total Non-time loss injury via OSTRC Questionnaire/Total Time Loss via Football Consensus (only locations with >10 time loss injuries included). Values within brackets show percentage of total injury locations (below 1% not shown) incidence (Bittencourt et al. 2016; Bolling et al. 2018). In this insight into the physical state of a player preceding a study, self-reports increased the detail of an injury occur- more severe injury resulting in TL. Therefore, our findings rence and encapsulated symptom severity and provided demonstrate a simple method to enhance the first stage of 6 M. WHALAN ET AL.
Figure 1. Prevalence of all injuries (dark grey) and non-TL only injuries (light grey) recorded by the weekly self-reported injury OSTRC Questionnaire on Health Problems (A); Combining both injury surveillance methods – Self-reported and Third Party (B). the injury prevention cycle illustrated by Van Mechelen (Van Uniquely, the presence of a non-TL injury in this study Mechelen and Hlobil 1992). displayed ‘good’ predictive power for future injury, suggest- ing that non-TL injuries or ‘complaints’ can classify ‘high risk’ players who may require an injury risk reduction inter- Another tool in the injury risk reduction tool box? vention (McCall et al. 2017). The strong associations observed between non-TL reports preceding a TL injury in The complex and multifactorial nature of injury (Bittencourt the same location (Table 3), suggest it may also be possible et al. 2016) challenge practitioners and researchers to to identify location-specific injury risks. However, the current search for tools that identify players at increased risk of research does not allow us to accurately determine whether injury, and to implement methods to mitigate this risk the TL injury suffered was a direct result of a worsening of (Windt and Gabbett 2017). The results of this study suggest an issue in the same location or related to a separate issue that the OSTRC Questionnaire may assist in identifying high- in a different location. Notably, all OSTRC questions were risk players in semi-professional football. Indeed, improving associated with identifying at risk players to similar degrees, communication between key stakeholders within a club can suggesting that a single question could be equally effective. reduce injury incidence and sustain player availability Reducing questionnaire burden may also facilitate compli- (Ekstrand et al. 2019). ance. The positive predictive values of 24.6% to 40% SCIENCE AND MEDICINE IN FOOTBALL 7
(increasing as reported symptom severity increased) asso- Limitations ciated with the risk of injury were substantially greater than Despite the clear association between non-TL injuries and the1.8%to3.8%workload-relatedrisksobservedinprofes- occurrence of a TL injury in this study, a number limitations sional football (McCall et al. 2018). However, whilst good at should be acknowledged. capturing players at increased risk (high sensitivity), consid- The low compliance rate of players (33%) completing the ering the presence of non-TL injury for the prediction of a weekly survey in this study highlights a potential barrier for the TL injury resulted in a high number of false positive results use of the OSTRC Questionnaire for both injury surveillance and as (low specificity). Considering non-TL injury reports in isola- a potential risk identification tool. This issue has also been tion to predict injury is not recommended, however using observed in other athletes with survey compliance over 12 weeks the OSTRC Questionnaire as an early identification tool to reported as 52% (24/46 players) (Møller et al. 2017). However, given prevent minor injuries progressing to more significant ones, the similarity of the results we observed between the entire cohort i.e. a secondary prevention tool, may be beneficial. As such, and the sub-group, we do not believe that there is an issue in a non-TL complaint may be considered as a ‘flag’ to open generalising our results on a larger scale. Methods to improve buy- player-coach/medical staff communication and assist in in to self-reported player monitoring methods are thus required. injury risk reduction. Adopting smartphone technology may improve compliance (Møller et al. 2017; Harøy et al. 2017) and allow sessional or daily application of the survey. Football consensus method vs OSTRC Questionnaire on The delivery design of the OSTRC Questionnaire presents Health Problems a limitation to the use of the questionnaire for injury ‘pre- Despite the lower capture of TL injury data, 2.3 times more diction’ with multiple injury locations able to be recorded total physical complaints were captured using the OSTRC each week. Whilst 90% of all TL hamstring injuries in this Questionnaire, with a third of players reporting a physical study were preceded by a non-TL hamstring complaint, 33% complaint of varying severity each week. Our findings thus of these preceding complaints included more than one suggest that the Football Consensus method of injury sur- location, and it has been suggested that pain at locations veillance underestimates the number of ‘slight’ (0–1dayTL) distal to a TL injury site may impact on future injury risk injuries sustained in semi-professional football and is con- (Wilke et al. 2019). As such, it is not possible to conclusively sistent with previous research (Harøy et al. 2017). This result determine whether the subsequent TL hamstring injury was is likely a consequence of methods that rely on players always a progression of the reported non-TL hamstring reporting injuries to a medical staff member (Fuller et al. injury, or was related to the non-TL injury in a different 2006). In professional sport, reporting medical complaints is location. To further evaluate the efficacy of using the perceivedtobeanissue(Bjørneboeetal.2011), and is OSTRC Questionnaire for injury prediction, more frequent likely exacerbated in semi-professional sport due to application is necessary. decreased medical access (vanBeijsterveldtetal.2015). We also acknowledge that differences in i) coaching The increased prevalence of self-reported non-TL injuries styles (Ekstrand et al. 2018), ii) previous injury history and observed in this study was thus a likely consequence of physical fitness levels (Windt and Gabbett 2017) and iii) providing the opportunity to report complaints indirectly workloads preceding a TL injury (McCall et al. 2018)were (Møller et al. 2017). each uncontrolled extraneous variables that may have Despite the increased prevalence of non-TL injuries impacted TL injury risk and non-TL injury prevalence includ- observed within self-reports recorded, PDC’sinthisstudy ing that were not considered in the analysis in this study. recorded >2.5 times the number of TL injuries compared Additionally, the translation of the findings from this study with self-reports. The consistent capture of this TL injury to the professional setting may be limited. In the profes- data is essential to determine severity profiles and burden sional setting, players are likely to be monitored far more associated with injury (Bahr et al. 2018) and our results thus closely than in semi-professional football. However, the also highlight the importance of third-party injury surveil- results may suggest that the use of changes in pain reports lance methods. There are a number of possible explanations commonly collected in daily monitoring in the professional for the observed TL report discrepancy, (i) an injured player setting (Thorpe et al. 2017), may have potential in second- who did not attend at training that week may have failed to ary injury prevention strategies and requires further investi- complete the survey; (ii) players may have perceived TL gation.Finally,thetreatmentreceived by players for non-TL injury disclosure may affect their eligibility for selection injuries or TL injuries was not monitored and it is possible (Ekegren et al. 2014), and (iii) player and PDC definitions that players may have had access to differing medical provi- of time-loss may have differed, e.g., a player in modified sion.Furthermore,playersthat received treatment may have training may perceive they have returned to play, yet the ‘self-reduced’ theirinjuryriskbyaddressingnon-TL PDC worked under a definition of returning to full training complaints. (Bjørneboe et al. 2011). The third party method of TL injury recording outlined in the Football Consensus (Fuller et al. Conclusion 2006) thus better facilitates thorough TL injury recording with a consistent injury definition and addresses the limita- In this study, the OSTRC Questionnaire combined with tions associated with questionnaire compliance. Football Consensus third party methods substantially 8 M. WHALAN ET AL. improved injury surveillance, which may assist in injury risk Bjørneboe J, Flørenes TW, Bahr R, Andersen TE. 2011. Injury surveillance in male reduction program design. Weekly non-time loss physical professional football; is medical staff reporting complete and accurate? – complaints were high in semi-professional football with ScandJMedSciSports.21(5):713 720. ff Bolling C, van Mechelen W, Pasman HR, Verhagen E. 2018. Context matters: 49% of all players a ected by a physical complaint of vary- revisiting the first step of the ‘Sequence of Prevention’ of sports injuries. ing severity (TL or non-TL) each week. TL injury risk was 3 to Sports Med. 48(10):2227–2234. 6 times higher when preceded (<7days) by self-reported Clarsen B. 2017. Current severity measures are insufficient for overuse injuries. non-TL physical complaints that have minor and moderate Sci Med Football. 1(1):91–92. fi impacts on participation, performance, training volume or Clarsen B, Bahr R. 2014. Matching the choice of injury/illness de nition to study setting, purpose and design: one size does not fit all!. Br J Sports perceived severity. Importantly, the presence of a non-TL Med. 48(7):510–512. injury had good injury prediction capacity for the incidence Clarsen B, Myklebust G, Bahr R. 2013. Development and validation of a new of a TL injury within the following week. method for the registration of overuse injuries in sports injury epide- miology: the Oslo Sports Trauma Research Centre (OSTRC) Overuse Injury Questionnaire. Br J Sports Med. 47(8):495–502. Practical Implications Clarsen B, Rønsen O, Myklebust G, Flørenes TW, Bahr R. 2014. The Oslo The combination of third party and self-report injury reporting Sports Trauma Research Center questionnaire on health problems: a new approach to prospective monitoring of illness and injury in elite methodsgreatlyincreasesthecaptureofinjurydatainsemi- athletes. Br J Sports Med. 48:754–760. professional football. Importantly, the presence of a non-TL Conn J, Annest JL, Gilchrist J. 2003. Sports and recreation related injury episodes injury is associated with an increased risk of a TL injury and in the US population, 1997–99. Inj Prev. 9(2):117–123. good predictive power relative to a future TL injury occur- Crowcroft S, McCleave E, Slattery K, Coutts AJ. 2016. Assessing the measure- rence. Therefore, it is suggested that the OSTRC ment sensitivity and diagnostic characteristics of athlete-monitoring tools in national swimmers. Int J Sports Physiol Perform. 12(Suppl2):S2- Questionnaire, in addition to improving injury surveillance, is 95-S2-100. a useful tool for secondary injury prevention and can be used EkegrenCL,DonaldsonA,GabbeBJ,FinchCF.2014. Implementing injury to assist in player monitoring. The similar results observed surveillance systems alongside injury prevention programs: evaluation of across each of the four OSTRC Questionnaire categories does an online surveillance system in a community setting. Inj Epidemiol. 1(1):19. however suggest that a single question may sufficiently iden- EkegrenCL,GabbeBJ,FinchCF.2015. Injury surveillance in community sport: can we obtain valid data from sports trainers? Scand J Med Sci Sports. 25 tify high-risk players, a strategy that might facilitate player (3):315–322. compliance. Ekstrand J, Hägglund M, Waldén M. 2011. Injury incidence and injury patterns in professional football: the UEFA injury study. Br J Sports Med. 45(7):553–558. Ekstrand J, Lundqvist D, Davison M, D’Hooghe M, Pensgaard AM. 2019. Acknowledgements Communication quality between the medical team and the head coach/ manager is associated with injury burden and player availability in elite The authors would like Dr Sean Williams for his invaluable assistance football clubs. Br J Sports Med. 53(5):304–308. regarding the statistical analysis for this paper. We also wish to thank Ekstrand J, Lundqvist D, Lagerbäck L, Vouillamoz M, Papadimitiou N, Karlsson J. Football South Coast and the Football Federation of Australia for facilitating 2018. 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ORIGINAL ARTICLE
Rescheduling Part 2 of the 11+ reduces injury burden and increases compliance in semi‐professional football
Matthew Whalan1,2,3 | Ric Lovell2,4 | Julie R. Steele5 | John A. Sampson1,2
1Centre for Human and Applied Physiology, School of Medicine, University of Although the 11+ program has been shown to reduce injuries in sub‐elite football, Wollongong, Wollongong, NSW, Australia program compliance is typically poor, suggesting that strategies to optimize deliv- 2NSW Football Medicine Association, ery are necessary. This study investigated the effect of rescheduling Part 2 of the Sydney, NSW, Australia three‐part 11+ program on program effectiveness. Twenty‐five semi‐professional 3Figtree Physiotherapy, Wollongong, NSW, football clubs were randomly allocated to either a Standard‐11+ (n = 398 players) Australia 4School of Science and Health, Western or P2post group (n = 408 players). Both groups performed the 11+ program at least Sydney University, Sydney, NSW, Australia twice a week throughout the 2017 football season. The Standard‐11+ group per- 5Biomechanics Research formed the entire 11+ program before training activities commenced, whereas the Laboratory, University of Wollongong, P2post group performed Parts 1 and 3 of the 11+ program before and Part 2 after train- Wollongong, NSW, Australia ing. Injuries, exposure, and individual player 11+ dose were monitored throughout
Correspondence the season. No significant between group difference in injury incidence rate (P2post Matthew Whalan, Centre for Human and vs Standard‐11+ = 11.8 vs 12.3 injuries/1000 h) was observed. Severe time loss Applied Physiology, School of Medicine, University of Wollongong, Northfields Ave, injuries > 28 days (33 vs 58 injuries; P < .002) and total days lost to injury (4303 vs Wollongong, NSW 2522, Australia. 5815 days; P < .001) were lower in the P2post group. A higher 11+ program dose was Email: [email protected] observed in the P2post (29.1 doses; 95% CI 27.9‐30.1) versus Standard‐11+ group (18.9 doses; 95% CI 17.6−20.2; P < .001). In semi‐professional football, reschedul- ing Part 2 of the 11+ program to the end of training maintained the effectiveness of the original 11+ program to reduce injury incidence. Importantly, rescheduling Part 2 improved player compliance and reduced the number of severe injuries and total injury burden, thereby enhancing effectiveness of the 11+ program.
KEYWORDS 11+, FIFA 11+, football, injury prevention, soccer
1 | INTRODUCTION player participation but also reduce health costs associated with sporting injury,5 a finding that has been specifically Football is a contact sport characterized by periods of high‐ observed following implementation of the 11+ program in intensity activity, which carries an inherent risk of injury.1-3 amateur football.7,8 While participation in football is associated with improved The 11+ program was developed and disseminated by health,4 injury is often the reason players discontinue par- Fédération Internationale de Football Association (FIFA) to ticipating in the sport, leading to longer term disability and reduce football injuries. The program consists of three parts; substantial medical costs.5 The high injury incidence and Parts 1 and 3 focus on running‐based activity including dy- burden observed in sub‐elite football6 suggest there is a need namic actions and accelerations, whereas Part 2 focuses on to develop injury prevention strategies. Importantly, injury strengthening and neuromuscular control exercises. The 11+ prevention strategies may not only help maintain long‐term program was designed to be delivered as a 20‐ to 25‐minute
Scand J Med Sci Sports. 2019;00:1–11. wileyonlinelibrary.com/journal/sms © 2019 John Wiley & Sons A/S. | 1 Published by John Wiley & Sons Ltd 2 | WHALAN et al. “warm‐up” before commencing other training activities, in terms of improving eccentric hamstring strength24 and without the need for specialized expertise or equipment. This reducing hamstring muscle injury incidence,22 but was also is important for sub‐elite sports where resources are typically associated with enhanced compliance to the intervention.24,25 scarce with limited access to staff6,9 and, as a result, injury These findings from one exercise may suggest rescheduling prevention programs are usually coach‐led.10 Previous re- Part 2 of the 11+ after training as a practical alternative to ad- search has shown that injury rates can be reduced by ≥ 40% dress identified barriers to implementation, such as program when players complete the 11+ program at least twice per duration, exercise difficulty/fatigue, and boredom. week,11 with higher program compliance and dose exposure Exploring ways to ensure that all three components of the associated with increased program effectiveness.12 However, 11+ program (Parts 1, 2, and 3) are performed, including the despite the proven effectiveness of the 11+ program, only strengthening exercises in Part 2, could therefore improve 10% of FIFA’s member associations have endorsed the program effectiveness, although research is required to con- program and several studies highlight low 11+ program firm or refute this notion. Therefore, the aim of this study compliance.13-15 was to determine whether rescheduling the 11+ program, Poor adoption and compliance rates of the 11+ program such that Parts 1 and 3 are performed at the beginning, and have been explained by (a) the time required to complete and Part 2 at the end of training, affected program effectiveness, boredom associated with the program,10,16 (b) fatigue and compared with the Standard 11+ program performed in its soreness caused by exercises contained in Part 2,10,15-17 and entirety at the beginning of training. (c) a lack of awareness and knowledge of how to perform the program.16,18 Furthermore, given the importance of strength- ening exercises in reducing injury risk,19 it is concerning 2 | MATERIALS AND METHODS that research has shown that the strengthening exercises per- formed in Part 2 of the 11+ program are often modified or 2.1 | Participant recruitment not performed.15 Potential fatigue caused by the exercises in Twenty‐five sub‐elite football clubs, each comprising 2‐3 Part 2 may contribute to why compliance to the full 11+ pro- teams, volunteered to participate in the study during the 2017 gram is poor,15 with fatigue considered by practitioners to season. The clubs consisted of 4 Tier 2 (National Premier be a primary injury risk factor in football.20,21 Interestingly, League) and 21 Tier 3 (Regional League) clubs in which all it has been found that performing an exercise in Part 2, the players received payment to play. Club and player recruit- Nordic Hamstring Exercise (NHE), prior to football activity ment and engagement were performed according to the exacerbates eccentric hamstring fatigue,22,23 although admin- Sports Setting Matrix,26 which was developed to help iden- istering these exercises after training did not affect the exer- tify key stakeholders and “levels” of engagement required cise stimulus. Furthermore, rescheduling the NHE to the end for successful implementation of an injury prevention pro- of training not only maintained the effectiveness of the NHE gram.26 In this study, this involved gaining approval from
FIGURE 1 Consolidated standards of reporting trials (CONSORT) diagram of the flow of participants in the study WHALAN et al. | 3 the National and State Federations, engaging with regional 2.3 Program compliance and injury associations and presenting to club officials, coaching staff, | data collection and players about the study. Before data collection, all play- ers provided signed informed consent. All procedures were To determine the effectiveness of rescheduling Part 2 of the approved by the University of Wollongong Human Research 11+ program, individual player exposure to the 11+ program Ethics Committee (15/340). was monitored. Given the cluster randomized controlled ex- Clubs were randomly allocated to either: (a) Standard‐11+ perimental design adopted, in which players were instructed or (b) a P2post groups. All groups were instructed to com- to complete a specific set of exercises, the term “compliance” plete the full 11+ program a minimum of twice per week at was used to assess player dose exposure and was used as a 30 training, and Parts 1 and 3 before matches (Figure 1). The continuous predictor for analysis. A player was deemed to Standard‐11+ group performed all three parts of the 11+ have performed the 11+ only when they completed all com- program at the start of training as a warm‐up, whereas the ponents of the program during that session. Data pertaining P2post group were instructed to perform Parts 1 and 3 at the to program compliance and player injuries for each partici- start of training as a warm‐up and Part 2 of the 11+ program pating team were collected by an allocated onsite primary at the end of training during the cool down period. Coaches data collector (PDC), a qualified sports trainer, who attended 31,32 and players were permitted to include additional exercises, all training sessions and matches. All PDCs completed including those involving a ball, into the warm‐up and cool at least 6 hours of training including how to record program down once the 11+ exercises were completed. compliance, injury and exposure data recording, injury defi- nitions, and details regarding the correct delivery of the 11+ program (see Appendix S1 for operational definitions).6 2.2 | Training to implement the Training included scenario‐based examples, and the primary 11+ program researcher (MW) was in weekly contact with PDCs during Before implementing the 11+ program, the chief investiga- the season to review data collected. A time loss injury was tor (MW) presented information to coaches, club officials, defined as an “injury that results in a player being unable 31 and medical staff about (a) the rate and burden of injury in to fully participate in matches or training.” Players were sub‐elite football, (b) the 11+ program and its effectiveness, deemed to have recovered from injury once they had returned (c) barriers affecting uptake of the 11+ program, (d) coach to full training/match participation or were considered eligi- 31 education regarding the importance of their role in 11+ pro- ble for team selection. Injury records were obtained during gram adoption,8,27 (v) when to progress the 11+ exercises, all training sessions (2‐3 per week) and matches including and (e) the role of the primary data collector (PDC) in pro- preseason, in‐season, and finals (28‐34 weeks). gram delivery. Coaches and medical staff were also shown The primary outcome variables for this study included videos of all exercises in the 11+ program, given explana- program compliance, represented by the total 11+ dose tions for the purpose and required technique for each exer- per player, and program effectiveness in reducing injury. cise in the program, instructed on the process and criteria for Program effectiveness was represented by injury count (total stage progress in Part 2, and informed of the positive impact number of injuries), injury severity, injury incidence (total coach delivery has upon effectiveness of the program.28 The number of injuries/total football exposure (h) × 1000 h), the 11+ program instructions allow players to progress through number of days lost to injury, and injury type, locations, and the three stages of Part 2 as they felt comfortable, on the mechanisms. Injury burden was then calculated (injury inci- 33 grounds that the coach and/or PDC were satisfied with their dence × mean absence (days) per injury). exercise technique. However, we applied progression re- strictions in accordance with previous research,29 whereby 2.4 Statistical analysis players remained at Level 1 of Part 2 for a minimum of | 2 weeks initially and progressed to Level 3 after a minimum To account for the potential club cluster effect on outcomes, of 6 weeks. In the event a player missed a week of training a generalized estimated equation (GEE) was performed with due to injury, they were required to return to a lower level Poisson distribution used to assess between group differences of Part 2 for a minimum of 1 week. At the information ses- in injury count, injury severity, and days lost to injury, with sions for club officials and coaches, it was made clear that participant group, 11+ dose, and total soccer exposure (h) the PDC would be trained in implementing the 11+ program entered as predictor variables. A second GEE was performed and would attend training sessions to coordinate the pro- to determine significant differences between the two groups gram. Coaches were not required to deliver the program, but (Standard‐11+ and P2post) for 11+ dose exposure with par- were encouraged to support its implementation. Paper and ticipant group and exposure imputed as predictor variables. A digital copies of the 11+ poster and field set up cards were Mann‐Whitney U test was used to assess differences between also provided. 11+ doses for each group (SPSS v25, IBM). 4 | WHALAN et al. TABLE 1 Player exposure, Standard‐11+ Group P2 Group post compliance, injury count, and severity for Variable (n = 398) (n = 408) P value participants in the Standard‐11+ and P2post Player characteristics & positions (mean [95% CI]) (mean [95% CI]) group Age (years) 24.8 [24.0,25.6] 23.8 [23.0,24.7] .218 Height (cm) 176.9 [176.2,177.6] 178.3 [177.5,179.1] .061 Weight (Kg) 79.3 [78.9,79.7] 78.3 [77.9,78.7] .120 Goalkeepers (%) 10.1 9.9 Defenders (%) 32.2 32.3 Midfielders (%) 32.7 31.2 Strikers (%) 25.0 26.6 Player exposure & compliance (mean [95% CI]) (mean [95% CI]) Total football exposure (h) 26 062.1 28 541.4 .972 Total training sessions (n) 51.6 [50.3,52.9] 49.7 [48.6, 50.9] .721 Total 11 + player doses (n) 7625 11 871 .004* Total 11 + player dose (sessions) 18.9 [17.6, 20.2] 29.1 [27.9, 30.1] <.001* 11+ player dose/training Session (%) 32.7 [31.1, 34.3] 57.7 [56.2, 59.2] ‐ 11+ Player dose/Exposure (h) 0.27 [0.26, 0.28] 0.42 [0.41, 0.43] ‐ Injury count n (% total) n (% total) Total injuries (n) 320 (48.7) 337 (51.3) .825 Days lost to injury (n) 5815* 4303* .026* Injury severity n (% total) n (% total) Minimal: 1‐3 days lost 60 (19) 95 (28) .335 Mild: 4‐7 days lost 93 (29) 104 (31) .832 Moderate: 8‐28 days lost 108 (34) 105 (31) .881 Severe: >28 days lost 59 (18) 33 (10) .012*
*Significant difference between the Standard‐11+ and P2post groups.
Injury incidence rate (IIR) ratios (±95% confidence in- the Standard‐11+ and P2post groups are presented in Table tervals [CI]) were calculated to compare injury locations and 1. A total of 657 time loss injuries were recorded during types between the groups. In addition, IIRs were also deter- 54 604 hours of football exposure (training and matches com- mined for a subset of players (Standard‐11+, n = 185 and bined) across both groups. A similar number of time loss in- P2post, n = 226) who participated in a previous surveillance juries were observed in both groups. However, significantly season (2016), in which no club implemented the 11+ or any higher 11+ dose, a lower number of severe injuries and cor- other known injury prevention program.6 Therefore, the data respondingly lower total number of days lost to injury were collected in 2016, which was conducted by the same research observed in the P2post group compared with the Standard‐11+ team and collection procedures, served as baseline, pre‐in- group (Table 1). tervention data pertaining to injury incidence. All IIR ratio The injury location differed between participant groups, analysis was performed via Hopkin's “compare and com- with a significantly lower incidence of ankle and recurrent in- bine” analysis to determine clinical inference ranging from juries in the P2post group, whereas the incidence of quadriceps “most unlikely to be beneficial < 0.5%” to “most likely to be muscle and contusion injury was lower in the Standard‐11+ beneficial > 99.5%.”34 group (Table 2). Total injury burden was also lower in the P2post group, with lower time lost (days) associated with non‐ contact, recurrent, and hamstring muscle injuries compared 3 | RESULTS with the Standard‐11+ group (Tables 3 and 4). There was also a significantly lower incidence of non‐contact ankle in- A total of 806 male players consented to participate in this jury injuries in P2post (Table 4). study with 398 players in the Standard‐11+ group and 408 Comparing the subset of the current data (Total com- players in P2post (Table 1). Player football exposure, com- bined IIR = 12.5 injuries/1000 h; Standard‐11+ IIR = 12.3 pliance and injury incidence, and severity for participants in injuries/1000 h, total injuries = 206; P2post group IIR = 12.9 WHALAN et al. | 5 b Clinical Inference IRR Unclear Possibly beneficial Possibly harmful Likely trivial effect Possibly beneficial Likely trivial effect Possibly trivial effect Very likely trivial Possibly beneficial Likely harmful Unclear Unclear Unclear Unclear Possibly beneficial Very likely trivial Likely beneficial Likely trivial .806 .370 .098 .857 .132 .618 .745 .882 .812 .116 .832 .891 .765 P value (No. of Injuries) .832 .367 .332 .242 .579 a
34 IRR [95% CI] 1.1 [0.8, 1.5] 0.8 [0.5, 1.2] 1.8 [1.0, 3.7] 0.9 [0.7, 1.3] 0.7 [0.4, 0.9] 1.1 [0.7, 1.7] 1.1 [0.7, 1.6] 0.9 [0.7, 1.2] 0.8 [0.6 to 1.1] 1.5 [1.0 to 2.3] 0.7 [0.3, 1.6] 1.0 [0.4, 2.5] 0.6 [0.2, 1.7] 1.2 [0.5, 2.9] 0.9 [0.7, 1.1] 1.1 [0.9, 1.4] 0.7 [0.5, 0.9] 1.0 [0.8 to 1.1] Groups post 2.8 [2.5, 3.0] 1.6 [1.3,1.8] 1.2 [0.9,1.4] 2.1 [1.9, 2.4] 1.4 [1.1,1.6] 1.8 [1.6,2.1] 1.6 [1.1,2.1] 4.9 [4.4,5.3] 2.7 [2.5,3.0] 2.2 [1.9,2.5] 0.4 [0.2,0.9] 0.3 [0.1,0.6] 0.2 [0.08,0.5] 0.4 [0.1,0.8] 6.2 [5.8,6.6] 5.6 [5.2,5.9] 1.7 [1.4,2.1] IR per 1000 h [95% CI] 11.8 [10.1, 13.9] Group post 9 7 79 45 34 60 39 50 47 77 64 10 12 48 P2 No. of Injuries 139 177 161 337 2.6 [2.4,2.7] 2.0 [1.8,2.2] 0.7 [0.5,0.9] 2.3 [2.1,2.5] 2.1 [1.9,2.4] 1.6 [1.4,1.7] 1.5 [1.1,1.9] 3.3 [3.0,3.7] 5.2 [4.7,5.4] 1.5 [1.2,1.8] 0.5 [0.2,0.8] 0.4 [0.1,0.9] 0.4 [0.1,0.8] 0.3 [0.1,0.7] 7.3 [7.0,7.5] 5.1 [4.7,5.5] 2.6 [2.1,2.9] IR per 1000 h [95% CI] 12.3 [10.4, 14.1] group: Standard‐11+ group). post 9 68 51 17 59 55 41 40 85 38 13 10 10 67 Standard‐11+ Group No. of Injuries 135 189 132 320 is more beneficial/harmful than the Standard‐11+ determined from IRR via Hopkins “combine and compare” analysis. post Injury pattern, incidence rate, and rate ratios for participants in the Standard‐11+ P2 tendon injury Thigh Hamstrings Quadriceps Knee Ankle Hip/groin Lower leg/Achilles Muscle injury/strain Sprain/ligament Hematoma/contusion Fracture Other bone injury Meniscus/cartilage Tendon injury Non‐contact Contact Recurrent Total injuries
Injury location Injury type Injury mechanism Clinical inference of P2 IRR—incidence rate ratio for injury incidence (P2 a b TABLE 2 6 | WHALAN et al.
TABLE 3 Injury burden and days lost to injury for participants in Standard‐11+ and P2post Groups
Standard‐11+ group P2post group Days lost per Days lost per P value (Total 1000 h Total days lost 1000 h Total days lost days lost) Injury location Thigh 45.7 1133 28.5 843 .058 Hamstrings 39.3 1001 19.6 559 .006* Quadriceps 6.2 162 8.9 254 .464 Knee 60.7 1622 41.7 1190 .203 Ankle 30.4 797 17.2 490 .300 Hip/groin 20.8 535 19.2 547 .867 Lower leg/Achilles tendon 26.4 697 13.6 371 .127 Injury type Muscle injury/strain 75.6 1970 48.7 1390 .080 Sprain/ligament injury 66.0 1720 53.9 1538 .121 Hematoma/contusion 11.1 290 13.6 385 .277 Fracture 26.2 682 15.8 450 .812 Other bone injury 5.8 151 3.4 96 .572 Meniscus/cartilage 7.1 185 5.1 146 .652 Tendon injury 12.6 329 4.9 140 .865 Injury mechanism Non‐contact 128.3 3377 72.5 2099 .010* Contact 94.9 2472 78.2 2166 .564 Recurrent 55.4 1445 18.2 519 .009* Total 223.1 5815 150.8 4303 .026*
*Statistically significant difference between the Standard‐11+ and P2post groups.
injuries/1000 h, total injuries = 171) to the 2016 baseline in- reduction; P2post = 40% reduction compared with 2016 base- jury incidence data (IIR = 19.9 injuries/1000 h, total inju- line) in this study. These reductions were consistent with pre- 6 6,11 ries = 558) showed that both the Standard and P2post groups vious research, and our results show that the 11+ program displayed reduced injury rates of 38% and 35%, respectively, is equally as effective in reducing injury incidence in football, to the 2016 injury incidence (IRR = 0.63; 95% CI–0.48‐0.68; whether performing all three parts collectively at the start of clinical inference—very likely beneficial; 99.3%). training or with Part 2 rescheduled until the end of training. There were, however, a significantly lower total number of severe injuries and days lost to injury observed in the P2post 4 | DISCUSSION group in this study. Players in the P2post group performed the 11+ more frequently than the Standard‐11+ group, which This is the first study to evaluate whether manipulating deliv- may have resulted in greater physiological adaptions to the ery of the 11+ program can enhance program effectiveness 11+ in the P2post group. The 11+ has been shown to result in and compliance. Simply rescheduling, such that Parts 1 and 3 both acute and chronic performance benefits, including speed are performed at the beginning and Part 2 of the 11+ program and agility, in addition to potential injury reduction effects, at the end of training, reduced the severity and burden asso- such as improving strength, balance, muscle activity, and ciated with the most common injuries observed in football, core stability.29,35,36 It is therefore plausible that the benefits while increasing individual player 11+ dose. The specific ef- observed in the P2post group are related to a dose effect, rather fects of rescheduling are discussed below. than any physiological changes in response to the scheduling of exercises. Performing the exercises contained in Part 2 of the 11+ 4.1 | Effect on program effectiveness before training is the source of most concern for practitioners Irrespective of how the 11+ program was scheduled, the and is the most modified component of the 11+.15 As such, in- injury incidence rate was reduced (Standard‐11+ = 38% vestigating methods to improve compliance and effectiveness WHALAN et al. | 7 of exercises in Part 2 of the 11+ program such as the Nordic Hamstring Exercise (NHE), which is known to reduce the risk of hamstring injuries,37 is important for improving adop- .010* .005* .580 .882 .231 .449 .237 P value (Total days lost) tion.38 Previous research has suggested that the scheduling of the NHE has no impact upon chronic strength gains, al- beit the muscle architectural mechanism seems to differ.24 In .395 .285 .999 .678 .556 .131 .238 P value (No. Injuries) the current study, however, the incidence of hamstring injury
c was similar in the Standard‐11+ and P2post groups, and col- lectively 50% lower than our previous research,6 suggesting that scheduling of the NHE does not impact effectiveness. Performing NHEs prior to training can, however, transiently reduce eccentric hamstring strength, which can in turn in- Clinical Inference ‐ IRR Possibly beneficial Possibly beneficial Unclear Possibly trivial Unclear Likely beneficial Unclear crease injury risk.22 This can contribute to negative per- ceptions of the 11+ because fatigue and soreness from the NHE are reported barriers to 11+ program adoption.10,16,17 [95%
b Performing NHEs at the start of training in the Standard‐11+ group did not increase training‐related hamstring injury risk CI] IRR 0.8 [0.5, 1.1] 0.7 [0.5, 1.1] 1.0 [0.4, 2.4] 0.8 [0.4, 1.5] 1.1 [0.7, 1.8] 0.4 [0.1, 0.6] 0.6 [0.3, 0.9] with most hamstring injuries occurring during matches. Interestingly, however, a significantly lower time lost, and Total days lost 672 552 116 151 404 474 441 subsequently severity, of hamstring injury was observed in groups the P2post group. This finding was in contrast to previous re- post search in which the inclusion of the NHE was not associated 3.2 5.2 9.1 25 Days lost per 1000 h 20.1 17.0 13.6 15.5 with a reduction in hamstring injury severity. Considering our finding and research that has shown hamstring eccentric strength decreases as a match progresses,39 performing the NHE, as a component of a larger injury prevention program, after training might be an effective strategy for reducing ham- 1.8 [1.4,2.2] IR per 1000 h [95% CI] 1.4 [1.0,2.0] 0.4 [0.1,1.1] 1.3 [0.9,1.8] 0.8 [0.4,1.4] 0.06 [0.01, 0.2] 1.1 [0.7, 1.7] string injury incidence and burden. A significantly lower incidence of ankle injuries was also group observed in the P2post group relative to their Standard‐11+ post 3 P2 56 No. of Injuries 44 11 38 23 31 counterparts. Ankle sprains most commonly occur in the later 40
stages of matches, with ankle function changing under fa- 34 tigue.41 Exercises that focus on improving balance have been 937 121 456 286 659 1092 Total days lost 1280 shown to be more effective when performed after football training42 and therefore suggest that performing the ankle sta- 43
groups. bility exercises in Part 2 at the end of training, in addition 4.6 post 22.1 Days lost per 1000 h 35.8 15.3 11.0 22.3 25.3 to the higher dose exposure, is likely to have improved the ef- fectiveness of this component of the 11+ program. However, the P2post group incurred a significantly higher quadriceps injury incidence compared with the Standard‐11+ group. group: Standard‐11+ group).
post The higher quadriceps injury incidence was a consequence 2.3 [1.7,2.7] IR per 1000 h [95% CI] 1.9 [1.3,2.5] 0.4 [0.1,0.9] 1.2 [0.7,1.9] 1.0 [0.6,1.5] 0.15 [0.01, 0.4] 1.7 [1.1,2.5] of a significantly higher number of anterior thigh contusion injuries incurred by the P2post (23 vs 7 injuries), whereas
8 non‐contact quadriceps muscle strains were similar between Standard 11+ group 56 No. of injuries 49 10 34 27 45 groups. The 11+ program is designed to reduce non‐con- tact injuries.44 Therefore, the higher quadriceps injury inci- and ligament injury pattern, incidence, burden for participants in the Standard‐11+ P2 a dence in the P2post group is unlikely the result of the program rescheduling. Muscle Recurrent injuries are problematic in sub‐elite football with inadequate recovery, poor physical conditioning on re- turn to play, and a lack of access to medical care believed Hamstrings Quadriceps
Ligament Rupture 6,9,45 Thigh Hip/groin Lower leg Anterior Cruciate Ankle to contribute to the high incidence rate. Interestingly,
Non‐contact muscle Non‐contact ligament IRR—incidence rate ratio for injury incidence (P2 Muscle injuries only included structural and functional (ie, muscle excluded contusions, hematoma, te ndon‐related injuries). Clinical inference determined from IRR via Hopkins “combine and compare” analysis. *Statistically significant difference between the Standard‐11+ and P2 TABLE 4 a b c recurrent injury incidence and time lost to recurrent injury 8 | WHALAN et al. were significantly lower in the P2post group compared with current study would be categorized as “low” and “moder- the Standard‐11+, and both groups had a lower injury inci- ate”12 or “low”50 relative to previous research. This result dence when compared to the 2016 cohort.6 Previous research was despite “best practice” strategies to encourage program has shown that increased compliance to strength programs is compliance, including extensive coach and staff education50 associated with reduced injury incidence.12,19 Our results ad- and engagement with stakeholders.26 The previous 11+ stud- ditionally suggest that rescheduling the exercises in Part 2 so ies, however, did not record or state whether all components that they are performed more regularly reduces ankle injury of the 11+ program were completed for an exposure to be incidence, hamstring injury severity, and injury recurrence. recorded.12,50 The apparently low compliance in this study We speculate that by significantly reducing the number of might have been a consequence of the strict compliance cri- severe injuries and reducing time lost to injury, players in the teria we applied, as only “doses” in which players completed P2post group returned to training earlier, increased their expo- all three components of the 11+ program were included in sure to the 11+ program as well as to football training, and, the analysis. in turn, reduced the injury risk caused by de‐training for the most common injuries in football.6,29,45-47 To our knowledge, this study is the first to analyze the in- 4.3 | Limitations jury burden associated with the 11+ program, allowing for an Performing large scale injury research across numerous clubs examination beyond injury incidence.33 A 33% lower injury can result in several methodological limitations that must be burden was observed in the P2post group compared with both acknowledged. We acknowledge potential issues that may the Standard‐11+ group and to the 2016 baseline,6 with the arise from performing multiple sub‐classification hypothesis greatest burden reductions associated with the most common testing on the same data set. Initial power calculations for injuries (ankle sprains, hamstring, and calf muscle strains) subject inclusion were based on evaluating total injury inci- in football.6,33 Lower time lost for hamstring, quadriceps, dence and burden. Once the overall effect was determined, we and calf injuries and lower injury incidence for ankle sprains performed sub‐classification analysis on different injury loca- account for the lower injury burden observed in the P2post tions and types, which will reduce the power size of the sam- group compared with the Standard‐11+ group. Interestingly, ple analyzed. To overcome the potential impact of obtaining a the Standard‐11+ showed a reduction in injury burden com- false‐positive or false‐negative result, we determined clinical pared with the 2016 baseline,6 which is likely to be the re- inferences34 to allow for practical implications to be drawn sult of a significantly higher number of severe injuries in from the findings. Although caution may need to be applied the baseline season. Additionally, injury burden associated to the sub‐class findings, the number of injuries recorded for with anterior cruciate ligament rupture (ACLR) in the P2post specific injuries, such as hamstring muscle injuries, in our group was lower compared with both the Standard 11+ group study was larger compared with other published research.25,37 and 2016 data,6 with ACLR incidence 2.5 times lower in the Attempts were made to control the delivery of 11+ exer- P2post compared with the Standard‐11+ group, and half that cises for both groups to allow for the efficacy of the sched- of 2016 baseline.6 Furthermore, it is noteworthy that 6 of the uling change to be correctly determined and compliance 8 ACLR in the Standard‐11+ group were non‐contact inju- accurately assessed. A limitation to the application of the ries, while all ACLR in the P2post group involved contact with “compliance” assessment when evaluating the 11+ program another player. Previous 11+ research found a similar dose‐ is the progression of stages in Part 2. There is not a specific related effect to ACLR incidence,48 and our findings present progression of Part 2 exercises within the program, and apart encouraging data that may help reduce non‐contact ACLR in from the restrictions applied at the initial stages, standardized sub‐elite football. progression through these stages for players is not possible. We attempted to address this issue by only “allowing” players to progress through a stage in Part 2 once the PDC or coach 4.2 | The potential role of rescheduling on was satisfied with the technique and performance of the exer- 11+ compliance cise and, as such, maintained control over the prescription of Rescheduling Part 2 of the 11+ to the end of training sig- exercises for the players. Although this limitation may be in- nificantly increased program compliance with a 20% higher dicative of a pragmatic issue associated with real‐world pro- number of 11+ doses observed in the P2post compared with gram coordination, we applied the more rigorous compliance the Standard‐11+ group. When considering the percent- definition to ensure the true effect of the rescheduling Part 2 age of 11+ doses relative to training sessions completed, was evaluated. the P2post group individual player dose (57.7%) was higher Notably, while a PDC was present to coordinate the 11+ than has previously been reported (47%) in 11+ research program, the quality of how well the exercises were per- in youth football,49 whereas the Standard‐11+ group was formed was not recorded. It is possible that how well the lower (32.7%). However, compliance in both groups in the 11+ exercises were performed and extra exercises may have WHALAN et al. | 9 impacted on injury incidence outcomes. It should also be ac- ACKNOWLEDGEMENTS knowledged that the presence of the PDC at training sessions The authors would like to thank Dr Sean Williams for his may have facilitated the compliance observed in this study. assistance in confirming the statistical methods used in this Multiple PDCs were assigned across different clubs, study. Thank you also to all of the players, coaches, primary which might have resulted in under‐ or overreporting of inju- data collectors, and medical staff for participating in this study. ries.6 Moreover, variations in coaching styles,51 player fitness and physical characteristics, and previous injury history of 52 players were not considered in the analysis. We attempted ORCID to standardize the knowledge base, program implementa- Matthew Whalan https://orcid.org/0000-0003-1532-7877 tion, and data collection by providing an extensive education Ric Lovell program for coaches and PDCs before the intervention was https://orcid.org/0000-0001-5859-0267 implemented to minimize these limitations. Additionally, Julie R. Steele https://orcid.org/0000-0002-2089-406X PDCs performed several practice injury reports before the John A. Sampson https://orcid.org/0000-0002-6800-7757 season started to improve interclub data reporting consis- tency. Further research, however, is necessary to determine whether the improved 11+ outcomes in the P2post group were REFERENCES due to increased dose exposure or the scheduling change, or 1. Carling C, Le Gall F, Dupont G. Analysis of repeated high‐in- a combination of the two elements. The long‐term physiolog- tensity running performance in professional soccer. 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Lauersen JB, Andersen TE, Andersen LB. Strength training as su- Sci. 2016;34(20):2011‐2017. perior, dose‐dependent and safe prevention of acute and overuse 36. Nakase J, Inaki A, Mochizuki T, et al. Whole body muscle activity sports injuries: a systematic review, qualitative analysis and meta‐ during the FIFA 11+ program evaluated by positron emission to- analysis. Br J Sports Med. 2018;52(24):1557‐1563. mography. PLoS ONE. 2013;8(9):e73898. 20. McCall A, Dupont G, Ekstrand J. Injury prevention strategies, 37. Petersen J, Thorborg K, Nielsen MB, Budtz‐Jørgensen E, Hölmich coach compliance and player adherence of 33 of the UEFA Elite P. Preventive effect of eccentric training on acute hamstring inju- Club Injury Study teams: a survey of teams’ head medical officers. ries in men’s soccer a cluster‐randomized controlled trial. Am J Br J Sports Med. 2016;50:725‐730. Sports Med. 2011;39(11):2296‐2303. 21. McCall A, Carling C, Davison M, et al. Injury risk factors, screen- 38. Bahr R, Thorborg K, Ekstrand J. Evidence‐based hamstring injury ing tests and preventative strategies: a systematic review of the ev- prevention is not adopted by the majority of Champions League or idence that underpins the perceptions and practices of 44 football Norwegian Premier League football teams: the Nordic Hamstring (soccer) teams from various premier leagues. Br J Sports Med. survey. Br J Sports Med. 2015;49(22):1466‐1471. 2015;49(9):583‐589. 39. Small K, McNaughton L, Greig M, Lovell R. The effects of multi- 22. Small K, McNaughton L, Greig M, et al. Effect of timing of eccentric directional soccer‐specific fatigue on markers of hamstring injury hamstring strengthening exercises during soccer training: implicaitons risk. J Sci Med Sport. 2010;13(1):120‐125. for muscle fatigability. J Strength Con Res. 2009;23(4):1077‐1083. 40. de Noronha M, Lay EK, McPhee MR, et al. Ankle sprain has 23. Lovell R, Siegler JC, Knox M, Brennan S, Marshall PWM. 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Malone S, Owen A, Mendes B, Hughes B, Collins K, Gabbett TJ. A study of 36 elite teams in 17 countries. Br J Sports Med. High‐speed running and sprinting as an injury risk factor in soccer: 2018;52:527‐531. Can well‐developed physical qualities reduce the risk? J Sci Med 52. Windt J, Gabbett TJ. How do training and competition workloads Sport. 2018;21(3):257‐262. relate to injury? The workload—injury aetiology model. Br J 47. Ekstrand J, Hägglund M, Waldén M. Injury incidence and injury Sports Med. 2017;51(5):428‐435. patterns in professional football: the UEFA injury study. Br J Sports Med. 2011;45(7):553‐558. 48. Silvers‐Granelli HJ, Bizzini M, Arundale A, et al. Does the 11+ in- jury prevention program reduce the incidence of ACL injury in male SUPPORTING INFORMATION soccer players? Clin Orthop Relat Res. 2017;475(10):2447‐2455. Additional supporting information may be found online in 49. Soligard T, Nilstad A, Steffen K, et al. Compliance with a compre- hensive warm‐up programme to prevent injuries in youth football. the Supporting Information section at the end of the article. Br J Sports Med. 2010;44:787‐793. 50. McKay CD, Steffen K, Romiti M, Finch CF, Emery CA. The effect of coach and player injury knowledge, attitudes and beliefs on ad- How to cite this article: Whalan M, Lovell R, Steele herence to the FIFA 11+ programme in female youth soccer. Br J JR, Sampson JA. Rescheduling Part 2 of the Sports Med. 2014;48(17):1281‐1286. 11+ reduces injury burden and increases compliance 51. Ekstrand J, Lundqvist D, Lagerbäck L, Vouillamoz M, in semi‐professional football. Scand J Med Sci Sports. Papadimitiou N, Karlsson J. Is there a correlation between 2019;00:1–11. https://doi.org/10.1111/sms.13532 coaches’ leadership styles and injuries in elite football teams? GRADUATE RESEARCH SCHOOL AGREEMENT FOR DEPOSIT OF HDR THESIS IN DIGITAL REPOSITORY
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