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Objective To determine the prevalence and impact of non-time loss injuries in semi-professional 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 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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Science and Medicine in Football
ISSN: 2473-3938 (Print) 2473-4446 (Online) Journal homepage: https://www.tandfonline.com/loi/rsmf20
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.
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Publisher: Taylor & Francis & Informa UK Limited, trading as Taylor & Francis Group
Journal: Science and Medicine in Football
DOI: 10.1080/24733938.2019.1705996
Title: Do Niggles Matter? - Increased injury risk following
physical complaints in football (soccer)
Submission type: Original Investigation
Authors: Matthew Whalan1,3,4
Ric Lovell2,3
John A Sampson1,3
Institutions: 1Centre for Human and Applied Physiology, School of
Medicine, University of Wollongong, Wollongong, New South
Wales, Australia
2School of Science and Health, Western Sydney University,
New South Wales, Australia
3NSW Football Medicine Association
4Figtree Physiotherapy, NSW, Australia
Corresponding author: Matthew Whalan
Centre for Human and Applied Physiology
School of Medicine
University of Wollongong
Northfields Ave.
Wollongong, NSW, 2522
Australia
Tel: +61 2 42252233
Fax: +61 2 42257464
E-mail: matt@figtreephysio.com.au
Abstract word count: 207
Word count: 4240
Number of figures: 1
Number of tables: 3
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ABSTRACT
Objective: To determine the prevalence and impact of non-time loss injuries in semi-
professional 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 was 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 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.
Key Terms: Time loss, non-time loss, prevention, injury surveillance
INTRODUCTION
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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
surveillance[7] 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 that non-TL
injuries in football may have on more serious TL injury risk. This information may have
particular importance in semi-professional environments, where the players’ primary source
of income may be from non-football occupations, and the long term cost of injury can effect
both the player’s health[15] and financial status[16]. Indeed, injuries in non-professional
settings; such as a college, high school or university, are associated with significant financial
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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 will therefore compare the prevalence and impact of “all physical
complaints” in semi-professional football between self-reported and third party injury
surveillance recording methods and further aims to; 1) determine the relative risk of
sustaining a TL injury within 7 days of reporting the presence (vs absence) of a reported non-
TL injury; 2) examine whether the presence of a non-TL injury, in isolation, is linked injury
occurrence.
METHODS
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).
Time Loss Injury Data Collection.
TL injury data and individual exposure minutes (training and match) were collected in
accordance with the Fuller et al (2006) consensus statement on injury definitions and data
collection procedures in football [2], with injury defined as “any physical complaint”, and TL
injury defined as an “inability to fully participate in football training or matches” [2]. To
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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 and were provided with additional tuition by a qualified physiotherapist
detailing injury description, definitions, and recording exposure to comply with the Fuller et
al (2006) Consensus statement[21]. 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.
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 (2006) 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 with health problems” (minor) or “reduced participation due to health
problems” (moderate). 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 (2006) football consensus statement. Illnesses were also
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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.
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 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
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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. ‘1 – 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 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,
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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.
RESULTS
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 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 1). Sensitivity, specificity and
positive predictive power values are displayed in Table 2. A cohort of 73 (33%) players
completed >80% of the weekly questionnaires (mean = 28.5 [CI: 26.2 to 31.3] completed
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questionnaires 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 1 and 2).
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TABLE 1. Associated injury risk and injury prediction using the OSTRC Questionnaire on Health Problems[22] for time loss injury for entire cohort and sub-
group.
Entire Cohort (n=218) Association Prediction
OSTRC Category P level Relative Risk (RR)* Clinical Inference[22] 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)
*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 2. Diagnostic accuracy assessment for OSTRC Questionnaire on Health Problems[22] for each sub-category drawn from entire cohort and sub-group
OSTRC Questionnaire
Category
True
Positive
(n)
False
Positive
(n)
False
Negative
(n)
True
Negative
(n)
Sensitivity (%) with
95% CI
Specificity (%) with
95% CI
Positive Predictive Value
(%) 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 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 health problems
75 120 0 25 100.0 (100) 17.2 (11.1 to 23.4) 38.5 (31.6 to 45.3)
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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Sub-Group. The magnitude of the increase in risk (RR) and predictive capacity for future TL
injury was similar for the sub-group and entire cohort (Table 2). The total number of
reported “physical complaints” was 2.3 times greater when comparing self-reported versus
PDC methods (n=604 vs 265). Within the self-reports, non-TL injuries were 13.2 times (516
vs. 39) higher, however TL injuries were 2.6 times lower (88 vs. 226) when compared to
PDC data (Table 3). The proportion and distribution of injuries was similar between methods,
with 87% (PDC) and 83% (self-reported) of all injuries affecting the lower limb. The most
common locations were the hamstring (17% - PDC; 16% - self report) and knee (19% - PDC;
17% - self report; Table 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). 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).
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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) [2] and self-reporting method (OSTRC Questionnaire on Health Problems) [22]
Football Consensus OSTRC Participation Category
Injury Location Time Loss – 3rd
Party Method
Total – Self
Report
Non-Time
Loss – Self
Report
Relative Risk (RR)* Clinical Inference[22] Factor – Non-
Time
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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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 1A). Combining self-reported non-TL and PDC recorded TL injury reports indicates
that 49% (95% CI – 47.0% to 51.0%) of players were affected by injury each week (Figure
1B).
INSERT FIGURE 1 HERE
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)
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 seven days of a self-reported minor or moderate non-TL injury (complaint)
effecting 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 2 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).
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Importance of Non-Time Loss Injuries
In this study, the majority (85%) of 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 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 behaviour[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 issues[30] 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 athletes[15] have been identified, with the
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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, 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
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].
Another tool in the injury risk reduction tool box?
The complex and multifactorial nature of injury[28] 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
Accepted Manuscript
17
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), 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 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.
Football Consensus Method vs OSTRC Questionnaire on Health Problems
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18
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 injury[8] 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 selection[40], 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 the PDC worked under a definition of returning to full
training[39]. The third party method of TL injury recording outlined in the Football
Consensus[2] thus better facilitates thorough TL injury recording with a consistent injury
definition and addresses the limitations associated with questionnaire compliance.
Limitations
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19
Despite the clear association between non-TL injuries and occurrence of a TL injury in this
study, a number 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].
However, 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. Methods to improve buy-in to self-reported player monitoring methods are thus
required. Adopting smartphone technology may improve compliance [13, 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 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 levels[35] and iii) workloads preceding a TL injury[38] were
each uncontrolled extraneous variables that may have impacted TL injury risk and non-TL
injury prevalence including that were not considered in the analysis in this study.
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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 far 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 that received treatment may have “self-reduced” their injury risk by addressing non-
TL complaints.
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
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 have 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.
Practical Implications
The combination of third party and self-report injury reporting methods greatly increases the
capture of injury data in semi-professional football. Importantly, 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. Therefore, it is suggested that the OSTRC Questionnaire, in
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21
addition to improving injury surveillance, is a useful tool for secondary injury prevention and
can be used to assist in player monitoring. The similar results observed across each of the
four OSTRC Questionnaire categories does however suggest that a single question may
sufficiently identify high risk players, a strategy that might facilitate player compliance.
Conflict of Interest Statement – no conflicts to declare
Disclosure of Funding – no funding was received to conduct this research
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22
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Acknowledgements
The authors would like Dr Sean Williams for his invaluable assistance regarding the
statistical analysis for this paper. We also wish to thank Football South Coast and the
Football Federation of Australia for facilitating this project and all of the clubs, coaches,
medical staff, players and data collectors involved in this study. Thank you to
physiotherapists, Michael Gabriel, Kieran Rooney and Steve Felsher for their roles in this
project.
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Figure 1
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... For self-reports, an accumulated injury score was not calculated, 30 as a modified OSTRC Questionnaire on Health Problems was used, rather the "participation" (question 1) and "severity" (questions 2 and 4) categories were analyzed. 32 All data preparation and analyses were performed with R (version 4.0.2, R Foundation for Statistical Computing, Vienna, Austria). ...
... 2,43 Although typically used as an injury surveillance tool, the OSTRC questionnaires have also been suggested as a potential daily monitoring tool, 20 and in sport the risk of sustaining a "time-loss" injury appears amplified if preceded by a self-reported injury-related problem. 32 Further examination of the use of self-reported injury data as a systematic recruit monitoring strategy may therefore be beneficial. ...
Article
Introduction The injury definitions and surveillance methods commonly used in Army basic military training (BMT) research may underestimate the extent of injury. This study therefore aims to obtain a comprehensive understanding of injuries sustained during BMT by employing recording methods to capture all physical complaints. Materials and methods Six hundred and forty-six recruits were assessed over the 12-week Australian Army BMT course. Throughout BMT injury, data were recorded via (1) physiotherapy reports following recruit consultation, (2) a member of the research team (third party) present at physical training sessions, and (3) recruit daily self-reports. Results Two hundred and thirty-five recruits had ≥1 incident injury recorded by physiotherapists, 365 recruits had ≥1 incident injury recorded by the third party, and 542 recruits reported ≥1 injury-related problems via the self-reported health questionnaire. Six hundred twenty-one, six hundred eighty-seven, and two thousand nine hundred sixty-four incident injuries were recorded from a total of 997 physiotherapy reports, 1,937 third-party reports, and 13,181 self-reported injury-related problems, respectively. The lower extremity was the most commonly injured general body region as indicated by all three recording methods. Overuse accounted for 79% and 76% of documented incident injuries from physiotherapists and the third party, respectively. Conclusions This study highlights that injury recording methods impact injury reporting during BMT. The present findings suggest that traditional injury surveillance methods, which rely on medical encounters, underestimate the injury profile during BMT. Considering accurate injury surveillance is fundamental in the sequence of injury prevention, implementing additional injury recording methods during BMT may thus improve injury surveillance and better inform training modifications and injury prevention programs.
... Recent research has also suggested that athletes experiencing minor injuries or "niggles" may be at an increased risk of injury in the following week. 9 As it is likely athletes will experience niggles when returning to training, flagging niggles may act as a tool for reducing the risk of more substantial injuries. Reducing the risk of injury in competitive, young gymnasts as they return to gym-based training was also important to minimise any further disruption to their development. ...
... From an applied perspective, taking into consideration any injury (including niggles) while training may reduce the risk of a more substantial injury developing in the following week. 9 Research in this area is limited and requires further exploration. ...
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... Subsequent trends suggests increased growth and overuse related injuries particularly in U13-U14 age groups in a distal to proximal nature, with Osgood-Schlatter's and Severs Disease widespread (Read, Oliver, et al., 2018). Additionally, audit methods likely underestimate incidences of overuse injuries as they typically adopt a 'time-loss' definition, when often players do not miss training but need modification (Whalan et al., 2020). Between 46-72% of EPPP injuries are non-contact and 30-43% are moderate in nature with approximately 50% injuries occurring during training sessions Read, Oliver, et al., 2018). ...
Thesis
Full-text available
The period surrounding the adolescent growth spurt is a turbulent but crucial stage of development for young footballers in their pursuit of becoming full-time athletes. At a time of almost constant talent (re)selection which coincides with major physical and physiological changes players experience large fluctuations in performance and a heightened injury incidence. Adding to the complexity of this period, the timing and tempo of biological maturation varies between individuals causing a diversity in physical and physiological capabilities, influencing the dose-response to training. Although differences in biological maturation and the links with injury are acknowledged in literature, little evidence exists to quantify the magnitude and extent to which these impacts perceptions of load and subsequent performance. This thesis aims to quantify the maturity-specific responses to load using ecologically valid approaches to aid the enhancement of provision offered to young academy players. To provide a context and informed backdrop for the rest of the thesis, it was deemed important to first identify the current practices of, and perceived barriers to monitoring training load and biological maturation in academies. A cross-sectional survey design was used to ascertain perceptions of staff from male (EPPP) and female (RTC) academies during the 2017/18 soccer season. In total, 49 respondents completed the survey who advocated injury prevention as highest importance for conducting training load and maturation monitoring across academy groups, with overall athletic development, load management, coach and player feedback considered important. However, there were clear differences in monitoring strategies that academies of different categories adopted, which were often associated with resources or staffing. Survey responses suggest that despite routine monitoring of biological maturation and training load being commonplace within adolescent soccer the communication and dissemination of this information is often lacking, which may ultimately impede the impact of the monitoring practices for the players. Resource and environmental constraints create natural diversity around the strategies adopted, but academies are recommended to adopt sustainable and consistent approaches to monitor key variables to inform the coaching, selection, and development process. The survey chapter identified that most clubs employ one of the various ‘non-invasive’, somatic equations to estimate biological maturation. However, the methodological differences associated with calculations often mean they provide variable estimations, even when using the same anthropometrical data. Therefore, it was deemed important to this thesis to observe the agreement of maturity estimations and compare concordance between methods when looking to estimate maturity status. Thus, anthropometric data from 57 participants was collected from a single assessment point during the 2017-18 season, with an additional 55 participants providing three repeated measurements during the 2018-19 season, resulting in 222 somatic estimations observed. Results indicated that all methods of maturity-offset (MO) produced an identical estimate of age of peak height velocity (13.3 years) with mean prediction of adult height (PAH%) providing a mean estimate of 93.6%, which also aligns closely. However, when looking to identify circa-PHV individuals there is greater concordance when using conservative thresholds (44-67%) than when using more stringent bandwidth thresholds (31-60%), with both being considered moderate concordance at best. Therefore, although overall findings indicate that there is very high to near perfect agreement between all approaches when predicting APHV, concordance of categorisation between these methods is less useful. Therefore, this chapter indicates that PAH% and MO methods are not interchangeable, and practitioners should utilise one approach routinely for all maturity-specific interventions. Academy squads are comprised of players within chronological parameters but often present significant variations in physical characteristics including body mass (~50%), stature (~17%), percentages of predicted adult height (10-15%) and fat free mass (~21%). These maturational changes likely influence performance and dose-responses to load, but limited studies using standardised activity profiles have directly observed this influence. Therefore, this thesis aimed to quantify the neuromuscular performance (CMJ, RSI absolute and relative stiffness) and psycho-physiological (d-RPE) responses to a simulated soccer-specific activity profile (Y-SAFT60) and analyse whether this dose-response was moderated by maturation in EPPP academy players. Data illustrated an interaction between perceived psycho-physiological load (RPE-T) and maturation, with absolute stiffness, relative stiffness and playerload (PL) showing slope significance across various stages of maturation (~86-96% PAH). These interactions suggest that psycho-physiological dose responses are influenced by maturation and should be considered for training prescription purposes, which is likely a result of the musculotendinous changes that occur around peak height velocity (PHV). 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Therefore, players less biologically mature are consistently working harder just to compete with more biologically advanced teammates of a similar chronological age. Again, these changes are mostly attributed to musculotendinous changes because of maturation and therefore a higher relative mechanical load experienced by less mature individuals. When accrued, these small inter-individual differences lead to a substantial variation in training load (~40-50%) over the 40-week season. This has the potential to undermine the whole developmental pathway, as the assumption that players of a similar chronological age are experiencing similar load-responses is precarious. Failure to act, by adopting more maturity sensitive ways of working for example, will result in a ‘survival of the fittest’ environment, rather than the systematic, considered, and individualised approach to optimal loading proposed in policy documents and literature. Bio-banding is a method to group individuals based on biological maturation rather than chronological age. Supplementing the chronological programme with bio-banded activities may offer practitioners a practical method to better control load exposure and ultimately mechanical load related injury risk. Therefore, the final thesis study explored effects of standardised chronological and bio-banded training sessions on neuromuscular performance and psycho-physiological perceptions of intensity in 55 male soccer players from a single academy. Players participated in bio-banded and chronologically categorised bouts (x5) of 5-minute 6v6 (including GK) SSG on a playing area 45 x 36 m (135m2 per player). Prior to and following this, players performed a standardised sub-maximal run using the audio controlled 30-15IFT wearing foot-mounted inertial devices. 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... Por otro lado, es una disciplina deportiva que requiere una buena condición física por parte de los jugadores, puesto que implica un alto grado de contacto entre jugadores, y deben estar en continuo desplazamiento por el espacio (Pringle, Parnell, Zwolinsky, Hargreaves & McKenna, 2014). Debido a esta alta exigencia física, se producen un gran número de lesiones en la práctica del fútbol, y este hecho dificulta la práctica del fútbol con personas adultas mayores (Whalan, Lovell & Sampson, 2020). Debido a este hecho, surgió la modalidad de Fútbol Caminando enfocado principalmente para poblaciones mayores (Cabrera-Ramos, Cabrera-Fernández & Cachón-Zagalaz, 2019). ...
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The study aims to conduct a systematic review based on the results found around the Walking football, in order to know the sport rules and the benefits of it practice for health and general well-being in older adults. The search phrases were always introduced in English and computerized databases: Web of Science, PubMed, Science Direct and Google Academy. Two search phrases were used: "Walking football-And-Older adults" and "Walking soccer – And-Older adults”. To limit the search, a series of inclusion and exclusion criteria were established in order to select the most appropriate documents on the subject. After the review, 18 manuscripts published up to November 2020, which met the inclusion criteria, were selected. The selected documents show that the Walking Football has benefits on a social, psychological, and physiological level. In addition, the Walking Football regulations are adapted to each training group, in order to minimize the risk of injury in older adults during its practice. Finally, the documents related to the subject are mainly Journal articles, published in 2019, and are found in the Google Academic database. © 2021, Federacion Extremena de Balonmano, University of Extremadura. All rights reserved.
... Using a single definition of a career time loss injury in this study, it was clear that the RSS scores of players with a past time loss injury were significantly higher than those with no reported history. Similar impact was seen on Kerlan-Jobe Orthopaedics Clinical Score (KJOC) of elite cricketers (Dutton et al., 2018) and Oslo Sports Trauma Research Centre (OSTRC) Questionnaire score, with semiprofessional footballers (Whalan et al., 2019). Collectively, these results suggest that previous injury at any point in an athletes career can result in reduced perceived function years after the index injury, and it is already well documented that previous musculoskeletal injury is the strongest predictor of future musculoskeletal injury across most sports (Toohey et al., 2017). ...
Article
Objective This study aimed to investigate the prevalence of self-reported shoulder dysfunction using the Rugby Shoulder Score (RSS) reported in arbitrary units (AU) of rugby players available for match selection (uninjured). Design Cross-sectional survey. Methods Paper survey at the mid-point of the season of uninjured players (n = 86 males (mean age (±SD): 26 ± 6.9y) from 8 squads (professional n = 34; amateur; n = 52)), using the RSS, subjective impact on rugby performance and previous shoulder injury, analysed using a Mann-Whitney U test. Results 55% of players reported a level of RSS dysfunction despite being uninjured. Players who also reported their shoulder was impacting on performance had significantly higher median RSS (61, IQR 28AU, p = 0.02) than those who reported no impact on performance (40, IQR 22AU). Conclusions: Findings from this study show that over half of players were playing with a level of self-reported shoulder dysfunction. This figure is higher in the professional game, for those with a history of previous injury and for forwards.
... Por otro lado, es una disciplina deportiva que requiere una buena condición física por parte de los jugadores, puesto que implica un alto grado de contacto entre jugadores, y deben estar en continuo desplazamiento por el espacio (Pringle, Parnell, Zwolinsky, Hargreaves & McKenna, 2014). Debido a esta alta exigencia física, se producen un gran número de lesiones en la práctica del fútbol, y este hecho dificulta la práctica del fútbol con personas adultas mayores (Whalan, Lovell & Sampson, 2020). Debido a este hecho, surgió la modalidad de Fútbol Caminando enfocado principalmente para poblaciones mayores (Cabrera-Ramos, Cabrera-Fernández & Cachón-Zagalaz, 2019). ...
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El objetivo del presente estudio fue realizar una revisión sistemática en la modalidad deportiva Fútbol Caminando, con la finalidad de conocer la normativa de juego, y los beneficios de su práctica físico-deportiva para la salud y el bienestar general en personas adultas mayores. Para la búsqueda de documentos, se utilizaron las bases de datos Web Of Science, PubMed, Science Direct y Google Académico. Además, se emplearon dos frases de búsqueda “Walking football -And - Older adults”, y “Walking soccer - And - Older adults”. Para limitar la búsqueda, se establecieron una serie de criterios de inclusión y exclusión, con el objeto de seleccionar los documentos más adecuados con la temática. Tras la revisión, se seleccionaron 18 manuscritos publicados hasta noviembre del 2020, que cumplían con los criterios de inclusión. Los documentos seleccionados muestran que los principales beneficios están vinculados a nivel social, psicológico y fisiológico. Además, la normativa del Fútbol Caminando está en función de cada grupo de entrenamiento, con el objeto de minimizar el riesgo de lesión de adultos mayores durante la práctica de esta modalidad. Por último, los documentos relacionados con la temática son principalmente Artículos de revista, publicados en el año 2019, y se encuentran en la base de datos Google Académico
... Nontime loss injuries are relevant to consider in injury surveillance and prevention strategies as they are associated with pain, reduced performance, and the occurrence of more severe subsequent injuries. 24,30,31 Furthermore, these data provide an insight of the impact these injuries have on service delivery from medical teams. The observed median 35 days of medical attention compared to only 15 days of time-loss per injury highlights the substantial burden that non-time loss injury management has on often limited medical resources. ...
Article
Objectives To report the medical attention and time-loss injury epidemiology of Australia's premier netball competition. Design Descriptive epidemiological study. Methods One-hundred and nineteen players in the Suncorp Super Netball league were under surveillance during three consecutive seasons (2017–2019), inclusive of pre-, in-, and post- season phases. Medical attention injuries were recorded by medical personnel, and additionally sub-categorised according to time loss. Injury incidence rates (IIR) and injury burden were calculated per 365 player contract days, with differences between season and season phase IIRs compared using negative binomial generated incidence rate ratios (IRR). Results Eight hundred and sixty-six medical attention injuries and 393 time-loss injuries were recorded. The majority of the players had multiple (≥2) medical attention (n = 92; 77.3%) and time-loss (n = 75, 63.0%) injuries reported. The ankle (n = 181; 20.9%), knee (n = 136; 15.7%) and foot (n = 98; 11.3%) were the body sites with the most frequently reported medical attention injuries. Overall, there was a comparable injury incidence rate between the pre-season and in-season periods (IRR = 1.13, 95%CI = 0.98–1.30, p = 0.0842), although variation in the injury burden was identified. Ankle tendon injuries (23.5 days absence) and knee joint injuries (44.9 days absence) the most burdensome injuries in the pre-season and in-season periods respectively. Conclusions Lower limb injuries are the most frequent in professional level netball. Knee and ankle injuries are the most burdensome overall, however the type of injuries with a high burden vary between pre- and in-season periods. Time-loss, non-time loss and subsequent injuries are prominent in professional level netball.
Article
Objectives To investigate the prevalence, incidence rate (IR) and burden of health problems (injuries and illnesses) in Australian Olympic class and State Sailing Pathway Program (SSPP) athletes over 12-months of training and competition. Design Descriptive epidemiological study. Methods Ninety-two Australian Sailing and SSPP athletes were prospectively followed during the 2019–2020 season. Medical attention injuries and illnesses were prospectively recorded, and further sub-categorised according to time loss. The IR and burden were calculated per 365 athlete-days, with differences in IR between sexes compared using negative binomial generated rate ratios. Results Three hundred and forty-nine injuries were reported in 53 athletes (57.6 %), with 14.3 % resulting in time loss. Injury IR was 3.71 (95%CI = 3.33–4.12) injuries per 365 athlete–days, with no difference overserved between sex (IRR = 1.64; 95%CI = 0.81–3.34). Shoulder injuries were found to have the greatest burden. Fifty-four illnesses were reported in 27 athletes (29.3 %), with 39.0 % resulting in time loss. Respiratory infection (n = 22, 40.7 %) was the most common illness reported. Illness IR was 0.57 (95%CI = 0.43–0.75) illnesses per 365 athlete days, with females found to have a 3.6 fold increase in illness compared to males (IRR = 3.6; 95%CI = 2.0–6.7). Conclusions The majority of health problems reported in sailing athletes did not result in time loss. There were no differences in the injury IR between sexes, however females had a 3.6-fold increase in reported illness. These results can inform future strategies to reduce key health problems in sailors. Future research investigating whether performance is impacted by the high rate of non-time loss health problems is warranted. Elsevier complementary full text access link for 50 days post-publication: https://authors.elsevier.com/c/1fRa157UJnKa2m
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This study aimed to investigate the incidence, severity, and burden of injury in English elite youth female soccer players. Qualified therapists at six English girls' academies prospectively recorded all injuries that required medical attention or caused time loss for matches and training in 375 elite youth female soccer players (under-10 , U12, U14 and U16) during the 2019/2020 season. One hundred- and eleven time-loss injuries (52 from training, 59 from matches) were sustained, resulting in 1,946 days absent (779 days from training injuries, 1,167 days from match injuries) from soccer activities. The injury incidence for matches (9.3/1000 hours, 95% CIs: 7.2-11.9) was significantly greater than training (1.1/1000 hours, 95% CIs: 0.9-1.5, p<0.001). Additionally, the injury burden for matches (183 days lost/1000 hours, 95% CIs: 142-237) was significantly greater than training (17 days lost/1000 hours, 95% CIs: 13-22, p<0.001). Injury incidence and burden were greatest in the U16 age group, and were found to increase with age. Whilst injury incidence and burden are greater in matches than training, a large proportion of preventable injuries, soft-tissue and non-contact in nature, were sustained in training. Findings provide comparative data for elite youth female soccer players.
Article
This study investigated time-loss injury occurrence and patterns between the first season (2020/21, S2) completed during the Covid-19 pandemic (longer pre-season following cancellation of the 2019/20 season but shorter duration) and a regular season (2018/19, S1) in French Ligue 1 and 2 professional soccer clubs. Epidemiological data were prospectively recorded in a national injury database by each club’s physician. In all clubs combined, the mean number of injuries per club was 31.5 and 36.6 in S2 and S1, respectively (−13.9%). Overall match injury incidence (per 1000 hours) in all clubs combined was lower in S2 versus S1 (22.23 vs 25.96, p < 0.01). In Ligue 1 clubs alone, match-play incidences for injury overall (24.92 vs 29.42), muscle strains (10.59 vs 13.24) and strains specifically in the hamstring region (4.52 vs 6.22) were lower in S2 versus S1 (all p < 0.05). No differences in the incidence of match injuries affecting the ankle and knee regions were observed. Changes in the 2020/21 season structure and duration owing to the Covid-19 pandemic seem not to have had a negative effect on injury occurrence and patterns in French professional soccer clubs.
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Objectives We investigated medical staff interpretations and descriptions of internal communication quality in elite football teams to determine whether internal communication was correlated with injuries and/or player availability at training and matches. Methods Medical staff from 36 elite football clubs across 17 European countries produced 77 reports at four postseason meetings to provide their perceptions of internal communications in their teams. They also recorded data on individual players’ exposure to football and time-loss injuries. Results The injury burden and incidence of severe injuries were significantly higher in teams with low quality of communication between the head coach/manager and the medical team (scores of 1–2 on a 5-point Likert scale) compared with teams with moderate or high-quality scores (scores of 3–5; p=0.008 for both). Teams with low scores had 4%–5% lower training attendance (76% vs 83%, p=0.001) and less availability at matches (82% vs 88%, p=0.004) compared with teams with moderate or high communication quality scores. Conclusions The quality of internal communication within a team was correlated with injury rates, training attendance and match availability.
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It is possible to prevent sports injuries. Unfortunately, the demonstrated efficacy and effectiveness of injury prevention approaches are not translated into lasting real-world effects. Contemporary views in sports medicine and injury prevention suggest that sports injuries are ‘complex’ phenomena. If the problem we aim to prevent is complex, then the first step in the ‘sequence of prevention’ that defines the ‘injury problem’ already needs to have considered this. The purpose of this paper is to revisit the first step of the ‘sequence of prevention’, and to explore new perspectives that acknowledge the complexity of the sports injury problem. First, this paper provides a retrospective of the ‘sequence of prevention’, acknowledging contemporary views on sports injuries and their prevention. Thereafter, from the perspective of the socioecological model, we demonstrate the need for taking into account the complex nature of sports injuries in the first step. Finally, we propose an alternative approach to explore and understand injury context through qualitative research methods. A better understanding of the injury problem in context will guide more context-sensitive studies, thus providing a new perspective for sports injury prevention research.
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Purpose: Hip and groin injuries in football are problematic due to their high incidence and risk of chronicity and recurrence. The use of only time-loss injury definitions may underestimate the burden of hip and groin injuries. Little is known about hip and groin injury epidemiology in female football. The first aim of this study was to examine the within-season (2014-2015) prevalence of total injury with and without time-loss in female amateur football players. The second aim was to study the within-season and preseason (2015-2016) prevalence of hip/groin injuries with and without time-loss. The third aim was to study the association between the duration of hip and groin injury in the 2014-2015 season and the severity of hip/groin problems during the 2015-2016 preseason. Methods: During the preseason, 434 Dutch female amateur football players completed an online questionnaire based on the previous season and current preseason. The hip and groin outcome score (HAGOS) was used to assess the severity of hip and groin injuries. Results: The hip/groin (17%), knee (14%), and ankle (12%) were the most frequent non-time-loss injury locations. The ankle (22%), knee (18%), hamstring (11%), thigh (10%), and hip/groin (9%) were the most common time-loss injury locations. The previous season prevalence of total injury was 93%, of which non-time-loss injury was 63% and time-loss injury was 37%. The prevalence of hip/groin injury was 40%, non-time-loss hip/groin injury was 36% and time-loss hip/groin injury was 11%. The preseason prevalence of hip/groin injury was 27%, non-time-loss hip/groin injury was 25%, and time-loss hip/groin injury was 4%. Players with longstanding hip/groin injury (> 28 days) in the previous season had lower HAGOS scores at the next preseason than players with short-term (1-7 days) or no hip/groin injury (p < 0.001). From all players with hip/groin injury from the previous season, 52% also sustained hip/groin injury in the following preseason, of which 73% were recurrent and 27% were chronic hip/groin injuries. Conclusion: Injury risk, and especially non-time-loss hip and groin injury risk, is high in female amateur football. Three-quarters of the players with longstanding hip and groin injuries in the previous season have residual problems at the start of the following season. Level of evidence: II.
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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. Design Descriptive Epidemiological Study. Methods 1049 sub-elite football players were recruited during the 2016 season. Injury and exposure data was 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 mitigation programmes to reduce healthcare costs to sub-elite players in Australia.
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Background Do coaches’ leadership styles affect injury rates and the availability of players in professional football? Certain types of leadership behaviour may cause stress and have a negative impact on players’ health and well-being. Aim To investigate the transformational leadership styles of head coaches in elite men’s football and to evaluate the correlation between leadership styles, injury rates and players’ availability. Methods Medical staff from 36 elite football clubs in 17 European countries produced 77 reports at four postseason meetings with a view to assessing their perception of the type of leadership exhibited by the head coaches of their respective teams using the Global Transformational Leadership scale. At the same time, they also recorded details of individual players’ exposure to football and time-loss injuries. Results There was a negative correlation between the overall level of transformational leadership and the incidence of severe injuries (rho=−0.248; n=77; p=0.030); high levels of transformational leadership were associated with smaller numbers of severe injuries. Global Transformational Leadership only explained 6% of variation in the incidence of severe injuries (r²=0.062). The incidence of severe injuries was lower at clubs where coaches communicated a clear and positive vision, supported staff members and gave players encouragement and recognition. Players’ attendance rates at training were higher in teams where coaches gave encouragement and recognition to staff members, encouraged innovative thinking, fostered trust and cooperation and acted as role models. Conclusions There is an association between injury rates and players’ availability and the leadership style of the head coach.
Article
Overuse injuries are suggested to result from repetitive micro-damage eliciting pain in the affected tissue. Therapy commonly focuses on the area of symptom localization, however, such approach may oversimplify the true etiopathology. This review hypothesizes that the development of some sports-related soft tissue disorders, e.g. plantar fasciitis or lumbago, is promoted by pathologically altered force transmission from anatomically connected structures.
Article
Injury rates in 12 U.S. men’s college sports and 5 U.S. boys’ high school sports are examined in this article. The sports are categorized as “contact” or “noncontact,” and differences in injury rates between the two are examined. Injury rates in the contact sports are considerably higher than those in the noncontact sports, and they are on average more severe. Estimates are presented of the injury savings that would result if the contact sports were changed to have injury rates similar to those in the noncontact sports. The estimated college savings are 48,100 fewer injuries per year and 5,900 fewer healthy years lost-to-injury per year. The estimated high school savings are 568,600 fewer injuries per year and 92,000 fewer healthy years lost-to-injury per year. For concussions, the savings are 6,900 per year for college and 161,400 per year for high school. The estimated dollar value (in 2015 dollars) of the total injury savings is between US$433 million and US$1.5 billion per year for college and between US$5.1 billion and US$18.4 billion per year for high school.
Article
Background Internal workload (ie, from training and matches) is considered one of the most important injury risk factors for elite European football teams, however there is little published evidence to support this belief. Objective We examined the association and predictive power of internal workload and non-contact injuries. Methods Five elite European teams, 171 players (age: 25.1±4.9 years; height: 181.6±6.7 cm; body mass: 77.5±7.2 kg) participated over one full competitive season. Using the session-rating of perceived exertion (s-RPE) method player’s internal workloads were calculated for acute week, week-to-week changes, cumulated weeks, chronic weeks and acute:chronic ratios and analysed for association with non-contact injury (using generalised estimating equations (GEE)). Associated variables from GEE analysis were categorised into very low to very high workload zones and checked for increased relative risks (RRs). Associated workload variables were also analysed for predictive power (receiver operating characteristics). Results Acute:chronic workload ratios at 1:3 and 1:4 weeks were associated with non-contact injury (P<0.05). Specifically, a greater risk of injury was found for players with an acute:chronic workload at 1:4 weeks of 0.97 to 1.38 (RR 1.68; 95% CI 1.02 to 2.78, likely harmful) and >1.38 (RR 2.13; 95% CI 1.21 to 3.77, very likely harmful) compared with players whose acute:chronic workload was 0.60 to 0.97. An acute:chronic workload 1:3 of >1.42 compared with 0.59 to 0.97 displayed a 1.94 times higher risk of injury (RR 1.90; 95% CI 1.08 to 3.36, very likely harmful). Importantly, acute:chronic workload at both 1:4 and 1:3 showed poor predictive power (area under the curve 0.53 to 0.58) despite previous reports and beliefs that it can predict injury. Conclusions This study provides evidence for the acute:chronic internal workload (measured using s-RPE) as a risk factor for non-contact injury in elite European footballers. However the acute:chronic workload, in isolation, should not be used to predict non-contact injury.