ArticlePDF Available

International Olympic Committee Consensus Statement: Methods for Recording and Reporting of Epidemiological Data on Injury and Illness in Sports 2020 (Including the STROBE Extension for Sports Injury and Illness Surveillance (STROBE-SIIS))

Authors:

Abstract and Figures

Background Injury and illness surveillance, and epidemiological studies, are fundamental elements of concerted efforts to protect the health of the athlete. To encourage consistency in the definitions and methodology used, and to enable data across studies to be compared, research groups have published 11 sport- or setting-specific consensus statements on sports injury (and, eventually, illnesses) epidemiology to date. Objective To further strengthen consistency in data collection, injury definitions, and research reporting through an updated set of recommendations for sports injury and illness studies, including a new Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist extension. Study Design Consensus statement of the International Olympic Committee (IOC). Methods The IOC invited a working group of international experts to review relevant literature and provide recommendations. The procedure included an open online survey, several stages of text drafting and consultation by working groups, and a 3-day consensus meeting in October 2019. Results This statement includes recommendations for data collection and research reporting covering key components: defining and classifying health problems, severity of health problems, capturing and reporting athlete exposure, expressing risk, burden of health problems, study population characteristics, and data collection methods. Based on these, we also developed a new reporting guideline as a STROBE extension—the STROBE Sports Injury and Illness Surveillance (STROBE-SIIS). Conclusion The IOC encourages ongoing in- and out-of-competition surveillance programs and studies to describe injury and illness trends and patterns, understand their causes, and develop measures to protect the health of the athlete. The implementation of the methods outlined in this statement will advance consistency in data collection and research reporting.
Content may be subject to copyright.
Consensus Statement
International Olympic Committee
Consensus Statement
Methods for Recording and Reporting of Epidemiological
Data on Injury and Illness in Sports 2020
(Including the STROBE Extension for Sports
Injury and Illness Surveillance (STROBE-SIIS))
International Olympic Committee Injury and Illness Epidemiology Consensus Group*
Background: Injury and illness surveillance, and epidemiological studies, are fundamental elements of concerted efforts to protect
the health of the athlete. To encourage consistency in the definitions and methodology used, and to enable data across studies to
be compared, research groups have published 11 sport- or setting-specific consensus statements on sports injury (and, even-
tually, illnesses) epidemiology to date.
Objective: To further strengthen consistency in data collection, injury definitions, and research reporting through an updated set of
recommendations for sports injury and illness studies, including a new Strengthening the Reporting of Observational Studies in
Epidemiology (STROBE) checklist extension.
Study Design: Consensus statement of the International Olympic Committee (IOC).
Methods: The IOC invited a working group of international experts to review relevant literature and provide recommendations. The
procedure included an open online survey, several stages of text drafting and consultation by working groups, and a 3-day
consensus meeting in October 2019.
Results: This statement includes recommendations for data collection and research reporting covering key components: defining
and classifying health problems, severity of health problems, capturing and reporting athlete exposure, expressing risk, burden of
health problems, study population characteristics, and data collection methods. Based on these, we also developed a new
reporting guideline as a STROBE extension—the STROBE Sports Injury and Illness Surveillance (STROBE-SIIS).
Conclusion: The IOC encourages ongoing in- and out-of-competition surveillance programs and studies to describe injury and
illness trends and patterns, understand their causes, and develop measures to protect the health of the athlete. The imple-
mentation of the methods outlined in this statement will advance consistency in data collection and research reporting.
Keywords: injuries; illness; epidemiologic methods; surveillance; STROBE
Injury and illness surveillance, and epidemiological stud-
ies, are fundamental elements of concerted efforts to pro-
tect the health of the athlete. Carefully designed injury
surveillance programs, accurate data capture, and careful
analysis of data are building blocks for sports injury/ill-
ness prevention programs. Important questions that
sports injury and illness surveillance projects are
designed to address include: What is the risk of an indi-
vidual athlete sustaining an acute injury, developing an
overuse injury, or becoming ill in a given sport? Within a
given sport, what is the typical pattern and severity of
injuries and illnesses? How do injury rates in various
sports compare? Do participant characteristics and factors
within competition and training affect the risk?
To encourage consistency in the definitions and methods
used, and to enable data across studies to be compared,
research teams have published 11 consensus papers on
sports injury (and, eventually, illness) epidemiology. Most
of them addressed specific sports—cricket,
84
football,
50
rugby union,
52
rugby league,
65
aquatic sports,
78
tennis,
86
athletics,
98
and horse racing.
102
Two statements covered
multisport events
64
and mass-participation events (eg,
marathon races).
92
We now have more than a decade of experience with the
existing recommendations. Sports epidemiology has
advanced, with a new focus on overuse injuries and also
The Orthopaedic Journal of Sports Medicine, 8(2), 2325967120902908
DOI: 10.1177/2325967120902908
ªThe Author(s) 2020
1
This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (https://creativecommons.org/
licenses/by-nc-nd/4.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are
credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For article reuse guidelines, please visit SAGE’s website at
http://www.sagepub.com/journals-permissions.
on illnesses. Data collection and reporting methods have
also advanced as data are being collected for routine sur-
veillance or predefined observational or intervention stud-
ies in diverse settings, ranging from community to elite
sports, from youth sports to the master’s level, in able-
bodied and athletes with disabilities, and in team sports
and individual sports. In 2005, when the first of these
sports injury surveillance consensus statements was devel-
oped, there were no agreed on research reporting methods
(eg, the EQUATOR Network [Enhancing the QUAlity and
Transparency Of health Research] was just holding its
inaugural meeting). Many important research epidemiolog-
ical issues were not discussed in any of the previous sports-
related consensus statements.
In 2019, the International Olympic Committee (IOC) con-
vened an expert panel to update recommendations for the
field of sports epidemiology—this consensus statement. We
drew on recent methods developments and the experience of
scientists working in the field of sports injury and illness
surveillance. A specific goal was to further encourage con-
sistency in data collection, injury definitions, and research
reporting (in line, where possible, with the EQUATOR Net-
work recommendations). Our aim was to provide hands-on
guidance to researchers on how to plan and conduct data
collection and how to report data. We anticipate that this
sports-generic statement will be complemented by subse-
quent sport-specific statements with more detailed recom-
mendations relevant for the sports and/or setting. We also
extended the Strengthening the Reporting of Observational
Studies in Epidemiology (STROBE) checklist
63
—the
STROBE Sports Injury and Illness Surveillance
(STROBE-SIIS)—to assist users in planning surveillance
studies and in writing articles based on injury/illness data.
METHODS
This was an 8-stage process: (1) an online survey; (2) work-
ing groups reviewed the survey responses, available litera-
ture, and drafted text; (3) all consensus group members
reviewed the draft text; (4) the initial working groups
revised their draft text; (5) a 3-day consensus meeting was
held in Lausanne, Switzerland (October 9-11, 2019); (6)
new working groups revised the draft text; (7) an editorial
group (R.B., K.C., B.R., K.M.K.) made final edits; and (8) all
authors reviewed and approved the final draft.
The IOC Medical and Scientific Department appointed
R.B. to chair the consensus group. He selected a consensus
group that included at least 1 author from previous consen-
sus statements on sports injury epidemiology. Care was
taken to include experts with research experience from
diverse settings (sports types, age groups, performance
levels) and with a variety of health problems as outcomes
(eg, illnesses, not only acute injuries).
1. Online survey: The survey included 25 questions invit-
ing free-text comments on aspects identified from pre-
vious consensus statements. The survey link was open
to the public and was launched via email and Twitter
on February 1, 2019, and closed on March 15, 2019. We
received comments from 188 respondents, including 19
consensus group members. A report including all
responses was distributed to the consensus group on
August 31, 2019.
2. The consensus group was split into 7 working groups.
Each working group was responsible for a subset of the
sections presented in this finaldocument (eg, “classifying
health problems”). For each section, the group reviewed
the survey responses, examined available relevant liter-
ature (including previous consensus statements), and
composed draft text with the necessary background and
proposed definitions and recommendations.
3. R.B. created a complete draft that was shared online
with the consensus group, asking all members to pro-
vide written comments/suggestions. Comments were
made online and were visible to all group members.
4. The working groups revised their sections based on
input from other members of the consensus group.
5. At the in-person consensus meeting, attended by all
consensus group members, the revised draft was dis-
cussed section by section, focusing on recommendations
and definitions.
6. Seven new revision groups made up of those not respon-
sible for drafting the original section under discussion
were responsible for taking notes and revising the text.
If necessary, items were voted on to achieve a majority.
7. The revised draft was edited for consistency and form
by R.B. and reviewed with the rest of the editorial
group (K.C., B.R., K.M.K.).
8. Finally, the manuscript was distributed to the consen-
sus group members for final approval.
DEFINING AND CLASSIFYING
HEALTH PROBLEMS
Terminology for Health Problems
The World Health Organization (WHO) defines health as “a
state of complete physical, mental, and social well-being”
and not merely the absence of a disease or infirmity.
114
Extending this definition, Clarsen et al
15
defined an
*Address correspondence to Roald Bahr, MD, PhD, Department of Sports Medicine, Oslo Sports Trauma Research Center, Norwegian School of Sport
Sciences, PB 4014 Ulleva
˚l Stadion, 0806 Oslo, Norway (email: roald@nih.no).
All authors are listed in the Authors section at the end of this article.
This article has been co-published in the British Journal of Sports Medicine. Minor differences exist between the 2 versions to be consistent with OJSM
editorial style.
Final revision submitted December 30, 2019; accepted January 3, 2020.
One or more of the authors has declared the following potential conflict of interest or source of funding: B.R. receives payment for duties as Editor-in-
Chief of The Orthopaedic Journal of Sports Medicine. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not
conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.
2IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
athletic health problem as any condition that reduces an
athlete’s normal state of full health, irrespective of its con-
sequences on the athlete’s sports participation or perfor-
mance or whether the athlete sought medical attention.
This constitutes an umbrella term that includes, but is not
limited to, injury and illness.
Health problems can have several consequences. A
health problem that results in an athlete receiving medical
attention is referred to as a “medical attention” health prob-
lem, and a health problem that results in a player being
unable to complete the current or future training session
or competition is referred to as a “time-loss” health prob-
lem.
51,52,65,78,84,98
As not all health problems limit an ath-
lete’s ability to participate nor require medical attention,
broader definitions (self-reported, symptom-based, or per-
formance based) will capture more health problems.
Figure 1 illustrates these differences.
Defining Injury and Illness
Previous consensus statements on injury and illness in
sports have proposed largely consistent definitions for an
injury and illness.
Differences in definition stem from the
specific sport or context for which statements were devel-
oped. For this consensus statement, we define an injury
and illness as follows:
Injury is tissue damage or other derangement of normal
physical function due to participation in sports, result-
ing from rapid or repetitive transfer of kinetic energy.
Illness is a complaint or disorder experienced by an ath-
lete, not related to the injury. Illnesses include health-
related problems in physical (eg, influenza), mental (eg,
depression), or social well-being or removal or loss of
vital elements (air, water, warmth).
We acknowledge that there is not always a clear distinc-
tion between injury and illness. The consensus was that for
injury, the primary mode involves the transfer of kinetic
energy, but other types of injury, such as sunburn or
drowning, may have a different etiology.
These definitions are meant to be inclusive; they embrace
a broad array of injury- and illness-related health problems
that may affect an athlete. Depending on the goal of the
monitoring activity, data recording may be limited to spe-
cific health problems that constitute a narrower subset of
the above definitions (ie, via an operational definition). If
the surveillance program has a narrow scope (eg, to capture
only concussions in school rugby), data recording can be
limited to the specific injury type of interest.
Relationship to Sports Activity
Health problems may result:
1. Directly from participation in competition or from train-
ing in the fundamental skills of a sport (eg, players col-
liding in a match, overuse from repetitive training, or
transmission of a skin infection from contact with
another player).
2. Indirectly from participation in activities related to com-
petition or training in a sport but not during competition
or a training session (eg, slipping, falling, and sustaining
an injury when in the Olympic village; developing an
illness after international travel to a competition or an
illness deemed to be related to an increased training load
over a few weeks).
3. From activities that are not at all related to participation in
sports, that is, would occur in the absence of participation
during competition or training in the fundamental skills of
a sport (eg, car crash, sudden cardiac arrest at home).
Depending on the purposes of the study, researchers
may want to report health problems in these categories
separately.
Mode of Onset
Traditionally, health problems have been classified into
those that have a sudden onset and those that have a grad-
ual onset. Sudden-onset health problems were considered
to be those that resulted from a specific identifiable event
(eg, a collision between an athlete and an object causing a
fracture). Gradual-onset health problems, on the other
hand,wereconsideredtobethosethatlackadefinable
sudden, precipitating event as the onset (eg, a tendinopathy
induced by repetitive movement).
The term “overuse injury” is commonly applied to
gradual-onset injuries. However, this term is used inconsis-
tently in the literature,
80,90
and most injury surveillance
systems do not define “overuse injury.”
90
Health problems may have elements of both sudden
onset and gradual onset. For example, a long-distance run-
ner with an intensive training regimen may have insuffi-
cient recovery, resulting in cumulative stress-related
changes to the bone, but presenting as an acute tibial frac-
ture without prior pain. The dichotomy between sudden
and gradual onset, which most methods of data capture are
Figure 1. Distribution of health problems by consequences
(not to scale). Adapted from Clarsen and Bahr.
14
References 51, 52, 64, 78, 83, 84, 86, 92, 98, 102.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 3
based on, means such important nuances may be missed.
Oneoptiontoaddressthisproblemwouldbetoclassify
health problems based on the underlying pathology,
whether this indicates a single or repetitive pathogenic
mechanism, based on imaging studies (eg, magnetic reso-
nance imaging, ultrasound) or tissue biopsies. However,
routine capture of such detail in a reliable manner within
a surveillance system is challenging.
Mode of Onset—Injury
For injuries, classic epidemiology provides a solution for
this issue by viewing health problems as the result of a
series of interactions between agent, host, and environ-
ment.
45,58
Injury epidemiology adapted this model by defin-
ing kinetic energy as the “agent” of injury.
56,69,107
In this paradigm, following the definition above,
injury results from a transfer of kinetic energy (agent)
that damages tissue. Injury may result from a near-
instantaneous exchange of large quantities of kinetic energy
(eg, as in a collision between athletes), from the gradual
accumulation of low-energy transfer over time (as in the
bone stress injury example), or from a combination of both
mechanisms (repetitive training regimen resulting in ten-
don weakness that then manifests itself acutely as a tear
from acceleration forces applied during a single jump). This
model suggests mode of onset for injuries should be concep-
tualized as a continuum interplay of energy exposures.
Mode of Onset—Illness
Illnesses, like injuries, may be either associated with a spe-
cific precipitating event (eg, a player ingesting a toxin from
food and suffering gastrointestinal illness that manifests
within hours of exposure) or may involve a progressive path-
way that cannot be linked to a specific precipitating event
(eg, progressive fatigue from increased training load). Simi-
larly, the time scale for sudden-onset illness can be seconds
or minutes (eg, acute anaphylaxis), develop within hours
after exposure to a pathogen or toxin (eg, gastroenteritis),
or even days or weeks (eg, upper respiratory tract infection).
The mode of onset for illnesses may also be related to a
specific event, with or without some underlying subclinical
pathology. For example, myalgic encephalomyelitis will
typically present without a precipitating event, whereas
influenza usually has a point source of exposure (although
this may be difficult to trace). As with injuries, many ill-
nesses reflect both the underlying pathology and a sudden-
onset event (eg, an athlete may be predisposed to bronchial
hyperreactivity, and this may present acutely as broncho-
constriction when exposed to air pollution at a venue).
Classifying the Mode of Onset
We recommend that injury/illness surveillance discontinue
use of sudden onset and gradual onset as a simple dichotomy
and implement methods that capture relevant subtleties.
We encourage researchers to develop and use measures that
will help identify injuries and illnesses that involve mixed
acute and repetitive mechanisms. Data collectors should
consider whether a health problem results from a clear acute
mechanism, clear repetitive mechanism, or appears to
include a mix of both elements (Table 1). Examples 1 and 3
in Table 1 reflect clear acute and repetitive etiology, respec-
tively, whereas example 2 represents a mixed etiology.
Classifying the Mechanism of Injury
Mechanism of onset has typically been defined only in the
context of sudden-onset injuries. Sudden-onset health pro-
blems can result from contact and noncontact mechanisms;
this classification is discussed below and presented
in Table 2.
Direct contact mechanisms directly lead to the health
problem in an immediate and proximal manner. Indirect
contact mechanisms also stem from contact with other ath-
letes or an object. The force is not applied directly to the
injured area but contributes to the causal chain, leading to
the health problem.
13,20,57,82
Noncontact mechanisms are
those that lead to health problems without any direct or
indirect contact from another external source. Gradual-
onset injuries, by their nature, are noncontact.
We anticipate that subsequent sport-specific consensus
statements will provide more detailed subclassifications to
address specific features of contact mechanisms (eg, subclas-
sification of contact with objects, such as ball, bat, net, gate).
Future sport-specific statements may also give specific
recommendations on other categories for classification
related to injury causation (eg, rule infringements, particular
movements, or other sport-specific features). The Interna-
tional Classification of Diseases (ICD) External Causes chap-
ter
111
and the International Classificationof External Causes
of Injury
112
provide specific codes that might be useful.
Multiple Events and Health Problems
One of the particular features of sports epidemiology, com-
pared with other settings, is the relatively high chance that
TABLE 1
Examples: Assessment of Mode of Onset
Mechanism Presentation Example
Acute Sudden
onset
1. A sprinter pulls up suddenly in a
race, stops, and hobbles a few steps
in obvious pain with a hamstring
injury.
Repetitive Sudden
onset
2. A gymnast experiences a frank tibial
and fibular fracture on landing from
a vault; computed tomography
imaging reveals pre-existing
morphological changes consistent
with bone stress, that is, a stress
fracture.
Repetitive Gradual
onset
3. A swimmer experiences a gradual
increase in shoulder pain over the
course of a season; diagnosed as
rotator cuff tendinopathy on
magnetic resonance imaging.
4IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
an athlete will sustain more than 1 health problem over the
follow-up period. This is illustrated in Figure 2.
The relatively common occurrence of multiple health pro-
blems in a single patient poses challenges for the reporting
and analysis of sports injury and illness data.
44
In particu-
lar, note that the number of athletes in a study is unlikely to
be the same as the number of reported health conditions, and
both should be stated. When reporting the frequency (or
proportion) of specific diagnoses or other characteristics, it
is important to state clearly whether this is expressed as the
proportion of all athletes followed up, the proportion of all
injured athletes, or the proportion of all reported injuries.
Subsequent, Recurrent, and/or Exacerbation of
Health Problems
Was a subsequent health problem related to previous
health problems? This is an important question in the field.
To know whether health problems follow previous health
problems requires both sets of problems to be classified
correctly using consistent terminology. This exercise can
providegreaterinsightintothe etiological factors that
underpin subsequent health problems.
34
Hamilton et al
60
provided a useful framework to catego-
rize subsequent injuries/illnesses and exacerbations in
sport (Figure 3). More recent frameworks incorporate
extensive criteria
34,100,101
that require judgment by trained
clinicians, which may be beyond the scope and capacity of
many surveillance protocols. When reporting frameworks
become more complex, there is a greater risk for data
errors.
93
In general, we do not recommend complex frame-
works but they can be considered for sophisticated data
collection and analysis where appropriate expertise and
resources exist.
The recommended subsequent injury terminology,
adapted from Hamilton et al,
60
includes noting whether
TABLE 2
Examples: Classification of Contact as a Mechanism for
Sudden-Onset Injuries
a
Injury Type of Contact Example
Noncontact
None No evidence of disruption
or perturbation of the
player’s movement
pattern
ACL tear in a basketball
player landing with
knee valgus/rotation
after a jump, with no
contact with other
players
Contact
Indirect Through another athlete ACL tear in a handball
player landing out of
balance after being
pushed on her shoulder
by an opponent while
in the air
Indirect Through an object Downhill skier suffers a
concussion from a
crash after being
knocked off balance,
hitting the gate with
his knee
Contact
Direct With another athlete ACL tear in a football
player from a direct
tackle to the anterior
aspect of the knee,
forcing the knee into
hyperextension
Direct With an object Volleyball player being
hit in the face by a
spiked ball, resulting
in a concussion
a
ACL, anterior cruciate ligament.
Figure 2. Examples of hypothetical prospectively collected injury/illness data (adapted from Finch and Marshall
37
). “X” indicates
when a period of surveillance is ended because the athlete left, unrelated to health problems, before the end of the study period;
this is called censoring.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 5
subsequent injuries (1) affect the same site but other
tissues (eg, knee but meniscus instead of anterior cruci-
ate ligament [ACL] alone) or (2) affect other sites. Sub-
sequent illness terminology
60
notes whether the
subsequent illnesses is the same system (eg, respiratory)
but other diagnosis (eg, bronchospasm as distinct from a
viral illness) or to other systems. The relevant defini-
tions are shown in Figure 3. Note that an injury may
be subsequent to an illness and vice versa (eg, bone
stress injury following diagnosis of an eating disorder,
depression following a lengthy recovery from revision
ACL reconstruction).
Subsequent injuries to the same location and tissue as
the index injury are recurrences if the index injury was
healed/fully recovered or exacerbations if the index injury
was not yet healed/fully recovered. Subsequent illnesses to
the same system and type as the index illness are recur-
rences if the individual has fully recovered from the index
illness and exacerbations if the patient has not yet recov-
ered from the index illness. Healed/fully recovered from
injury (or illness) is defined as when the athlete is fully
available for training and competition (see “Severity of
Health Problems” section).
To illustrate how to classify a subsequent injury, con-
sider athlete “A” who, following an ACL rupture and surgi-
cal reconstruction, presents late in the rehabilitation period
before returning to play with swelling and pain in the knee
after a slip and fall injury, resulting in a graft tear. This
injury would be classified as an exacerbation of the index
injury. In contrast, athlete “B” rehabilitated successfully
after ACL reconstruction and returned to play; that player
presents with pain and swelling in the same knee. If the
diagnosis is a torn ACL graft, this would be classified as a
recurrent injury. If the diagnosis is a meniscal tear (ACL
graft intact), this is a local subsequent injury.
To illustrate how to classify subsequent illness, consider
athlete “C” who has withdrawn from sports participation
due to an upper respiratory tract infection caused by influ-
enza type A virus, which then progresses to a lower respira-
tory tract infection, resulting in a diagnosis of viral
pneumonia. As athlete “C” is diagnosed with pneumonia
before recovery and return to play, the diagnosis of pneumo-
nia is an exacerbation of a recurrent illness. In contrast,
athlete “D,” following full recovery from the upper respira-
tory tract infection and returning to play, is diagnosed with
pneumonia; this illness is a subsequent new illness.
Time to recurrence or an exacerbation should be recorded
in days (see “Severity of Health Problems” section). A min-
imum list of data items recommended when collecting infor-
mation on subsequent injuries or illnesses is shown in
Table 3.
Classifying Sports Injury and Illness Diagnoses
Injury and illness classification systems are used in sports
medicine to:
Accurately classify and group diagnoses for research or
reporting, allowing easy grouping into parent classifica-
tions for summary, so that injury and illness trends can
be monitored over time or injury or illness incidence or
prevalence can be compared between groups (eg, differ-
ent teams, leagues, sports, sexes), potentially leading to
risk factor and preventive studies.
Create databases from which cases can be extracted for
research on particular or specific types of injuries and
illnesses.
In the late 1980s, clinicians and researchers were using
the 9th edition of the ICD.
111
The ICD system is an impor-
tant international standard, yet even the 11th edition,
released in 2018, lacks some classifications important in
Figure 3. Classification tree for subsequent health problems
(adapted from Hamilton et al
60
). Definitions: (1) index injury
(illness) is the first recorded injury (illness), and (2) subsequent
injury (illness) is any injury (illness) occurring after the index
injury (illness): (a) subsequent injury to a different location than
the index injury (subsequent illness involving a different sys-
tem than the index illness), (b) subsequent injury to the same
location but of a different tissue type than the index injury
(subsequent illness involving the same system but of a differ-
ent type/other diagnosis), or (c) subsequent recurrent injury
(illness) is a subsequent injury to the same site and of the
same type as the index injury (subsequent illness involving
the same system and type as the index illness). Third, fourth,
or more health problems should be assessed relative to the
initial index health problem and all other previous ones (eg,
second and third health problems).
6IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
sports injury and illness surveillance. Hamstring strain
and exercise-associated postural hypotension are 2 exam-
ples.
1,27,88
We encourage developers to include more sports
medicine diagnoses in future revisions of the ICD.
In the early 1990s, in Canada and Australia, 2 alternate
diagnostic coding systems were developed specifically
for sports medicine, and these have flourished into the
most widely used systems in sports injury surveillance
in the world today. Their “open access” nature has allowed
other researchers to use them free of charge (with acknowl-
edgment). These diagnostic coding systems are the Sport
Medicine Diagnostic Coding System (SMDCS) and the
Orchard Sports Injury Classification System (OSICS). Both
are based on initial codes to represent the body area and
further codes to represent the injury type or pathology.
One advantage of these coding systems is that they are
less cumbersome to apply than ICD codes, especially when
built into electronic systems with drop-down menus, taking
advantage of the body area and tissue/pathology type cate-
gories. The full ICD-11 coding system includes 55,000
codes, of which the majority are not relevant in sports med-
icine, compared with 750 to 1500 codes for versions of the
SMDCS and OSICS.
When reporting aggregate injury data, we recommend
using the categories for body area (Table 4) and tissue type
and pathology (Table 5) outlined below. In addition, the
categories for organ system/region (Table 7) and etiology
(Table 8) are presented below for illnesses.
When recording injuries or illnesses, the diagnosis
should be recorded in as much detail as possible given the
information available and the expertise of the individual
reporting. Acknowledging that some studies will rely on
athlete self-reports or proxy reports by parents, coaches,
or other nonmedically trained staff, this consensus group
also suggests categories to guide reporting of illnesses
(Table 9). When injury data are reported by athletes or
nonmedical staff, we recommend that reporting is limited
to the body area, as their reporting of tissue type and abnor-
mality is unreliable.
53
To facilitate reporting based on diagnostic codes, a com-
panion paper has been written with a supplemental Excel
(Microsoft) data file that provides a full list of revised
SMDCS and OSIICS (Orchard Sports Injury and Illness
Classification System) codes, along with a translation
between both systems and the ICD system.
85
Injuries—Body Area Categories
Wherever possible, we tried to define body areas anatom-
ically as either joints or segments. However, we made
exceptions based on common clinical presentations in
sport where needed. For example, the hip/groin is an area
that we have defined, which is a combination of a joint and
part of a segment, and therefore not a singular anatomical
region.
When 1 injury event results in more than 1 injury, the
individual diagnoses should be recorded and classified
separately. However, for injury incidence and prevalence
reporting purposes, this will be counted as 1 injury,
andseverityshouldbereportedastheseverityofthe
principal (most severe) injury (see below for further
explanations).
Injuries—Tissue- and Pathology-Type Categories
Using consensus methodology, we compared “injury type”
codes from the OSICS and SMDCS to arrive at definitions
of injury types. We constructed this table to be a single table
reflecting “injury types” (as per the OSICS) but split 2
TABLE 3
Recommendations for Key Data Items That Should Be
Collected and Reported on in Surveillance Systems
to Enable Multiple and Subsequent Injuries/Illnesses
to Be Monitored
a
Data Item Why It Is Important
Unique identifier to link all
injuries/illnesses in 1
participant
All participants require a unique
identifier that covers all
seasons/time periods and
should be anonymized to
protect privacy and
confidentiality.
Injury/illness time order
sequence
The exact date (day, month, year)
of the onset of each health
problem is essential for the
sequence to be clear. For
greater precision, time can be
important if there are multiple
events/heats each day (eg,
swimming).
Multiple injury/illness type
details
Multiple injuries and illnesses
can be the result of different or
same events or etiology,
coincide at the same time, or a
mixture of both. Injuries/
illnesses need to be linked to
the specific circumstances/
events that led to them. Date
and time stamping, directly
linked to diagnoses of all
injuries/illnesses, can inform
these relationships.
Injury/illness details, including
diagnosis
Collect information on the
nature, body region/system,
tissue/organ, laterality, and
diagnosis for all injuries/
illnesses. Sport injury/illness
diagnostic classification and
coding are optimal.
Details of circumstances and
time elapsed between
The time elapsed between
injuries/illnesses will be
determined by date and time
stamping. If away from
participation in sport, then it is
important to collect details and
date/time stamps regarding
rest, rehabilitation, treatment,
training, modified sport
participation, and return to
play.
a
Modified from Finch and Fortington.
35
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 7
columns into “tissue” (as the broad area) and then
“pathology” type more specifically. This reflects the original
approach taken in the SMDCS.
Recommendations: Reporting
Injury Characteristics
Injury characteristics are often reported in a single table by
region, injury type, or both. Cross-tabulations depicting
data by region and injury type (ie, combining the 2 into 1
table) often become large and unwieldy. It can leave many
cells empty or with very few cases (which can then compro-
mise confidentiality) unless the dataset is unusually large.
Such tables often also provide insufficient information for
research focused on specific areas or sports. For example, in
a sport where knee sprains dominate, it may be desirable to
report subgroups of these (eg, ACL, medial collateral liga-
ment) in greater detail.
In many cases, a better reporting option is to combine
region and type and diagnosis in 1 table, such as in the
exampleshowninTable6,wheresomecategorieshave
been collapsed at the level of body region (bold), some
regions have been split further into injury types (subhea-
der), and some even at the level of specific diagnosis (ita-
lics). It is expected that subsequent consensus statements
on specific sports will provide recommendations on suit-
able, standard formats for each sport to facilitate a direct
comparison of data on key injury types from studies on the
same sport.
Illness—Categories for Organ System and Etiology
Illness consensus categories are presented in Tables 7 and 8.
These are more detailed than the original versions of the
SMDCS and OSICS. Our tables diverge from the ICD cate-
gorization format in which body systems and abnormality
types are grouped together. We believe that it is important
to recognize that an illness, like an injury, both affects a body
system and has a specific pathological type. A respiratory
infection does not need to be considered either only as a
respiratory condition or an infection; it is certainly both. Our
recommended illness systems are similar to many of those in
the ICD, but we have merged some systems, such as the
upper respiratory system and nose/throat.
The professional background of those who report health
data will influence the final data quality (see “Data Collec-
tion Methods” section).
39
When athletes themselves (or non-
clinical recorders like coaching staff) are asked to capture
illness data, they should be encouraged to record symptoms
rather than attempt a diagnosis. Table 9 lists symptom clus-
ters that are characteristic of various systems. We caution
that this table requires additional validation and may be
modified in the future. Mapping symptoms to body systems
sacrifices some accuracy; however, in circumstances where
expert recorders are unavailable, it is better to have general
systems diagnosis data than no data at all.
Recommendations: Reporting
Illness Characteristics
As was the case when we discussed reporting of injury data,
we recommend against illness data being reported as
cross-tabulations of organ system by type of etiology type.
TABLE 4
Recommended Categories of Body Regions
and Areas for Injuries
a
Body Region/Area OSIICS SMDCS Note
Head and neck
Head H HE Includes face, brain
(concussion), eyes, ears,
teeth
Neck N NE Includes cervical spine,
larynx, major vessels
Upper limb
Shoulder S SH Includes clavicle, scapula,
rotator cuff, biceps
tendon origin
Upper arm U AR
Elbow E EL Ligaments, insertional
biceps and triceps tendon
Forearm R FA Includes nonarticular
radial and ulnar injuries
Wrist W WR Carpus
Hand P HA Includes finger, thumb
Trunk
Chest C CH Sternum, ribs, breast, chest
organs
Thoracic spine D TS Thoracic spine,
costovertebral joints
Lumbosacral L LS Includes lumbar spine,
sacroiliac joints, sacrum,
coccyx, buttocks
Abdomen O AB Below diaphragm and
above inguinal canal,
includes abdominal organs
Lower limb
Hip/groin G HI Hip and anterior
musculoskeletal
structures (eg, pubic
symphysis, proximal
adductors, iliopsoas)
108
Thigh T TH Includes femur, hamstring
(including ischial
tuberosity), quadriceps,
middistal adductors
Knee K KN Includes patella, patellar
tendon, pes anserinus
Lower leg Q LE Includes nonarticular tibial
and fibular injuries, calf,
Achilles tendon
Ankle A AN Includes syndesmosis,
talocrural and subtalar
joints
Foot F FO Includes toes, calcaneus,
plantar fascia
Unspecified Z OO
Multiple (single
injury crossing
2 regions)
XOO
a
OSIICS, Orchard Sports Injury and Illness Classification Sys-
tem; SMDCS, Sport Medicine Diagnostic Coding System.
8IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
A better option is to combine system/region and etiology in
1 table, as in the example on injuries shown in Table 6.
Depending on the illness pattern of the sport/setting, some
region categories may be collapsed and others split further
into etiology type and even to the level of specific diagnosis
(where available) to highlight the most significant ill-
nesses. We expect that subsequent sport-specific consen-
sus statements will recommend useful standard formats
for each sport.
SEVERITY OF HEALTH PROBLEMS
The severity of health problems in sport can be described
using various criteria.
33,99,104
These include the duration
of the period for which an athlete is unable to train/play
(called “time loss”), the athlete’s self-reported conse-
quences (various patient-rated measures of both health
and sports performance), the clinical extent of the
illness/injury, and societal cost (economic evaluation).
When considering which severity criterion to use, investi-
gators should consider the strengths and limitations of
each approach related to the objectives of their study or
surveillance program.
Time Loss From Training and Competition
The most widely used severity measure in sports medicine
is the duration of time loss. It has been recommended in
previous consensus statements
49,52,78,102
and is relatively
simple to capture, even when data collectors are nonexperts
(coaches, parents, or athletes themselves).
TABLE 5
Recommended Categories of Tissue and Pathology Types for Injuries
a
Tissue/Pathology Type OSIICS SMDCS Note
Muscle/tendon
Muscle injury M 10.07-10.09 Includes strain, tear, rupture, intramuscular tendon
Muscle contusion H 10.24
Muscle compartment
syndrome
Y 10.36
Tendinopathy T 10.28-10.29 Includes paratenon, related bursa, fasciopathy, partial tear, tendon
subluxation (all nonrupture), enthesopathy
Tendon rupture R 10.09 Complete/full-thickness injury; partial tendon injuries considered to be
tendinopathy
Nervous
Brain/spinal cord injury N 20.40 Includes concussion and all forms of brain injuries and spinal cord
Peripheral nerve injury N 20.39, 20.41-20.42 Includes neuroma
Bone
Fracture F 30.13-30.16, 30.19 Traumatic, includes avulsion fracture, teeth
Bone stress injury S 30.18, 30.32 Includes bone marrow edema, stress fracture, periostitis
Bone contusion J 30.24 Acute bony traumatic injury without fracture; osteochondral injuries are
considered “joint cartilage”
Avascular necrosis E 30.35
Physis injury G 30.20 Includes apophysis
Cartilage/synovium/bursa
Cartilage injury C 40.17, 40.21, 40.37 Includes meniscal, labral, articular cartilage, osteochondral injuries
Arthritis A 40.33-40.34 Posttraumatic osteoarthritis
Synovitis/capsulitis Q 40.22, 40.34 Includes joint impingement
Bursitis B 40.31 Includes calcific bursitis, traumatic bursitis
Ligament/joint capsule
Joint sprain (ligament tear or
acute instability episode)
L or D 50.01-50.11 Includes partial and complete tears plus injuries to nonspecific ligaments
and joint capsule; includes joint dislocations/subluxations
Chronic instability U 50.12
Superficial tissues/skin
Contusion (superficial) V 60.24 Contusion, bruise, vascular damage
Laceration K 60.25
Abrasion I 60.26-60.27
Vessels (vascular trauma) V 70.45
Stump (stump injury) W 91.44 In amputees
Internal organs (organ trauma) O 80.46 Includes trauma to any organ (excluding concussions), drowning, relevant
for all specialized organs not mentioned elsewhere (lungs, abdominal and
pelvic organs, thyroid, breast)
Nonspecific (injury without
tissue type specified)
P or Z 00.00 (also 00.23,
00.38, 00.42)
No specific tissue/pathology diagnosed
a
OSIICS, Orchard Sports Injury and Illness Classification System; SMDCS, Sport Medicine Diagnostic Coding System.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 9
When using this approach, we recommend that investi-
gators record severity as the number of days that the ath-
lete is unavailable for training and competition, from the
date of onset until the athlete is fully available for training
and competition.
The number of time-loss days should be counted from the
day after the onset that the athlete is unable to participate
(day 1) through the day before the athlete is fully available
for training and competition. Therefore, cases in which an
athlete does not complete a particular competition or train-
ing session but returns on the same or following day should
be recorded as 0 days of time loss (see Table 10 for exam-
ples). We note that in some cases, time loss does not follow
immediately after the health problem occurred and may be
delayed and/or intermittent (Table 10).
When athletes recover from health problems during per-
iods with no planned training or competition (eg, during an
end-of-season break), investigators should record the end
date as when the athlete normally would have been ready
for full training and competition participation.
When aggregating data across athletes, severity should
be reported as the total number of time-loss days, together
with medians and quartiles. Means and standard devia-
tions should be interpreted with care, given that the distri-
bution of time-loss days is likely to be right-skewed.
When reporting data separately in severity categories,
we recommend using the following time bins: 0 days, 1 to
7 days, 8 to 28 days, and >28 days.
If a single injury event results in multiple injuries, injury
severity should be based on the injury leading to the longest
time loss (eg,if a downhill skier crashes and suffers 2 injuries,
a concussionthat takes 10 days to resolve and a tibial fracture
that takes 120 days, the time loss for the event is 120 days).
Health Problems Contracted During Multiday Events
After athletes have left an event, it may be difficult to
obtain accurate follow-up information on their condition
and return to play. For cases that were not closed by a date
TABLE 6
Data on Injury Pattern and Burden of Specific Match Injuries Among Professional Rugby Teams in New Zealand
a
Region/Type/Diagnosis No. of Injuries
Incidence, Injuries/
1000 h (95%CI)
Time Loss,
Median (95%CI), d
Burden, Time-Loss Days/
1000 h (95%CI)
Head 277 12.9 (11.5-14.5) 9 (8-10) 325 (317-333)
Concussion 204 9.5 (8.3-10.9) 10 (9-11) 257 (250-263)
Neck 60 2.8 (2.2-3.6) 8 (6-10) 135 (130-140)
Shoulder 168 7.8 (6.7-9.1) 21 (14-27) 628 (618-639)
Acute dislocation 15 0.7 (0.4-1.1) 209 (27-337) 165 (159-170)
Hematoma 18 0.8 (0.5-1.3) 8 (4-13) 25 (23-27)
Joint sprain 102 4.8 (3.9-5.7) 19 (12-25) 292 (285-300)
Acromioclavicular joint sprain 54 2.5 (1.9-3.3) 14 (10-20) 68 (65-72)
Glenohumeral joint sprain 48 2.2 (1.7-2.9) 30 (14-80) 225 (218-231)
Upper arm 4 0.2 (0.1-0.4) 6 (3-133) 7 (6-8)
Elbow 27 1.3 (0.9-1.8) 9 (5-17) 42 (39-44)
Forearm 10 0.5 (0.2-0.8) 99 (44-131) 65 (61-68)
Wrist and hand 96 4.5 (3.6-5.4) 10 (7-27) 194 (188-200)
Chest 81 3.8 (3.0-4.7) 13 (10-16) 75 (71-79)
Thoracic spine 6 0.3 (0.1-0.6) 5 (3-50) 5 (4-6)
Lumbar spine 32 1.5 (1.0-2.1) 10 (5-21) 66 (63-70)
Pelvis/buttock (excluding groin) 6 0.3 (0.1-0.6) 12 (5-20) 3 (3-4)
Hip/groin 40 1.9 (1.4-2.5) 9 (6-11) 82 (78-86)
Thigh 138 6.4 (5.4-7.6) 14 (11-17) 171 (165-176)
Knee 165 7.7 (6.6-8.9) 31 (23-37) 544 (535-554)
Knee cartilage injury 29 1.4 (0.9-1.9) 43 (29-58) 124 (120-129)
Meniscal cartilage injury 22 1.0 (0.7-1.5) 44 (28-62) 101 (96-105)
Knee ligament injury 125 5.8 (4.9-6.9) 30 (20-37) 390 (382-398)
MCL injury 75 3.5 (2.8-4.4) 33 (24-37) 154 (149-159)
ACL injury 9 0.4 (0.2-0.8) 275 (70-295) 92 (88-96)
PCL injury 6 0.3 (0.1-0.6) 20 (12-218) 23 (21-25)
PLC and LCL injury 8 0.4 (0.2-0.7) 35 (7-132) 55 (52-58)
Lower leg 100 4.0 (3.2-4.9) 17 (14-23) 190 (184-196)
Ankle 147 6.9 (5.8-8.0) 15 (11-21) 320 (313-328)
Ankle sprain 113 5.3 (4.4-6.3) 15 (11-21) 228 (222-235)
Lateral ligament sprain 46 2.1 (1.6-2.8) 15 (9-19) 78 (74-82)
Syndesmosis sprain 34 1.6 (1.1-2.2) 33 (28-43) 108 (104-112)
Foot 40 1.9 (1.4-2.5) 37 (14-57) 84 (80-88)
a
From 2005 to 2018 (unpublished data). See also Figure 5, illustrating the same data set in less detail as a risk matrix as well as the
sections on rates, severity, and burden of health problems for an explanation of these concepts. ACL, anterior cruciate ligament; LCL, lateral
collateral ligament; MCL, medial collateral ligament; PCL, posterior cruciate ligament; PLC, posterolateral corner.
10 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
of return to play at the time of the end of the event, we
recommend that:
1. If the researcher can liaise with team medical staff
and record the actual date of return to play, this infor-
mation should be captured. Collecting actual dates is
recommended.
2. If this is not possible, then team medical staff should
be asked to provide an estimate of when the athlete is
expected to return to play. In such cases, this infor-
mation should be clearly labeled as an estimated
severity.
3. If this is not possible, then event medical staff should
record the date that the athlete leaves the tourna-
ment, that is, the last date on which the athlete was
seen with the unclosed health problem. In such cases,
the information should clearly be labeled as right-
censored injury duration (a statistical term for situa-
tions in which only a portion of the time loss can be
observed).
Limitations of Using Time Loss to Measure Severity
Time loss generally reflects injury severity but has limita-
tions. First, the demarcation between the end of time loss
and the resumption of “normal training and competition” is
not necessarily a clear line in the sand. In some sports,
athletes may be able to participate before an injury or illness
has fully resolved, for example, by adapting their technique,
accepting a lower performance level, or playing a different
role on the team (eg, a ballet dancer working at the barre but
not dancing on the floor or doing any jumps). Participation
before an injury or illness is fully resolved would tend to
underestimate the absolute severity of the injury if one con-
sidered full healing as the gold standard. Conversely, ath-
letes may choose not to resume their “normal” training and
competition for an extended period after an injury or illness
has clinically resolved toallow them to regain full fitness (eg,
a professional footballplayer after ACL reconstruction). This
would overestimate the severity of the condition.
Second, a time loss–based severity measure underesti-
mates the severity of those health problems that limit a
player’s performance but do not stop the person from play-
ing. Many gradual-onset injuries fit that bill (eg, patellar
tendinopathy). Similarly, when athletes have a recurrent
or chronic illness, such as asthma or inflammatory arthri-
tis, they may have relatively low time loss (from training or
competition) but may be markedly affected in training con-
tent and intensity.
3,16,17
Third, time loss is inappropriate to describe the most
severe types of health problems, such as those leading to
TABLE 7
Recommended Categories of Organ
System/Region for Illnesses
a
Organ System/
Region ICD-11 OSIICS SMDCS Note
Cardiovascular 11 MC CV
Dermatological 14 MD DE
Dental (13) MT DT
Endocrinological 05 MY EN
Gastrointestinal (13) MG GI
Genitourinary 16 MU GU Includes renal,
obstetrical,
gynecological
Hematological 03 MH BL
Musculoskeletal 15 MR MS Includes
rheumatological
conditions
Neurological 08 MN NS
Ophthalmological 09 MO OP
Otological 10 ME OT Ear only
Psychiatric/
psychological
06 MS PS
Respiratory 12 MP RE Includes nose and
throat
Thermoregulatory (22) MA TR
Multiple systems MX MO
Unknown or not
specified
MZ UO
a
ICD-11, International Classification of Diseases–11th Revi-
sion; OSIICS, Orchard Sports Injury and Illness Classification Sys-
tem; SMDCS, Sport Medicine Diagnostic Coding System.
TABLE 8
Recommended Categories for Etiology of Illnesses
a
Etiology ICD-11 OSIICS SMDCS Note
Allergic (22) MxA 71
Environmental
(exercise
related)
(23) MxE 72 Heat illness,
hypothermia,
hyponatremia,
dehydration
Environmental
(nonexercise)
(22/7) MxS 73 Includes sleep/
wake, sunburn
Immunological/
inflammatory
(04) MxY 74
Infection 01 MxI 75 Viral, bacterial,
parasitic
Neoplasm 02 MxB 76
Metabolic/
nutritional
05 MxN 77
Thrombotic/
hemorrhagic
(11/03) MxV 78
Degenerative or
chronic
condition
MxC 79 Chronic acquired
conditions
Developmental
anomaly
20 MxJ 80 Includes congenital
conditions
Drug-related/
poisoning
22 MxD 81 Includes
pharmaceutical,
illicit
Multiple MxX 82
Unknown or not
specified
MxZ 83
a
ICD-11, International Classification of Diseases–11th Revi-
sion; OSIICS, Orchard Sports Injury and Illness Classification Sys-
tem; SMDCS, Sport Medicine Diagnostic Coding System.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 11
retirement from sport, permanent disability, or death,
because the time-loss data from those injuries are right-
censored.
Athlete-Reported Symptoms and Consequences
There are tools to measure injury and illness symptoms
that directly address the second limitation of time loss
discussed earlier, underestimating the effect of ongoing
pain and symptoms that are below the time-loss thresh-
old. A tool such as the Oslo Sports Trauma Research
Center Questionnaire on Health Problems (OSTRC-H)
complements time-loss measures of severity, as it also
captures symptoms and functional consequences of
injury and illness. This purpose-built instrument was
devised in 2013
17
and updated in 2020
15
and has played
an increasing role in sports injury and illness surveil-
lance, especially in sports and settings where overuse
injuries and illnesses represent a substantial burden on
health and performance.
71
The tool (which can be delivered via a mobile applica-
tion) invites athletes to record reduced sports participa-
tion, training modifications, performance reductions,
and symptoms.
17
Based on the response to these
questions, researchers can calculate a severity score
ranging from 0 to 100 at specific time points. These can
be aggregated (summed as the area under the curve) to
monitor injury and illness over time (Figure 4). This is
called the cumulative severity score. A limitation of this
method is that the severity score is an arbitrary num-
ber, and it has not been thoroughly validated as a proxy
for injury severity.
Recording the Severity of Health Problems
Based on Clinical Assessment
Investigators may also report the severity of health pro-
blems based on clinical outcomes such as the need for hos-
pitalization or surgery,
33,92
retirement from sport,
permanent disability, or death.
43,92
Degree and Urgency of Medical Attention. The severity of
an injury or illness can also be recorded based on the degree
and urgency of medical attention received by the athlete.
This approach is best suited to record acute conditions and
is often used in mass-participation events and community
sports settings.
33,40,41
An example using this approach is
provided by Schwellnus et al
92
in their work on mass
community-based endurance sports events.
TABLE 9
Recommended Categories of Illness Symptom Clusters for Athlete Self-reports or Nonmedical Data Reporters
System/Region Symptom Cluster
Upper respiratory (nose, throat) Runny nose, congestion, hay fever (allergy), sinus pain, sinus pressure, sore throat, cough,
blocked/plugged nose, sneezing, scratchy throat, hoarseness, head congestion, swollen
neck glands, postnasal drip (mucus running down the back of the nose to the throat)
Lower respiratory Chest congestion, wheezing (whistling sound), chesty cough, chest pain when breathing/
coughing, short of breath, labored breathing
Gastrointestinal Heartburn, nausea, vomiting, loss of appetite, abdominal pain, constipation, weight loss
or gain (>5 kg in the past 3 months), change in bowel habits, diarrhea, blood in the stool
Cardiovascular Shortness of breath, racing heart beats, irregular or abnormal heart beats, chest pain,
chest pain or discomfort with exercise, dizziness, fainting spells, blackouts, collapse
Urogenital/gynecological Burning urination, blood in urine, loin pain, difficulty in passing urine, poor urine stream,
frequent urination, genital sores, loss of normal menstruation, irregular or infrequent
menstruation, menstrual cramps/pain, excessively long periods, excessive bleeding
during periods, vaginal discharge, penile discharge, swollen groin glands
Neurological Headache, fits or convulsions, muscle weakness, nerve tingling, nerve pain, loss of
sensation, chronic fatigue
Psychological Anxiety, nervousness, excessive restlessness, feeling depressed (down), excessive sadness,
not sleeping well, mood swings, feeling excessively stressed
Dermatological Skin rash, dark/light/colored areas on the skin that have changed in size or shape, itchy
skin lesions
Musculoskeletal, rheumatological, and connective
tissue (unrelated to injury)
Joint pain, joint stiffness, joint swelling, muscle twitching, muscle cramps, muscle pain,
joint redness, warmth in a joint
Dental Toothache, painful gums, bleeding gums, oversensitive teeth, persistent bad breath,
cracked or broken teeth, jaw pain, mouth sores
Otological Ear pain, ear discomfort, loss of hearing (new onset), deafness, discharge from the ear
canal, bleeding from the ear canal, ringing in the ears
Ophthalmological Pain in eye, itching or burning eye, scratchy eye, eye discharge, change in vision including
double vision, blood in eye, excessive tearing, abnormal eye movements, swelling of eye,
blind spot in eye, drooping eye, halo around lights, lightning flashes, swelling of eyelid
Nonspecific illness Feeling feverish, chills, pain, whole body aches, feeling tired
Energy, load management, and nutrition
(nonbody system)
Unexplained underperformance, reduced ability to train and compete, fatigue
12 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
Permanent Disability and Death. All conditions leading
to permanent disability or death that occur during the
period of data collection should be reported separately.
There are some specific definitions accepted in the field:
A “catastrophic injury” refers to a confirmed spinal
cord or traumatic brain injury, resulting in perma-
nent functional disability (using the American Spinal
Injury Association scale
2
and assessed at 12 months).
This does not include injuries resulting in transient
neurological deficits such as burners/stingers, pares-
thesia, transient quadriplegia, or cases of concus-
sions in which there is full recovery. The term
“catastrophic event” has also been extended to
include noninjury events that are life-threatening,
such as sports-related sudden cardiac arrest and
exertional heat stroke.
28
More detailed recommenda-
tions on this issue are provided in the consensus
statement on mass community-based endurance
sports events.
92
A “fatality” refers to any athlete fatality related to
training or competition. When fatalities occur
months or years after the event, researchers should
justify the relationship to training/competition.
43,66
As such cases often receive media attention, we remind
investigators to consider privacy issues. Special considera-
tions apply to approaching, consenting, and collecting data
from families who have sustained a major loss.
Other Severity Measures
Depending on the sport setting and the purpose of data
collection, investigators may also quantify severity in other
ways.
99
Function, performance, and patient-reported out-
come measures may be used to capture severity. Specific
examples include the following:
Functional measures, for example, the International
Classification of Functioning, Disability and Health
(ICF).
113
Sports-related performance measures, for example,
balance, strength, and endurance. We include ath-
letes reporting retirement from sports in this
category.
Patient-reported outcome measures, for example, the
ACL Quality of Life Questionnaire (ACL-QOL),
75
Knee injury and Osteoarthritis Outcome Score
(KOOS),
89
and Sport Concussion Assessment Tool–
5th Edition (SCAT5).
23
CAPTURING AND REPORTING
ATHLETE EXPOSURE
Assessing exposure is fundamental to quantifying injury
and illness risk in sports.
33,46
There are many ways to
quantify athletic exposure, and no single measure will suit
all surveillance settings and research questions. The choice
of exposure measures is heavily influenced by sport-specific
and contextual factors as well as which types of health pro-
blems are of interest. Therefore, it is often necessary to
record exposure in several ways.
Tracking Exposure for Injury Analyses
For injuries, exposure is generally quantified as the time
during which athletes are at risk of injury (eg, minutes
played), the distance covered, or a count of the number of
Figure 4. Example of severity scores being used to track the
severity of 3 “typical” health problems. Each black dot repre-
sents the weekly severity score. The area in orange repre-
sents a gradual-onset injury (cumulative severity score [sum
of weekly scores, as the area under the curve] ¼1820), the
black area represents a short-duration illness (score ¼100),
and the dark red area represents an acute medial collateral
ligament injury (score ¼362).
17
TABLE 10
Practical Examples of How to Calculate Time Loss
Case
Time
Loss, d
A collegiate volleyball player is substituted from a match
because of an injury but returns to compete in another
match later the same day.
0
A cyclist interrupts a training session because of mild
diarrhea and resumes normal training the
following day.
0
A hockey player strains her hamstring during a training
session on Monday and returns to normal training on
Monday of the following week.
6
A recreational-level cricket player injures his shoulder
during a match on Saturday. His shoulder is stiff and
painful for 2 days after the match (Sunday and
Monday). The team only trains once per week, every
Thursday, but the player feels that he would have been
able to train normally had training been on Tuesday
instead.
2
“Delayed” time loss: An athlete suffers an injury on
Sunday, a thigh contusion, is able to train on Monday
and Tuesday, but is unable to train on Wednesday and
returns on Sunday (time loss starts on Wednesday,
even though the injury occurred on Sunday).
3
“Intermittent” time loss: A player with Osgood-Schlatter
disease that gets reported at the start of a training
camp on Monday. He may train fully on Monday,
Tuesday, and Thursday but miss training on
Wednesday and Friday (time loss counted as
Wednesday and Friday only).
2
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 13
specified events (eg, tackles, throws, or jumps). In some
sports, exposure is commonly expressed as the number of
athletic participations (eg, games, races, training sessions),
often referred to as “athletic exposures.” Table A2 in Appen-
dix 1 provides a range of examples of exposure measures
used.
In team sports, we recommend recording exposure for
each individual within a team rather than merely estimat-
ing the number of matches that the team plays and match
duration (team exposure) because the former permits the
researcher to examine individual risk factors. Results of all
the individuals are then summed to provide exposure at the
sport or team level.
As the injury risk is often markedly different between
training and competition, these exposures should be
recorded and reported separately. To do this consistently,
it is necessary to define competition and training and to
consider situations where applying the definition may be
challenging.
We define competition as organized scheduled play
between opposing athletes or teams of athletes or as ath-
lete(s) competing (1) against time and/or (2) to obtain a
score (judged or measured). We define training as physical
activities performed by the athlete that are aimed at main-
taining or improving their skills, physical condition, and/or
performance in their sport.
In many sports, it is common to simulate competition as a
part of training. Examples include preseason “friendly
scrimmages” between 2 teams or dividing a single squad
into teams that compete against each other. In general, this
should be counted as training exposure. Additionally, activ-
ities such as warm-up and cool-down should be counted
separately and reported as training injuries, even if occur-
ring around competition.
It is likely that, in some sports, these definitions will not
be fully applicable. In such cases, we encourage sport-
specific consensus groups to define what constitutes com-
petition and training in that sport.
Tracking Exposure for Illness Analyses
Because athletes remain at risk of developing an illness
even when they are not participating in sports, it is inap-
propriate to use exposure measures such as playing hours
or movement counts to quantify the illness risk (except for
the rare cases of transmissible infections that are specific to
participation in a sport; eg, scrum pox). Instead, it is often
most appropriate to use exposure measures based on the
time that athletes are under surveillance (days or years)
rather than time engaged in competition and training.
Recording Exposure During Multiday Competitions
Multiday competitions, such as championships and tourna-
ments, represent an exposure measurement challenge, par-
ticularly for injury analyses. Ideally, investigators should
obtain accurate records of every athlete’s individual partic-
ipation (eg, training and competition minutes) throughout
the tournament. However, this is not always feasible.
Acceptable exposure estimates can also be made by
obtaining summary data from every team for each day of
the tournament (eg, squad numbers). As a minimum stan-
dard, exposure can be estimated for each event by multi-
plying the number of registered athletes by the duration of
the tournament (the number of days of competition). In
multisport tournaments, this should be calculated for each
sport. However, this approach assumes that all athletes
have the same exposure and participate every day, which
is rarely the case.
Training Subcategories
Different types of training should, if possible, be recorded
and reported separately. Training types can be generally
categorized as follows:
Sport-specific training: sessions involving the
techniques and/or tactics of the sport, usually
supervised by a coach.
Strength and conditioning: sessions solely composed
of resistance training and/or conditioning training.
In many cases, training sessions are mixed (sport-
specific, but with the addition of some strength and
conditioning; eg, plyometrics and endurance). As a
pragmatic consideration, any session containing
sport-specific training should be categorized as
such, even if the session includes some strength and
conditioning, purely to streamline exposure
tracking.
Other training sessions: sessions that include activi-
ties other than sport-specific training or strength and
conditioning. These include recovery sessions (eg,
low-intensity running and stretching), rehabilita-
tion, and postrehabilitation transition sessions (after
return to sport but prior to resuming normal
training).
Sport-specific injury surveillance systems may need to
depart from this guidance if there is a need to address a
specific training concern; however, at a minimum, all train-
ing exposures that contain sport-specific training should be
tracked.
Sport-specific injury surveillance systems are encour-
aged to develop specialized procedures for tracking the
diversity of training exposures in their particular sport.
Training programs vary considerably among sports, and
many coaches intentionally design training programs that
integrate multidimensional training (eg, plyometric
stretching, sport-specific training, light running) into a sin-
gle session. In general, investigators should prioritize cap-
turing specific data on the training activities considered to
present the greatest health risk.
Wearable physical activity tracking devices enable inves-
tigators to capture large volumes of competition and train-
ing data at the elite level and from community sports
participants across large sample groups. We encourage the
use of these devices for tracking exposure. However, we
caution that any device needs to be fit for the purpose, and
researchers should obtain evidence on their validity and
14 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
reliability before data collected through these devices are
used for injury surveillance.
EXPRESSING RISK
Rates and Proportions
Rates and proportions of injury and illness in studies of
sports are usually reported as counts of “cases” of the out-
come of interest (the “numerator”) divided by a population
at risk of developing the outcome (the “denominator”).
18
Because research questions such as “How many players
have suffered a knee injury?” “What is the risk of getting
injured in this sport?” and “How does sport A compare with
sport B for concussion risk?” are very different, there are
various ways of reporting risks related to sports injury and
illness. We explain some fundamental terms here.
Prevalence: How Many? Prevalence is a proportion and
refers to the number of existing cases divided by the total
population at risk at a given point in time (point preva-
lence; eg, the proportion [percentage] of players on a volley-
ball team who, today, are suffering from patellar
tendinopathy). It is a snapshot at one point in time but can
be repeated to determine changes in prevalence over time
(eg, weekly). With serial measurements, it is possible to
report, for example, the average prevalence over the course
of the season and also to compare different stages of the
season.
Period prevalence extends the concept of a single point in
time to a window of time (eg, 1 season, 1 year). It refers to
the proportion of athletes that has reported the condition of
interest (eg, patellar tendinopathy) at any time during that
given window. Notably, this includes people who already
had the condition at the start of the study period as well
as those who acquired it during that period.
Incidence: How Often (Do New Cases Occur)? Incidence
is a rate, and as with any rate, time comes into play. Inci-
dence refers to the number of new injuries/illnesses in the
population that develop during a defined period of time.
The term “incidence rate” is synonymous, but we argue that
it is a tautology; “incidence” is a rate.
Note that prevalence is calculated based on the number
of athletes with a health problem, while incidence refers to
the number of new health problems.
Recommendations: Expressing Risk in
Sports Injury/Illness Surveillance
Incidence-based measures usually represent more appro-
priate outcomes for sudden-onset conditions (eg, ankle
sprains, ACL injuries) and prevalence-based measures for
gradual-onset conditions (eg, asthma, patellar tendinopa-
thy).
3
Overuse injuries and pain problems such as low back
pain and patellar tendinopathy are often chronic, with per-
iods of remission and exacerbation. For example, in a pro-
fessional volleyball team, there could be only 1 new case of
patellar tendinopathy (so the incidence will be low), yet 40%
of the players (nearly all pre-existing) could be affected by
patellar tendinopathy during the season (period
prevalence). Therefore, for such conditions, prevalence (the
proportion of athletes affected) is a more appropriate meas-
ure than incidence (the number of new cases during the
season).
Because sports and the activities that comprise them are
so diverse, there is no single approach to expressing risk
appropriately for all sports injury surveillance projects.
70
In general, incidence-based measures that provide a stan-
dard time window for the population at risk (injuries per
hour) are preferable to measures for which the time at risk
varies across individuals (injuries per athletic exposure, ie,
per training session or match) because time-based mea-
sures better facilitate comparison across sports.
To provide numbers that are easy to interpret, avoiding
small decimals, these data are typically reported as per
1000 player-hours (eg, the concussion rate in a men’s rugby
study was reported as 4.7/1000 player-hours rather than
0.0047 per player-hour).
55
Such numbers allow risks to be
compared (eg, how does the concussion risk vary across
contact sport codes?). We expect that subsequent sport-
specific statements will recommend suitable, standard
incidence-based measures for each sport. Table A2 in
Appendix 1 provides a range of examples of risk measures.
If 1 injury event results in multiple injuries, these should
only be counted as 1 when calculating overall injury inci-
dence (eg, if a downhill skier crashes and suffers 2 injuries,
a concussion and a tibial fracture, these are counted as 1
injury when calculating incidence).
Because of the difficulties in accurately measuring expo-
sure to pathogens (which may be greater when not training
or competing), illness risk should be estimated based on the
entire period of exposure (eg, the duration of a competition,
a “season of play,” a year), not athletic exposure only. We
recommend reporting illness risk as either the incidence;
the number of new cases divided by a period of time (eg,
illnesses per 365 athlete-days)
91
; or as the period preva-
lence of the illness, the proportion of athletes who were ill
during a defined period.
94,95
Where time-based measurements of exposure are
unavailable but participant numbers are available, crude
rates of injury per number of participants per period can be
derived. In such cases, we suggest that the incidence that
may be most useful to permit population-level comparisons
among sports or studies is “injuries per 365 athlete-days.”
Similarly, the proportion of participants with new or
recurring injury or illness (ie, excluding pre-existing cases
and exacerbations) during the event has been used to pro-
vide an impression of the risk associated with participation
in each sport in both the summer and winter Olympic
Games.
94,95
However, this approach—period prevalence—
can suggest widely different relative risks of activities that
differ substantially in the amount of exposure participants
experience.
94
For example, exposure differs substantially
between a football player and a sprinter. Period prevalence
describes the absolute risk of participation in the Olympic
Games but not the relative risk (the risk of injury during 1
hour of football play vs 1 hour of marathon running).
Injury rates reported on a per-event (eg, per rugby
tackle) basis provide information about how likely a partic-
ular aspect of play (event) is to result in an injury.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 15
Understanding events that both do
5
and do not result in
injury
73,74
helps researchers identify injury prevention
opportunities. In the absence of information about how fre-
quently the event occurs within a sport and the average
duration of the sport to which participants are exposed,
rates per event also provide an incomplete view of the over-
all risks that a sport poses. Using time- and event-based
denominators (eg, tackles in football codes) in parallel can
help provide insights into both which event (eg, tackle type)
is most frequently associated with injuries and which event
carries the highest risk when it occurs. To date, there have
been relatively few injury surveillance studies in which
such statistics have been provided together.
44
For televised
sports and those using new technology such as activity
trackers, measurement of the duration of playing time and
intensity for each athlete is feasible, and coding of the num-
ber, characteristics, and duration of activities each partic-
ipant engages in (eg, tackles) is routine for some
professional sports (eg, football). We include a real-life illus-
trative case of surveillance methods being used to investi-
gate injury risk in rugby in Appendix 1.
Communicating the Risk to Stakeholders
From clinical and practical perspectives, it is important
that the end users (the athletes, coaches, and medical staff
members) can make sense of the injury reports and
increase the chances of having them participate in risk
management plans. This can be done by expressing the
injury incidence based on the concerned sport’s specifica-
tions. For instance, if an injury incidence for a specific mus-
cle group (eg, hamstring) is expressed as 0.9 injuries per
1000 hours of exposure, the incidence per player per season
(0.28 injuries/player/season) could be multiplied by the
average number of athletes per squad for the concerned
sport (eg, 25 in football). This gives 7 hamstring injuries
per squad per season, a quantity that is more easily inter-
preted by end users.
Another relevant measure, which is easy to communi-
cate to managers, coaching staff, and athletes and that is
associated with team performance in football,
59
is player
availability. Player match availability is calculated as the
sum of player match opportunities (ie, the number of
matches multiplied by the full size of the squad) minus the
sum of player match absences due to injury or illness and
can be expressed as the average percentage over the
period of interest (eg, 1 season). Training availability can
be calculated in the same way.
We encourage sport-specific consensus statements to rec-
ommend relevant measures to communicate risk to rele-
vant stakeholders.
BURDEN OF HEALTH PROBLEMS
Burden is a collective measure of the overall impact of a
health problem in a specified population. In public health,
burden is often expressed by financial cost, mortality, or
morbidity. One common approach is specific measures such
as quality-adjusted life years or disability-adjusted life
years.
79
Burden allows different health problems to be com-
pared—Does low back pain or diabetes cause more burden
to society?
The burden of injuries and illnesses can also be
expressed using measures that combine their frequency
and consequences.
4,21
For example, in football and rugby
union, injury burden has been reported as the number of
days of time loss per 1000 hours of player exposure.
8-
12,87,110
This contrasts with incidence (discussed earlier),
where the numerator is the number of injuries rather than
the consequence of those injuries—days of time loss.
As measures of incidence and consequences vary depend-
ing on the purpose and setting of data collection, there is no
single method of calculating burden in sports. To facilitate
comparison among sports, investigators should consider
reporting the number of days of time loss per 365 athlete-
days for each outcome of interest in addition to measures
based on sport-specific exposures. We expect that subse-
quent sport-specific statements will provide recommenda-
tions on suitable, standard burden measures for each sport.
Burden can also be visualized using a risk matrix in
which the incidence of each health problem of interest is
plotted against its consequences (such as mean time loss, as
illustrated in Figure 5). This is an effective way to commu-
nicate the overall burden (and its determinants) for a range
of health problems. However, there are certain limitations
to interpreting risk matrices, depending on how figures are
designed and how data are structured (see Fuller
47
for a
detailed review).
Burden measures that use time loss as a measure of
severity fail to incorporate the most severe health problems
(ie, fatalities and nonfatal catastrophic injuries and ill-
nesses) and other cases where the athlete fails to return
Figure 5. Risk matrix based on the duration of time loss illus-
trating the burden of match injuries among professional rugby
teams in New Zealand between 2005 and 2018 (unpublished
data). The darker the yellow, the greater the burden. The
curved gray lines represent points with equal burden. The
vertical and horizontal error bars represent 95% CIs. See also
Table 6, illustrating the same dataset in more detail.
16 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
to sport (eg, due to retirement). As previously discussed,
time loss–based severity measures also underrepresent
overuse injuries and chronic illnesses.
3,16
In this case,
mean OSTRC-H severity scores can be used instead of time
loss, as illustrated in Figure 6.
15
STUDY POPULATION CHARACTERISTICS
Depending on the purpose of the study, demographic and
health data may be included in injury and illness surveil-
lance protocols. The demographic information captured
should, as a minimum, include age, sex, and level of com-
petition and disability/impairment type in Paralympic
sport. These can be supplemented with data on other rele-
vant characteristics that could help investigators evaluate
risk factors.
It is important to describe the performance and training
level of the study population both because they are often
closely related to health outcomes and to allow appropriate
studies to be compared.
33
It is beyond the scope of this con-
sensus group to provide a universal classification of com-
petitive level. For example, the criteria used to define
“elite” vary considerably among sports. We encourage
sport-specific methodological consensus groups to define
what constitutes “elite,” “subelite,” and “recreational” ath-
letes in their sport.
Classification of Sport Categories
There are many ways of classifying and grouping sports.
Any sports classification system used in surveillance
should be clearly described in the methods section of
reports. The description should permit other researchers
to understand and replicate the process by which sports
were grouped. The research problem being addressed
should shape the classification system used rather than
vice versa.
DATA COLLECTION METHODS
The methods underpinning the data collection have great
impact on the outcome of sports injury and illness surveil-
lance studies.
33,38,97
A systematic review of ongoing injury
surveillance systems in sport found that data quality
aspects were published for only 7 of the 15 systems and
validation studies for only 4.
26
The review concluded that
data quality could be improved through the establishment
of data collection standards.
Given the wide range of settings in which surveillance is
undertaken, data collection methods should be flexible
enough to adapt to the specific context (eg, sport culture,
level of sport, availability of resources) and to the specific
research question and objectives of the study.
33
These fac-
tors in combination will determine:
Who should provide the information (eg, athlete, physi-
cian, physical therapist, coach, nonclinical volunteer)
What data sources should be used (eg, athlete self-
report, medical records, examinations, video recording)
The frequency of data collection and reporting (eg, daily,
weekly, monthly)
The timing of and window for data collection (eg, day of
injury/illness or of competition/training or following
day, within a week)
The duration of surveillance (eg, tournament, season,
whole year, playing career)
Taking all of these variables into account, it is evident
that “one size does not fit all.”
14,105
In 2001, the WHO
38,62
published guidelines for injury
surveillance that remain relevant. In particular, some gen-
eral aspects about quality of data collection systems (ie,
objectivity, reliability, validity, practicability, risk of bias,
cost-/time-effectiveness, acceptability), quality of imple-
mentation (eg, guidance document, communication, com-
pliance, data check), and some methodological issues (eg,
handling of missing values, completeness of reports, cover-
age, response rate) are important.
24,36,64
In addition, the
choice of injury definition, exposure measure, and methods
used to express rates influence the results substantially, as
discussed in the relevant sections of this document.
The reliability of the system can be improved by tailored
education, ongoing support for the people who report the
data, and a detailed process manual
62
and should be eval-
uated at least by analysis of interrater reliability of people
reporting the data.
24
Validity and completeness of data reporting can be ana-
lyzed, comparing with another “gold-standard” data
source.
6,42,53,67,77,81
A recent study showed that research-
involved staff recording the data in a surveillance program
reported a greater number of mild injuries than did
nonresearchers.
109
Figure 6. Risk matrix based on Oslo Sports Trauma Research
Center Questionnaire on Health Problems severity scores
illustrating the burden of injuries and illnesses affecting elite
Norwegian endurance athletes (unpublished data). Error bars
represent 95% CIs.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 17
An example of specific measures to improve the reliabil-
ity of a surveillance project is illustrated in Table 11, based
on the procedure of the Professional Rugby Injury Surveil-
lance Project.
29
From Pen and Paper to Electronic Solutions
Health problems and exposure can be captured using dif-
ferent methods ranging from paper copy data collection
forms to a comprehensive web-based surveillance system,
for example, internet platforms, mobile applications, or text
messaging.
7,31,40,76,77,81,96,117
The traditional pen-and-
paper approach is often easy to implement,
41
as it reduces
the need for specific technical knowledge, equipment, and
related costs.
40,72
Data can be verified and cleaned as they
are manually entered.
72
Electronic data capture reduces time for the duplication of
data entry
41
and associated entry errors.
72
In terms of costs,
there is potential long-term cost-effectiveness through the
elimination of expenseslinked to the printing, shipping,man-
agement, and storage of physical documents.
72
Web-based solutions allow instant and remote on-
demand queries of real-time data (including end users such
as team medical staff) as well as integration with other data
feeds (eg, performance, load, sleep). Web-based solutions
should preferably be prototyped prior to being implemented
in a larger injury surveillance setting. Full integration of
surveillance reporting systems within clinical electronic
medical record-keeping systems has been used successfully
in a number of professional elite leagues.
22
While electronic
solutions can lead to high response rates among
athletes,
76,77,81
there are also reports of poor athlete
engagement,
7
and thus demonstrates the importance of
understanding uptake barriers. It is important to use sur-
veillance tools that minimize intrusion into the daily activ-
ities of the data reporters (athletes, medical teams,
coaches), for example, by limiting the number of questions
to responders so that only essential data are captured.
Another recommendation is to provide a clear incentive to
athletes and teams to participate in injury surveillance, for
example, by allowing continuous feedback within the data
collection system (eg, performance data, load monitoring
data) or sending regular reports back to the teams, ath-
letes, and other relevant stakeholders.
25
Data collection methods must be adapted to the specific
research question, the sport context, and the skill set of the
research team and should follow strict quality standards.
The quality of the surveillance system includes the quality
of the forms (baseline, health problems, and exposure) as
well as the quality of the data collection procedure, imple-
mentation, data cleansing, and analysis methods.
40
The
quality and usability of the forms and the data collection
procedures should be examined beforeimplementation. Reli-
ability and validity should be analyzed, and all translations
should follow the standards of intercultural adaptation.
54,61
The adherence to the data collection protocol as well as the
completeness and consistency of responses should be moni-
tored on a regular basis during implementation. Collabora-
tion between research groups to share resources and joint
data analytics can help advance the management of sport
injuries/illnesses.
103
Having data collection forms and
related material available in free-to-access formats makes
it easier for sports bodies to participate in surveillance activ-
ities,
40
and this consensus statement includes some sample
forms as mentioned in Appendix 2.
Research Ethics and Data Security
Research ethics govern the conduct of medical research and
aim to protect the dignity, rights, and welfare of human
participants. They detail principles such as informed con-
sent, data confidentiality, the use of research ethics com-
mitteesandrisks,burdens,andbenefits.Importantly,
informed consent is the process in which permission is
granted in full knowledge of the possible consequences
(risks and benefits), for example, for their data to be used
for research purposes. In some contexts, injury and illness
surveillance may be regarded as an integral part of data
audit and quality control processes and, as long as individ-
ual patient data are fully deidentified, may not require
informed consent. It is the duty of all researchers (and all
other users of the data) to consider, and adhere to where
appropriate, internationally recognized guidelines for
research ethics (such as the Declaration of Helsinki
115
and
the Declaration of Taipei
116
).
Data protection governs how data are collected, shared,
used, and conserved and aims to ensure that personal data
are safe from unforeseen, unintended, or malevolent use.
Particular attention must be directed to the security of data
stored on cloud-based systems and other electronic reposi-
tories. Researchers must adhere to the data protection
TABLE 11
Implementation Recommendations for
Injury/Illness Surveillance
The implementation of an injury and illness surveillance project
should include the following aspects:
Methods based on this consensus statement on definitions and
data collection procedures
Mandatory standards for compliance with defined time scales for
completion for report forms
Guidance document (a quality protocol) shared with all club/
national team medical staff (preseason/tournament)
Regular contact between study lead and responsible person at each
club/national team (face-to-face meeting preseason/prior to
tournament, conference call midseason/tournament)
All injuries cross-checked with club/team medical records and
followed up with medical staff for missing, incomplete,
inconsistent, or duplicate entries (regularly during season/
tournament)
Data cleaning and final review of dataset with responsible person
at each club/team before definitive analysis (end of season/
tournament)
Injury reports where individual club/team data are reported,
analyzed, and compared with the average of all participating
clubs/teams (midseason and end of season/tournament)
Medical meeting (end of season/tournament) where whole
surveillance results and translational value are presented to
club/team medical practitioners for discussion
18 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
regulations applicable to their context (such as the General
Data Protection Regulation in Europe).
30
REPORTING GUIDELINES: STROBE SPORTS
INJURY AND ILLNESS SURVEILLANCE
The statement on STROBE was published in 2007.
106
Since then, it has been adapted (extensions) to ensure the
statement is relevant to other areas of interest such as
infectious diseases
32
and most recently (2018) for pharma-
coepidemiology.
68
These extensions of STROBE have
stressed, like the original, that they only guide on how
to report findings from observational studies rather than
guiding study design. However, the two are related, and
researchers are strongly encouraged to consider the ele-
ments of the checklists when planning studies; this may
eventually improve study quality and ensure that
researchers are able to report what is needed at the end
of the study. STROBE has checklists for the 3 most com-
mon study types: cohort studies, case-control studies, and
cross-sectional studies. Here, we summarize our consen-
sus recommendations on the collection and reporting of
SIIS data as an extension to the initial STROBE checklist.
These apply regardless of study design. Note that many
other study designs common in sports and exercise med-
icine research, such as randomized controlled trials,
should be reported against other reporting standards (like
CONSORT, which will be refreshed in 2020).
19
As most
sports medicine studies rely on surveillance methods to
collect injury and illness outcome data, the recommenda-
tions in this consensus statement apply widely.
To guide researchers in the field of sport and exercise
medicine, we have adapted (extended) the STROBE check-
list so that it reflects recommendations from this current
IOC consensus statement on studies of injury and illness
surveillance in sports. This extension refers to 21 of the
original items. It includes only items specific to the report-
ing of injuries and illnesses in sport, as amendments to
reflect broader epidemiology methodology developments
should be more appropriately documented by the EQUA-
TOR Network, which oversees STROBE.
It is intended that this new checklist, the STROBE-SIIS,
will help researchers design an injury/illness surveillance
study and plan the study protocol as well as better report
their observations (Appendix 3). By consistently using the
STROBE-SIIS, authors ensure that other researchers will
be able to more easily replicate, compare, and synthesize
sport and exercise medicine research studies.
We also strongly recommend that researchers publish
their study protocols ahead of study completion, ideally
with an open access formal register, and also report on any
changes made to the initial protocol during study conduct,
together with their rationale for the change, once the study
has been completed. Details of where protocols and their
amendments are publicly available should be stated in
papers submitted for publication.
Feedback on this checklist is welcome, and we will both
monitor and evaluate the impact of its use over time. We
welcome researchers with relevant expertise to translate
this checklist to other languages for the benefit of the inter-
national sports medicine community.
AUTHORS
International Olympic Committee Injury and Illness Epide-
miology Consensus Group; Roald Bahr, MD, PhD (Oslo
Sports Trauma Research Center, Department of Sports
Medicine, Norwegian School of Sport Sciences, Oslo, Nor-
way; Aspetar Orthopaedic and Sports Medicine Hospital,
Doha, Qatar); Ben Clarsen, PT, PhD (Oslo Sports Trauma
Research Center, Department of Sports Medicine, Norwe-
gian School of Sport Sciences, Oslo, Norway; Department
of Health Promotion, Norwegian Institute of Public Health,
Bergen, Norway); Wayne Derman, MD, PhD (Institute of
Sport and Exercise Medicine, Division of Orthopaedic Sur-
gery, Faculty of Medicine and Health Sciences, Stellenbosch
University, Stellenbosch, South Africa); Jiri Dvorak, MD,
PhD (Spine Unit, Swiss Concussion Center and Swiss Golf
Medical Center, Schulthess Clinic, Zurich, Switzerland);
Carolyn A. Emery, PT, PhD (Sport Injury Prevention
Research Centre, Faculty of Kinesiology, University of Cal-
gary, Calgary, Alberta, Canada; Pediatrics and Community
Health Sciences, Cumming School of Medicine, University of
Calgary, Calgary, Alberta, Canada); Caroline F. Finch, PhD
(School of Medical and Health Sciences, Edith Cowan Uni-
versity, Joondalup, Western Australia, Australia); Martin
Ha
¨gglund, PT, PhD (Department of Medical and Health
Sciences, Division of Physiotherapy, Linko
¨ping University,
Linko
¨ping, Sweden); Astrid Junge, PhD (Medical School
Hamburg, Hamburg, Germany; Swiss Concussion Centre,
Schulthess Clinic, Zurich, Switzerland); Simon Kemp,
MBBS, MSc (Rugby Football Union, London, UK; Depart-
ment of Epidemiology and Population Health, London
School of Hygiene and Tropical Medicine, London, UK);
Karim M. Khan, MD, PhD (Department of Family Practice,
University of British Columbia, Vancouver, British Colum-
bia, Canada; British Journal of Sports Medicine, London,
UK); Stephen W. Marshall, PhD (Injury Prevention
Research Center and Department of Epidemiology at the
Gillings School of Global Public Health, University of North
Carolina at Chapel Hill, Chapel Hill, North Carolina, USA);
Willem Meeuwisse, MD, PhD (Sport Injury Prevention
Research Centre, University of Calgary, Calgary, Alberta,
Canada; National Hockey League, Calgary, Alberta,
Canada); Margo Mountjoy, MD, PhD (Department of Family
Medicine (Sport Medicine), McMaster University, Hamilton,
Ontario, Canada; FINA Bureau (Sport Medicine), Lausanne,
Switzerland); John W. Orchard, MD, PhD (School of Public
Health, University of Sydney, New South Wales, Sydney,
Australia); Babette Pluim, MD, PhD, MPH (Department of
Sports Medicine, Royal Netherlands Lawn Tennis Associa-
tion, Amstelveen, the Netherlands; Amsterdam Collabora-
tion on Health & Safety in Sports (ACHSS), AMC/VUmc
IOC Research Center of Excellence, Amsterdam, the Nether-
lands); Kenneth L. Quarrie, PhD (New Zealand Rugby, Wel-
lington, New Zealand; Sports Performance Research
Institute New Zealand, AUT University, Auckland, New
Zealand); Bruce Reider, MD (Department of Orthopaedic
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 19
Surgery and Rehabilitation, University of Chicago, Chicago,
Illinois, USA); Martin Schwellnus, MD, PhD (Sport, Exer-
cise Medicine and Lifestyle Research Institute (SEMLI),
University of Pretoria, Hatfield, South Africa); Torbjørn Soli-
gard, PhD (Medical and Scientific Department, Interna-
tional Olympic Committee, Lausanne, Switzerland; Sport
Injury Prevention Research Centre, Faculty of Kinesiology,
Calgary, Alberta, Canada); Keith A. Stokes, PhD (Depart-
ment for Health, University of Bath, Bath, UK; Rugby Foot-
ball Union, Twickenham, UK); Toomas Timpka, MD, PhD
(Athletics Research Center, Linko
¨ping University, Linko
¨p-
ing, Sweden; Centre for Healthcare Development, Region
O
¨stergo
¨tland, Linko
¨ping, Sweden); Evert Verhagen, PhD
(Amsterdam Collaboration on Health and Safety in Sports,
Department of Public and Occupational Health, Amsterdam
UMC, Amsterdam, the Netherlands); Abhinav Bindra,
DPhil (Athlete Commission, International Olympic Commit-
tee, Lausanne, Switzerland); Richard Budgett, MD (Medical
and Scientific Department, International Olympic Commit-
tee, Lausanne, Switzerland); Lars Engebretsen, MD, PhD
(Oslo Sports Trauma Research Center, Department of
Sports Medicine, Norwegian School of Sport Sciences, Oslo,
Norway; Medical and Scientific Department, International
Olympic Committee, Lausanne, Switzerland); Ug
˘ur Erd-
ener, MD (Medical and Scientific Department, International
Olympic Committee, Lausanne, Switzerland); and Karim
Chamari, PhD (Aspetar Sports Medicine and Orthopedic
Hospital, Doha, Qatar).
ACKNOWLEDGMENT
The authors thank Ali Abdalla Hassan and Mohamed Abdo
Badwi Ismael at Aspetar Orthopaedic and Sports Medicine
Hospital for their assistance with the online survey. They
acknowledge invaluable assistance from Paul Blazey and
David Moher in developing and revising the STROBE-SIIS
checklist.
REFERENCES
1. Ahmad CS, Dick RW, Snell E, et al. Major and Minor League Baseball
hamstring injuries: epidemiologic findings from the Major League
Baseball Injury Surveillance System. Am J Sports Med. 2014;42(6):
1464-1470.
2. American Spinal Injury Association. International Standards for Neu-
rological Classification of Spinal Injury. Chicago: American Spinal
Injury Association; 2019.
3. Bahr R. No injuries, but plenty of pain? On the methodology for
recording overuse symptoms in sports. Br J Sports Med. 2009;
43(13):966-972.
4. 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.
5. Bahr R, Krosshaug T. Understanding injury mechanisms: a key com-
ponent of preventing injuries in sport. Br J Sports Med. 2005;39(6):
324-329.
6. Bjorneboe J, Florenes TW, Bahr R, et al. Injury surveillance in male
professional football: is medical staff reporting complete and accu-
rate? Scand J Med Sci Sports. 2011;21(5):713-720.
7. Bromley S, Drew M, Talpey S, et al. Collecting health and exposure
data in Australian Olympic combat sports: feasibility study utilizing an
electronic system. JMIR Hum Factors. 2018;5(4):e27.
8. Brooks JH, Fuller CW. The influence of methodological issues on the
results and conclusions from epidemiological studies of sports inju-
ries: illustrative examples. Sports Med. 2006;36(6):459-472.
9. Brooks JH, Fuller CW, Kemp SP, et al. An assessment of training
volume in professional rugby union and its impact on the incidence,
severity, and nature of match and training injuries. J Sports Sci. 2008;
26(8):863-873.
10. Brooks JH, Fuller CW, Kemp SP, et al. Epidemiology of injuries in
English professional rugby union, part 1: match injuries. Br J Sports
Med. 2005;39(10):757-766.
11. Brooks JH, Fuller CW, Kemp SP, et al. Epidemiology of injuries in
English professional rugby union, part 2: training injuries. Br J Sports
Med. 2005;39(10):767-775.
12. Brooks JH, Fuller CW, Kemp SP, et al. Incidence, risk, and prevention
of hamstring muscle injuries in professional rugby union. Am J Sports
Med. 2006;34(8):1297-1306.
13. Brophy RH, Johnston JT, Schub D, et al. Video analysis of anterior
cruciate ligament tears in professional American football athletes:
response. Am J Sports Med. 2018;46(14):NP73-NP74.
14. 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.
15. Clarsen B, Bahr R, Myklebust G, et al. Improved reporting of overuse
injuries and health problems in sport: an update of the Oslo Sport
Trauma Research Center questionnaires. Br J Sports Med. In press.
16. Clarsen B, Myklebust G, Bahr R. Development and validation of a new
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. 2013;47(8):495-502.
17. Clarsen B, Ronsen O, Myklebust G, et al. 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(9):754-760.
18. Coggon D, Barker DJP, Rose G. Epidemiology for the Uninitiated. 5th
ed. London: BMJ Books; 2003.
19. CONSORT Group. The CONSORT statement. 2010. http://www.
consort-statement.org/. Accessed October 9, 2019.
20. Cooper DE. Video analysis of anterior cruciate ligament tears in pro-
fessional American football athletes: letter to the editor. Am J Sports
Med. 2018;46(14):NP73.
21. Drawer S, Fuller CW. Evaluating the level of injury in English profes-
sional football using a risk based assessment process. Br J Sports
Med. 2002;36(6):446-451.
22. Dreyer NA, Mack CD, Anderson RB, et al. Lessons on data collection
and curation from the NFL Injury Surveillance Program. Sports Health.
2019;11(5):440-445.
23. Echemendia RJ, Meeuwisse W, McCrory P, et al. The Sport Concus-
sion Assessment Tool 5th edition (SCAT5): background and rationale.
Br J Sports Med. 2017;51(11):848-850.
24. Edouard P, Branco P, Alonso JM, et al. Methodological quality of the
injury surveillance system used in international athletics champion-
ships. J Sci Med Sport. 2016;19(12):984-989.
25. Ekegren CL, Donaldson A, Gabbe BJ, et al. Implementing injury sur-
veillance systems alongside injury prevention programs: evaluation of
an online surveillance system in a community setting. Inj Epidemiol.
2014;1(1):19.
26. Ekegren CL, Gabbe BJ, Finch CF. Sports injury surveillance systems:
a review of methods and data quality. Sports Med. 2016;46(1):49-65.
27. Ekstrand J, Healy JC, Walden M, et al. Hamstring muscle injuries in
professional football: the correlation of MRI findings with return to
play. Br J Sports Med. 2012;46(2):112-117.
28. Endres BD, Kerr ZY, Stearns RL, et al. Epidemiology of sudden death
in organized youth sports in the United States, 2007-2015. JAthl
Train. 2019;54(4):349-355.
29. England Professional Rugby Injury Surveillance Project Steering
Group. The England Professional Rugby Injury Surveillance Project.
2018. https://www.englandrugby.com/participation/playing/player-
welfare-rugby-safe/rugbysafe-research. Accessed October 9, 2019.
20 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
30. European Commission. EU data protection rules. 2018. https://ec.
europa.eu/commission/priorities/justice-and-fundamental-rights/
data-protection/2018-reform-eu-data-protection-rules/eu-data-
protection-rules_en. Accessed November 11, 2019.
31. Fagher K, Jacobsson J, Dahlstrom O, et al. An eHealth application of
self-reported sports-related injuries and illnesses in Paralympic sport:
pilot feasibility and usability study. JMIR Hum Factors. 2017;4(4):e30.
32. Field N, Cohen T, Struelens MJ, et al. Strengthening the Reporting of
Molecular Epidemiologyfor InfectiousDiseases (STROME-ID):an exten-
sion of the STROBE statement. Lancet Infect Dis. 2014;14(4):341-352.
33. Finch CF. An overview of some definitional issues for sports injury
surveillance. Sports Med. 1997;24(3):157-163.
34. Finch CF, Cook J. Categorising sportsinjuriesinepidemiological
studies: the subsequent injury categorisation (SIC) model to address
multiple, recurrent and exacerbation of injuries. Br J Sports Med.
2014;48(17):1276-1280.
35. Finch CF, Fortington LV. So you want to understand subsequent inju-
ries better? Start by understanding the minimum data collection and
reporting requirements. Br J Sports Med. 2018;52(17):1077-1078.
36. Finch CF, Goode N, Shaw L, et al. End-user experiences with two
incident and injury reporting systems designed for led outdoor activ-
ities: challenges for implementation of future data systems. Inj Epide-
miol. 2019;6:39.
37. Finch CF, Marshall SW. Let us stop throwing out the baby with the
bathwater: towards better analysis of longitudinal injury data. Br J
Sports Med. 2016;50(12):712-715.
38. Finch CF, Mitchell DJ. A comparison of two injury surveillance sys-
tems within sports medicine clinics. JSciMedSport. 2002;5(4):
321-335.
39. Finch CF, Orchard JW, Twomey DM, et al. Coding OSICS sports
injury diagnoses in epidemiological studies: does the background of
the coder matter? Br J Sports Med. 2014;48(7):552-556.
40. Finch CF, Staines C. Guidance for sports injury surveillance: the 20-
year influence of the Australian Sports Injury Data Dictionary. Inj Prev.
2018;24(5):372-380.
41. Finch CF, Valuri G, Ozanne-Smith J. Injury surveillance during medical
coverage of sporting events: development and testing of a standar-
dised data collection form. J Sci Med Sport. 1999;2(1):42-56.
42. Florenes TW, Nordsletten L, Heir S, et al. Recording injuries among
World Cup skiers and snowboarders: a methodological study. Scand
J Med Sci Sports. 2011;21(2):196-205.
43. Fortington LV, Kucera KL, Finch CF. A call to capture fatalities in
consensus statements for sports injury/illness surveillance. Br J
Sports Med. 2017;51(14):1052-1053.
44. Fortington LV, van der Worp H, van den Akker-Scheek I, et al. Report-
ing multiple individual injuries in studies of team ball sports: a system-
atic review of current practice. Sports Med. 2017;47(6):1103-1122.
45. Frost WH. Some conceptions of epidemics in general by Wade
Hampton Frost. Am J Epidemiol. 1976;103(2):141-151.
46. Fuller C, Drawer S. The application of risk management in sport.
Sports Med. 2004;34(6):349-356.
47. Fuller CW. Injury risk (burden), risk matrices and risk contours in team
sports: a review of principles, practices and problems. Sports Med.
2018;48(7):1597-1606.
48. Fuller CW, Brooks JH, Cancea RJ, et al. Contact events in rugby union
and their propensity to cause injury. Br J Sports Med. 2007;41:
862-867.
49. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury
definitions and data collection procedures in studies of football (soc-
cer) injuries. Br J Sports Med. 2006;40(3):193-201.
50. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury
definitions and data collection procedures in studies of football (soc-
cer) injuries. Clin J Sport Med. 2006;16(2):97-106.
51. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury
definitions and data collection procedures in studies of football (soc-
cer) injuries. Scand J Med Sci Sports. 2006;16(2):83-92.
52. Fuller CW, Molloy MG, Bagate C, et al. Consensus statement on injury
definitions and data collection procedures for studies of injuries in
rugby union. Br J Sports Med. 2007;41(5):328-331.
53. Gabbe BJ, Finch CF, Bennell KL, et al. How valid is a self reported 12
month sports injury history? Br J Sports Med. 2003;37(6):545-547.
54. Gamage PJ, Fortington LV, Finch CF. Adaptation, translation and
reliability of the Australian “Juniors Enjoying Cricket Safely” injury risk
perception questionnaire for Sri Lanka. BMJ Open Sport Exerc Med.
2018;4(1):e000289.
55. Gardner AJ, Iverson GL, Williams WH, et al. A systematic review and
meta-analysis of concussion in rugby union. Sports Med. 2014;44(12):
1717-1731.
56. Gordon JE. The epidemiology of accidents. Am J Public Health
Nations Health. 1949;39(4):504-515.
57. Griffin LY, Agel J, Albohm MJ, et al. Noncontact anterior cruciate
ligament injuries: risk factors and prevention strategies. J Am Acad
Orthop Surg. 2000;8(3):141-150.
58. Haddon W Jr. Energy damage and the ten countermeasure strate-
gies. Hum Factors. 1973;15(4):355-366.
59. Hagglund M, Walden 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.
60. Hamilton GM, Meeuwisse WH, Emery CA, et al. Subsequent injury
definition, classification, and consequence. Clin J Sport Med. 2011;
21(6):508-514.
61. Harkness J, Pennell BE, Schoua-Glusberg A. Survey questionnaire
translation and assessment. In: Presser S, Rothgeb JM, Couper
MP, et al, eds. Methods for Testing and Evaluating Survey Question-
naires. Hoboken, New Jersey: John Wiley and Sons; 2004:453-473.
62. Holder Y, Peden M, Krug E, et al. Injury Surveillance Guidelines.
Geneva: World Health Organization; 2001.
63. Institute of Social and Preventive Medicine, University of Bern.
STROBE statement: Strengthening the Reporting of Observational
Studies in Epidemiology. 2009. https://www.strobe-statement.org/
index.php?id¼available-checklists. Accessed November 11, 2019.
64. Junge A, Engebretsen L, Alonso JM, et al. Injury surveillance in multi-
sport events: the International Olympic Committee approach. Br J
Sports Med. 2008;42(6):413-421.
65. King DA, Gabbett TJ, Gissane C, et al. Epidemiological studies of
injuries in rugby league: suggestions for definitions, data collection
and reporting methods. J Sci Med Sport. 2009;12(1):12-19.
66. Kucera KL, Fortington LV, Wolff CS, et al. Estimating the international
burden of sport-related death: a review of data sources. Inj Prev.
2019;25(2):83-89.
67. Kucera KL, Marshall SW, Bell DR, et al. Validity of soccer injury data
from the National Collegiate Athletic Association’s Injury Surveillance
System. J Athl Train. 2011;46(5):489-499.
68. Langan SM, Schmidt SA, Wing K, et al. The reporting of studies con-
ducted using observational routinely collected health data statement
for pharmacoepidemiology (RECORD-PE). BMJ. 2018;363:K3532.
69. Langley J, Brenner R. What is an injury? Inj Prev. 2004;10(2):69-71.
70. Lee TA, Pickard AS. Exposuredefinition andmeasurement.In: Velentgas
P, Dreyer NA, Nourjah P, et al, eds. Developing a Protocol for Observa-
tional Comparative Effectiveness Research: A User’s Guide. Rockville,
Maryland: Agency for Healthcare Research and Quality; 2013:45-58.
71. Leppanen M, Pasanen K, ClarsenB, et al. Overuse injuries areprevalent
in children’scompetitive football: a prospective studyusing the OSTRC
overuse injury questionnaire. Br J Sports Med. 2019;53(3):165-171.
72. Malik I, Burnett S, Webster-Smith M, et al. Benefits and challenges of
electronic data capture (EDC) systems versus paper case report
forms. Trials. 2015;16:37.
73. Meeuwisse WH. What is the mechanism of no injury (MONI)? Clin J
Sport Med. 2009;19(1):1-2.
74. Meeuwisse WH, Tyreman H, Hagel B, et al. A dynamic model of
etiology in sport injury: the recursive nature of risk and causation. Clin
J Sport Med. 2007;17(3):215-219.
75. Mohtadi N. Development and validation of the quality of life outcome
measure (questionnaire) for chronic anterior cruciate ligament defi-
ciency. Am J Sports Med. 1998;26(3):350-359.
76. Moller M, Wedderkopp N, Myklebust G, et al. The SMS, Phone, and
Medical Examination sports injury surveillance system is a feasible
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 21
and valid approach to measuring handball exposure, injury occur-
rence, and consequences in elite youth sport. Scand J Med Sci
Sports. 2018;28(4):1424-1434.
77. Moller M, Wedderkopp N, Myklebust G, et al. Validity of the SMS,
Phone, and Medical Staff Examination sports injury surveillance sys-
tem for time-loss and medical attention injuries in sports. Scand J
Med Sci Sports. 2018;28(1):252-259.
78. Mountjoy M, Junge A, Alonso JM, et al. Consensus statement on the
methodology of injury and illness surveillance in FINA (aquatic sports).
Br J Sports Med. 2016;50(10):590-596.
79. Murray CJ. Quantifying the burden of disease: the technical basis for
disability-adjusted life years. Bull World Health Organ. 1994;72(3):
429-445.
80. Neil ER, Winkelmann ZK, Edler JR. Defining the term “overuse”: an
evidence-based review of sports epidemiology literature. J Athl Train.
2018;53(3):279-281.
81. Nilstad A, Bahr R, Andersen TE. Text messaging as a new method for
injury registration in sports: a methodological study in elite female
football. Scand J Med Sci Sports. 2014;24(1):243-249.
82. Olsen OE, Myklebust G, Engebretsen L, et al. Injury mechanisms for
anterior cruciate ligament injuries in team handball: a systematic
video analysis. Am J Sports Med. 2004;32(4):1002-1012.
83. Orchard J, Newman D, Stretch R, et al. Methods for injury surveillance
in international cricket. J Sci Med Sport. 2005;8(1):1-14.
84. Orchard JW, Ranson C, Olivier B, et al. International consensus state-
ment on injury surveillance in cricket: a 2016 update. Br J Sports Med.
2016;50(20):1245-1251.
85. Orchard O, Meeuwisse W, Derman W, et al. Refinement and presen-
tation of the Calgary Sport Medicine Diagnostic Coding System
(SMDSC) and the Orchard Sport Injury & Illness Classification System
(OSIICS). Br J Sports Med. In press.
86. Pluim BM, Fuller CW, Batt ME, et al. Consensus statement on epide-
miological studies of medical conditions in tennis, April 2009. Br J
Sports Med. 2009;43(12):893-897.
87. Quarrie KL, Hopkins WG. Tackle injuries in professional rugby union.
Am J Sports Med. 2008;36(9):1705-1716.
88. Roberts SP, Trewartha G, England M, et al. Epidemiology of time-loss
injuries in English community-level rugby union. BMJ Open. 2013;
3(11):e003998.
89. Roos EM, Lohmander LS. The Knee injury and Osteoarthritis Out-
come Score (KOOS): from joint injury to osteoarthritis. Health Qual
Life Outcomes. 2003;1:64.
90. Roos KG, Marshall SW. Definition and usage of the term
“overuse injury” in the US high school and collegiate sport epi-
demiology literature: a systematic review. Sports Med. 2014;
44(3):405-421.
91. Schwellnus M, Derman W, Page T, et al. Illness during the 2010 Super
14 Rugby Union tournament: a prospective study involving 22 676
player days. Br J Sports Med. 2012;46(7):499-504.
92. Schwellnus M, Kipps C, Roberts WO, et al. Medical encounters
(including injury and illness) at mass community-based endurance
sports events: an international consensus statement on definitions
and methods of data recording and reporting. Br J Sports Med.
2019;53(17):1048-1055.
93. Shrier I, Steele RJ. Classification systems for reinjuries: a continuing
challenge. Br J Sports Med. 2014;48(18):1338-1339.
94. Soligard T, Steffen K, Palmer D, et al. Sports injury and illness inci-
dence in the Rio de Janeiro 2016 Olympic Summer Games: a pro-
spective study of 11274 athletes from 207 countries. Br J Sports Med.
2017;51(17):1265-1271.
95. Soligard T, Steffen K, Palmer-Green D, et al. Sports injuries and ill-
nesses in the Sochi 2014 Olympic Winter Games. Br J Sports Med.
2015;49(7):441-447.
96. Soomro N, Chhaya M, Soomro M, et al. Design, development, and
evaluation of an injury surveillance app for cricket: protocol and qual-
itative study. JMIR mHealth uHealth. 2019;7(1):e10978.
97. Tabben M, Whiteley R, Wik EH, et al. Methods may matter in injury
surveillance: “how” may be more important than “what, when or
why”. Biol Sport. 2020;37(1):3-5.
98. Timpka T, Alonso JM, Jacobsson J, et al. Injury and illness defini-
tions and data collection procedures for use in epidemiological stud-
ies in athletics (track and field): consensus statement. Br J Sports
Med. 2014;48(7):483-490.
99. Timpka T, Jacobsson J, Bickenbach J, et al. What is a sports injury?
Sports Med. 2014;44(4):423-428.
100. Toohey LA, Drew MK, Fortington LV, et al. Comparison of subse-
quent injury categorisation (SIC) models and their application in a
sporting population. Inj Epidemiol. 2019;6:9.
101. Toohey LA, Drew MK, Fortington LV, et al. An updated subsequent
injury categorisation model (SIC-2.0): data-driven categorisation of
subsequent injuries in sport. Sports Med. 2018;48(9):2199-2210.
102. Turner M, Fuller CW, Egan D, et al. European consensus on epide-
miological studies of injuries in the thoroughbred horse racing indus-
try. Br J Sports Med. 2012;46(10):704-708.
103. van Dyk N, van der Made AD, Timmins RG, et al. There is strength in
numbers for muscle injuries: it is time to establish an international
collaborative registry. Br J Sports Med. 2018;52(19):1228-1229.
104. van Mechelen W. The severity of sports injuries. Sports Med. 1997;
24(3):176-180.
105. van Mechelen W. Sports injury surveillance systems: “one size fits
all”? Sports Med. 1997;24(3):164-168.
106. von Elm E, Altman DG, Egger M, et al. Strengthening the Reporting
of Observational Studies in Epidemiology (STROBE) statement:
guidelines for reporting observational studies. BMJ. 2007;
335(7624):806-808.
107. Waller JA. Injury Control: A Guide to the Causes and Prevention of
Trauma. Lexington, Massachusetts: Lexington Books; 1985.
108. Weir A, Brukner P, Delahunt E, et al. Doha agreement meeting on
terminology and definitions in groin pain in athletes. Br J Sports Med.
2015;49(12):768-774.
109. Wik EH, Materne O, Chamari K, et al. Involving research-invested
clinicians in data collection affects injury incidence in youth football.
Scand J Med Sci Sports. 2019;29(7):1031-1039.
110. Williams S, Trewartha G, Kemp SP, et al. Time loss injuries compro-
mise team success in elite rugby union: a 7-year prospective study.
Br J Sports Med. 2016;50(11):651-656.
111. World Health Organization. International Classification of Diseases,
11th Revision. 2018. https://www.who.int/classifications/icd/en/.
Accessed November 11, 2019.
112. World Health Organization. International Classification of External
Causes of Injury (ICECI). 2003. https://www.who.int/classifications/
icd/adaptations/iceci/en/. Accessed November 11, 2019.
113. World Health Organization. International Classification of Function-
ing, Disability and Health. 2018. https://www.who.int/classifications/
icf/en/. Accessed December 5, 2019.
114. World Health Organization. Preamble to the Constitution of the
World Health Organization as Adopted by the International Health
Conference. New York: World Health Organization; 1946.
115. World Medical Association. WMA Declaration of Helsinki: ethical
principles for medical research involving human subjects. 2013.
https://www.wma.net/policies-post/wma-declaration-of-helsinki-
ethical-principles-for-medical-research-involving-human-subjects/.
Accessed October 9, 2019.
116. World Medical Association. WMA Declaration of Taipei on ethical
considerations regarding health databases and biobanks. 2016.
https://www.wma.net/policies-post/wma-declaration-of-taipei-on-
ethical-considerations-regarding-health-databases-and-biobanks/.
Accessed October 9, 2019.
117. Yeomans C, Kenny IC, Cahalan R, et al. The design, develop-
ment, implementation and evaluation of IRISweb: a rugby-
specific web-based injury surveillance system. Phys Ther Sport.
2019;35:79-88.
22 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
APPENDIX 1
Case Study: Tackle Injuries to
Ball Carriers in Rugby
Data Set
A study was conducted in which video records of every
tackle that occurred in 434 professional rugby matches
were coded on a range of dimensions, including the location
on the body at which the tackler(s) contacted the ball car-
rier (“tackle height”).
87
The information in the table has
been restricted to that from 43,366 tackles in which a single
tackler tackled a ball carrier (ie, the 100 tackle events per
match that met this criteria). For the purposes of the exam-
ple below, an injury is defined as “any injury sustained by a
ball carrier during a rugby tackle that required them to be
removed from the field of play for the remainder of the
match.”
Different Denominators: Different Perspectives on Risk
Rates of injury have been presented in Table A1 as “per
10,000 tackles” and “per 10,000 player-hours.” If data were
reported using only the time-based denominator, as has
been the case in most studies of sports injury epidemiology,
the conclusion drawn would be that “high” and “middle”
tackles are those that carry the greatest risk to ball car-
riers. When the relative frequency of the tackles is consid-
ered, and the rates are presented on a “per 10,000 tackles”
basis, head/neck tackles place ball carriers at the greatest
risk of injuries when they occur.
The different perspectives provided by per-event and
per-time denominators can be helpful in identifying injury
prevention priorities. If the overall risk of injuries was con-
sidered unacceptably high by those responsible for manag-
ing the risks in the sport, then reducing the numbers of the
most common tackles in the game would have the greatest
effect; together, high and middle tackles account for over
two-thirds of all tackle injuries requiring ball carriers to be
removed from the pitch. Reducing the numbers of such
tackles, or the characteristics of them, would probably
require major changes to the sport of rugby. If, however,
the overall degree of risk were considered acceptable, then
focusing on decreasing the number of head and neck tackles
would have a modest effect on overall injury rates but
reduce the occurrence of a particularly risky element of the
sport (note: head/neck tackles are not permitted within the
laws of rugby, but sometimes occur).
The types of exposure measures that can form the basis
of risk statistics are presented in Table A2, along with a
range of risk measures that have been reported in studies of
team sports injury epidemiology. The examples are taken
from the same study discussed above.
TABLE A1
Injury Rates to Ball Carriers in Rugby Tackles
a
Injuries Requiring Player to Be
Removed From Match
Tackle
Height
Tackles
per
Match
Per
10,000
Tackles
Per
10,000
Player-Hours
Percentage
of Injuries
per 10,000
Player-Hours
Head/neck 4 ±2 43 (23-79) 4 (2-8) 13 (7-23)
High 37 ±10 12 (8-17) 11 (8-16) 36 (26-47)
Middle 44 ±9 9 (6-13) 10 (7-15) 32 (23-43)
Low 15 ±5 16 (9-26) 6 (3-10) 19 (12-29)
a
Rates are expressed via event- and time-based denomina-
tors. Data are shown as mean ±standard deviation or mean
(range).
TABLE A2
A Range of Exposure and Risk Measures Derived From Injury Surveillance Data
a
Statistic Value Calculation Explanation Comment
Injury statistics
No. of injuries (carrier
injury replacements
in 434 matches)
53 Nil Count of the number of
tackler injuries requiring
the injured player to be
replaced observed in 434
matches
The “numerator” used for calculating the
rate of tackler replacement injuries per
unit of time or per tackle. Absolute
numbers and costs of injuries are of
interest to risk managers, especially
when provided in parallel with rates.
No. of injured players
(some were injured
more than once)
48 Nil This is the numerator for calculating
injury risk.
Exposure measures
Player-hours in 434
matches
17,360 30 579 30 players (15 from each
team) multiplied by 579
(hours of play in 434
matches of 80 minutes’
duration)
This number provides a “time-window”
denominator. Usually, it is assumed
that time lost for yellow and red cards,
or time gained for “extra time,” is
negligible and is ignored.
(continued)
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 23
Table A2 (continued)
Statistic Value Calculation Explanation Comment
No. of single-tackler
tackle events in 434
matches
43,366 Nil All tackles in 434 matches
were coded, regardless of
whether they resulted in
injury
This number forms an “event-based”
denominator.
No. of players who
appeared in the 434
matches
1403 Nil This is a count of the size of the cohort
across the entire study period. It is used
as the denominator for calculating
injury risk.
No. of full player
matches
13,020 30 434 30 players (15 from each
team) multiplied by 434
matches
This number provides a “per-match”
denominator.
No. of athlete-
exposures (athlete-
participations)
17,685 Nil Count of the number of
players who took the field
over 434 matches (players
can be substituted for
tactical purposes or
replaced due to injury)
The similarity to the number of player-
hours is coincidental. There are 40
hours of player time per match, and the
average number of athlete-exposures
per match over this series of matches
was 40.8.
Risk measures
Period prevalence
(percentage of cohort
injured)
3%(48/1403) 100 Percentage of people who
appeared in matches who
were replaced
Often reported as the “risk per season” or
“risk per year.” It cannot be easily used
to compare between activities if the
duration of surveillance varies from
activity to activity. The longer the
surveillance period, the higher the risk
will appear to be for closed cohorts.
Injuries per 1000
player-hours
3.1 (53/17,360) 1000 Number of injuries is divided
by the number of hours of
player exposure and
multiplied by a scaling
factor (eg, 1000, 10,000) to
provide a rate that is
convenient to work with
(eg, numbers in the range
of 1 to 1000 rather than
numbers <0or>1000)
The most commonly reported metric of
injury rates in studies of rugby injury
epidemiology has been the rate of
injuries per 1000 player-hours. This
convention is endorsed in the consensus
statement by Fuller et al.
52
It is
relatively simple to estimate based on
the number of matches played.
Comparisons of incidence rates between
activities or within activities over time
based on this denominator require the
assumption that the number and
characteristics of energy transfers to
which participants are exposed remain
relatively constant per unit of exposure
time.
Injuries per 1000
matches
122 (53/434) 1000 Rate of tackler replacements
per rugby union match
multiplied by 1000; rate
per match multiplied by a
factor that provides a
convenient interpretation
(0.12 carrier replacement
injuries per match, 12.2
per 100 matches, 122 per
1000 matches, etc)
Ignores the number of players and match
duration and provides an estimate of the
number of injuries that an observer
would expect to see if they watched 1000
matches. Not useful for comparing
incidence rates between activities of
differing durations or numbers of
participants.
(continued)
24 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
Table A2 (continued)
Statistic Value Calculation Explanation Comment
Injuries per 1000 hours
of play (ignoring
number of players)
92 (53/579) 1000 Rate per hour is multiplied
by a factor that provides a
convenient interpretation
(0.9 carrier replacement
injuries per hour, 9.2 per
100 hours, 92 per 1000
hours, etc)
Ignores number of players and provides an
estimate of the number of injuries an
observer would expect to see if they
watched 1000 hours of play. Not useful
for comparing between activities with
differing numbers of participants
because the sizes of the populations at
risk differ.
Injuries per 1000
athlete-exposures
(athlete-
participations)
3.0 (53/17,685) 1000 Carrier injury replacements
per 1000 athlete-exposures
Injuries per 1000 athlete-exposures are
commonly reported in injury
surveillance in the United States.
Problematic for comparing between
activities that have different numbers of
typical athlete-exposures per match or
when the average exposure time per
player changes over time.
Injuries per 1000 full
player matches
4.1 (53/13,020) 1000 Not commonly used. It ignores the
duration of the match and, as such, has
similar drawbacks to reporting injuries
per athlete-exposure because the time
window of exposure varies between
activities of different durations.
Injuries per 1000 “ball
in play” player-hours
6.8 (53/7740) 1000 Not commonly used but technically a more
accurate measure of exposure than
injuries per 1000 player-hours because
players are only exposed to tackles when
the ball is “in play.”
Injuries per 1000 “ball
in play and ball
carrier’s team in
possession” player-
hours
13.5 (53/3819) 1000 Again, not commonly used but an even
closer approximation of the actual time
exposed to the risk of ball carrier
injuries. Players are only tackled when
the ball is in play and their team is in
possession.
Injuries per 1000 tackle
events
1.2 (53/43,366) 1000 Ball carrier injury
replacements per 1000
times tackled
Provides an accurate assessment of per-
event injury rates but in isolation
ignores the frequency of occurrence of
the event of interest. Injury rates per
event have sometimes been termed
“injury propensity.”
48
Injuries per 1000
players per year
24 ([23 þ17 þ13]
1000) / (983 þ
589 þ627)
Sometimes provided as a gross estimate of
the injury risk when participant
numbers and injury numbers are
available but no measure of exposure for
players is available (eg, data derived
from insurance claims combined with
registers of participants). Of limited use
when exposure varies by subgroup or
across sports.
a
Examples from a study of rugby tackle injuries.
87
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 25
APPENDIX 2A
Daily Medical Report on Injuries and Illnesses
Country: Date of report:
Form completed by: Name: Contact details:
Please report: (1) All sport injuries and (2) all illnesses of your athletes newly incurred, recurrent or an exacerbation of an
underlying stable injury/illness during the <name of the championship> regardless of the consequences with respect to
absence from competition or training. The information provided will be treated strictly confidential.
1. Injury –Example Definitions and codes (see reverse)
age
22
gender
male / female
sport and event
decathlon
date of injury
21. July
competition / training
sprint competition
code
2
onset code
1
new code
1
injury mechanism
slipped and fell
code
5
injured body region
ankle
code
17
injury type
sprain
code
10
time-loss
no / yes
duration
28 days
age gender
male / female
sport and event date of injury competition / training code onset code new code
injury mechanism code injured body region code injury type code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of injury competition / training code onset code new code
injury mechanism code injured body region code injury type code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of injury competition / training code onset code new code
injury mechanism code injured body region code injury type code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of injury competition / training code onset code new code
injury mechanism code injured body region code injury type code time-loss
no / yes
duration
days
2. Illness –Example Definitions and codes (see reverse)
age
27
gender
male / female
sport and event
athletics, pole vault
date of onset
24th July
organ system / region
respiratory system
code
13
aetiology
Environmental - not exercise related
code
3
new, recurrent or exacerbation code
1
time-loss
no / yes
duration
2days
age gender
male / female
sport and event date of onset organ s ystem / region code
aetiology code new, recurrent or exacerbation code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of onset organ s ystem / region code
aetiology code new , recurrent or exacerbation code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of onset organ s ystem / region code
aetiology code new , recurrent or exacerbation code time-loss
no / yes
duration
days
age gender
male / female
sport and event date of onset organ s ystem / region code
aetiology code new , recurrent or exacerbation code time-loss
no / yes
duration
days
If space is not sufficient to report all injuries or illnesses, please use additional forms.
no new injury or illness in any athlete of our team today
(continued)
26 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
Definitions and codes
For injuries (defined as tissue damage or other derangement of normal physical function due to participation in
sports, resulting from rapid or repetitive transfer of kinetic energy)
Competition or training
1competition, please specify event 2training 3peri-competition activities
(e.g. warm-up, cool-down)
Mode of onset
1sudden after acute trauma 2sudden but no acute trauma 3gradual 4mixed
Injury mechanism
1no identifiable single event
(repetitive transfer of energy, overuse)
2acute non-contact trauma
3direct contact with another athlete
4following contact with another
athlete (e.g. fall after a push)
5direct contact with an object (e.g. ball,
wall, ground, i.e. slipped and fell)
6following contact with an object
Injured body region
1head / face
2neck / cervical spine
3chest (incl. chest organs)
4thoracic spine / upper back
5lumbar-sacral spine / buttock
6abdomen (incl. abdominal organs)
7shoulder
8upper arm
9elbow
10 forearm
11 wrist
12 hand
13 hip / groin
14 thigh
15 knee
16 lower leg / Achilles tendon
17 ankle
18 foot
Injury type
1concussion / brain injury
2spinal cord injury
3peripheral nerve injury
4bone fracture
5bone stress injury
6bone contusion
7avascular necrosis
8physis injury
9cartilage injury
10 joint sprain / ligament tear
11 chronic instability
12 tendon rupture
13 tendinopathy
14 muscle strain / rupture / tear
15 muscle contusion
16 muscle compartment syndrome
17 laceration
18 abrasion
19 contusion / bruise (superficial)
20 arthritis
21 bursitis
22 synovitis
23 vascular damage
24 stump injury
25 internal organ trauma
26 unknown, or not specified
For illnesses (defined as a complaint or disorder not related to injury)
Organ system
1 cardiovascular
2 dermatological
3 dental
4 endocrinology
5 gastrointestinal
6 genitourinary
7 hematologic
8 musculoskeletal
9 neurological
10 ophthalmological
11 otological
12 psychiatric/psychological
13 respiratory system
14 thermoregulatory system
15 unknown, or not specified
Aetiology
1 allergic
2 environmental - exercise-related
3 environmental - non-exercise
4 immunological/inflammatory
5 infection
6 neoplasm
7 metabolic/nutritional
8 thrombotic/haemorrhagic
9 degenerative or chronic condition
10 developmental anomaly
11 drug-related/poisoning
12 unknown, or not specified
For injuries and illnesses
Sport and event
Please report the sport (e.g. athletics) AND specify the event (e.g. pole vault) if applicable.
New, recurrent or exacerbation
1 newly incurred during the championships 3 exacerbation of a stable (not recovered) condition
2 recurrent after full recovery and return-to-sport 4 unknown, or not specified
Time-loss in sport due to injury or illness
no athlete continues to train or compete, even if not at usual level (duration, intensity, performance)
yes athlete did not finish the training or competition when the injury occurred OR could not participate in sport later
Duration of impaired participation/ limited performance in sport due to injury or illness (in days)
Please provide an estimate of the number of days that the athlete will not be able to undertake his/her normal training or
will not be able to compete as usual, counting the day after the onset of the injury/illness as day 1.
If an athlete is not expected to return to sport after the injury or illness, please state the reason: F=fatality, P=permanent
disability, OR=reasons.
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 27
APPENDIX 2B
Medical Report of Injury or Illness Date of report: __________
Team: ____________ Athlete identification: ___________ Date of onset: __________
For injury
Competition or training
competition training peri-competition activities
(e.g. warm-up, cool-down)
Mode of onset
sudden after acute trauma sudden but no acute trauma gradual mixed
Injury mechanism (each category might have subcategories based on the purpose of the surveillance)
no identifiable single event
non-contact trauma
direct contact with another athlete
following contact with another athlete
direct contact with an object
following contact with an object
Injured body region (each category might have subcategories based on the purpose of the surveillance)
head
neck / cervical spine
chest (incl. chest organs)
thoracic spine / upper back
lumbar-sacral spine / buttock
abdomen (incl. abdominal organs)
shoulder
upper arm
elbow
forearm
wrist
hand
hip / groin
thigh
knee
lower leg / Achilles tendon
ankle
foot
Injury type
concussion / brain injury
spinal cord injury
peripheral nerve injury
bone fracture
bone stress injury
bone contusion
avascular necrosis
physis injury
cartilage injury
joint sprain / ligament tear
chronic instability
tendon rupture
tendinopathy
muscle strain / rupture / tear
muscle contusion
muscle compartment syndrome
laceration
abrasion
contusion / bruise (superficial)
arthritis
bursitis
synovitis
vascular damage
stump injury
internal organ trauma
unknown, or not specified
For illness
Organ system
cardiovascular
dermatological
dental
endocrinology
gastrointestinal
genitourinary
hematologic
musculoskeletal
neurological
ophthalmological
otological
psychiatric / psychological
respiratory system
thermoregulatory system
unknown, or not specified
Aetiolog y
allergic
environmental - exercise-related
environmental - non-exercise
immunological / inflammatory
infectious disease
neoplasm
metabolic / nutritional
vascular
degenerative or chronic condition
developmental anomaly
drug-related / poisoning
unknown, or not specified
For injury and illness
New, recurrent or exacerbation
new recurrent after full recovery and return-to-sport unknown, or not specified
exacerbation of a stable (not recovered) condition
Time-loss in sport due to injury / illness
no yes
Date of full return to normal training and competition ______________ (dd/mm/yy)
No return to sport possible: fatality permanent disability other reasons _______________
28 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
APPENDIX 3
Strobe-SIIS (Sports Injury and Illness Surveillance) Statement 1.0
Checklist of Items for Reporting Observational Studies on Injury and Illness in Sports
a
Item
Recommendation From
STROBE Statement STROBE-SIIS Extension
Source of Rationale for Item From
Consensus Statement and Where to
Find Further Details
(1) Title and abstract (a) Indicate the study’s design
with a commonly used term in
the title or abstract
(b) Provide in the abstract an
informative and balanced
summary of what was done
and what was found
SIIS 1.1: Include information on the
sport, athlete population (sex,
age, geographic region), and level
of competition
SIIS 1.2: Include the duration of
observation (eg, 1 season, 1 year,
multiple years)
SIIS 1.1: “Study population
characteristics”
SIIS 1.2: “Capturing and reporting
athlete-exposure”
Introduction
(2) Background/rationale Explain the scientific
background and rationale for
the investigation being
reported
(3) Objectives State specific objectives,
including any prespecified
hypotheses
SIIS 3.1: State whether study was
registered. Identify the registration
number and database used
SIIS 3.2: State the specific purpose
of the study (eg, to describe the
injury burden associated with
Olympic-level rowing)
SIIS 3.1: “Reporting guidelines:
STROBE Sports Injury and
Illness Surveillance (STROBE-
SIIS)”
SIIS 3.2: Throughout consensus
statement
Methods
(4) Study design Present key elements of study
design early in the paper
SIIS 4.1: Clearly specify which
health problems are being
observed
SIIS 4.2: State explicitly which
approach was used to record the
health problem data, including
all outcome measures or tools
SIIS 4.3: State explicitly which
coding system was used to
classify the health problems (eg,
OSIICS, SMDCS, ICD, etc)
SIIS 4.4: Where relevant, clearly
describe how athletes were
categorized. Variables to consider
could include the type of athlete
and/or sport, environment in
which the sport occurs (eg, type of
course or playing area), the
typical duration of the sport, the
degree of physical contact
permitted in the sport, and the
equipment permitted
SIIS 4.1: “Defining and classifying
health problems”
SIIS 4.2: “Data collection methods”
SIIS 4.3: “Classifying sports injury
and illness diagnoses”
SIIS 4.4: “Study population
characteristics”
(5) Setting Describe the setting, locations,
and relevant dates, including
periods of recruitment,
exposure, follow-up, and data
collection
SIIS 5.1: Describe the location, level
of play, dates of observation, and
data collection methods (ie, who,
what, where)
SIIS 5.2: Specify the dates of the
surveillance period and how
the data were handled when
the study covered more than 1
season/calendar year
SIIS 5.3: Define whether the health
problem data were collected
prospectively or retrospectively
SIIS 5.1: “Study population
characteristics”
SIIS 5.2: “Capturing and reporting
athlete-exposure”
SIIS 5.3: “Capturing and reporting
athlete-exposure” and “Data
collection methods”
(continued)
The Orthopaedic Journal of Sports Medicine Injury/Illness Surveillance Methods 29
(continued)
Item
Recommendation From
STROBE Statement STROBE-SIIS Extension
Source of Rationale for Item From
Consensus Statement and Where to
Find Further Details
(6) Participants (a) Cohort study: give the
eligibility criteria and the
sources and methods of
selection of participants.
Describe the methods of
follow-up
Case-control study: give the
eligibility criteria and the
sources and methods of case
ascertainment and control
selection. Give the rationale
for the choice of cases and
controls
Cross-sectional study: give the
eligibility criteria and the
sources and methods of
selection of participants
SIIS 6.1: Define the population of
athletes as well as describe how
they were selected and recruited
SIIS 6.1: “Data collection methods”
and “Study population
characteristics”
(b) Cohort study: for matched
studies, give matching criteria
and the number of exposed
and unexposed participants
Case-control study: for matched
studies, give matching
criteria and the number of
controls per case
(7) Variables Clearly define all outcomes,
exposures, predictors,
potential confounders, and
effect modifiers. Give the
diagnostic criteria, if
applicable
SIIS 7.1: Justify why you measured
your primary and secondary
outcomes of interest in the
specific way chosen
SIIS 7.2: Describe the method for
identifying the health problem
outcome of interest
SIIS 7.1: “Defining and classifying
health problems”
SIIS 7.2: “Defining and classifying
health problems”
(8) Data sources/
measurement
b
For each variable of interest,
give sources of data and
details of methods of
assessment (measurement).
Describe comparability of
assessment methods if there is
more than 1 group
SIIS 8.1: Specify who collected/
reported the data for the study
and their qualifications (eg,
qualified doctor, data analyst, etc)
SIIS 8.2: Specify who coded the data
for the study and their
qualifications (eg, qualified
doctor, data analyst, etc; in many
instances, this will not be the
same as in SIIS 8.1)
SIIS 8.3: Specify the direct methods
used to collect the data and the
use of physical documents or
electronic tools (if extracting
information from existing
sources, specify the data source)
SIIS 8.4: Specify the timing of and
window for data collection (eg,
day health problem occurred or
following day). Specify the
frequency of data collection (eg,
daily, weekly, monthly)
SIIS 8.5: Report the duration of
surveillance (eg, tournament,
season, whole year, playing
career)
SIIS 8.1: “Classifying sports injury
and illness diagnoses” and “Data
collection methods”
SIIS 8.2: “Classifying sports injury
and illness diagnoses”
SIIS 8.3: “Data collection methods”
SIIS 8.4: “Relationship to sports
activity” and “Capturing and
reporting athlete-exposure”
SIIS 8.5: “Relationship to sports
activity” and “Capturing and
reporting athlete-exposure”
(continued)
30 IOC Injury and Illness Epidemiology Consensus Group The Orthopaedic Journal of Sports Medicine
(continued)
Item
Recommendation From
STROBE Statement STROBE-SIIS Extension
Source of Rationale for Item From
Consensus Statement and Where to
Find Further Details
(9) Bias Describe any efforts to address
potential sources of bias
SIIS 9.1: Clearly report any
validation or reliability
assessment of the data collection
tools
SIIS 9.2: Formally acknowledge any
potential biases associated with
the data collection method (eg,
self-report, recall bias, reporting
by nonmedically trained staff, etc)
SIIS 9.1: “Data collection methods”
SIIS 9.2: “Data collection methods”
(10) Study size Explain how the study size was
arrived at
(11) Quantitative variables Explain how quantitative
variables were handled in the
analyses. If applicable,
describe which groupings
were chosen and why
SIIS 11.1: Explain in detail how
multiple injuries/illness episodes
are handled both in individual
athletes and across athletes/
surveillance periods
SIIS 11.2: Specify how injury
severity was calculated
SIIS 11.1: “Multiple events and
health problems” and
“Subsequent, recurrent, and/or
exacerbation of health problems”
SIIS 11.2: “Severity of health
problems”
(12) Statistical methods (a) Describe all the statistical
methods, including those used
to control for confounding
SIIS 12.1: Specify how the exposure
to risk has been adjusted for and
specify units (eg, per participant,
per athlete-exposure, etc)
SIIS 12.2: Specify how relevant risk
measures (incidence, prevalence,
etc) were calculated
SIIS 12.3: Whenrelevant to the study
aim, specifyhow the injury burden
was calculated and analyzed
SIIS 12.1: “Capturing and reporting