CrossFit Overview: Systematic Review and Meta-analysis
Claudino et al. Sports Medicine - Open
CrossFit Overview: Systematic Review and Meta-analysis
João Gustavo Claudino 0 1 3 4
Tim J. Gabbett 2 8
Frank Bourgeois 7
Helton de Sá Souza 6
Rafael Chagas Miranda 6
Bruno Mezêncio 1 4
Rafael Soncin 1 4
Carlos Alberto Cardoso Filho 1 4
Martim Bottaro 5
Arnaldo Jose Hernandez 9
Alberto Carlos Amadio 1 4
Julio Cerca Serrão 1 4
0 Faculty of Physical Education, University of Itaúna , Itaúna , Brazil
1 School of Physical Education and Sport, Laboratory of Biomechanics, University of São Paulo , São Paulo , Brazil
2 Gabbett Performance Solutions , Brisbane , Australia
3 Faculty of Physical Education, University of Itaúna , Itaúna , Brazil
4 School of Physical Education and Sport, Laboratory of Biomechanics, University of São Paulo , São Paulo , Brazil
5 College of Physical Education, University of Brasília , Brasília , Brazil
6 Department of Psychobiology, Federal University of São Paulo , São Paulo , Brazil
7 Sport Performance Research Institute New Zealand, Auckland University of Technology , Auckland , New Zealand
8 Institute for Resilient Regions, University of Southern Queensland , Ipswich , Australia
9 Orthopedics and Traumatology Institute, University of São Paulo , São Paulo , Brazil
Background: CrossFit is recognized as one of the fastest growing high-intensity functional training modes in the world. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the objective of this study is to analyze the findings of scientific literature related to CrossFit via systematic review and meta-analysis. Methods: Systematic searches of the PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO online databases were conducted for articles reporting the effects of CrossFit training. The systematic review followed the PRISMA guidelines. The Oxford Levels of Evidence was used for all included articles, and only studies that investigated the effects of CrossFit as a training program were included in the meta-analysis. For the meta-analysis, effect sizes (ESs) with 95% confidence interval (CI) were calculated and heterogeneity was assessed using a randomeffects model. Results: Thirty-one articles were included in the systematic review and four were included in the meta-analysis. However, only two studies had a high level of evidence at low risk of bias. Scientific literature related to CrossFit has reported on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. In the meta-analysis, significant results were not found for any variables. Conclusions: The current scientific literature related to CrossFit has few studies with high level of evidence at low risk of bias. However, preliminary data has suggested that CrossFit practice is associated with higher levels of sense of community, satisfaction, and motivation.
High-intensity functional training; High-intensity interval training; Training load
For a large majority of studies, a low level of
evidence and a high risk of bias were found. There is
a need to improve the methodological approaches in
In the scientific literature, there is a gap to be filled
in the area of controlling training load. Given the
importance of managing training load in reducing
injury risk and optimizing athletic performance,
these approaches could be used to support CrossFit
Initial reports of higher levels of sense of
community, satisfaction, and motivation during
CrossFit training were found in the scientific
CrossFit is recognized as one of the fastest growing
modes of high-intensity functional training. According
to the official CrossFit website (map.crossfit.com),
CrossFit boxes are located in 142 countries across seven
continents with more than 10,000 affiliates [
strength and conditioning program is used to optimize
physical competence in ten fitness domains: (1)
cardiovascular/respiratory endurance, (2) stamina, (3) strength,
(4) flexibility, (5) power, (6) speed, (7) coordination, (8)
agility, (9) balance, and (10) accuracy [
training is usually performed with high-intensity,
functional movements called “workout of the day”
]. In these training sessions, high-intensity
exercises are executed quickly, repetitively, and with
little or no recovery time between sets [
]. With the
focus on constantly varying functional movements,
CrossFit training uses the main elements of gymnastics
(e.g., handstand and ring exercises), weightlifting
exercises (e.g., barbell squats and presses), and
cardiovascular activities (e.g., running or rowing) as exercise tasks
]. According to Glassman, who is the founder of
CrossFit, the methodology that drives CrossFit training
is entirely empirical. Furthermore, Glassman described
that “meaningful statements about safety, efficacy, and
efficiency, the three most important and interdependent
facets of any fitness program, can be supported only by
measurable, observable, repeatable facts, i.e., data” [
CrossFit is also considered an option for high-intensity
interval training (HIIT). Consequently, HIIT has become
one of the top 3 worldwide fitness trends since 2013
according to the American College Sports Medicine
(ACSM) annual survey [
]. Notably, CrossFit was
indicated as the primary reason HIIT workouts were ranked
so high [
]. However, a consensus paper produced by
the Consortium for Health and Military Performance
(CHAMP) and ACSM associated a potential emergence of
a high injury risk with programs such as CrossFit [
While positive influences on body composition and
physical fitness were recognized, the consensus
highlighted a “disproportionate musculoskeletal injury risk
from these demanding programs, particularly for novice
participants, resulting in lost duty time, medical treatment
and extensive rehabilitation”. In addition, the consensus
suggested the existence of a training paradigm requiring
advanced level technique during maximal timed exercise
repetitions without adequate rest intervals between sets,
as well as an insufficient recovery time between
high-volume loads and training sessions. This overload situation
can lead to early fatigue, additional oxidative stress, less
resistance to subsequent repetitive exercise strain, greater
perception of effort, and unsafe movement execution [
Furthermore, this training context associated with
inadequate training load progression increases the risk of
overuse injury, overreaching, and overtraining. The consensus
authors suggested, as a possible solution, individual
monitoring of training load to minimize these risks [
Despite the proposed risks of CrossFit, others have suggested
that high-intensity functional training programs, including
CrossFit, have similar or lower potential for injury than
many traditional physical training activities [
the authors also stated that controlling training volume
must be done in order to reduce injury risk in military
populations. For an effective training process and
adaptation to occur, the monitoring [
], quantification [
] of training load is necessary. However,
managing training load poses a considerable challenge for
sport scientists [
]. Despite this challenge, managing
training load is fundamental to achieving the objectives of
reducing injury risk and optimizing sports performance
Although there are a large number of CrossFit
participants, empirical evidence demonstrating the improvements
in physical fitness that arise from this form of training are
far from substantive. Furthermore, an overview of
CrossFit’s outcomes has not been verified. Therefore, the
purpose of the present study was to analyze the findings of
the scientific literature related to CrossFit through a
systematic review and meta-analysis.
One author conducted the literature search, collated
the abstracts, and applied the initial inclusion
criteria. The keyword “CrossFit” was used during the
electronic search. The following electronic databases
were searched on the 25th of November 2016:
PubMed, Web of Science, Scopus, Bireme/MedLine,
and SciELO (Fig. 1). The Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA)
reporting guidelines were adhered to in this manuscript.
In the initial analysis, all CrossFit articles included in
this manuscript were peer-reviewed and not limited
to specific years or language. During the second
phase of study selection, two authors reviewed and
identified the titles and abstracts based on the
To meet the inclusion criteria for the meta-analysis,
studies investigating humans “in vivo” or “in obitus” and
analyzed the effects of CrossFit as a training program
were considered. The meta-analysis was only conducted
on variables from short-term intervention studies (i.e., ≥
3 weeks) with healthy male and/or female participants
split into distinct gender groups (the procedures were
consistent from those of another meta-analysis) [
Moreover, the variables analyzed were to be found in
more than one study. If pertinent data were absent,
authors were contacted and the necessary information
requested via e-mail. If the original data were not
provided by the authors, the mean and standard deviations
were extracted from graphical representation using
] or estimated from the median, range, and
sample size [
]. The remaining articles were included
in the systematic review.
The Consolidated Standards of Reporting Trials
(CONSORT) statement was adapted and used for checking the
quality of reporting by two authors independently. Thus,
the articles’ quality was evaluated based on the 25 items
identified in the CONSORT criteria, providing a maximal
possible score of 37. The CONSORT items are distributed
in sections and topics such as “Title and abstract”;
“Introduction” (Background and objectives); “Methods”
(Trial design, Participants, Interventions, Outcomes,
Sample size, Blinding, Statistical methods); “Results”
(Participant flow, Recruitment, Baseline data, Numbers
analyzed, Outcomes and estimation, Ancillary analyses,
Harms); “Discussion” (Limitations, Generalizability,
Interpretation); and “Other information” (Registration,
Protocol, Funding) [
]. Additionally, the Oxford Levels of
] were used to evaluate the level of evidence
for all articles found in the literature on CrossFit. Where
the five levels (i.e., Level 1 = systematic reviews; Level 2 =
randomized controlled trials with low/moderate risk of
bias or observational studies with dramatic effect; Level 3
= cohort study, non-randomized controlled trials with
low/moderate risk of bias or randomized controlled trial
at high risk of bias; Level 4 = case series, case report,
case-control studies, cohort study, historically controlled
studies or non-randomized controlled trials at high risk of
bias; and Level 5 = mechanism-based reasoning/expert
opinion) are determined based on the following questions:
(i) “How common is the problem?”; (ii) “Is this diagnostic
or monitoring test accurate? (diagnosis)”; (iii) “What will
happen if we do not add a therapy? (prognosis)”; (iv)
“Does this intervention help? (treatment benefits)”; (v)
“What are the COMMON harms? (treatment harms)”;
(vi) “What are the RARE harms? (treatment harms)”; and
(vii) “Is this (early detection) test worthwhile? (screening)”.
For the systematic review, two authors independently
assessed the quality of the included studies using the
Cochrane risk of bias tool [
] with a priori formulated
criteria adopted from the studies of Pas et al. [
Winters et al. [
]. Five domains of bias were appraised:
selection bias (random allocation and allocation
concealment), performance bias (blinding of personnel and
participants), detection bias (blinding of outcome assessment),
attrition bias (loss to follow-up), reporting bias (outcome
reporting), and other biases. Each item was scored as low
(+), high (−), or unclear (?) risk of bias. Studies were
considered low risk of bias when all domains were scored
as low risk of bias or if one item was scored as high risk or
unable to determine. If two domains were scored as high
or unable to determine risk of bias, the study received a
moderate risk of bias. Finally, when more than two
domains were scored as high risk of bias, the study was
regarded to possess a high risk of bias. In case of
disagreement between authors, consensus was sought during a
consensus meeting. If no consensus was reached, a third
author was asked to provide a final verdict. Publication bias
was determined for the meta-analysis using an approach
where differences in baseline assessments were checked for
all intervention groups. Next, the interventions were
divided into non-significant (p > 0.05) or significant (p < 0.05)
results to determine the percentage of interventions with
non-significant differences (these procedures were followed
as per another meta-analysis) [
For the meta-analysis, the heterogeneity of the included
studies was evaluated by examining forest plots, confidence
intervals (CI), and I2. I2 values of 25, 50, and 75 indicated
low, moderate, and high heterogeneity, respectively [
Random effects were analyzed using the DerSimonian and
] approach. The meta-analysis was conducted
based on the number of variables from short-term
intervention studies. Statistical significance was set at p ≤ 0.05,
and the magnitude of differences for each dependent
variable was calculated using effect size (ES) with 95% CI [
The ES classification was large > 0.80; moderate =
0.20–0.80; small < 0.20 [
]. Inferential statistics were used
for the descriptive analysis of the data. All data were
analyzed using CMA v3 trial (Biostat, New Jersey, USA)
and Excel 2010 worksheet (Microsoft, Washington, USA).
The initial search found 204 articles (Fig. 1). When the
inclusion criteria were applied, 32 articles were included in
the systematic review. When the inclusion criteria were
applied for the meta-analysis, five of these articles met the
criteria and were included in the manuscript [
4, 5, 34–63
However, during this manuscript peer-reviewing process,
one of 32 articles had a retraction published .
Quality assessment of the 31 included articles ranged
from 22 to 84% with a mean CONSORT rating of 37% [
Only 9% (i.e., absolute number = 3) of the included articles
38, 53, 54
] had ratings exceeding 50% (Additional file 1:
Table S1). Ethical approval was obtained in all articles. The
evidence level ranged between levels 2 and 4 for included
articles. However, just 6% (i.e., absolute number = 2) of
articles were considered level 2 (i.e., randomized controlled
trials with low risk of bias) (Fig. 2) [
For the systematic review, only 6% of the assessed
articles were at low risk of bias (Fig. 2) [
]. These articles
2013 Hak 
2013 Joondeph [
2014 Alexandrino [
2014 Heinrich [
2014 Larsen [
2014 Partridge [
2014 Weisenthal [
2015 Bellar [
2015 Butcher [
2015 Fernandez [
2015 Friedman [
2015 Heinrich [
2015 Kliszczewicz [
2015 Lu [
2015 Martinez [
2015 Murawska [
2015 Shaw [
2016 Eather a [
2016 Eather b [
2016 Fisher [
2016 Fisker [
2016 Koteles [
2016 Lichtenstein [
2016 Middlekauff [
2016 Perciavalle [
2016 Pickett [
2016 Sprey [
2016 Summitt [
2016 Tibana [
2016 Whiteman [
2017 Drum [
Fig. 2 Risk of bias and level of evidence
performed adequate randomization and allocation
methods, blinding strategy, and clinical trial registry. In
contrast, a majority of the non-controlled trials,
crosssectional studies based on an electronic questionnaire,
and correlation studies or case report/case series did not
explicitly describe if and how they controlled for detection
bias. For the included articles in the meta-analysis, 78% of
the intervention groups resulted in non-significant (p >
0.05) differences in baseline assessments (i.e., 83
interventions with non-significant differences ÷ 106 overall
interventions = 78%).
The pooled sample size for this manuscript was 3597
with 81% of participants in the CrossFit group and the
remaining 19% in the control group. Male participants
(60%) were utilized more so than females (40%). CrossFit
samples were composed of adolescents (male 4%, n =
112 and age = 15 ± 1 years; female 3%, n = 94 and age =
15 ± 1 years), adults (male 56%, n = 1638 and age = 30 ±
7 years; female 37%, n = 1065 and age = 30 ± 7 years),
and elderly (male 0.2%, n = 5 and age > 60 years; female
0.1%, n = 2 and age > 60 years). The sample profile
included 6% competitors (i.e., in the CrossFit Games),
63% trained individuals (i.e., in the CrossFit program
more than 6 months), 22% physically active individuals,
and 9% sedentary individuals. The average duration of
each CrossFit intervention was 9 ± 3 weeks.
In summary, the following aspects of CrossFit were
examined in the scientific literature: body composition (n
= 4), psycho-physiological parameters (n = 12),
musculoskeletal injury risk (n = 7), life and health aspects (n = 4),
and psycho-social behavior (n = 11) (Table 1).
Among the included short-term intervention studies,
five CrossFit fitness domains were found in the
literature, i.e., cardiovascular/respiratory endurance [
], strength [
], flexibility [
], and power
]. Five domains were yet to be verified, i.e., speed,
coordination, agility, balance, and accuracy.
Forty-three variables were found from short-term
intervention studies in the meta-analysis. These variables
represented cardiovascular/respiratory endurance and
stamina (i.e., absolute and relative maximal oxygen
consumption, VO2max), as well as body composition (i.e.,
body mass, body mass index, relative body fat, fat mass,
lean body mass, and waist circumference). No significant
results were found for any of the variables (Fig. 3).
Although CrossFit has a large number of participants, a
high level of evidence demonstrating positive outcomes
has yet to be established in the literature. Therefore, the
present study aimed to verify the findings of scientific
investigations related to CrossFit fitness domains as well
as present outcome validity of CrossFit via systematic
review and meta-analysis. Five of ten CrossFit fitness
domains (cardiovascular/respiratory endurance, stamina,
strength, flexibility, and power) were found in short-term
intervention studies, with the remaining fitness domains
(speed, coordination, agility, balance, and accuracy)
lacking. Furthermore, CrossFit’s outcome evidence was
provided for studies examining body composition,
psycho-physiological parameters, musculoskeletal injury
risk, life and health aspects, and psycho-social behavior.
With respect to these studies, few achieved a high level of
evidence at low risk of bias.
Meta-analyses were performed on body composition
parameters including body mass index, relative body fat,
fat mass, lean body mass, and waist circumference. All
variables had non-significant results, reinforcing the
need for more high-quality studies on CrossFit as well as
A study comparing CrossFit training with a training
approach based on ACSM recommendations reported
CrossFit training as more strenuous and considered a “very
hard” activity by participants [
]. CrossFit participants
also reported greater fatigue, greater muscle pain and
swelling, and limb movement difficulties during or within
48 h after the workout [
]. Furthermore, the authors
reported the five most frequently used and hardest WODs
were “Fran,” “Murph,” “Fight Gone Bad,” “Helen,” and
“Filthy Fifty.” Except for “Fran,” the psycho-physiological
responses to these WODs were not reported. “Fran” and
another popular WOD known as “Cindy” presented
greater magnitudes for heart rate (95–97% of HRmax),
%VO2max (57–66%), blood lactate (14–15 mmol/L), and
rate of perceived exertion (RPE) [
]. Perciavalle et al. [
also observed lactate concentrations around 14 mmol/L
following a WOD called “15.5”. “Cindy” (98% HRmax and
RPE = 9) also presented an acute blood oxidative stress
response similar to a traditional bout of high-intensity
treadmill running (running at a minimum intensity of 90%
maximum heart rate over 20 min) [
Researchers have reported a decrease in
antiinflammatory cytokines without decrements in muscle
power following two consecutive days of CrossFit
training sessions [
]. The WODs employed included a
rest interval between sets and exercises (i.e., 2–5 min,
for more details see Table 1). Thus, IL-6 displayed an
increase immediately after training WOD 1 and WOD 2
while IL-10 displayed an increase immediately after
WOD 1 only and decreased 24 and 48 h following
WOD 2 when compared to baseline values [
findings should be considered with caution as while
there are designated rest intervals in some CrossFit
workouts (e.g., Fight Gone Bad, 5 × 500 m row), the
inclusion of rest intervals is not common practice in
Descriptive The inclusivity is highlighted in CrossFit.
epidemiological However, motivational climate and
study goals in CrossFit may vary based on
demographic variables (i.e., gender and
length of time in a program) and that
these differences may impact how to
most effectively motivate, encourage,
and instruct group members.
Descriptive 19% of practitioners had suffered at
epidemiological least one injury while practicing CrossFit.
study the shoulder and lower back were the
most commonly injured in gymnastic
and power lifting movements,
AMRAP workout performance was associated with both aerobic fitness and anaerobic power.
CrossFit benchmark WOD performance
cannot be predicted by VO2max, Wingate
power/capacity, or either respiratory
compensation or anaerobic thresholds.
Both WODs could be characterized as
high intensity workouts, achieving near
maximal physiological (e.g., 90–95% of
CrossFit teens training did not improve
mental health outcomes in the full
students. However, the results from this
study provides preliminary evidence for
improving mental health in adolescents
“at risk” of developing psychological
CrossFit teens training had improved
body composition (i.e., waist
circumference, BMI) and results in
performance tests (i.e., sit and reach,
standing jump, and shuttle run).
Retention was 82%, adherence was 94%, and satisfaction ranged from 4.2 to 4.6 out of 5 (1 = strongly disagree to 5 = strongly agree)
Competitors WOD 15.5: Thrusters + rowing with 29/ (n = 15) 27/15/9 repetitions Acute effects Intervention or method of analysis
ACSM American College of Sports Medicine, AMRAP as many rounds as possible, BMI body mass index, bpm beats per minute, HRmax maximum heart rate, mmol/L
millimole/liter, MR maximum repetitions, RPE ratings of perceived exertion, VO2max maximal oxygen uptake, WOD workout of the day
Fig. 3 Meta-analysis of short-term intervention studies
In an acute study, the WOD “CrossFit triplet” (i.e., three
burpees, four push-ups, and five squats; for details see
Table 1) was associated with significant changes in
physiological responses [
]. Participants achieved approximately
12,000 mmHg for rate pressure product, 6 mmol/L for
blood lactate, and 54% of HRmax [
]. According to the
authors, “CrossFit triplet” was of moderate to high
intensity and thus considered a viable interval training option
that provides sufficient intensity in a safe manner [
In the correlation studies, whole-body strength, power,
endurance, and experience seemed to be important
measures associated with performance in CrossFit [
Butcher et al. [
] reported whole-body strength as a
predictor of performance in some WODs such as “Grace,”
“Fran,” and “Cindy”. The authors also found VO2max,
Wingate power, and anaerobic thresholds were
unsuccessful in predicting WOD performance. Conversely, Bellar et
] found VO2max and anaerobic power to be
significant predictors of performance after one CrossFit training
session. The authors also divided 32 young healthy men
into two groups and found CrossFit experience, or CrossFit
training history, was also a predictor of performance
during a WOD. Nonetheless, more research is required as
the present literature is inconclusive regarding predictors
of CrossFit performance.
Based on the systematic review, in general, WODs
present highly varied psycho-physiological demands:
heart rate between 54 and 98% of HRmax, blood lactate
levels between 6 and 15 mmol/L, %VO2max between 57
and 66%, RPE between 8 and 9 (out of 10), and rate
pressure product around 12,000 mmHg. Some WODs
(e.g., “Fran,” “Cindy,” and “15.5”) can be identified as
high-intensity level whereas others (e.g., “CrossFit
triplet”) can be considered moderate.
Musculoskeletal Injury Risk
In one of the first publications on musculoskeletal injury
risk, a descriptive epidemiological investigation used an
electronic questionnaire to examine 132 CrossFit
]. Results revealed 74% of CrossFit participants
suffered at least one injury. The most common injury
sites were shoulder and lower back followed by arm/
elbow, with an injury rate of 3.1 events every 1000 h of
]. A total of 186 lesions were reported with
some participants injured more than once in a period of
18 months. Nine of these cases required surgical
intervention. In another study that examined the epidemiological
profile of CrossFit participants, an injury prevalence of
31% was recorded [
]. In addition, when the participants
were separated according to CrossFit experience, those
who practiced CrossFit for more than 6 months (35%)
showed significantly (p = 0.004) higher injury rates than
those who practiced for less than 6 months (23%). This
study also reported a 45% injury prevalence rate among
athletes with more than 2 years of practice [
Another descriptive epidemiological study employed an
electronic questionnaire to verify injury risk of the
shoulder in CrossFit participants (n = 187). The authors found
that 24% of participants reported at least one shoulder
injury in the last 6 months of practice, with an injury rate
of 1.9 per 1000 h. The most common attributed causes of
injury were inadequate form of movement (33%) and
exacerbation of previous injury (33%). Furthermore, 64%
of those who suffered an injury reported a reduction in
training for 1 month or less due to injury [
Similar electronic questionnaire and experimental
approaches have also been used to examine injury risk in
CrossFit (n = 381). Musculoskeletal injuries accounted for
19% of all injuries, with men injured more frequently than
women (p = 0.03). The shoulder was injured most often
during gymnastic movements whereas the lower back was
injured most often during power lifting movements [
In addition, two case reports offered insight on injury
risk. The first case study examined a traumatic tear of
the latissimus dorsi myotendinous junction inflicted
during the “muscle up” exercise [
]. This injury usually
occurs in the acute configuration of forced abduction
and external rotation during resisted contraction.
Performing this exercise requires sound technique and
high levels of strength, particularly at the transition
point of the maneuver. The participant in this case
report returned to complete pre-injury level of activity
within 6 months after the inciting event, with mild
residual functional deficit. The second case report was a
retinal detachment due to CrossFit training [
25-year-old male presented an inferior scotoma in the
right eye after engaging in a CrossFit workout which
required “pull ups” with an elastic band tied around the
waist and secured to the pull up bar, thus partially
supporting body weight. The retina was successfully
reattached, and vision was successfully recovered after
The acute effects of high-intensity CrossFit training on
tendon properties were evaluated via ultrasonography (n
= 34). Thickness of the patellar and Achilles tendons
increased significantly after the session. These findings
suggest the high-intensity loads associated with concentric
and eccentric muscle actions during CrossFit exercise may
result in an increase in patellar and Achilles tendon
thickness. However, long-term interventions are needed to
investigate the effect of recovery between high-intensity
sessions as a deterministic factor in altering the structure
of biomaterials within tendons and the subsequent effects
of changes in tendon morphology on risk of injury [
In summary, the number of injuries that affect
CrossFit participants varies between 19 and 74% with 1.9–3.1
per 1000 training hours. In this sense, the percentage of
injury is relatively high while the incidence of injuries per
1000 h is low. These results may reflect a sampling bias or
inadequate management of training volume. Although
higher training volume and perception of intensity have
been found in CrossFit participants [
studies directly comparing the injury rates of CrossFit
with other ACSM-recommended training modalities are
The second aspect highlighted by the CHAMP and
ACSM consensus was monitoring individual-specific
training load and its potential to minimize injury risk
]. Although the cause of injury is multifactorial, injury
can result from the summation of load that imposes a
force that exceeds the capacity of the biological tissue
]. To attenuate this deleterious outcome, an
integrated approach that incorporates individual-specific
], quantification [
], and regulation [
may aid in decreasing injury risk. Monitoring is defined
as the verification of responses to the training loads
performed that were previously planned by the coach
]. Quantification is defined as the sum of the training
load that was effectively executed by the athlete [
Regulation is defined as the adjustments in the training
loads lifted in relation to the athlete responses [
However, no studies investigating training load management
were found in the systematic review, which presents a gap
in current knowledge. Presently, controlling training load
is based on the coach’s anecdotal and scientific
background which can be highly varied around the world. Due
to the potentially positive impact an evidence-based
integrated approach to training load management could have
on reducing injury, risk while achieving training objectives
(i.e., enhancing sports performance) [
greater research in this area.
Life and Health Aspects
Though sparse, case report and case series studies were
found in the literature examining life and health aspects.
Only two reported cases of rhabdomyolysis were found
]. However, this does not rule out the need to
develop strategies of recovery between training sessions,
respecting biological individuality of participants.
Other life and health aspects related to CrossFit training
were found in the literature. Lu et al. [
] reported three
cases of cervical carotid dissection that were associated
with CrossFit workouts. Specifically, participant 1 suffered
a distal cervical internal carotid artery dissection near the
skull base and a small infarct in Wernicke’s area. The
individual was placed on anticoagulation and on follow-up
was near complete recovery. Participant 2 suffered a
proximal cervical internal carotid artery dissection that led to
arterial occlusion and recurrent middle cerebral artery
territory infarcts, in addition to significant neurological
sequelae. Participant 3 had a skull base internal carotid
artery dissection that led to a partial Horner’s syndrome
but no cerebral infarct. None of the three individuals died.
While direct causality cannot be proven, the authors
speculated the high-intensity CrossFit workouts likely led
to the internal carotid artery dissections in these
Similarly, Alexandrino et al. [
] examined 10 cases of
stroke in participants aged between 27 and 65 years
(80% being male). Among them, one man (32 years old)
had an intracerebral hemorrhage stroke during a
CrossFit session. The participant did not die, but he was left
disabled ( no. 3 in the modified Rankin scale = moderate
disability; requiring some help, but able to walk without
assistance). The authors’ conclusion was that stroke
during sport activity is rare, occurring mostly in healthy
young males and that cervicocerebral arterial dissection
is the primary mechanism of stroke, often without an
explicit history of trauma.
Finally, researchers demonstrated neither beneficial
nor deleterious effects on pelvic floor strength or
support in nulliparous young women after CrossFit training
]. The majority of these studies were evidence level 4
with high risk of bias and, as such, did not permit any
To date, no studies have examined the effect of CrossFit
training on resting blood pressure or heart rate. Further
research examining the acute and chronic effects of
CrossFit training on these health indicators is warranted.
A greater sense of community in CrossFit sessions was
verified when compared to traditional training whether
in a group or analyzed on an individual basis. This social
interaction level was assessed via questionnaire in
physically active participants [
]. However, sense of
community was not related to participant
retention/adherence for any of the modalities analyzed .
The retention/adherence of participants was assessed in
a randomized intervention study involving obese
individuals (BMI > 30). The same number of dropouts was also
revealed after 8 weeks of traditional training when
compared to CrossFit with aerobic and resistance training.
Nonetheless, the intention for continuing physically
vigorous activity was greater for the CrossFit group [
Furthermore, a European Organization for Research and
Treatment of Cancer core 30-item questionnaire revealed
5 weeks of CrossFit training was well received by cancer
survivors with an adherence rate of 75%. This intervention
was also considered feasible and effective in improving
emotional function [
Motivation for the practice of physical activity was also
assessed by questionnaire in four groups: CrossFit,
resistance exercise, alone, and in individuals who train with a
personal trainer. Enjoyment, challenge, and affiliation were
identified in the CrossFit group more than all other training
groups. Such source of motivation is compatible with that
presented in sports practice. Individuals who trained with a
personal trainer had higher health-related motives.
However, this group was older than the other groups, which
may represent a confounding factor in the response [
In schoolchildren (i.e., 12 to 16 years) participating in
CrossFit exercise, an older age has been associated with
higher ratings of perceived intensity and less enjoyment. In
the between-sex comparison, boys perceived greater
intensity and enjoyment [
]. Among adults, no sex difference
was identified for the perceived motivational climate of
CrossFit sessions, although the achievement goals varied
between males and females [
]. With respect to
achievement goals, the mastery-based motivational climate is
initially predominant, but when a domain of the tasks is
reached, the performance approach becomes predominant.
These variations are also present between sexes, with
females emphasizing mastery avoidance (i.e., to do as well as
I can) and males emphasizing the performance approach
(i.e., to do better than others) [
Although the goals within CrossFit practice vary with
practice time, the same does not appear to be true for
psychological functioning as well-being, affection, body
awareness, and self-esteem were not influenced by the
time or frequency of CrossFit practice [
results were found in an 8-week intervention study in
adolescent students (i.e., 15 years), where no
improvement in mental health was observed. However, a
subgroup of individuals at risk of psychological distress
presented significant improvements in mental health
]. In another study of the same research group, high
levels of retention (i.e., 82%), adherence (i.e., 94%), and
satisfaction (4.2–4.6 where 5 is the highest level) were
found in the students after 8 weeks of CrossFit Teens
Lastly, CrossFit’s motivational characteristics, which
aim to lead the individual to achieve the best
performance possible, generated a 5% prevalence of exercise
addiction in CrossFit participants which is similar to
other exercise programs. This observation has also been
shown to be even greater in men and young individuals
(i.e., < 30 years). Exercise addiction was associated with a
tendency to exercise despite injury, feelings of guilt
when unable to exercise, passion turning into obsession,
and taking medication to be able to exercise. These
negative attitudes toward exercise can facilitate damage,
such as injuries and losses in social relations, within
In summary, there is preliminary evidence of a higher
sense of community, satisfaction, and motivation among
CrossFit participants. However, it is still necessary for
new studies to verify the positive relationship between
these factors and retention/adherence of participants.
Before finalizing, we wish to emphasize that this study
did not seek to define CrossFit as “bad” or “good.”
Rather, this investigation sought to present the possible
benefits and risks associated with CrossFit according to
current findings in the scientific literature. The low level
of evidence at high risk of bias revealed by this study
does not allow a stronger position on the advantages
and disadvantages of CrossFit. The authors believe this
disparity demonstrates the need to improve current
methodological approaches in further studies, thus
influencing current practice.
Until now, current CrossFit scientific literature has been
based on studies that investigated the effects of CrossFit
on body composition, psycho-physiological parameters,
musculoskeletal injury risk, life and health aspects, and
psycho-social behavior. Meta-analysis did not find a
significant effect of CrossFit training changes in body mass
index, relative body fat, fat mass, lean body mass, and waist
circumference. Unfortunately, the number of studies
investigating CrossFit with high level of evidence at low risk of
bias is sparse. As a result, these findings neither firmly
establish the benefits or risks of CrossFit, nor provide
definitive practical recommendations concerning CrossFit
training. Despite this disparity, there is the existence of
initial evidence of higher levels of sense of community,
satisfaction, and motivation among CrossFit participants.
Additional file 1: Table S1. The Consolidated Standards of Reporting
Trials (CONSORT). (DOCX 43 kb)
We would like to thank the authors of the cited articles who collaborated to
obtain the data and “Coordenação de Aperfeiçoamento de Pessoal de Nível
Superior/ Programa de Excelência Acadêmica” (CAPES/PROEX), “Conselho
Nacional de Desenvolvimento Científico e Tecnológico” (CNPq), “Fundação
de Amparo à Pesquisa do Estado de Minas Gerais” (FAPEMIG), and
“Fundação de Amparo à Pesquisa do Estado de São Paulo” (FAPESP).
No sources of funding were used to assist in the design, collection, analysis,
and interpretation of data or in writing of this manuscript.
Availability of data and materials
After publication, all data necessary to understand and assess the
conclusions of the manuscript are available to any reader of Sports
JGC contributed in the design, collection, analysis, and interpretation of data
and in writing. TJG contributed in the interpretation of data and in writing.
FB and HSS helped in the design, collection, analysis, and interpretation of
data and in writing. RM, BM, RS, CACF, AJH, and MB contributed in the
design and interpretation of data and in writing.. ACA and JCS helped in the
design, analysis, and interpretation of data and in writing. All authors read
and approved the final manuscript.
Ethics Approval and Consent to Participate
All authors – João Gustavo Claudino, Tim J. Gabbett, Frank Bourgeois, Helton
de Sá Souza, Rafael Chagas Miranda, Bruno Mezêncio, Rafael Soncin, Carlos
Alberto Cardoso Filho, Martim Bottaro, Arnaldo Jose Hernandez, Alberto
Carlos Amadio and Julio Cerca Serrão – declare that they have no conflicting
Springer Nature remains neutral with regard to jurisdictional claims in
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1. Beers E. Virtuosity goes viral . CrossFit J . 2014 ; 6 : 1 - 10 .
2. Glassman G . What is fitness . CrossFit J . 2002 ; 3 : 1 - 11 .
3. Glassman G. Understanding CrossFit. CrossFit J. 2007 ; 56 : 1 - 2 .
4. Sprey JWC , Ferreira T , de Lima MV , Duarte A , Jorge PB , Santili C. An epidemiological profile of crossfit athletes in Brazil . Orthop J Sport Med . 2016 ; 4 : 1 - 6 .
5. Fisker FY , Kildegaard S , Thygesen M , Grosen K , Pfeiffer-Jensen M . Acute tendon changes in intense CrossFit workout: an observational cohort study . Scand J Med Sci Sports . 2016 ; https://doi.org/10.1111/sms.12781.
6. Thompson WR . Worldwide survey or ftiness trends for 2016: 10th Anniversary edition . ACSMs. Health Fit J 2015 ; 19 : 9 - 18 .
7. Thompson WR . World wide survey of fitness trends for 2017 . ACSMs. Health Fit J 2016 ; 20 : 8 - 17 .
8. Thompson WR . Now trending: worldwide survey of fitness trends for 2014 . ACSMs. Health Fit J 2013 ; 17 : 10 - 20 .
9. Thompson WR . World wide survey of fitness trends for 2015: what's driving the market . ACSMs. Health Fit J . 2014 ; 18 : 8 - 17 .
10. Bergeron MF , Nindl BC , Deuster PA , Baumgartner N , Kane SF , Kraemer WJ , et al. Consortium for Health and Military Performance and American College of Sports Medicine consensus paper on extreme conditioning programs in military personnel . Curr Sports Med Rep . 2011 ; 10 : 383 - 9 .
11. Poston WSC , Haddock CK , Heinrich KM , Jahnke SA , Jitnarin N , Batchelor DB . Is high-intensity functional training (HIFT)/CrossFit safe for military fitness training? Mil Med . 2016 ; 181 : 627 - 37 .
12. Akenhead R , Nassis GP . Training load and player monitoring in high-level football: current practice and perceptions . Int J Sports Physiol Perform . 2016 ; 11 : 587 - 93 .
13. Borresen J , Lambert MI . The quantification of training load, effect on performance . Sports Med . 2009 ; 39 : 779 - 95 .
14. Siff MC . In: CO, editor. Supertraining . 6th ed. Denver: Supertraining Institute; 2003 .
15. Halson SL . Monitoring training load to understand fatigue in athletes . Sports Med . 2014 ; 44 : 139 - 47 .
16. Gabbett TJ . The training-injury prevention paradox: should athletes be training smarter and harder? BrJ Sports Med . 2016 ; 50 : 273 - 80 .
17. Amadio AC , Serrão JC . A biomecânica em educação física e esporte . Rev Bras Educ Fis Esporte . 2011 ; 25 : 15 - 24 .
18. Elliott B. Biomechanics: an integral part of sport science and sport medicine . J Sci Med Sport . 1999 ; 2 : 299 - 310 .
19. Jones CM , Griffiths PC , Mellalieu SD . Training load and fatigue marker associations with injury and illness: a systematic review of longitudinal studies . Sports Med . 2017 ; 47 : 943 - 74 .
20. Hopkins WG . Quantification of training in competitive sports. Methods and applications . Sports Med . 1991 ; 12 : 161 - 83 .
21. Claudino JG , Cronin JB , Mezêncio B , Pinho JP , Pereira C , Mochizuki L , et al. Autoregulating jump performance to induce functional overreaching . J Strength Cond Res . 2016 ; 8 : 2242 - 9 .
22. Claudino JG , Mezêncio B , Soncin R , Ferreira JC , Couto BP , Szmuchrowski LA , et al. Pre vertical jump performance to regulate the training volume . Int J Sports Med . 2012 ; 33 : 101 - 7 .
23. Claudino JG , Cronin J , Mezêncio B , McMaster DT , McGuigan M , Tricoli V , et al. The countermovement jump to monitor neuromuscular status: a metaanalysis . J Sci Med Sport . 2017 ; 20 : 397 - 402 .
24. Gross A , Schirm S , Scholz M . Ycasd-a tool for capturing and scaling data from graphical representations . BMC Bioinformatics . 2014 ; 15 : 219 .
25. Hozo SP , Djulbegovic B , Hozo I. Estimating the mean and variance from the median, range, and the size of a sample . BMC Med Res Methodol . 2005 ; 5 : 13 .
26. Begg C , Cho M , Eastwood S , Horton R , Moher D , Olkin I , et al. Improving the quality of reporting of randomized controlled trials. The CONSORT statement . JAMA . 1996 ; 276 : 637 - 9 .
27. Group OL of EW. The Oxford Levels of Evidence 2 . In: Medicine OC for E-B. 2011 .
28. Higgins JPT , Green S . Cochrane Handbook for Systematic Reviews of iInterventions. Version 5 . The Cochrane Collaboration; 2011 .
29. Pas HI , Winters M , Haisma HJ , Koenis MJ , Tol JL , Moen MH . Stem cell injections in knee osteoarthritis: a systematic review of the literature . Br J Sports Med . 2017 ; 15 : 1125 - 33 .
30. Winters M , Eskes M , Weir A , Moen MH , Backx FJG , Bakker EWP . Treatment of medial tibial stress syndrome: a systematic review . Sports Med . 2013 ; 43 : 1315 - 33 .
31. Higgins JPT , Thompson SG , Deeks JJ , Altman DG . Measuring inconsistency in meta-analyses . BMJ . 2003 ; 327 : 557 - 60 .
32. DerSimonian R , Laird N. Meta-analysis in clinical trials . Control Clin Trials . 1986 ; 7 : 177 - 88 .
33. Cohen J . Statistical power analysis for the behavioral sciences . 2nd ed. Hillsdale: L. Erlbaum Associates; 1988 .
34. Hak PT , Hodzovic E , Hickey B. The nature and prevalence of injury during CrossFit training . J Strength Cond Res . 2013 ; https://doi.org/10.1519/JSC. 0000000000000318.
35. Joondeph SA , Joondeph BC . Retinal detachment due to CrossFit training injury . Case Rep Ophthalmol Med . 2013 ; 2013 : 189837 .
36. Smith MM , Sommer AJ , Starkoff BE , Devor ST . Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition . J Strength Cond Res . 2013 ; 27 : 3159 - 72 .
37. Alexandrino GM , Damásio J , Canhão P , Geraldes R , Melo TP , Correia C , et al. Stroke in sports: a case series . J Neurol . 2014 ; 261 : 1570 - 4 .
38. Heinrich KM , Patel PM , O'Neal JL , Heinrich BS . High-intensity compared to moderate-intensity training for exercise initiation, enjoyment, adherence, and intentions: an intervention study . BMC Public Health . 2014 ; 14 : 789 .
39. Larsen C , Jensen MP . Rhabdomyolysis in a well-trained woman after unusually intense exercise . Ugeskr Laeger . 2014 ; 176 : 1 - 2 .
40. Partridge JA , Knapp BA , Massengale BD . An investigation of motivational variables in CrossFit facilities . J Strength Cond Res . 2014 ; 28 : 1714 - 21 .
41. Weisenthal BM , Beck CA , Maloney MD , DeHaven KE , Giordano BD . Injury rate and patterns among CrossFit athletes . Orthop J Sport Med . 2014 ; 2 : 2325967114531177 .
42. Bellar D , Hatchett A , Judge LW , Breaux ME , Marcus L . The relationship of aerobic capacity, anaerobic peak power and experience to performance in CrossFit exercise . Biol Sport . 2015 ; 32 : 315 - 20 .
43. Butcher S , Neyedly T , Horvey K , Benko C . Do physiological measures predict selected CrossFit(®) benchmark performance? Open Access J Sport Med . 2015 ; 6 : 241 - 7 .
44. Fernández JF , Solana RS , Moya D , Marin JMS , Ramón MM . Acute physiological responses during Crossfit® workouts . Eur J Hum Mov . 2015 ; 35 : 114 - 24 .
45. Friedman MV , Stensby JD , Hillen TJ , Demertzis JL , Keener JD . Traumatic tear of the latissimus dorsi myotendinous junction: case report of a CrossFitrelated injury . Sport Heal . 2015 ; 7 : 548 - 52 .
46. Heinrich KM , Becker C , Carlisle T , Gilmore K , Hauser J , Frye J , et al. High-intensity functional training improves functional movement and body composition among cancer survivors: a pilot study . Eur J Cancer Care . 2015 ; 24 : 812 - 7 .
47. Kliszczewicz B , John QC , Daniel BL , Gretchen OD , Michael ER , Kyle TJ . Acute exercise and oxidative stress: CrossFit™ vs. treadmill bout . J Hum Kinet . 2015 ; 47 : 81 - 90 .
48. Lu A , Shen P , Lee P , Dahlin B , Waldau B , Nidecker AE , et al. CrossFit-related cervical internal carotid artery dissection . Emerg Radiol . 2015 ; 22 : 449 - 52 .
49. Sánchez-Alcaraz Martínez BJ , Gómez-Mármol A . Percepción de esfuerzo, diversión y aprendizaje en alumnos de educación secundaria en las clases de Educación Física durante una unidad didáctica de CrossFit . Sport Rev Euroam Ciencias del Deport . 2015 ; 4 : 63 - 8 .
50. Murawska-Cialowicz E , Wojna J , Zuwala-Jagiello J . Crossfit training changes brain-derived neurotrophic factor and irisin levels at rest, after wingate and progressive tests, and improves aerobic capacity and body composition of young physically active men and women . J Physiol Pharmacol . 2015 ; 66 : 811 - 21 .
51. Shaw BS , Dullabh M , Forbes G , Brandkamp J-L , Shaw I. Analysis of physiological determinants during a single bout of Crossfit . Int J Perform Anal Sport . 2015 ; 15 : 809 - 15 .
52. Drum SN , Bellovary BN , Jensen RL , Moore MMT , Donath L . Perceived demands and post-exercise physical dysfunction in CrossFit® compared to an ACSM based training session . J Sports Med Phys Fitness . 2017 ; 57 : 604 - 9 .
53. Eather N , Morgan PJ , Lubans DR . Effects of exercise on mental health outcomes in adolescents: findings from the CrossFit™ teens randomized controlled trial . Psychol Sport Exerc . 2016 ; 26 : 14 - 23 .
54. Eather N , Morgan PJ , Lubans DR . Improving health-related fitness in adolescents: the CrossFit teens™ randomised controlled trial . J Sports Sci . 2016 ; 34 : 209 - 23 .
55. Fisher J , Sales A , Carlson L , Steele J. A comparison of the motivational factors between CrossFit participants and other resistance exercise modalities: a pilot study . J Sports Med Phys Fitness . 2016 ; 9 : 1227 - 34 .
56. Kötele F , Kollsete M , Kollsete H , Köteles F , Kollsete M , Kollsete H , et al. Psychological concomitants of CrossFit training: does more exercise really make your everyday psychological functioning better? Kinesiology . 2016 ; 48 : 39 - 48 .
57. Lichtenstein MB , Jensen TT . Exercise addiction in CrossFit: prevalence and psychometric properties of the Exercise Addiction Inventory . Addict Behav Reports . 2016 ; 3 : 33 - 7 .
58. Middlekauff ML , Egger MJ , Nygaard IE , Shaw JM . The impact of acute and chronic strenuous exercise on pelvic floor muscle strength and support in nulliparous healthy women . Am J Obstet Gynecol . 2016 ; 215 : 316 . e1- 7
59. Perciavalle V , Marchetta NS , Giustiniani S , Borbone C , Perciavalle V , Petralia MC , et al. Attentive processes, blood lactate and CrossFit® . Phys Sportsmed . 2016 ; 44 : 403 - 6 .
60. Pickett AC , Goldsmith A , Damon Z , Walker M. The influence of sense of community on the perceived value of physical activity: a cross-context analysis . Leis Sci . 2016 ; 38 : 199 - 214 .
61. Summitt RJ , Cotton RA , Kays AC , Slaven EJ . Shoulder injuries in individuals who participate in CrossFit training . Sports Health . 2016 ; 8 : 541 - 6 .
62. Tibana RA , de Almeida LM , Frade de Sousa NM , Nascimento D Da C , Neto IV de S , de Almeida JA , et al. Two consecutive days of CrossFit training affects pro and anti-inflammatory cytokines and osteoprotegerin without impairments in muscle power . Front Physiol . 2016 ; 7 : 260 .
63. Whiteman-Sandland J , Hawkins J , Clayton D. The role of social capital and community belongingness for exercise adherence: an exploratory study of the CrossFit gym model . J Health Psychol . 2016 ; 1 : 1359105316664132 .
64. Smith MM . CrossFit-based high intensity power training improves maximal aerobic fitness and body composition: retraction . J Strength Cond Res . 2017 ; 31 : e76 .
65. Zernicke RF , Whiting WC . Mechanisms of musculoskeletal injury . In: Zatsiorsky VM , editor. Biomechanics in Sport. Oxford: Blackwell Science Ltd ; 2000 : 507 - 22 .