[
research report
]
AGNETHE NILSTAD, PT, MSc1 • THOR EINAR ANDERSEN, MD, PhD1 • EIRIK KRISTIANSLUND, MD, PhD1
ROALD BAHR, MD, PhD1 • GRETHE MYKLEBUST, PT, PhD1 • KATHRIN STEFFEN, PhD1 • TRON KROSSHAUG, PhD1
Physiotherapists Can Identify Female
Football Players With High Knee Valgus
Angles During Vertical Drop Jumps Using
Real-Time Observational Screening
E
xcessive knee valgus motion has been identified as contributing
to noncontact anterior cruciate ligament (ACL) injuries15,18,28
and is visually associated with a medial collapse of the knee
during dynamic tasks. Greater knee valgus angles, side-to-side
TTSTUDY DESIGN: Clinical measurement, controlled laboratory study.
TTOBJECTIVES: To assess the relationships
among real-time observational screening of frontal
plane knee control and knee valgus angles and
abduction moments calculated from 3-D motion
analysis during a vertical drop jump. A secondary
purpose was to investigate interrater agreement for
3 independent physiotherapists.
TTBACKGROUND: Current approaches to screen
for anterior cruciate ligament injury risk are based
on complex biomechanical analyses or 2-dimensional video reviews. There is a need for simple
and efficient, low-cost screening methods.
TTMETHODS: Sixty Norwegian elite female
football (soccer) players performed a vertical dropjump task. Using real-time observational screening, 3 physiotherapists independently scored
each participant’s frontal plane knee control as
good, reduced, or poor, based on specific criteria.
Screening test scores were correlated to frontal
plane knee kinematics and kinetics using 3-D motion analysis. Interrater agreement was determined
using kappa correlation coefficients.
TTRESULTS: Knee valgus angles differed
significantly among players rated as having poor,
reduced, or good knee control (10.3°  3.4°,
5.4°  4.1°, and 1.9°  4.3°, respectively). The
correlation between the observation test scores
and valgus angles was moderate for all raters
(0.54-0.60, P≤.001), but the observation scores
correlated poorly with abduction moments (0.090.11, P>.05). The highest discriminative accuracy
was found for knee valgus angles across all raters
(area under the receiver-operating-characteristic
curve, 0.85-0.89). The interrater agreement
between the physiotherapists was substantial to
almost perfect, with percentage agreement and
kappa coefficients ranging from 70% to 95% and
0.52 to 0.92, respectively.
TTCONCLUSION: Physiotherapists can reliably
identify female athletes with high knee valgus
angles in a vertical drop-jump landing using
real-time observational screening. J Orthop Sports
Phys Ther 2014;44(5):358-365. doi:10.2519/
jospt.2014.4969
TTKEY WORDS: anterior cruciate ligament (ACL),
injury risk, interrater agreement, motion analysis,
real-time assessment
differences in knee valgus,12 and lower
hip and knee flexion angles21 have been
reported to be more common in females
compared to males. In addition, females
exhibit higher external knee abduction
moments compared to males during
vertical drop-jump landing, with greater
differences observed during pubertal
growth.13 This may in part explain the
higher ACL injury incidence documented in female athletes.2,23,32 Furthermore,
1 prospective study14 reported that high
dynamic knee valgus and knee abduction
moments were predictive of ACL injury
in female athletes.
To identify female athletes at risk for
ACL injury and to facilitate targeted injury-prevention programs, there is a need
for standardized, time-efficient, and lowcost assessment methods. Such methods
should be easy to use and to implement
for large-scale screening, and at the same
time provide valid and reliable data. Although 3-D motion analysis is considered
the gold standard method to assess knee
kinematics and kinetics, this approach is
not suitable for large-scale screening of
athletes.27 As a consequence, several investigators have sought to develop more
Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway. The Oslo Sports Trauma Research Center was
established at the Norwegian School of Sport Sciences through generous grants from the Royal Norwegian Ministry of Culture, the South-Eastern Norway Regional Health
Authority, the International Olympic Committee, the Norwegian Olympic Committee and Confederation of Sport, and Norsk Tipping AS. This study also received financial support
from FIFA. The study was approved by the Regional Committee for Medical Research Ethics, South-Eastern Norway Regional Health Authority, and by the Norwegian Social
Science Data Services. The authors certify that they have no affiliations with or financial involvement in any organization or entity with a direct financial interest in the subject
matter or materials discussed in the article. Address correspondence to Agnethe Nilstad, Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian
School of Sport Sciences, PB 4014 Ullevål Stadion, N-0806 Oslo, Norway. E-mail: [email protected] t Copyright ©2014 Journal of Orthopaedic & Sports Physical Therapy®
1
358 | may 2014 | volume 44 | number 5 | journal of orthopaedic & sports physical therapy
simplistic screening methods.10,22,24,29 For
example, the assessment of frontal plane
knee motion using 2-dimensional video
(2-D) during a drop-jump landing task
is commonly used clinically. The relationship between 3-D motion analysis
and 2-D video reviews of vertical drop
jumps has been evaluated, with moderate to good correlations reported.10,22,24
Other studies have attempted to develop
clinic-based algorithms to predict high
knee abduction moments during dropjump landings.25-27
Real-time observational screening
represents an easy and low-cost method for assessing knee valgus during a
drop-jump task. However, reliable visual
criteria are necessary to standardize ratings and to ensure adequate reliability.
The reliability of visual assessments of
frontal plane knee motion using 2-D
video recordings has been investigated
during single-leg squats1,7 and vertical
drop jumps,10,24 with varying results. For
single-leg squats, the percentage agreement between raters has been reported
to be 41% to 96%, with kappa coefficients ranging from 0.00 to 0.92. Higher
agreement has been found for vertical
drop-jump assessments, with agreement
of 88% to 93% and corresponding kappa
coefficients of 0.75 to 0.85 in 1 study10
and intraclass correlation coefficients of
0.89 and 0.92 in another.24 However, the
drop-jump assessments in these studies
were based on video reviews, and only
1 study31 has investigated real-time assessment of knee kinematics during a
vertical drop-jump task. Stensrud et al31
reported good agreement between realtime visual evaluation of knee control
during a vertical drop-jump landing task
and 2-D video analysis of knee valgus.
Although high intrarater agreement of
the real-time assessment was reported
by Stensrud et al,31 neither the interrater
reliability of the real-time assessment nor
the relationship among 3-D kinematics
and kinetics was investigated.
The purpose of the current study was
to assess the relationships among realtime observational screening of frontal
plane knee valgus and actual knee valgus
angles and abduction moments calculated from 3-D motion analysis during a
vertical drop-jump landing task. A second purpose was to investigate the interrater agreement of 3 physiotherapists
using real-time observational screening.
We hypothesized that participants rated
as having poor frontal plane knee control,
as determined by observational screening, would display higher valgus angles
and moments than participants rated as
having good control.
METHODS
Study Design and Participants
W
e invited all players in the
Norwegian female elite football
(soccer) league (Toppserien) to
participate in a series of baseline screening tests as part of a prospective cohort
study investigating risk factors for noncontact ACL injuries. Players who were
expected to play in the elite league during the 2009 competitive football season
were eligible for participation. To be included in the study, the participants had
to be free of any lower extremity injury
that prevented them from full participation in football training and match play
at the time of testing. A total of 77 participants volunteered to participate; however, only 60 completed all phases of data
collection (mean  SD age, 23  5 years;
height, 166  5 cm; body weight, 63  7
kg). Prior to participation, informed consent was obtained from all participants.
The study was approved by the Regional
Committee for Medical Research Ethics,
South-Eastern Norway Regional Health
Authority, and by the Norwegian Social
Science Data Services.
Real-Time Observational Screening
To assess frontal plane knee control, participants performed a vertical drop-jump
task from a 30-cm box (FIGURE 1A).14 The
participants wore shorts, a sports bra,
and indoor training shoes. Prior to performing the drop-jump task, the anterior
superior iliac spines and the tibial tuber-
FIGURE 1. Real-time observational screening (A) and
3-D motion analysis during a drop-jump task (B).
osities were marked with small pieces
of sports tape. Participants performed a
standardized warm-up procedure consisting of squats (2 sets of 8 repetitions),
maximal vertical jumps (2 sets of 5 repetitions), and calf stretching (stretch duration, 2-3 minutes).
Participants were instructed to step
off the box using a 2-foot landing strategy, immediately followed by a maximal
vertical jump. To ensure that maximal
effort was achieved, participants were
encouraged to touch a football hanging
from a string 260 cm above the floor. A
trial was considered invalid if the participants jumped off the box or failed to
perform a vertical jump after the first
landing. Participants were allowed up
to 3 practice trials prior to testing. Participants completed 3 valid trials, and the
trial that scored the lowest with respect
to knee control was used for analysis.
The participants’ ability to control
their knees in the frontal plane during
the landing phase of the drop-jump task
was assessed using a graded scoring scale
ranging from 0 to 2.31 A score of 0 corresponded to good control, in which the
participant displayed proper knee alignment, with a straight line from the knees
to the mid toes, no obvious valgus motion of either of the knees, and no mediolateral side-to-side movement of the
journal of orthopaedic & sports physical therapy | volume 44 | number 5 | may 2014 | 359
[
knee during the performance. The score
of 1 corresponded to reduced control and
indicated improper alignment, with 1
or both knees moving into a slight valgus position and/or some mediolateral
side-to-side movement during the performance. A score of 2 corresponded to
poor control and was given when the
alignment of the knees was poor, with at
least 1 of the knees clearly moving into
a substantial amount of valgus (ie, knee
medial to foot) and/or clear mediolateral
side-to-side movement of the knee.
Three sports physiotherapists independently and simultaneously assessed
frontal plane knee control during the
landing phase of the drop-jump task,
according to the criteria outlined above.
One had 5 years of clinical experience as
a physiotherapist working with athletes
with musculoskeletal disorders. The other 2 had 20 and 15 years, respectively, of
experience as sports physiotherapists. All
3 physiotherapists were familiar with the
drop-jump task and routinely used this
test when screening athletes. In addition
to each independent assessment, a raterconsensus score for each participant was
established as the score given by at least
2 of the 3 raters. Consensus was reached
for all 60 cases.
During testing, the raters were positioned 3 m in front of the 30-cm box and
scored each participant while blinded to
the scores of the other raters. No discussion was allowed between the raters during the scoring of the participants. The
rating forms were collected by the project
coordinator at the end of the testing session to maintain blinding of the results.
The raters were also blinded to the results
of the 3-D motion analysis (see below for
details), and the participants were blinded to their scores.
To ensure scoring consistency, the raters received standardized rating instructions and practice prior to the actual
testing. This included detailed written
information on the testing procedures,
as well as group and individual training
sessions using photographs and videos
of examples of knee control during ver-
research report
]
FIGURE 2. Marker setup.
tical drop jumps. Each physiotherapist
screened approximately 30 players during 2 days of training.
Three-Dimensional Motion Analysis
To obtain 3-D knee joint kinematics and
kinetic data, participants performed an
additional vertical drop-jump task from
a 30-cm box in a motion analysis laboratory under conditions similar to those
of the real-time visual assessment (with
the exception of the hanging football to
encourage jump performance) (FIGURE
1B). Eight infrared cameras (ProReflex;
Qualisys AB, Gothenburg, Sweden) were
used to capture kinematic data at 240
Hz, while ground reaction forces and the
center-of-pressure data were recorded
from 2 force platforms collecting at 960
360 | may 2014 | volume 44 | number 5 | journal of orthopaedic & sports physical therapy
Hz (LG6-4-1000; Advanced Mechanical
Technology, Inc, Watertown, MA). Prior
to performing the drop-jump task, participants completed a static calibration
trial to determine the anatomical segment coordinate systems. To estimate
body-segment parameters, anthropometric measures of all participants were obtained, including 46 measures of segment
lengths, circumferences, and widths.34,35
Thirty-five reflective markers were attached over anatomical landmarks on the
legs, arms, and torso (FIGURE 2).17 One research assistant palpated the anatomical
landmarks and placed the markers on all
participants to ensure standardization.
Participants were allowed up to 3 practice
trials, and at least 3 successful trials were
collected. For a trial to be considered successful, the participants had to land with
1 foot on each of the 2 adjacent force platforms, and all reflective markers had to be
visible to the cameras throughout the task.
Marker trajectories were identified
with the Qualisys Track Manager (Qualisys AB). Motion and force data were filtered using a 15-Hz smoothing spline.33
The contact phase consisted of the time
from initial contact to toe-off and was defined as the period when the unfiltered
vertical ground reaction force exceeded
20 N. Knee valgus angles and abduction
moments were obtained using custom
MATLAB scripts (The MathWorks, Inc,
Natick, MA). External knee joint moments were calculated using inverse dynamic equations.8
Peak knee valgus angles and external knee abduction moments during the
contact phase of the drop-jump task were
the variables of interest. Using the average for the right and left knees, the jump
with the highest valgus angles out of the
3 trials for all participants was chosen, as
this jump reflected the worst trial for the
participant and better corresponded to
the procedures used during the real-time
observational screening.
Statistical Analysis
Statistical analyses were performed using SPSS for Windows Version 18 (SPSS
Rater 1
Rater 2
Rater 3
Rater Consensus†
Good control
32 (53)
31 (52)
29 (48)
31 (52)
Reduced control
14 (23)
19 (32)
22 (37)
20 (33)
Poor control
14 (23)
10 (17)
9 (15)
9 (15)
60
60
60
60
Total
*Values are n (%) or n.
†
Rater consensus is defined as the score being given by at least 2 of the 3 raters.
Inc, Chicago, IL). Using the consensus
scores, differences in knee valgus angles
and abduction moments between the
groups rated as having good, reduced,
and poor knee control were determined
using 1-way analyses of variance. Post hoc
testing consisted of the Tukey honestly
significant difference test. The Spearman
rank correlation coefficient was used to
assess the association among the classification of participants from the observational screening test scores (independent
categorical variable) and knee valgus angles and abduction moments (dependent
continuous variables). This analysis was
performed for each of the raters, as well
as for the rater consensus scores. Correlation coefficients of 0.81 to 1.00 were interpreted as being very good, 0.61 to 0.80
as good, 0.41 to 0.60 as moderate, 0.21 to
0.40 as fair, and less than 0.20 as poor.3
The ability of each rater to identify participants with the highest knee valgus angles and abduction moments was assessed
with receiver-operating-characteristic
(ROC) curves. The area under the curve,
with 95% confidence intervals, was calculated for the 3 raters. Values for the ROC
range between 1.0 (perfect separation of
the test values) and 0.5 (no apparent distributional difference), and describe the
discriminative ability of a test.36
Interrater agreement among the 3
physiotherapists was assessed by calculating kappa coefficients for paired assessments.10,11,30 The kappa coefficient
is based on the percentage agreement
between raters and corrects for agreement expected by chance. Kappa coeffi-
20
Maximal Knee
Valgus Angle, deg
TABLE 1
Classification of Knee Control by the 3
Independent Raters and Rater Consensus*
15
10
5
0
–5
–10
Good
Reduced
Poor
Knee Control
FIGURE 3. Differences in knee valgus angles assessed
in real time between the groups of participants
rated as having good (n = 31), reduced (n = 20), and
poor (n = 9) knee control. The box represents the
interquartile range, with the median and range of
knee valgus angles.
cients were interpreted as follows: 0.81
to 1.00, almost perfect agreement; 0.61
to 0.80, substantial agreement; 0.41 to
0.60, moderate agreement; 0.21 to 0.40,
fair agreement; 0.01 to 0.20, slight agreement. Coefficients less than or equal to
zero were considered as poor agreement.19
For all analyses, we considered an alpha level of .05 or less as being statistically significant.
0.54 to 0.60, P≤.001) (TABLE 2). Based on
the ROC curves, the ability to identify
participants with high knee valgus angles
using real-time observational screening
was very good across all raters (TABLE 3).
RESULTS
Knee Abduction Moments
A
summary of the rating scores
of knee control, as determined by
the 3 physiotherapists, is presented
in TABLE 1. Based on the rater consensus,
half of the participants were rated as
having good frontal plane knee control,
whereas 33% and 15% were rated with
reduced and poor control, respectively.
Knee Valgus Angles
The analysis of variance comparing knee
valgus angles across groups was significant (P≤.001) (FIGURE 3). Post hoc testing
revealed that participants rated with poor
knee control had higher mean  SD knee
valgus angles compared to participants
with good control (10.3°  3.4° versus
1.9°  4.3°). Furthermore, participants
rated as having reduced knee control
(5.4°  4.1°) differed from the groups
rated as good and poor control.
The correlation between the real-time
observational screening test scores and
knee valgus angles was moderate for all
3 raters, as well as for the rater consensus (correlation coefficients ranging from
The analysis of variance comparing peak
knee abduction moments for participants
rated with good, reduced, and poor knee
control was not significant (P = .20)
(FIGURE 4). In addition, the correlations
between peak knee abduction moments
and the real-time observational screening test scores were not significant (TABLE
2). Based on the ROC curves, the ability
to identify participants with high peak
knee abduction moments using real-time
observational screening was moderate
across all raters (TABLE 3).
The interrater agreement among the
physiotherapists with respect to classifying participants as having good, reduced,
or poor knee control was substantial to
almost perfect. Percentage agreement
and kappa coefficients ranged from 70%
to 95% and 0.52 to 0.92, respectively
(TABLE 4).
DISCUSSION
T
he results of the current study
suggest that participants with high
knee valgus angles during a vertical
journal of orthopaedic & sports physical therapy | volume 44 | number 5 | may 2014 | 361
TABLE 2
research report
]
Spearman Rank Correlation Coefficients
Evaluating the Association Among the
Observational Screening Test Scores and
Knee Valgus Angles and Abduction Moments
for All 3 Raters and Rater Consensus
Valgus Angle Correlations*
P Value
Abduction Moment Correlations*
P Value
Rater 1
0.58 (0.39, 0.74)
≤.001
0.11 (–0.16, 0.35)
.40
Rater 2
0.54 (0.34, 0.70)
≤.001
0.11 (–0.15, 0.34)
.39
Rater 3
0.60 (0.41, 0.75)
≤.001
0.09 (–0.17, 0.32)
.49
Rater consensus
0.56 (0.34, 0.71)
≤.001
0.11 (–0.16, 0.34)
.41
*Values in parentheses are 95% confidence interval.
TABLE 3
The AUC for All 3 Raters
Valgus Angle AUC*
P Value
Abduction Moment AUC*
P Value
Rater 1
0.88 (0.79, 0.97)
.001
0.57 (0.39, 0.75)
.44
Rater 2
0.85 (0.74, 0.96)
.001
0.57 (0.40, 0.75)
.46
Rater 3
0.89 (0.80, 0.98)
.001
0.56 (0.38, 0.75)
.56
Abbreviation: AUC, area under the curve.
*Values in parentheses are 95% confidence interval.
drop-jump landing task can be identified
using real-time observational screening. Our findings support the hypothesis
that participants scored as having poor
or reduced knee control would display
higher knee valgus angles than participants scored as having good knee control,
and that the observational screening test
scores would be correlated to the knee
valgus angles. However, the observational
screening was not capable of identifying
participants with high peak abduction
moments. Our findings also indicate that
real-time observational scores are consistent among physiotherapists who receive
rating instructions and training in scoring knee control.
There were significant differences in
peak knee valgus angles between participants rated as having good, reduced,
and poor knee control. Furthermore, the
observational classifications correlated
moderately with the objectively measured
valgus angles. Moreover, our results revealed that the observational screening
test had a discriminating accuracy (area
under the curve) of 0.85 to 0.89 for all
3 raters, with respect to identifying high
valgus angles and distinguishing players
with poor knee control. Our findings suggest that real-time observational screening may be useful for identifying athletes
who would benefit from injury-prevention training.
Our findings are consistent with a
previously published study of a cohort
of elite handball players that compared
observational screening scores to valgus
angles measured with 2-D frontal plane
video analysis.31 These authors31 used the
same scoring system as that of the current study, and found good agreement
between the subjective assessment of
players with poor knee control and valgus
angles measured from frontal plane video. Similar to our study, Ekegren et al10
compared observational evaluations of
frontal plane knee control during a dropjump landing to valgus angles measured
with 3-D motion analysis, and reported
substantial specificity (60%-72%) but
inadequate sensitivity (67%-87%). These
authors10 defined athletes with valgus
angles above 10.8° as high-risk individu-
362 | may 2014 | volume 44 | number 5 | journal of orthopaedic & sports physical therapy
Maximal Knee Abduction
Moment, Nm/kg
[
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Good
Reduced
Poor
Knee Control
FIGURE 4. Differences in knee abduction moments
(Nm/kg) assessed in real time between the groups of
participants rated as having good (n = 31), reduced
(n = 20), and poor (n = 9) knee control. The box
represents the interquartile range, with the median
and range of knee abduction moments.
als who were more likely to experience
an injury. Interestingly, this value corresponded closely to the valgus angles for
participants displaying poor control in
the current study. Another study24 compared the frontal plane projection angle
and knee separation distance measured
from 2-D video recordings and 3-D motion analysis and reported intraclass
correlation coefficients of 0.89 to 0.97,
demonstrating higher agreement than
that reported in the current study. This is
logical, as video analysis permits a more
standardized and detailed assessment
than real-time observational screening.
On average, the mean peak knee abduction moments of the participants in
our study were relatively low (0.33 Nm/
kg); however, considerable variability
was observed (range, 0.08-0.60 Nm/kg).
There was no correlation between the
subjective classification of participants’
knee control and objective measures of
knee abduction moments for any of the
raters. This finding was further confirmed
by the poor discriminative accuracy with
respect to the knee moments, with areaunder-the-curve values at or below 0.57
for all 3 raters. This suggests that realtime observational screening cannot be
used to identify those individuals with
high knee abduction moments during a
vertical drop-jump task. Furthermore, a
post hoc analysis revealed that the correlation between knee valgus angles and ab-
TABLE 4
Rater
Interrater Agreement for Classifying
Participants as Having Good, Reduced,
or Poor Knee Control
Agreement, %
Kappa Value
Rater 1 versus rater 2
72
0.54
Rater 1 versus rater 3
70
0.52
Rater 2 versus rater 3
95
0.92
duction moments in our study was poor
(r = 0.04), which indicates that factors
other than knee valgus angles may contribute to knee abduction moments. Our
findings of no correlation between abduction moments and knee valgus angles are
somewhat surprising, considering those
of a previous study16 that reported a significant correlation between knee valgus
angles and abduction moments (0.51)
in a cohort of Norwegian handball players. It should be noted, however, that
the present study considered peak knee
abduction moments during the entire
stance phase, whereas Kristianslund and
Krosshaug16 only considered knee abduction moments during the first 100 milliseconds of the stance phase.
In the current study, rater consensus
was reached for all 60 participants, and
there was substantial to almost perfect
agreement between the 3 raters (70%95%), with kappa coefficients ranging
from 0.52 to 0.92. The raters were sports
physiotherapists with different levels of
experience, and their consistent scores
suggest that observational screening can
be used by other clinicians, assuming that
adequate training is provided.
The observational screening procedures used in the current study were
evaluated in a previous investigation by
Stensrud et al,31 who reported high intrarater agreement (κ = 0.90). Ekegren
et al10 investigated interrater agreement
for 3 physiotherapists using the dropjump test to evaluate knee control. Using
video footage captured by a digital camcorder, the participants were rated twice,
1 month apart. Multirater kappa coefficients of 0.80 and 0.77 were reported at
the 2 time points. However, the observa-
tional screening evaluation was based on
reviews of video recordings, and the rating procedures differed from the current
study. These authors10 used a dichotomous rating scale, classifying the player
as either landing with the knees medial to
the toes or in line with the toes, whereas
the current study scored frontal plane
knee control using 3 categories. Hence,
differences in the rating procedures limit
the ability to directly compare the level of
rater agreement across studies.
A potential limitation of the current
study is that the real-time observational
screening and the motion analysis were
not assessed simultaneously, hence 2 separate jumps were evaluated. Though the
test procedures were similar, participants
might have performed the 2 jumps differently. It should also be acknowledged
that an overhead target was included in
the screening test but not in the motion
analysis lab, due to technical reasons related to the camera system. Using a ball
as an overhead target in the screening
test might have affected performance
and resulted in a knee-motion pattern
that differed from that during the 3-D
motion analysis.
Even though 3-D motion analysis is
considered the gold standard for assessing lower extremity kinetics and kinematics, there are several potential sources of
error, including marker placement, skin
movement artifacts, and joint-center estimations.4,6,9,20 These factors could affect
the accuracy of the calculated joint angles
and moments. Another limitation of the
present study is that the valgus angles
and abduction moments for the right and
left knees from the 3-D analysis were averaged, which precluded the assessment
of potential side-to-side differences.
However, as the observational screening
test was based on an overall evaluation of
frontal plane knee control rather than a
single-leg assessment, calculating the average values enabled a better comparison
to the observational scores.
We also acknowledge that mediolateral knee motion observed by the raters
represents a multiplane and multijoint
pattern that not only consists of knee valgus motion but also involves ankle, knee,
and hip motions in the transverse plane.
The rationale for investigating frontal
plane knee kinematics and kinetics is
that these variables have previously been
shown to predict ACL injuries in female
athletes14 and that a valgus collapse has
been identified as a part of the ACL injury mechanism.5,15,18,28 In addition, existing screening tools developed to identify
knee injury risk have focused on frontal
plane knee kinematics and kinetics.10,27,29
Although the real-time assessment of
knee control appears to be promising for
large-scale screening of athletes, there is
a need to investigate the predictive value
of such screening for knee injuries.
CONCLUSION
P
hysiotherapists can identify female athletes with high knee valgus
angles during a vertical drop-jump
landing using real-time observational
screening. We found a moderate correlation between the observational screening test scores and objectively measured
knee valgus angles for all 3 raters. However, the screening test scores correlated
poorly with knee abduction moments.
Finally, we found substantial to almost
perfect interrater agreement among the
3 physiotherapists, suggesting that the
observational screening test can provide
reliable results when used by physiotherapists who receive training similar to that
provided in this study. t
KEY POINTS
FINDINGS: Physiotherapists can identify
female athletes with high knee valgus
journal of orthopaedic & sports physical therapy | volume 44 | number 5 | may 2014 | 363
[
angles during a drop-jump landing task
using real-time observational screening.
However, the observational screening
test scores did not correlate with knee
abduction moments.
IMPLICATIONS: The screening procedures
used in the current study are simple and
easy to use and implement in a clinical setting, as they do not necessitate
specialized equipment. Real-time assessment using a simple screening test
enables large-scale screenings of athletes with the aim of identifying those at
risk for knee injury.
CAUTION: The predictive ability of the observational screening test with respect
to knee injury was not assessed in the
current study.
research report
7.
8.
9.
10.
ACKNOWLEDGEMENTS: The authors acknowl-
edge all players in the Norwegian female elite
football league (Toppserien) for their participation in this study, and the physiotherapists
(J.K., G.M., and A.F.) who participated in
collecting the data. We also thank Kam-Ming
Mok for his valuable help with the data
processing.
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journal of orthopaedic & sports physical therapy | volume 44 | number 5 | may 2014 | 365