Abstract
Background:
Sport-related concussion is a public concern with between 1.6 and 3.8 million sport- and recreation-related injuries occurring annually. An estimated 65% to 90% of concussed athletes show oculomotor disruption such as difficulty with saccades, accommodation, smooth pursuit, and fixation. A rapid number-naming saccade test, the King-Devick (K-D) test, has shown promising results as part of a multifaceted concussion assessment tool.
Purpose:
The purpose of the current study was to evaluate the two versions of the K-D in collegiate aged (18-24) athletes to determine the agreement between versions. A secondary purpose was to investigate the association of K-D scores with sport, sex, use of glasses or contacts, and age of the athlete.
Study design:
Descriptive laboratory study.
Methods:
Division 1 NCAA collegiate athletes across ten sports were recruited to participate in baseline concussion assessments at the beginning of their respective athletic season. Correlations and multivariable logistic regression analyses were used to investigate the association of K-D scores with sex and age.
Results:
One-hundred and nine athletes (69 males, 40 females; mean age = 20.40 ± 1.38 years) were baseline tested. There was excellent agreement (ICC=0.93, 95% CI: 0.90, 0.95) between the paper and computer version. Preseason K-D scores were statistically different (r2=0.873, p<0.05) with athletes scoring a mean of 37.58 seconds on the paper version (95% CI, 36.21, 38.96) and athletes scoring a mean of 41.48 seconds for the computerized tablet version (95% CI, 40.17, 42.91). There were no significant differences in sex, sport, or use of glasses noted for both versions. Age differences were identified; eighteen-year-old athletes took statistically longer than their peers for both K-D versions. Pairwise comparisons showed statistically significant differences between 18-year olds up to the age of 21-year-olds (p<0.05) for the computer version and statistically significant differences between 18-year olds up to 22-year-olds (p<0.05) for the paper version.
Conclusion:
This study supports the use of either version of the K-D test as a potential part of a multifaceted concussion assessment. The age of the athlete influences scores and therefore a K-D baseline should be repeated annually for collegiate athletes. Clinicians should not substitute K-D versions (computer vs. paper) in comparing baseline to a post-concussion K-D score as the scores are quite different.
Level of evidence:
Level 3
Keywords: athletes, concussion, movement system, number-naming, oculomotor, saccades
INTRODUCTION
Concussion is a significant public health concern,1 prompting researchers and healthcare providers to investigate tools for assessment. In sport-related concussions, healthcare providers must decide on assessment tools that are efficient, affordable, and evidence-based. Baseline concussion testing of an athletic team using the recommended multifaceted approach can take hours. Therefore, healthcare providers face a conundrum when considering what tools to use, and must consider the time and effort of testing that is evidence-based. For example, in a rural high school or collegiate setting, there may only be one athletic trainer to baseline test 50 to 500 athletes. The school may not be able to meet all recommended guidelines for testing due to financial and personnel resource constraints. This leaves the athletic trainer facing the dilemma of deciding on what he or she can reasonably use for assessment tools from both a logistic and economic approach.
A multifaceted approach to baseline concussion assessment is recommended and should evaluate as many neuroanatomical functions efficiently as possible.2-4 Oculomotor assessment of saccades is supported in the literature as one component of a multifaceted evaluation of an athlete suspected of having a concussion.4-8 The King-Devick (K-D) test has been well researched and authors have reported excellent test-retest reliability in athletes from multiple sports.6-12 These cohorts were predominantly male with smaller sample sizes.6,8,9,11,13-15 In 2015, King-Devick Technologies, inc® phased out the original spiral-bound, or paper, version to a computerized tablet version. Differences in the two versions have been examined in younger athletes (mean age of 15.7) and excellent agreement (ICC=0.92, 95% CI 0.82, 0.96) was found.16 Recently, researchers examined the two versions of the K-D in collegiate athletes and found similar results as the previous study investigating younger athletes.16,17
The computerized tablet version of the K-D requires an electronic device for collecting data and requires an annual subscription whereas the paper version of the K-D is inexpensive. The manufacturer of the K-D suggests that the computerized tablet version K-D is more effective in assessing oculomotor function as compared to the paper version. The purpose of the current study was to evaluate the two versions of the K-D in collegiate aged (18-24) athletes to determine the agreement between versions. A secondary purpose was to investigate the association of K-D scores with sport, sex, use of glasses or contacts, and age of the athlete. The hypothesis was that the paper K-D test would positively correlate with the computer version K-D test.
METHODS
The current study used a prospective cohort research design to evaluate the King–Devick test trials in 109 Division 1 NCAA collegiate athletes. For inclusion in the study, athletes were required to be 18 to 24 years old and possess sufficient English language skills to complete all tasks. Exclusion criteria were lower extremity musculoskeletal injuries in the prior three months; a history of a head injury in the past year; or a diagnosis of visual, vestibular, or balance disorders. Additionally, athletes were asked if they had ever been diagnosed as having a learning disorder, attention deficit disorder, or dyslexia, and athletes were excluded if the answer was affirmative. Athletes provided informed consent and all experimental procedures were approved by the institutional review board at Northern Arizona University. Athletes were recruited between July and December 2017. All testing was conducted within the university athletic training room to provide adequate lighting. Background noise and distractions were not controlled and varied across baseline testing days. Athletes were permitted to use glasses or contacts if they were needed to perform the test. The K–D test was performed with the athlete in a seated position at a self-selected distance for reading both versions of the K-D, which was approximately 40 cm away from the athlete, similar to recent studies.2,16 All athletes received standardized instructions before performing both versions of the K–D test in random order. The researcher, when testing with the paper version, started the stopwatch timer for the K–D score when the athlete read the first number on the K-D, and stopped the timer when the participant completed the last number of the K-D test card. The computerized tablet version timer started or stopped by the researcher touching the screen in between each K-D test card. This procedure was repeated two times and randomized by a random number generator for both versions of the K-D test and the K–D baseline score was recorded for both versions of the test. If the athlete made an error, the K-D test card was repeated until error-free.
A power analysis was conducted using PASS software version 12 (NCSS Statistical Software, Kaysville, Utah) that indicated that 82 participants were needed. For the current study, ICC's were used to measure agreement, and an ICC less than 0.40 indicated poor reliability, an ICC between 0.40 and 0.75 indicated moderate to good reliability, and an ICC greater than 0.75 indicated excellent reliability.18 Significance was set at (p<0.05) and 95% confidence intervals were reported when appropriate. Statistical software program SPSS version 24.0 (IBM, Armonk, New York) was used for the analyses.
RESULTS
One hundred and nine athletes (69 males, 40 females; mean age = 20.40 ± 1.38 years) were baseline tested. The demographic characteristics of the athletes, as well as the K-D score, are shown in Table 1. Preseason K-D scores were correlated across version but statistically different (r=0.873, p<0.05) with athletes scoring a mean of 37.58 seconds on the paper version (95% CI, 36.21, 38.96) and athletes scoring a mean of 41.48 seconds for the computerized tablet version (95% CI, 40.17, 42.91) (Table 1). Figure 1 shows the regression model comparison of the paper version to the computerized tablet version of the K-D (p<0.05, R2=0.762). As can be observed in Figure 1, all K-D results were included and two athletes had prolonged scores on both versions of the K-D.
Table 1.
Demographic Characteristics of the Athletes of the Current Study (N=109)
| Demographic Characteristic | No. (%) or Mean (SD)a |
|---|---|
| K-D computer score K-D paper score | 41.48 (6.93) 37.58 (6.94) |
| Male | 69 (63) |
| Female | 40 (36) |
| Age, y | 20.40 (1.39) |
| Glasses/contacts | 29 (26.6) |
| Sport | |
| Football | 45 (41.28%) |
| Men's basketball | 6 (.05%) |
| Cross country | 4 (.03%) |
| Track and field | 15 (13.76%) |
| Swimming and diving | 19 (17.43%) |
| Men's tennis | 7 (.06%) |
| Women's tennis | 3 (.02%) |
| Women's soccer | 5 (.04%) |
| Golf | 4 (.03%) |
| Women's basketball | 1 (.009%) |
K-D=King-Devick; K-D computer score, K-D paper score, and age are reported as mean (SD).
Figure 1.
Regression model of King-Devick (K-D) test scores for the computer version and the spiral bound paper version.
KDcomp on the y-axis represents King-Devick computerized tablet version baseline scores and KDpaper on the x-axis represents the spiral-bound King-Devick baseline scores.
The mean K-D score comparisons for both versions of the K-D specific to the athlete's sport participation are presented in Table 2. The mean K-D score comparisons specific to sex are presented in Table 3. The mean K-D score comparisons specific to the use of glasses or contacts are presented in Table 4. There were no significant differences noted for both K-D versions scores by sex, sport, or use of glasses. Table 5 shows the mean K-D score comparisons specific to age. Age differences in scores were identified across ages, but the eighteen-year-old athletes took longer than their peers for both versions of the K-D. Pairwise comparisons showed statistically significant differences between 18-year-olds up to the age of 21-year-olds (p<0.05) for the computer version and statistically significant differences between 18-year-olds up to 22-year-olds (p<0.05) for the paper version.
Table 2.
Mean King-Devick (K-D) Score Comparisons Specific to Sport Participation of the Athletes of the Current Study (N=109)
| Estimates | |||||||
|---|---|---|---|---|---|---|---|
| 95% Confidence Interval | |||||||
| Dependent Variable | Sport | Mean | Std. Error | N | Lower Bound | Upper Bound | |
| KD computer | Football | 41.018 | .991 | 45 | 39.051 | 42.985 | |
| Men's basketball | 37.267 | 2.715 | 6 | 31.879 | 42.654 | ||
| Women's basketball | 37.200 | 6.651 | 1 | 24.003 | 50.397 | ||
| Cross country | 41.125 | 3.325 | 4 | 34.527 | 47.723 | ||
| Track and field | 40.173 | 1.717 | 15 | 36.766 | 43.581 | ||
| Swim and dive | 46.553 | 1.526 | 19 | 43.525 | 49.580 | ||
| Men's tennis | 38.429 | 2.514 | 7 | 33.441 | 43.416 | ||
| Women's tennis | 36.400 | 3.840 | 3 | 28.781 | 44.019 | ||
| Women's soccer | 42.800 | 2.974 | 5 | 36.898 | 48.702 | ||
| Golf | 42.825 | 3.325 | 4 | 36.227 | 49.423 | ||
| KD paper | Football | 36.088 | .942 | 45 | 34.218 | 37.957 | |
| Men's basketball | 35.237 | 2.580 | 6 | 30.117 | 40.356 | ||
| Women's basketball | 29.630 | 6.320 | 1 | 17.089 | 42.171 | ||
| Cross country | 40.485 | 3.160 | 4 | 34.215 | 46.755 | ||
| Track and field | 35.718 | 1.632 | 15 | 32.480 | 38.956 | ||
| Swim and dive | 44.053 | 1.450 | 19 | 41.176 | 46.930 | ||
| Men's tennis | 34.450 | 2.389 | 7 | 29.710 | 39.190 | ||
| Women's tennis | 35.093 | 3.649 | 3 | 27.853 | 42.334 | ||
| Women's soccer | 41.226 | 2.827 | 5 | 35.618 | 46.834 | ||
| Golf | 36.000 | 3.160 | 4 | 29.730 | 42.270 | ||
Table 3.
Mean King-Devick (K-D) Score Comparisons Specific to Sex of the Athletes of the Current Study (N=109)
| Descriptive Statistics | ||||
|---|---|---|---|---|
| sex | Mean | Std. Deviation | N | |
| K-D computer | females | 41.7450 | 8.16675 | 40 |
| males | 41.3319 | 6.16168 | 69 | |
| Total | 41.4835 | 6.93032 | 109 | |
| K-D paper | females | 37.6065 | 7.93617 | 40 |
| males | 37.5652 | 6.34787 | 69 | |
| Total | 37.5804 | 6.93653 | 109 | |
N represents the number of athletes of each sex.
Table 4.
Mean King-Devick (K-D) Score Comparisons Specific to Glasses or Contacts Used by the Athletes of the Current Study (N=109)
| Descriptive Statistics | ||||
|---|---|---|---|---|
| vision | Mean | Std. Deviation | N | |
| K-D computer | no glasses | 41.0013 | 7.13546 | 80 |
| glasses | 42.8138 | 6.25350 | 29 | |
| Total | 41.4835 | 6.93032 | 109 | |
| K-D paper | no glasses | 36.5370 | 6.51174 | 80 |
| glasses | 40.4586 | 7.36621 | 29 | |
| Total | 37.5804 | 6.93653 | 109 | |
N represents the number of athletes in each category
Table 5.
Mean King-Devick (K-D) Score Pairwise Comparisons Specific to Age of the Athletes of the Current Study (N=109)
| Pairwise Comparisons | |||||||
|---|---|---|---|---|---|---|---|
| 95% Confidence Interval for Differenceb | |||||||
| Dependent Variable | (I) age | (J) age | Mean Difference (I-J) | Std. Error | Sig.b | Lower Bound | Upper Bound |
| KDcomp | 18.00 | 19.00 | 7.073* | 2.599 | .008 | 1.918 | 12.229 |
| 20.00 | 5.705* | 2.429 | .021 | .886 | 10.523 | ||
| 21.00 | 7.345* | 2.394 | .003 | 2.597 | 12.094 | ||
| 22.00 | 5.070 | 2.660 | .059 | -.206 | 10.347 | ||
| 23.00 | 6.479 | 3.447 | .063 | -.358 | 13.315 | ||
| 24.00 | 6.345 | 7.093 | .373 | -7.724 | 20.415 | ||
| 19.00 | 18.00 | -7.073* | 2.599 | .008 | -12.229 | -1.918 | |
| 20.00 | -1.369 | 2.067 | .509 | -5.468 | 2.731 | ||
| 21.00 | .272 | 2.025 | .893 | -3.744 | 4.288 | ||
| 22.00 | -2.003 | 2.333 | .393 | -6.631 | 2.626 | ||
| 23.00 | -.594 | 3.202 | .853 | -6.945 | 5.756 | ||
| 24.00 | -.728 | 6.978 | .917 | -14.568 | 13.112 | ||
| 20.00 | 18.00 | -5.705* | 2.429 | .021 | -10.523 | -.886 | |
| 19.00 | 1.369 | 2.067 | .509 | -2.731 | 5.468 | ||
| 21.00 | 1.641 | 1.802 | .365 | -1.933 | 5.214 | ||
| 22.00 | -.634 | 2.143 | .768 | -4.884 | 3.616 | ||
| 23.00 | .774 | 3.065 | .801 | -5.306 | 6.854 | ||
| 24.00 | .641 | 6.916 | .926 | -13.077 | 14.359 | ||
| 21.00 | 18.00 | -7.345* | 2.394 | .003 | -12.094 | -2.597 | |
| 19.00 | -.272 | 2.025 | .893 | -4.288 | 3.744 | ||
| 20.00 | -1.641 | 1.802 | .365 | -5.214 | 1.933 | ||
| 22.00 | -2.275 | 2.102 | .282 | -6.445 | 1.895 | ||
| 23.00 | -.867 | 3.037 | .776 | -6.891 | 5.158 | ||
| 24.00 | -1.000 | 6.904 | .885 | -14.693 | 12.693 | ||
| 22.00 | 18.00 | -5.070 | 2.660 | .059 | -10.347 | .206 | |
| 19.00 | 2.003 | 2.333 | .393 | -2.626 | 6.631 | ||
| 20.00 | .634 | 2.143 | .768 | -3.616 | 4.884 | ||
| 21.00 | 2.275 | 2.102 | .282 | -1.895 | 6.445 | ||
| 23.00 | 1.408 | 3.251 | .666 | -5.040 | 7.857 | ||
| 24.00 | 1.275 | 7.000 | .856 | -12.610 | 15.160 | ||
| 23.00 | 18.00 | -6.479 | 3.447 | .063 | -13.315 | .358 | |
| 19.00 | .594 | 3.202 | .853 | -5.756 | 6.945 | ||
| 20.00 | -.774 | 3.065 | .801 | -6.854 | 5.306 | ||
| 21.00 | .867 | 3.037 | .776 | -5.158 | 6.891 | ||
| 22.00 | -1.408 | 3.251 | .666 | -7.857 | 5.040 | ||
| 24.00 | -.133 | 7.336 | .986 | -14.683 | 14.417 | ||
| 24.00 | 18.00 | -6.345 | 7.093 | .373 | -20.415 | 7.724 | |
| 19.00 | .728 | 6.978 | .917 | -13.112 | 14.568 | ||
| 20.00 | -.641 | 6.916 | .926 | -14.359 | 13.077 | ||
| 21.00 | 1.000 | 6.904 | .885 | -12.693 | 14.693 | ||
| 22.00 | -1.275 | 7.000 | .856 | -15.160 | 12.610 | ||
| 23.00 | .133 | 7.336 | .986 | -14.417 | 14.683 | ||
| KDpaper | 18.00 | 19.00 | 7.477* | 2.578 | .005 | 2.365 | 12.590 |
| 20.00 | 6.100* | 2.409 | .013 | 1.322 | 10.879 | ||
| 21.00 | 8.122* | 2.374 | .001 | 3.413 | 12.831 | ||
| 22.00 | 5.705* | 2.638 | .033 | .473 | 10.938 | ||
| 23.00 | 6.724 | 3.418 | .052 | -.056 | 13.504 | ||
| 24.00 | 7.225 | 7.035 | .307 | -6.728 | 21.179 | ||
| 19.00 | 18.00 | -7.477* | 2.578 | .005 | -12.590 | -2.365 | |
| 20.00 | -1.377 | 2.049 | .503 | -5.442 | 2.688 | ||
| 21.00 | .645 | 2.008 | .749 | -3.338 | 4.628 | ||
| 22.00 | -1.772 | 2.314 | .446 | -6.362 | 2.818 | ||
| 23.00 | -.753 | 3.175 | .813 | -7.051 | 5.544 | ||
| 24.00 | -.252 | 6.920 | .971 | -13.977 | 13.473 | ||
| 20.00 | 18.00 | -6.100* | 2.409 | .013 | -10.879 | -1.322 | |
| 19.00 | 1.377 | 2.049 | .503 | -2.688 | 5.442 | ||
| 21.00 | 2.022 | 1.787 | .261 | -1.522 | 5.565 | ||
| 22.00 | -.395 | 2.125 | .853 | -4.610 | 3.820 | ||
| 23.00 | .624 | 3.040 | .838 | -5.406 | 6.653 | ||
| 24.00 | 1.125 | 6.859 | .870 | -12.479 | 14.729 | ||
| 21.00 | 18.00 | -8.122* | 2.374 | .001 | -12.831 | -3.413 | |
| 19.00 | -.645 | 2.008 | .749 | -4.628 | 3.338 | ||
| 20.00 | -2.022 | 1.787 | .261 | -5.565 | 1.522 | ||
| 22.00 | -2.416 | 2.085 | .249 | -6.552 | 1.719 | ||
| 23.00 | -1.398 | 3.012 | .644 | -7.372 | 4.576 | ||
| 24.00 | -.896 | 6.846 | .896 | -14.476 | 12.684 | ||
| 22.00 | 18.00 | -5.705* | 2.638 | .033 | -10.938 | -.473 | |
| 19.00 | 1.772 | 2.314 | .446 | -2.818 | 6.362 | ||
| 20.00 | .395 | 2.125 | .853 | -3.820 | 4.610 | ||
| 21.00 | 2.416 | 2.085 | .249 | -1.719 | 6.552 | ||
| 23.00 | 1.018 | 3.224 | .753 | -5.377 | 7.414 | ||
| 24.00 | 1.520 | 6.942 | .827 | -12.250 | 15.290 | ||
| 23.00 | 18.00 | -6.724 | 3.418 | .052 | -13.504 | .056 | |
| 19.00 | .753 | 3.175 | .813 | -5.544 | 7.051 | ||
| 20.00 | -.624 | 3.040 | .838 | -6.653 | 5.406 | ||
| 21.00 | 1.398 | 3.012 | .644 | -4.576 | 7.372 | ||
| 22.00 | -1.018 | 3.224 | .753 | -7.414 | 5.377 | ||
| 24.00 | .502 | 7.275 | .945 | -13.928 | 14.931 | ||
| 24.00 | 18.00 | -7.225 | 7.035 | .307 | -21.179 | 6.728 | |
| 19.00 | .252 | 6.920 | .971 | -13.473 | 13.977 | ||
| 20.00 | -1.125 | 6.859 | .870 | -14.729 | 12.479 | ||
| 21.00 | .896 | 6.846 | .896 | -12.684 | 14.476 | ||
| 22.00 | -1.520 | 6.942 | .827 | -15.290 | 12.250 | ||
| 23.00 | -.502 | 7.275 | .945 | -14.931 | 13.928 | ||
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
DISCUSSION
These findings support that either the paper or the computerized version of the K-D test can be used as a baseline concussion measure for collegiate athletes. Reliability of the K-D test has been examined in multiple sports to include boxing,6 mixed martial arts,6 basketball,7,12 hockey,13 soccer,12,19 football,12,19,20 volleyball,19 rugby, softball,19 cheerleading,12,19 as well as in Army soldiers21 and recreational athletes.2 Intraclass Correlation Coefficients (ICC) ranged from 0.81 to 0.98 indicating excellent test-retest reliability. ICC's are used as a marker of repeatability in measures that are continuous and the findings of these studies are indicative of the ability of the K-D to repeatedly measure performance on a saccadic number-naming test across sport. In terms of an evidence-based concussion assessment tool, the K-D appears to be reliable in multiple sport populations.
In a recent study investigating collegiate athletes, authors investigated differences between the paper and computer version of the K-D during baseline testing.17 The authors investigated 13 women's and 11 men's collegiate sports and reported baseline K-D means of 42.8 seconds (95% CI, 42.1-43.3) and 40.0 seconds (95% CI, 39.7 to 40.3) for the computer and paper respectively. The authors noted a 2.8-second difference in the two versions of the K-D in athletes in their first year of collegiate athletic participation.17 The authors excluded athletes with a diagnosis of a learning disorder or attention deficit hyperactivity disorder. In the current study athletes differed by 3.9 seconds between the two versions of the K-D which is similar to the 3.7-second difference noted by Raynowska et al.16 The current study found similar time differences to other authors’ findings with the computer version being slower than the paper version of the K-D. This finding reinforces the Clugston et al17 findings that K-D scores are slower on the computer version and that the two versions of the K-D should not be used interchangeably as it may lead to the potential of underdiagnosing or over-diagnosing concussion.
The authors of the current study examined the two available administration versions of the test and found that their scores are highly correlated which suggests that the test is measuring the same construct. However, the scores are likely to differ (computerized version slower), thus, the authors would like to suggest that clinicians should not use one version of the K-D such as the paper version at baseline and another version such as the computer version after a suspected concussion as there is a statistically significant difference in the measures obtained between the two versions of this test. Two independent studies found similar results when comparing the two versions of the K-D but did not report the effect of confounding variables such as sex, sport, use of glasses/contacts, or age.16,17 The current study did not reveal significant differences for sex, sport, or use of glasses/contacts but significant differences were present when the age of the athlete was considered.
Similar to the findings of other authors investigating the K-D,2,13,22-24 the current study findings suggest that the age of the athlete should be considered when interpreting the K-D test. In terms of comparing age groups of athletes, several authors have noted age differences with improved K-D scores as age increases in junior high school,22 high school,23,24 college,7,24,25 and in professional athletes.6,13 Weise et al26 performed a cross-sectional study of junior high and high school athletes (mean age of 14.2) to compare relationships of the K-D to Optometric tests (ocular alignment, near point convergence, and pupil function via pupillometry). Weise et al26 reported no association between K-D and near point of convergence, ocular alignment, or pupillometry which suggests that these measures are evaluating different aspects of vision. The researchers did note that K-D scores improved, or decreased in time, with increasing age in junior high and high school athletes up to the age of 18 as they did not investigate older athletes. Hasanaj et al25 compared collegiate hockey athlete K-D scores to consider age differences in a small sample size (n=13). Hasanaj et al25 reported older age was a predictor of increased time, or poor K-D scores occurred for K-D baseline scores in older healthy males. The authors concluded that athlete age at the time of baseline testing should be considered when interpreting K-D scores and that increasing age may be a marker for the duration of contact sports exposure.25 Galetta et al6 have noted that athletes that took 5.9 seconds longer to complete the K-D in comparison to baseline scores were indicative of a concussion. Therefore, it is important to make sure that K-D testing is precise to ensure that athletes are not being misdiagnosed as having a concussion.
In the current study, the results suggest age differences in collegiate athletes need to be considered. Similar to other studies of collegiate athletes, almost all of the athletes in the current study improved their baseline K-D scores as the athlete aged.7,24,25 When considering the results of the current study, K-D baseline scores should be performed at preseason on an annual basis for collegiate athletes because using a K-D score from the previous year may change considerably depending on the age of the athlete. Moran and Covassin22 reported similar findings for 8 to 14-year-old athletes and recommended that athletes receive an annual baseline concussion assessment due to physiological changes occurring in the athlete during the year. Alsalaheen et al23 made similar recommendations for 13 to 18-year-old athletes, specifically that clinicians working with adolescents should consider frequent updates of baseline K-D scores. The current study results differed from previous studies that investigated adolescents most likely because the athletes in this study were collegiate athletes aged 18 to 24 and the current study results suggest that younger collegiate athletes should also have frequent updates of their baseline K-D scores.
In consideration of the cost of performing the K-D as a baseline test on an annual basis and in light of the current study's findings, the authors suggest that perhaps the paper version of the K-D test is more appropriate than the computerized tablet version. Currently, the cost for the computerized tablet version of the K-D test is listed on their website with three different rates: 1-99 athletes are $20 an athlete, 100-199 athletes are $15 an athlete, and 200 + are $10 an athlete. The paper version of the K-D test is no longer sold by King-Devick Technologies but was last sold in 2015 at $300 per test. The paper version could potentially be used indefinitely. The authors of the current study queried health care professionals at a regional athletic training meeting and the health care professionals noted that they copied the paper version test sheets and used the copies to test their athletes before every athletic season. This may have dissuaded King-Devick Technologies, Inc® to continue selling the paper version. The authors of the current study are concerned that the cost of this evidence-based tool will prevent administrators from high school athletics and collegiate athletic directors to consider using the computerized tablet version of the K-D test.
As part of a multifaceted approach, the cost of an assessment tool is not the only criteria to consider. Health care providers must use evidence-based tools. Recent studies have investigated the use of the K-D in comparison to other evidence-based concussion assessment tools to determine if the K-D is measuring a similar or different construct. The Vestibular Ocular Motor Screening (VOMS) is an evidence-based tool that has been investigated and is free. There are seven assessment components in the VOMS: saccades for horizontal and vertical, vestibular ocular reflex for horizontal and vertical, visual motion sensitivity, smooth pursuit, and near point convergence. Recently, authors investigating the use of the VOMS found that all seven assessment components of the VOMS were strongly correlated with K-D scores in concussed adolescents.27 Specifically, two of the seven assessment components (near point convergence and visual motion sensitivity) predicted K-D scores.27 Although the two assessment components of the VOMS are both visual tests and the K-D is an oculomotor test, the visual system is quite complex and these three tests involve different anatomical components of vision that change the angle of visual focus or gaze.4 The assessment components of these three vision tests utilizes different anatomical components of vision specifically saccades, vergence, and smooth pursuit. The VOMS and the K-D evaluate these three components of vision and only recently do authors suggest to collect this information at baseline as a reference comparator. The authors of the current study stress the importance of using an objective standardized approach to ensure reliable tests that assess as many neuroanatomical locations as possible in an efficient manner.
Limitations of the current study include a sample of convenience as athletes were recruited from the local university athletic department. Another potential limitation is that athletes were tested in a busy athletic training department which does not allow optimal circumstances of testing in a controlled quiet laboratory which could have influenced attention during testing of the athletes but best replicates clinical settings. Background noise and distractions were not controlled throughout the study and varied across baseline testing days. The authors note that this is a limitation that did vary across testing days but is realistic to a busy athletic training department. Another limitation was that representation across sports was not evenly distributed as it was reflective of the number of athletes within the sport. Ideally, when investigating differences across sports, there should be an even distribution across the sport to compare for differences.
CONCLUSION
This study supports the use of either version of the K-D test as a potential part of a multifaceted concussion assessment. The results of the current study suggest that the age of the collegiate athlete influences K-D scores therefore clinicians should consider testing athletes on an annual basis. Secondary to the differences noted in baseline scores across the two versions of the test, clinicians should not substitute K-D versions (computer vs. paper) in comparing baseline to a post-concussion K-D score. The authors recommend that clinicians perform a K-D test at baseline and that the K-D could be repeated annually for collegiate athletes.
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