Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 May 1.
Published in final edited form as: Clin J Sport Med. 2021 May 1;31(3):244–249. doi: 10.1097/JSM.0000000000000740

Multimodal Assessment of Sport-related Concussion

Natalie Sandel Sherry 1,2, Vanessa Fazio-Sumrok 1,2, Alicia Sufrinko 1,2, Michael W Collins 1,2, Anthony P Kontos 1,2
PMCID: PMC6751034  NIHMSID: NIHMS1521569  PMID: 30908330

Abstract

Objective:

The purpose of this study was to determine which assessments best identify athletes with sport-related concussion (SRC) from healthy controls in the acute/early subacute (within 10 days of SRC) of injury.

Design:

Prospective, cohort study.

Setting:

Specialty concussion clinic.

Participants:

Sixty-four athletes with SRC (52% male) and 59 matched (age, sex), healthy controls (56% male) aged 12 to 20 years old (M=15.07, SD=2.23).

Assessment:

Participants completed symptom, cognitive, vestibular/oculomotor, near point of convergence, and balance assessments.

Main Outcome Measures:

Univariate analyses were conducted to compare athletes with SRC to healthy controls across all assessments. Assessments that significantly differed between the SRC group and healthy controls were used as predictors in an enter method logistic regression (LR) model, and subsequent forward stepwise LR.

Results:

Results of LR analyses indicated that symptom inventory and symptom provocation on vestibular/oculomotor assessments significantly predicted athletes with SRC versus controls. The forward stepwise LR accurately classified 84.6% of the overall sample (78.3% of athletes with SRC and 91.2% of controls were accurately predicted), and accounted for 60.5% of the variance in predicting athletes with SRC versus controls. Total symptom inventory score (p=.003) and vestibular/oculomotor symptom provocation (p<.01) were the most sensitive and specific measures in a comprehensive, multimodal assessment for distinguishing athletes with SRC from healthy controls within 10 days of injury.

Conclusion:

Elements within a multimodal evaluation that are the most robust at discriminating athletes with SRC from healthy controls in the acute/early subacute phase of injury include symptom report and provocation of symptoms on vestibular/oculomotor assessment. These assessments should be considered in conjunction with other objective assessments (i.e., near point of convergence measurement, cognitive testing) as part of a comprehensive evaluation of SRC.

Keywords: sport-related concussion, symptoms, vestibular, oculomotor, multimodal, mtbi

Introduction

International consensus statements1–5 have advocated for the inclusion of a multimodal approach to managing SRC1 due to the heterogeneous nature of the injury and to improve diagnostic yield. Based on recently defined criteria by the National Institute of Health (NIH)6 the standard components of a comprehensive, multimodal approach to assessing SRC includes an assessment of symptoms7–9, cognitive/mental status 10–15, vestibular/oculomotor function 16,17, near point of convergence 17–21, and balance 22–25. Researchers have demonstrated the effectiveness of a multimodal approach for diagnosing mild traumatic brain injury (mTBI) in adult populations with non-sport injuries, and found that an integration of vestibular/oculomotor and cognitive assessments has good sensitivity and specificity for identifying individuals with mTBI from healthy controls26,27. However, the generalizability of these study findings to populations of adolescent/young adult athletes with uncomplicated, sport-related injuries is questionable given these studies did not exclude patients with complicated mTBI (e.g., intracranial bleed, skull fracture) or life-threatening traumatic injuries (e.g., bullet-related, blast exposure)26,27, some patients were evaluated up to five years post-injury26, and the studies were conducted among adults26,27 who are known to demonstrate different recovery patterns from youth28–30. McDevitt et al.31 evaluated the utility of a battery of vestibular/oculomotor assessments for differentiating athletes diagnosed with SRC within 4–90 days post-injury in a sample of collegiate athletes, and found good sensitivity (91.7%) and specificity (81.7%) for components of vestibular/oculomotor screening. However, other elements of a standard evaluation of SRC (i.e., cognitive testing, symptom inventories)6 were not included as part of their analyses, thus limiting conclusions regarding the usefulness of vestibular/oculomotor screening within a multimodal model for evaluation of SRC. Although these studies provide preliminary support for the use of a multimodal assessment approach for diagnosing concussion, the results may not be generalizable to evaluating adolescent and young adults with recently sustained, uncomplicated sport-related concussions, who are otherwise healthy. Limited studies have investigated the sensitivity and specificity of a multimodal approach for diagnosing SRC, or the tools within a standard evaluation6 that are most robust for detecting the injury among athletes. Understanding which tools within a multimodal evaluation are the most robust in discriminating athletes with SRC from healthy athletes is important for clinicians who rely on functional outcomes to make clinical judgments regarding diagnosis and return to play decisions after a suspected injury.

The objective of the current study was to determine which assessments from a comprehensive, multimodal approach- including symptom inventory, cognitive testing, vestibular/oculomotor screening, near point of convergence (NPC) measurement, and balance assessments- best identify adolescent and young adult athletes with SRC from healthy controls within 10 days of injury (i.e., acute/early subacute). We hypothesized that higher symptom severity scores on the symptom inventory; worse cognitive, balance, and vestibular/oculomotor impairment; and higher NPC distance would discriminate athletes with SRC from healthy controls

Methods

Participants

Participants in this study were prospectively recruited through an outpatient concussion clinic as part of a larger research initiative, and must have been diagnosed with an SRC by a licensed healthcare professional based on international criteria1. Specifically, diagnosis was made based upon the presence of 1) evidence of a forcible blow to the head, 2) acute onset of symptoms or markers of head injury (e.g., headache, loss of consciousness [LOC], 3) performance on SRC assessment tools (i.e., cognitive testing, vestibular/oculomotor screening), and 4) a pattern of symptoms characteristic of SRC over time that could not be accounted for by another medical condition (e.g., learning disorder, history of strabismus). Given that the diagnosis of SRC remains a clinical judgment, clinicians in this study rendered a diagnosis based upon a multitude of available evidence from a thorough clinical interview, review of records (e.g., performance on sideline assessments, emergency department visits, pediatrician examinations), SRC assessment tools (i.e., cognitive testing, symptom inventories, balance testing, vestibular/oculomotor screening), and consideration of past personal and family medical history. Although the assessments in the multimodal evaluation of interest in this study were considered by clinicians when determining diagnosis of SRC, the assessment tools are only a portion of the available evidence that clinicians considered when making a diagnosis. Inclusion criteria for participants with SRC included: a sport-related mechanism of injury, males and females aged 12 to 20 years old, and completion of their initial visit for evaluation of SRC within 10 days of injury. Athletes with SRC sustained their injury within 2 to 10 days (M=6.94, SD=2.30) of their initial clinic visit, and completed the multimodal assessment at this visit. Healthy controls (i.e., non-concussed individuals per self-report) were recruited from the local community (i.e., through a voluntary general research registry at the University of Pittsburgh, family/friends of SRC participants), and matched as closely as possible to concussed athletes on the basis of year of age and sex. Data was collected from October 2014 through June 2017. No incentives were provided for this study protocol and participation was voluntary. For healthy controls, inclusion criteria included: males or females aged 12 to 20 years old who were able to cooperate with consent procedures and complete all assessments. Information on the healthy controls’ participation in sports or physical activity was not collected as part of this study. Participants in both groups were excluded from the study if they met one or more of the following criteria: musculoskeletal disorder, brain surgery, moderate/severe TBI, persistent symptoms from a prior concussion, substance abuse disorder, psychiatric disorder, pre-existing vestibular disorder, symptomatic orthopedic injury to lower body, or neurological disorder. Healthy controls were also excluded if they were currently experiencing symptoms or impairment from a prior concussion or had a history of two or more concussions.

Measures

Symptom Inventory.

Symptoms were evaluated using the Post-Concussion Symptom Scale (PCSS) 8,32 as part of a computerized test battery. The PCSS is a 22-item symptom inventory for SRC, which encompasses physical, cognitive, affective, and sleep-related symptoms of concussion.32,33 Participants rated the presence and severity of symptoms on a Likert-type scale from 0 (not experiencing the symptom) to 6 (severe), for a total symptom severity score ranging from 0 to 132.

Cognitive.

The Immediate Post-concussion Assessment and Cognitive Testing (ImPACT)8 was used to evaluate cognitive impairment. The ImPACT tests yields four composite scores including verbal and visual memory, visual motor speed, and reaction time. cognitive-memory (Verbal Memory composite and Visual Memory composite) and cognitive-processing speed components (Visual Motor Speed composite and Reaction Time composite) were calculated using averaged z-score conversions from normative data34,35.

Vestibular and Oculomotor.

The Vestibular/Ocular Motor Screening (VOMS) tool is a brief clinical screening tool that assesses vestibular/oculomotor symptoms and impairment. The VOMS includes evaluations of the following head and eye movements: 1) smooth pursuits, 2) horizontal saccades, 3) vertical saccades, 4) horizontal vestibular ocular reflex (VOR), 5) vertical VOR, 6) visual motion sensitivity (VMS), and 7) near point of convergence (NPC). Patients rate on a Likert-type scale ranging from 0 (none) to 10 (severe) their experience of headache, dizziness, nausea and fogginess symptoms at baseline (i.e., prior to vestibular/oculomotor screening in static head and eye position) and following each VOMS component.16,17 Symptoms reported across each vestibular/oculomotor task can be totaled to yield a total VOMS score; the use of a combined score across vestibular/oculomotor tasks has demonstrated utility in discriminating between subjects with mTBI and controls17,26. Clinicians diagnosing SRC utilized the established cutoff (i.e., a score ≥2 on any vestibular/oculomotor task of the VOMS) for clinical decision making. Provocation of reported symptoms on the VOMS was calculated by subtracting baseline symptoms from the total VOMS score (excluding symptom provocation during NPC measurement)28 to yield provocation of symptoms during VOMS17,36, to isolate whether vestibular/oculomotor provocation when engaged in dynamic head/eye movement provides unique value to the multimodal assessment relative to evaluating symptoms in a static position, such as when completing a traditional symptom inventory. In addition, the average of three measurements (in centimeters) of NPC distance were conducted to evaluate convergence.

Balance.

The Balance Error Scoring System (BESS)37 was used to measure balance. The BESS is a clinical assessment of balance that examines the number of errors during the performance of static and dynamic postural stability. The BESS includes three stances- fee together, single leg, tandem leg- performed with eyes closed and hands placed on the iliac crests on a flat surface followed by a foam pad for a total of six trials23,37. A higher total BESS error score reflects more balance impairment.

Procedures

This University of Pittsburgh Institutional Review Board (IRB) approved the current study procedures. Participants and/or their parents completed informed written consent/assent prior to enrolling in the study, and after being informed of the study and its risks and benefits. All participants included in the study then completed the comprehensive assessments in the following order: PCSS, ImPACT, VOMS, and BESS. For participants diagnosed with SRC, assessments were completed as part of standard clinical care during their initial appointment in a concussion specialty clinic, with the exception of the BESS, which was conducted by research staff supervised by clinicians immediately preceding the clinic appointment. Healthy controls completed all assessments in a research laboratory by research staff trained in concussion assessment.

Data Analysis

Groups were compared using independent samples t-tests and chi-squared tests to evaluate differences on demographic variables. A series of univariate analyses of variance (ANOVAs) with Bonferroni correction for multiple comparisons ([α=.05/6] to control for multiple comparisons, p < .008) were conducted to compare the athletes with SRC and controls at their initial visit on total symptom inventory scores, cognitive-memory, cognitive-processing speed, VOMS, NPC measurement, and BESS. Assessments that significantly differed between the athletes with SRC and controls were then included in subsequent regression analyses. An initial enter method logistic regression (LR) was conducted to determine the ability of significant predictors from ANOVAs (symptom inventory score, cognitive-memory, vestibular/oculomotor screening, and NPC) to discriminate between athletes with SRC and controls. A follow-up forward stepwise LR was then performed that included only the significant predictors from the first model.

Results

A total of 64 athletes with SRC (52% male) and 59 controls (56% male) aged 12 to 20 years old (M=15.07, SD=2.23) were recruited as part of a larger study. There were no significant differences between the SRC and control groups on age, t(121)= −0.14, p=.89, sex, χ2(1, N=123) = .001, p=.97, history of greater than three concussions, χ2(1, N=121) = 2.74, p=.10, history of an attention disorder, χ2(1, N=123) = 2.07, p=.15, or a history of a learning disability, χ2(1, N=123) = 1.09, p=.30. A series of one-way ANOVAs revealed that athletes with SRC and controls significantly differed across symptom inventory score, cognitive-memory, vestibular/oculomotor screening, and NPC measurement. Results are presented in Table 1.

Table 1.

Results of ANOVAs with Bonferroni Correction for Multimodal Assessments

Concussed Controls
M SD M SD F p
Balance 12.60 4.54 10.59 4.77 5.69 .019
Cognitive Memory 90.02 20.14 102.16 13.77 14.91 <.001*
Cognitive Processing Speed 89.03 24.67 98.64 15.09 6.63 .011
Near Point of Convergence 5.06 8.23 1.16 2.20 12.40 .001*
Symptom Inventory 27.81 19.56 4.95 9.79 65.27 <.001*
Vestibular/Oculomotor Screening 38.23 31.86 4.14 11.73 57.89 <.001*
Open in a new tab
*

P < .008

These assessments were therefore included in subsequent analyses. An enter method LR was performed with athletes with SRC versus controls as the dependent variable, and the following assessments as predictor variables: symptom inventory score, cognitive-memory, vestibular/oculomotor screening, and NPC. A total of 117 cases were analyzed and the full model significantly predicted group membership for athletes with SRC and controls (χ2= 73.10, df = 4, p<.001). The model accounted for 62.0% of the variance in predicting athletes with SRC versus controls, with 83.8% of subjects correctly predicted (78.3% of athletes with SRC and 89.5% of controls were accurately predicted). Significant predictors in the model included the symptom inventory and vestibular/oculomotor screening, while all other predictors were non-significant (see Table 2).

Table 2.

Results of Enter Method Logistic Regression for Predicting Athletes with SRC from Controls

β SE Wald test p-value OR (95% CI)
Symptom Inventory −0.09 .03 6.93 .008* 0.92 (0.86 – 0.98)
Vestibular/Oculomotor Screening −0.05 .02 4.82 .03* 0.95 (0.91 – 0.99)
Cognitive Memory .002 .02 0.02 .90 1.00 (0.97 – 1.04)
Near Point of Convergence −0.17 .12 2.13 .15 0.84 (0.67 – 1.06)
Open in a new tab
*

p < .05

A follow-up forward stepwise LR was performed with athletes with SRC versus controls as the dependent variable, and the symptom inventory and vestibular/oculomotor screening as predictors. A total of 117 cases were analyzed and the full model significantly predicted athletes with SRC from controls (Step 1: χ2= 62.94, df = 1, p <.001; Step 2: χ2= 70.71, df = 2, p <.001). The model accurately predicted 84.6% of the overall sample (78.3% of athletes with SRC and 91.2% of controls were accurately predicted), and accounted for 60.5% of the variance in predicting athletes with SRC versus controls. Both predictors were retained in the model indicating that vestibular/ocular motor screening contributed unique variance beyond a symptom inventory in classifying SRC versus controls (see Table 3). These results suggest that symptom inventory and vestibular/oculomotor assessments are the most robust tools for differentiating athletes with SRC from healthy controls.

Table 3.

Results of Forward Stepwise Logistic Regression for Predicting Athletes with SRC from Controls

β SE Wald test p-value OR (95% CI)
Step 1
Constant 1.68 .35 22.52 <.001* 5.34
Symptom Inventory −0.14 .03 26.82 <.001* 0.87 (0.82 – 0.92)
Step 2
Constant 1.84 .37 24.11 <.001* 6.27
Symptom Inventory −0.09 .03 9.07 .003* 0.91 (0.86 – 0.97)
Vestibular/Oculomotor Screening −0.06 .02 6.09 .01* 0.95 (0.90 – 0.99)
Open in a new tab
*

p < .05

Discussion

The purpose of this study was to determine which clinical tools utilized in a standard multimodal assessment best discriminated athletes with SRC from healthy controls. The assessment methods evaluated in this study included total symptom inventory score, cognitive testing of memory and processing speed, vestibular/oculomotor screening, NPC measurement, and balance assessment. Results of a stepwise logistic regression yielded a significant model with the symptom inventory and vestibular/oculomotor screening as the most robust methods for discriminating athletes with SRC from controls. Utilizing these two clinical tools correctly classified 85% of the overall sample, with 78.3% of athletes with SRC and 91.2% of controls accurately classified. Performance on tests of cognitive-memory and NPC measurement significantly differed (p< .008) between athletes with SRC and controls on univariate analyses, but these assessments did not remain significant predictors when entered into a logistic regression model.

Results of this study are consistent with prior research demonstrating that athletes with SRC endorse more concussion symptoms than controls on self-report post-concussion symptom inventories38,39. However, this study also demonstrates that there are unique sensory-motor indicators after SRC, such as those elicited during vestibular/oculomotor screening that are not fully captured using a symptom inventory. Although symptoms characteristic of vestibular dysfunction (e.g., dizziness, headache, nausea, fogginess) are often assessed on post-concussion symptom inventories7–9, this study shows that evaluating the provocation of these symptoms during vestibular/oculomotor screening adds significant value to simply asking about these symptoms on an inventory. This is noteworthy given that central vestibular dysfunction is a common subtype of SRC that occurs in about 60% of injured athletes17. It is presumed that athletes may be unaware of vestibular symptoms until tasked with engaging in specific dynamic head and eye movements that elicit vestibular/oculomotor reflexes. This is consistent with prior research indicating that signs and symptoms reported during vestibular/oculomotor stimulation were a sensitive measure of SRC in a collegiate athlete population31, and vestibular, balance and oculomotor assessment were sensitive predictors of mTBI in non-sports-related injuries, among adults, and in protracted cases of mTBI26,27. Other domains of assessment in this study, including memory and NPC measurement significantly differed between SRC and control groups, but the symptom inventory and vestibular/oculomotor screening were the most sensitive and specific measures for accurately classifying athletes.

Although symptoms reported on an inventory and provoked by vestibular/oculomotor screening appear to be robust in diagnosing SRC, there are limitations to relying on measures that only examine symptoms. The practice of relying solely on reported symptoms rather than including objective measures in the evaluation of SRC is contraindicated for several reasons.40–43 First, athletes tend to underreport their symptoms in an effort to avoid missing playing time, and there can be other complicating psychosocial factors that may also influence symptom reporting (e.g., secondary gain, psychological diagnoses)1,44–47. Second, multimodal assessment is important for injury management beyond accurate diagnosis. Some studies have shown that symptoms resolve prior to cognitive or vestibular deficits28,42,48 and symptoms may not be the best measure to distinguish athletes who continue to exhibit concussion sequelae from healthy controls in later phases of recovery. Similarly, a multimodal approach should include a combination of both subjective and objective measures to delineate a comprehensive clinical profile of sequelae from the injury1–5 to assist with treatment recommendations.

Although this study provides information about the most useful methods for discriminating athletes with SRC from healthy controls, on an individual level there may be nuanced deficits after SRC across other clinical tools (e.g., balance assessment, cognitive testing), that were not fully captured in this study. For instance, athletes may have premorbid strengths and weaknesses in certain cognitive functions (e.g., above average reaction time), that after sustaining an SRC fell to the average range. This may be a significant decline for an individual athlete, but not fully captured when conducting research using a design evaluating between-group differences. In the future, it would be advantageous to collect larger samples with baseline (i.e., preinjury) data of athletes to explore within and between-group differences across subtests included in each of the assessment modalities investigated to further assist in clinical decision-making. There is research to indicate nuanced differences (i.e., premorbid cognitive strengths and weaknesses) in the performance of different athlete groups and non-athletes on traditional concussion assessment tools49–51, which were not accounted for in this study as our control group consisted of individuals from the local community regardless of their participation in sport. In the future, it would be advantageous to use a multimodal assessment to compare athletes with a concussion to a control group of athletes with other types of injuries (e.g., orthopedic injuries). Lastly, although vestibular/oculomotor screening yields both subjective information (i.e., reported provocation of symptoms), as well as an objective, clinical examination of neuromotor function, this study only utilized athletes’ report of provocation of symptoms as an outcome variable. Future studies should include coding of clinically observed impairment to determine whether this objective data adds additional utility to vestibular/oculomotor screening for SRC.

Overall, the current study demonstrates that symptom reporting on a post-concussion symptom inventory and symptom provocation on vestibular/oculomotor screening are the most sensitive and specific measures in a multimodal assessment for differentiating concussed athletes from controls within 10 days of injury. Utilizing a combination of these measures results in the correct classification of 85.0% of athletes. The findings from this study have several clinical implications. First, results of this study warrant the use of both symptom report inventories and vestibular/oculomotor screening in a multimodal assessment when determining diagnosis of concussion within 10 days of a potential injury. It also provides empirical evidence to assist clinicians’ judgment of which measures in a multimodal assessment offer the greatest utility in diagnosing SRC. This is important as the diagnosis of SRC largely remains a functional assessment guided by clinical judgment. The assessment model utilized in the current study indicated an acceptable diagnostic yield for SRC, but there remains a subset of individuals who were incorrectly classified (15%). This is particularly concerning in the case of false negatives (i.e., a concussed athlete who is misdiagnosed as healthy) in which an athlete may be at risk for being prematurely returned to play. This study supports the need for clinicians to understand the sensitivity and specificity of the clinical tools utilized when evaluating SRC and utilize multiple sources of information when available (e.g., clinical interview, sideline data) to supplement a multimodal assessment. Despite our findings that symptom reporting on an inventory and vestibular/oculomotor screening were the most useful measures for diagnosis in a multimodal assessment, we continue to advocate for a comprehensive, multimodal evaluation when assessing and managing the individual athlete with SRC. Future research should focus on the advancement of concussion assessment tools to improve clinical diagnosis and management of SRC.

Clinical Relevance:

Clinicians should include both symptoms and vestibular/oculomotor outcomes as part of a multimodal assessment to inform more accurate diagnosis of SRC in the acute and early sub-acute phases of injury.

Acknowledgments

Funding Received: National Institutes of Health (NIH) training grant. NIH NIDCD K01DC012332

References

  • 1.McCrory P, Meeuwisse W, Dvorak J, et al. Consensus statement on concussion in sport—the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med. 2017:bjsports-2017-097699. [DOI] [PubMed] [Google Scholar]
  • 2.McCrory P, Meeuwisse W, Aubry M, et al. Consensus statement on Concussion in Sport--the 4th International Conference on Concussion in Sport held in Zurich, November 2012. Journal of Science and Medicine in Sport / Sports Medicine Australia. 2013;16(3):178–189. [DOI] [PubMed] [Google Scholar]
  • 3.McCrory P, Meeuwisse W, Johnston K, et al. Consensus Statement on Concussion in Sport: the 3rd International Conference on Concussion in Sport held in Zurich, November 2008. British Journal of Sports Medicine. 2009;43 Suppl 1:i76–90. [DOI] [PubMed] [Google Scholar]
  • 4.McCrory P, Johnston K, Meeuwisse W, et al. Summary and agreement statement of the 2nd International Conference on Concussion in Sport, Prague 2004. British Journal of Sports Medicine. 2005;39(4):196–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Aubry M, Cantu R, Dvorak J, et al. Summary and agreement statement of the First International Conference on Concussion in Sport, Vienna 2001. Recommendations for the improvement of safety and health of athletes who may suffer concussive injuries. British Journal of Sports Medicine. 2002;36(1):6–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.National Institute of Neurological Disorders and Stroke. Sport-Related Concussion Common Data Elements. 2017; https://www.commondataelements.ninds.nih.gov/SRC.aspx#tab=Data_Standards. [DOI] [PMC free article] [PubMed]
  • 7.King NS, Crawford S, Wenden FJ, Moss NEG, Wade DT. The Rivermead Post Concussion Symptoms Questionnaire: a measure of symptoms commonly experienced after head injury and its reliability. Journal of neurology. 1995;242(9):587–592. [DOI] [PubMed] [Google Scholar]
  • 8.Lovell MR. The ImPACT Neuropsychological Test Battery. Sports Neuropsychology. New York: Guilford Press, Inc.; 2006. [Google Scholar]
  • 9.McLeod TC, Leach C. Psychometric properties of self-report concussion scales and checklists. Journal of athletic training. 2012;47(2):221–223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Cernich A, Reeves D, Sun W, Bleiberg J. Automated neuropsychological assessment metrics sports medicine battery. Archives of Clinical Neuropsychology. 2007;22:101–114. [DOI] [PubMed] [Google Scholar]
  • 11.Cole WR, Arrieux JP, Schwab K, Ivins BJ, Qashu FM, Lewis SC. Test-Retest Reliability of Four Computerized Neurocognitive Assessment Tools in an Active Duty Military Population. Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists. 2013. [DOI] [PubMed] [Google Scholar]
  • 12.Echemendia RJ, Iverson GL, McCrea M, et al. Advances in neuropsychological assessment of sport-related concussion. British journal of sports medicine. 2013;47(5):294–298. [DOI] [PubMed] [Google Scholar]
  • 13.Gualtieri CT, Johnson LG. Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Archives of Clinical Neuropsychology. 2006;21(7):623–643. [DOI] [PubMed] [Google Scholar]
  • 14.Iverson G, Lovell MR, Collins MW. Reliable change in ImPACT version 2.0 following sports concussion. Archives of clinical neuropsychology. 2003;18:744. [Google Scholar]
  • 15.McCrea M Standardized mental status testing on the sideline after sport-related concussion. Journal of athletic training. 2001;36(3):274. [PMC free article] [PubMed] [Google Scholar]
  • 16.Anzalone AJ, Blueitt D, Case T, et al. A Positive Vestibular/Ocular Motor Screening (VOMS) Is Associated With Increased Recovery Time After Sports-Related Concussion in Youth and Adolescent Athletes. The American Journal of Sports Medicine. 2016. [DOI] [PubMed] [Google Scholar]
  • 17.Mucha A, Collins MW, Elbin RJ, et al. A Brief Vestibular/Ocular Motor Screening (VOMS) assessment to evaluate concussions: preliminary findings. The American Journal of Sports Medicine. 2014;42(10):2479–2486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Galetta KM, Brandes LE, Maki K, et al. The King–Devick test and sports-related concussion: study of a rapid visual screening tool in a collegiate cohort. Journal of the neurological sciences. 2011;309(1):34–39. [DOI] [PubMed] [Google Scholar]
  • 19.Leong DF, Balcer LJ, Galetta SL, Liu Z, Master CL. The King-Devick test as a concussion screening tool administered by sports parents. The Journal of sports medicine and physical fitness. 2014;54(1):70–77. [PubMed] [Google Scholar]
  • 20.Master CL, Scheiman M, Gallaway M, et al. Vision Diagnoses Are Common After Concussion in Adolescents. Clinical pediatrics. 2016;55(3):260–267. [DOI] [PubMed] [Google Scholar]
  • 21.Pearce KL, Sufrinko A, Lau BC, Henry L, Collins MW, Kontos AP. Near Point of Convergence After a Sport-Related Concussion: Measurement Reliability and Relationship to Neurocognitive Impairment and Symptoms. The American Journal of Sports Medicine. 2015;43(12):3055–3061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Cavanaugh JT, Guskiewicz KM, Giuliani C, Marshall S, Mercer V, Stergiou N. Detecting altered postural control after cerebral concussion in athletes with normal postural stability. British journal of sports medicine. 2005;39(11):805–811. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Guskiewicz KM. Balance assessment in the management of sport-related concussion. Clinics in sports medicine. 2011;30(1):89–102. [DOI] [PubMed] [Google Scholar]
  • 24.Guskiewicz KM. Postural stability assessment following concussion: one piece of the puzzle. Clinical Journal of Sport Medicine. 2001;11(3):182–189. [DOI] [PubMed] [Google Scholar]
  • 25.Riemann BL, Guskiewicz KM. Effects of mild head injury on postural stability as measured through clinical balance testing. Journal of athletic training. 2000;35(1):19–25. [PMC free article] [PubMed] [Google Scholar]
  • 26.Baruch M, Barth JT, Cifu D, Leibman M. Utility of a multimodal neurophysiological assessment tool in distinguishing between individuals with and without a history of mild traumatic brain injury. Journal of Rehabilitation Research & Development. 2016;53(6). [DOI] [PubMed] [Google Scholar]
  • 27.Balaban C, Hoffer ME, Szczupak M, et al. Oculomotor, vestibular, and reaction time tests in mild traumatic brain injury. PloS one. 2016;11(9):e0162168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Henry LC, Elbin RJ, Collins MW, Marchetti G, Kontos AP. Examining Recovery Trajectories After Sport-Related Concussion With a Multimodal Clinical Assessment Approach. Neurosurgery. 2016;78(2):232–241. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lovell MR, Collins MW, Iverson GL, et al. Recovery from mild concussion in high school athletes. Journal of neurosurgery. 2003;98(2):296–301. [DOI] [PubMed] [Google Scholar]
  • 30.McCrea M, Guskiewicz K, Randolph C, et al. Incidence, clinical course, and predictors of prolonged recovery time following sport-related concussion in high school and college athletes. Journal of the International Neuropsychological Society : JINS. 2013;19(1):22–33. [DOI] [PubMed] [Google Scholar]
  • 31.McDevitt J, Appiah-Kubi K, Tierney R, Wright W. Vestibular and oculomotor assessments may increase accuracy of subacute concussion assessment. International journal of sports medicine. 2016;37(09):738–747. [DOI] [PubMed] [Google Scholar]
  • 32.Pardini D, Stump JE, Lovell M, Collins MW, Moritz K, Fu FH. The post-concussion symptoms scale (PCSS): A factor analysis. British journal of sports medicine. 2004;38:661. [Google Scholar]
  • 33.Kontos AP, Elbin RJ, Schatz P, et al. A revised factor structure for the post-concussion symptom scale: baseline and postconcussion factors. The American Journal of Sports Medicine. 2012;40(10):2375–2384. [DOI] [PubMed] [Google Scholar]
  • 34.Schatz P, Maerlender A. A Two-Factor Theory for Concussion Assessment Using ImPACT: Memory and Speed. Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists. 2013. [DOI] [PubMed] [Google Scholar]
  • 35.Gerrard PB, Iverson GL, Atkins JE, et al. Factor structure of ImPACT® in adolescent student athletes. Archives of clinical neuropsychology. 2017;32(1):117–122. [DOI] [PubMed] [Google Scholar]
  • 36.Moran RN, Covassin T, Elbin R, Gould D, Nogle S. Reliability and Normative Reference Values for the Vestibular/Ocular Motor Screening (VOMS) Tool in Youth Athletes. The American journal of sports medicine. 2018:0363546518756979. [DOI] [PubMed] [Google Scholar]
  • 37.Guskiewicz KM, Ross SE, Marshall SW. Postural Stability and Neuropsychological Deficits After Concussion in Collegiate Athletes. Journal of athletic training. 2001;36(3):263–273. [PMC free article] [PubMed] [Google Scholar]
  • 38.Broglio SP, Sosnoff JJ, Ferrara MS. The relationship of athlete-reported concussion symptoms and objective measures of neurocognitive function and postural control. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine. 2009;19(5):377–382. [DOI] [PubMed] [Google Scholar]
  • 39.Sandel NK, Schatz P, Goldberg KB, Lazar M. Sex-based differences in cognitive deficits and symptom reporting among acutely concussed adolescent lacrosse and soccer players. 2016;Electronically Published. [DOI] [PubMed] [Google Scholar]
  • 40.Delaney JS, Lacroix VJ, Leclerc S, Johnston KM. Concussions among university football and soccer players. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine. 2002;12(6):331–338. [DOI] [PubMed] [Google Scholar]
  • 41.Sandel NK, Lovell MR, Kegel NE, Collins MW, Kontos AP. The Relationship of Symptoms and Neurocognitive Performance to Perceived Recovery From Sports-Related Concussion Among Adolescent Athletes. Applied Neuropsychology: Child. 2012:1–6. [DOI] [PubMed] [Google Scholar]
  • 42.Schatz P, Sandel N. Sensitivity and Specificity of the Online Version of ImPACT in High School and Collegiate Athletes. The American Journal of Sports Medicine. 2012. [DOI] [PubMed] [Google Scholar]
  • 43.Van Kampen DA, Lovell MR, Pardini JE, Collins MW, Fu FH. The “value added” of neurocognitive testing after sports-related concussion. The American Journal of Sports Medicine. 2006;34(10):1630–1635. [DOI] [PubMed] [Google Scholar]
  • 44.Iverson GL. Misdiagnosis of the persistent postconcussion syndrome in patients with depression. Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists. 2006;21(4):303–310. [DOI] [PubMed] [Google Scholar]
  • 45.Hou R, Moss-Morris R, Peveler R, Mogg K, Bradley BP, Belli A. When a minor head injury results in enduring symptoms: a prospective investigation of risk factors for postconcussional syndrome after mild traumatic brain injury. Journal of neurology, neurosurgery, and psychiatry. 2012;83(2):217–223. [DOI] [PubMed] [Google Scholar]
  • 46.Ponsford J, Cameron P, Fitzgerald M, Grant M, Mikocka-Walus A, Schonberger M. Predictors of postconcussive symptoms 3 months after mild traumatic brain injury. Neuropsychology. 2012;26(3):304–313. [DOI] [PubMed] [Google Scholar]
  • 47.Binder LM, Rohling ML. Money matters: a meta-analytic review of the effects of financial incentives on recovery after closed-head injury. The American Journal of Psychiatry. 1996;153(1):7. [DOI] [PubMed] [Google Scholar]
  • 48.Fazio VC, Lovell MR, Pardini JE, Collins MW. The relation between post concussion symptoms and neurocognitive performance in concussed athletes. NeuroRehabilitation. 2007;22(3):207–216. [PubMed] [Google Scholar]
  • 49.Sandel NK, Worts PR, Burkhart S, Henry L. Comparison of baseline ImPACT performance in amateur motocross riders to football and basketball athletes. Brain injury. 2018;32(4):493–497. [DOI] [PubMed] [Google Scholar]
  • 50.Tomczyk CP, Mormile M, Wittenberg MS, Langdon JL, Hunt TN. An Examination of Adolescent Athletes and Nonathletes on Baseline Neuropsychological Test Scores. Journal of athletic training. 2018;53(4):404–409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Tsushima WT, Siu AM, Yamashita N, Oshiro RS, Murata NM. Comparison of neuropsychological test scores of high school athletes in high and low contact sports: A replication study. Applied neuropsychologyChild. 2016:1–7. [DOI] [PubMed] [Google Scholar]

RESOURCES