Comparison of Vestibular/Ocular Motor Screening (VOMS) and Computerized Eye-tracking to Identify Exposure to Repetitive Head Impacts
Bibliographic record
Abstract
INTRODUCTION: Military service members (SMs) are exposed to repetitive head impacts (RHIs) in combat and training that are purported to adversely affect brain health, including cognition, behavior, and function. Researchers have reported that RHI from blast-related exposure may affect both vestibular and ocular function, which in turn may be related to symptomology. As such, an examination of the effects of RHI on exposed military SMs should incorporate these domains. To date, researchers have not compared groups of exposed special operations forces (SOF) operators on combined clinical vestibular/ocular and eye-tracker-based outcomes. Therefore, the primary purpose of this study was to compare participant-reported symptoms and performance on the Vestibular/Ocular Motor Screening (VOMS) tool with performance on the computerized RightEye tracking system between SOF operators exposed to blast-related RHI and healthy controls without blast-related exposure. In addition, the study aimed to compare subgroups of snipers and breachers exposed to RHI to controls on the preceding metrics, as well as identify a subset of individual (demographic) factors, participant-reported symptoms, and performance metrics on VOMS and RightEye that best identify SOF operators exposed to RHI from unexposed controls. MATERIALS AND METHODS: The study involved a cross-sectional design including 25 Canadian SOF SMs comprised of breachers (n = 9), snipers (n = 9), and healthy, unexposed controls (n = 7). The former 2 groups were combined into an RHI group (n = 18) and compared to controls (n = 7). Participants provided demographics and completed a self-reported concussion-related symptom report via the Military Acute Concussion Evaluation 2, the VOMS, and RightEye computerized eye-tracking assessments. Independent samples t-tests and ANOVAs were used to compare the groups on the outcomes, with receiver operating characteristic curve and area under the curve (AUC) analyses to identify predictors of blast exposure. This study was approved by the Defence Research Development Canada Human Research Ethics Committee and the Canadian Forces Surgeon General/Special Forces Command. RESULTS: The results from t-tests supported group differences for age (P = .012), participant-reported symptoms (P = .006), and all VOMS items (P range = <.001-.02), with the RHI group being higher than healthy controls on all variables. ANOVA results supported group differences among snipers, breachers, and controls for age (P = .01), RightEye saccades (P = .04), participant-reported total symptom severity (P = .03), and VOMS total scores (P = .003). The results of the receiver operating characteristic curve analyses supported age (AUC = 0.81), Military Acute Concussion Evaluation 2 participant-reported total symptom severity (AUC = 0.87), and VOMS total scores (AUC = 0.92) as significant predictors of prior blast exposure. CONCLUSIONS: Participant-reported concussion symptoms, VOMS scores, and age were useful in identifying SOF operators exposed to RHI from controls. RightEye metrics were not useful in differentiating RHI groups from controls. Differences between snipers and breachers warrant further research. Overall, the findings suggest that VOMS may be a useful tool for screening for the effects of exposure to RHI in SOF operators. Future investigations should be conducted on a larger sample of military SMs, consider additional factors (e.g., RHI exposure levels, medical history, and sex), and include additional assessment domains (e.g., balance, cognitive, and psychological).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".