Risk Factors for Postconcussion Symptom Reporting after Traumatic Brain Injury in U.S. Military Service Members
Bibliographic record
Abstract
The purpose of this study was to identify factors that are predictive of, or associated with, postconcussion symptom reporting after traumatic brain injury (TBI) in the U.S. military. Participants were 125 U.S. military service members (age: M=29.6 years, standard deviation [SD]=8.9, range=18-56 years) who sustained a TBI, divided into two groups based on symptom criteria for postconcussional disorder (PCD): PCD-Present (n=65) and PCD-Absent (n=60). Participants completed a neuropsychological evaluation at Walter Reed Army Medical Center (M=9.4 months after injury, SD=9.9; range: 1.1 to 44.8). Factors examined included demographic characteristics, injury-related variables, psychological testing, and effort testing. There were no significant group differences for age, sex, education, race, estimated premorbid intelligence, number of deployments, combat versus non-combat related injury, or mechanism of injury (p>0.098 for all). There were significant main effects for severity of body injury, duration of loss of consciousness, duration of post-traumatic amnesia, intracranial abnormality, time tested post-injury, possible symptom exaggeration, poor effort, depression, and traumatic stress (p<0.044 for all). PCD symptom reporting was most strongly associated with possible symptom exaggeration, poor effort, depression, and traumatic stress. PCD rarely occurred in the absence of depression, traumatic stress, possible symptom exaggeration, or poor effort (n=7, 5.6%). Many factors unrelated to brain injury were influential in self-reported postconcussion symptoms in this sample. Clinicians cannot assume uncritically that endorsement of items on a postconcussion symptom checklist is indicative of residual effects from a brain injury.
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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 | 0.004 | 0.006 |
| 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 | 0.001 |
| 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".