A Multisite Study of the Relationships between Blast Exposures and Symptom Reporting in a Post-Deployment Active Duty Military Population with Mild Traumatic Brain Injury
Bibliographic record
Abstract
Explosive devices have been the most frequent cause of traumatic brain injury (TBI) among deployed contemporary U.S. service members. The purpose of this study was to examine the influence of previous cumulative blast exposures (that did or did not result in TBI) on later post-concussion and post-traumatic symptom reporting after sustaining a mild TBI (MTBI). Participants were 573 service members who sustained MTBI divided into four groups by number of blast exposures (1, 2, 3, and 4-10) and a nonblast control group. Post-concussion symptoms were measured using the Neurobehavioral Symptom Inventory (NSI) and post-traumatic stress disorder (PTSD) symptoms using the Post-traumatic Checklist-Civilian version (PCL-C). Results show groups significantly differed on total NSI scores (p<0.001), where symptom endorsement increased as number of reported blast exposures increased. Total NSI scores were significantly higher for the 3- and 4-10 blast groups compared with the 1- and 2-blast groups with effect sizes ranging from small to moderate (d=0.31 to 0.63). After controlling for PTSD symptoms using the PCL-C total score, NSI total score differences remained between the 4-10-blast group and the 1- and 2-blast groups, but were less pronounced (d=0.35 and d=0.24, respectively). Analyses of NSI subscale scores using PCL-C scores as a covariate revealed significant between-blast group differences on cognitive, sensory, and somatic, but not affective symptoms. Regression analyses revealed that cumulative blast exposures accounted for a small but significant amount of the variance in total NSI scores (4.8%; p=0.009) and total PCL-C scores (2.3%; p<0.001). Among service members exposed to blast, post-concussion symptom reporting increased as a function of cumulative blast exposures. Future research will need to determine the relationship between cumulative blast exposures, symptom reporting, and neuropathological changes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".