Multiple Past Concussions Are Associated with Ongoing Post-Concussive Symptoms but Not Cognitive Impairment in Active-Duty Army Soldiers
Bibliographic record
Abstract
The extent to which multiple past concussions are associated with lingering symptoms or mental health problems in military service members is not well understood. The purpose of this study was to examine the association between lifetime concussion history, cognitive functioning, general health, and psychological health in a large sample of fit-for-duty U.S. Army soldiers preparing for deployment. Data on 458 active-duty soldiers were collected and analyzed. A computerized cognitive screening battery (CNS-Vital Signs(®)) was used to assess complex attention (CA), reaction time (RT), processing speed (PS), cognitive flexibility (CF), and memory. Health questionnaires included the Neurobehavioral Symptom Inventory (NSI), PTSD Checklist-Military Version (PCL-M), Zung Depression and Anxiety Scales (ZDS; ZAS), Perceived Stress Scale (PSS), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and the Alcohol Use and Dependency Identification Test (AUDIT). Soldiers with a history of multiple concussions (i.e., three or more concussions) had significantly greater post-concussive symptom scores compared with those with zero (d=1.83, large effect), one (d=0.64, medium effect), and two (d=0.64, medium effect) prior concussions. Although the group with three or more concussions also reported more traumatic stress symptoms, the results revealed that traumatic stress was a mediator between concussions and post-concussive symptom severity. There were no significant differences on neurocognitive testing between the number of concussions. These results add to the accumulating evidence suggesting that most individuals recover from one or two prior concussions, but there is a greater risk for ongoing symptoms if one exceeds this number of injuries.
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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 | 0.001 | 0.004 |
| 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".