Gender Disparities in Neurobehavioral Symptoms and the Role of Post-Traumatic Symptoms in US Service Members Following Mild Traumatic Brain Injury
Bibliographic record
Abstract
Women are more directly involved in combat operations today than ever before, currently making up 18.6% of officers and 16.8% of enlisted personnel in the United States military. However, women continue to be under-represented in military research. Studies that do consider gender differences in traumatic brain injury (TBI) outcomes have shown that women report significantly more post-concussive symptoms than men. Conclusions for true gender differences related to TBI are hard to make without controlling for non-TBI factors. The effects previously identified in the literature may be an artifact of how men and women differ in their response to injury, unrelated to the neurological recovery process associated with TBI. The objective of this study was to examine the effects of gender specifics on mild TBI (mTBI) sequelae on injured and uninjured control groups, and to investigate the role of post-traumatic stress disorder (PTSD) on symptom reporting. It should be noted that the terms “gender” and “men/women” are used in this article in place of “sex” or “males/females” given that we are not discussing biological attributes. A total of 966 United States military service members and veterans were included in the study. Of the total sample, 455 men and 46 women were in the mTBI group, 285 men and 31 women were in the injured controls group (IC), and 111 men and 38 women in the non-injured controls group (NIC). Post-concussive and quality of life symptoms were compared for men and women while controlling for combat exposure. MTBI and IC groups were also stratified by PTSD presentation. Measures used included the Neurobehavioral Symptom Inventory (NSI), PTSD Checklist (PCL-C), Traumatic Brain Injury Quality of Life (TBI-QOL), and Combat Exposure Scale. In the mTBI group, women had worse scores on NSI total, NSI Somatosensory and Affective clusters, and the TBI-QOL Anxiety, Fatigue, and Headache scales ( n 2 = 0.018–0.032, small to small-medium effect sizes). When PTSD was present, women had worse scores on the NSI Somatosensory cluster only ( n 2 = 0.029, small-medium effect size). In contrast, when PTSD was absent, women had worse scores than men on the NSI Somatosensory and Affective clusters, and the TBI-QOL Anxiety and Headache scales ( n 2 = 0.032–0.063, small to medium effect sizes). In the IC group, women had worse scores on the NSI Cognitive cluster and the TBI-QOL Fatigue and Pain Interference scales ( n 2 = 0.024–0.042, small to small-medium effect sizes). However, group differences were no longer found when stratified by PTSD sub-groups. In the NIC group, there were no significant group differences for any analyses. We were able to identify symptoms unique to women recovering from mTBI that were not present following other forms of physical injury or in healthy controls. However, the impact of PTSD exacerbates the symptom profile and its comorbidity with mTBI equates to most of the noted gender differences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".