Sex Differences in Emotional Insight After Traumatic Brain Injury
Bibliographic record
Abstract
Objective: To compare sex differences in alexithymia (poor emotional processing) in males and females with traumatic brain injury (TBI) and uninjured controls. Design: Cross-sectional study. Setting: TBI rehabilitation facility in the United States and a university in Canada. Participants: Sixty adults with moderate to severe TBI (62% men) and 60 uninjured controls (63% men) (N=120). Interventions: Not applicable. Main Outcome Measures: Toronto Alexithymia Scale-20 (TAS-20). Results: Uninjured men had significantly higher (worse) alexithymia scores than uninjured female participants on the TAS-20 (P=.007), whereas, no sex differences were found in the TBI group (P=.698). Men and women with TBI had significantly higher alexithymia compared with uninjured same-sex controls (both P<.001). The prevalence of participants with scores exceeding alexithymia sex-based norms for men and women with TBI was 37.8% and 47.8%, respectively, compared with 7.9% and 0% for men and women without TBI. Conclusions: Contrary to most findings in the general population, men with TBI were not more alexithymic than their female counterparts with TBI. Both men and women with TBI have more severe alexithymia than their uninjured same-sex peers. Moreover, both are equally at risk for elevated alexithymia compared with the norms. Alexithymia should be evaluated and treated after TBI regardless of patient sex. © 2020 American Congress of Rehabilitation Medicine
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".