Psychiatric Hospitalization and Veterans With Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: To determine risk factors for psychiatric hospitalization after traumatic brain injury (TBI) in veterans. SUBJECTS AND PROCEDURES: Medical records of 96 veterans with histories of TBI (17 mild, 33 moderate, and 46 severe) were reviewed for information concerning psychiatric history, including hospitalization and substance misuse. RESULTS: Subjects with a history of problematic drug and alcohol use had a significantly higher probability of psychiatric hospitalization than those without such a history. Gender, age, problematic alcohol use without problematic drug use, injury severity, time since injury, years of follow-up, and a history of psychiatric symptoms (including those attributed to general medical conditions) were not identified as significant risk factors. Ninety-one veterans (95%) had a history of psychiatric difficulty. In addition, the probability of post-TBI problematic drug and alcohol use, given a pre-TBI history of such use, was significantly higher than the probability given no history. CONCLUSIONS: Veterans with problematic drug and alcohol use are at increased risk for psychiatric hospitalization after TBI. In addition, the likelihood of problematic post-TBI drug and alcohol use was significantly greater for those with a preinjury history. Ninety-five percent of veterans in the current sample endorsed lifetime histories of psychiatric difficulty. These findings highlight the need for evidence-based means of psychiatric and/or substance abuse treatment of those with a history of TBI.
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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 | 0.001 |
| 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".