Relations Among Sociodemographic, Neurologic, Clinical, and Neuropsychologic Variables, and Vocational Status Following Mild Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVES: To explore the long-term relations among sociodemographic, neurologic, clinical, and neuropsychologic variables, and vocational status in persons with mild traumatic brain injury (MTBI), and to identify the symptoms that determine whether or not these individuals return to work. DESIGN: Longitudinal quasi-experimental between-groups design. PARTICIPANTS: Eighty-five MTBI subjects aged between 16 and 65 years. SETTING: The emergency ward of the Trois-Rivieres Regional Hospital Centre in Quebec, Canada. MAIN OUTCOME MEASURES: Age, gender, Glasgow Coma Scale score, duration of posttraumatic amnesia, duration of retrograde amnesia, total of symptoms at emergency, time elapsed since the trauma, Paced Auditory Serial Addition Task, Stroop Color Word Test, California Verbal Learning Test, and the number of symptoms at follow-up (12 to 36 months posttrauma). RESULTS: Only the total number of symptoms reported at follow-up was related to vocational status. The majority of individuals had returned to work 1 year or more post-MTBI. Individuals who had not returned to work reported the greatest number of symptoms, which could be linked to their affective status. Six affective symptoms, 5 cognitive symptoms, 6 physical symptoms, and 8 symptoms relating to social and daily life activities differentiated the participants who had returned to work from those who had not. CONCLUSIONS: Patient characteristics, injury severity indicators, and cognitive functions were not associated with vocational status. To better understand post-MTBI vocational status, it is important to focus on subjective complaints that arise following the injury.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".