The public's misconceptions about traumatic brain injury: a follow up survey
Bibliographic record
Abstract
Two prior surveys from rural Louisiana, Canada, and New York [Arch. Clin. Neuropsychol. 3 (1988) 331; Arch. Clin. Neuropsychol. 8 (1993) 461] revealed that a high portion of the population endorses misconceptions about the sequelae of traumatic brain injury (TBI). The purpose of this study was to assess the public's perceptions of head trauma in an urban setting in the Northeast region of the country and to compare those results with surveys from other geographical areas conducted 8 and 13 years ago. This study also examined the prevalence of perceptions about TBI that may be relevant to personal injury litigation with TBI plaintiffs. Data were collected at an office of the Department of Motor Vehicles from persons conducting business there. Participants (n = 179) voluntarily completed a 19-item survey covering several facets of brain injury. This sample endorsed misconceptions at a level consistent with previous studies, indicating a comparable lack of knowledge about moderate to severe TBI. With regard to mild TBI, however, our sample generally endorsed fewer misconceptions than previous samples. The public also holds perceptions of TBI that may be relevant to personal injury litigation involving TBI plaintiffs.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".