The development and initial validation of a new tool to measure self‐awareness of driving ability after brain injury
Bibliographic record
Abstract
Aim The aim of this study was to develop and provide initial validation data for a self‐awareness of on‐road driving ability measure for individuals with brain injury. Method Thirty‐nine individuals with Traumatic Brain Injury completed an on‐road driving assessment, the Self‐Regulation Skills Interview (SRSI) and the newly developed Brain Injury Driving Self‐Awareness Measure (BIDSAM). Results BIDSAM self, clinician and discrepancy scales demonstrated high levels of internal consistency (α = 0.83–0.92). Criterion‐related validity was established by demonstrating significantly higher correlations between clinician ratings and on‐road performances, rs = 0.82, P < 0.01, compared to self‐ratings, rs = 0.45, P < 0.05. Discrepancy scores were significantly correlated with the SRSI emergent, rs = 0.52, P < 0.01, and anticipatory awareness scores, rs = 0.37, P < 0.05, indicative of convergent validity. Conclusions These results provide initial support for the BIDSAM as a reliable and valid measure of self‐awareness of on‐road driving ability following 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".