The Introduction of a New Screening Tool for the Identification of Cognitively Impaired Medically At-Risk Drivers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
UNLABELLED: The number of drivers with a cognitive impairment due to dementia or other age-associated pathologies will increase significantly over the next 3 decades. Physicians are well placed to identify medically at-risk drivers, but are hampered by the lack of a valid, easy to administer screening tool. This research develops and validates a brief screening tool for use in the primary care setting to identify drivers with cognitive impairment with or without dementia. Initial Study Participants: A cohort of 146 consecutive referrals from community-based family physicians, diagnosed with an undifferentiated cognitive impairment or dementia, as well as 35 community dwelling healthy controls. Validation Study: A cohort of 192 consecutive referrals carrying the same diagnosis as above and 52 community dwelling healthy controls. Criterion Measure: Pass/fail on an On-Road evaluation. Predictor Measures: Subtests of the DemTect, a screening test for cognitive impairment or dementia developed by Kalbe and colleagues.(1) Initial Study: Three of the DemTect measures predicted On-Road outcomes (R(2) = .262). Regression results were used to develop a simple scoring algorithm, with cut-points then derived by identifying those most at risk for failing and passing the On-Road assessment, and those needing a driving assessment for determination of driving competency. 89 individuals scored in the indeterminate range, with 49 and 43 predicted to fail and pass, respectively-86% and 84% of those predicted to fail and pass did subsequently fail and pass. Validation Study: 123 individuals scored in the indeterminate range, with 66 and 55 predicted to fail and pass, respectively-80% and 87% of those predicted to fail and pass did subsequently fail and pass. CONCLUSIONS: The SIMARD A Modification of the DemTect ( S creen for the I dentification of cognitively impaired M edically A t- R isk D rivers) is a brief paper and pencil screening tool with a high degree of accuracy that can be used for immediate decisions in the clinical setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it