Temporal stability and responsiveness of the Montreal Cognitive Assessment following acquired brain injury
Bibliographic record
Abstract
OBJECTIVES: To evaluate the temporal stability and responsiveness of the Montreal Cognitive Assessment (MoCA) in acquired brain injury (ABI). RESEARCH DESIGN AND METHODS: English-speaking adults with stroke or moderate-to-severe traumatic brain injury were administered alternate forms of the MoCA (version 1, then 2), 6 weeks apart. Chronic group participants (n = 40) were community-dwelling, at least 1 year post-ABI (mean = 12.1 years, SD = 9.0), and presumed clinically stable. Sub-acute group participants (n = 36) were 30.8 days post-ABI (SD = 12.4) and were undergoing intensive rehabilitation. Individuals with an unstable medical or psychiatric condition or severe receptive aphasia were not eligible. RESULTS: The chronic group scored 21.6 (SD = 4.5) initially and 22.7 (SD = 3.8) on the second administration, demonstrating a small but significant practise effect (p = 0.009). The Pearson test-re-test correlation coefficient was 0.83. Using reliable change methodology in the chronic group, the 80% confidence interval (CI) for change across the two administrations was -2 to +4, adjusting for practise. Applied to the sub-acute group, 39% improved and 0% declined. CONCLUSIONS: The MoCA is a brief standardized tool that appears useful for monitoring cognitive change after ABI. The findings enable clinicians to detect statistically reliable change across serial MoCA administrations in individuals with an ABI.
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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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".