Reliable change indices for the Italian version of the Montreal Cognitive Assessment (MoCA) in non-demented Parkinson’s disease patients
Bibliographic record
Abstract
BACKGROUND: . The present study aimed at deriving regression-based reliable change indices (RCIs) for the Montreal Cognitive Assessment (MoCA) in an Italian cohort of non-demented Parkinson's disease (PD) patients. METHODS: N = 33 consecutive, non-demented PD patients were followed-up at a 5-to-8-month interval (M = 6.6; SD = 0.6) with the MoCA. Practice effects and test-retest reliability were assessed via dependent-sample t-tests and intra-class correlation (ICC) coefficients, respectively. RCIs were derived separately for raw and demographically adjusted MoCA scores according to a standardized regression-based approach by accounting for both baseline confounders (i.e., demographics, disease duration and Unified Parkinson's Disease Rating Scale scores) and retest interval. RESULTS: No practice effects were found (t(32) = 0.29; p = .778), with acceptable test-retest reliability being detected (ICC = 0.67). MoCA scores at T0 proved to be the only significant predictor of T1 MoCA performances within both the model addressing raw scores and that addressing adjusted scores (ps < 0.001). CONCLUSIONS: The present study provides Italian practitioners and researchers with regression-based RCIs for the MoCA in non-demented PD patients, which can be reliably adopted for retest interval ≥ 5 and ≤ 8 months without encountering any practice effect.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".