Ecological Validity of the Montreal Cognitive Assessment in Non-Demented Parkinson’s Disease Patients
Bibliographic record
Abstract
BACKGROUND: The ecological validity of performance-based cognitive screeners needs to be tested in order for them to be fully recommended for use within clinical practice and research. OBJECTIVES: The objective of this study was to examine, within an Italian cohort of non-demented Parkinson's disease (PD) patients, the ecological validity of the Montreal Cognitive Assessment (MoCA) by assessing its association with (1) functional independence (FI), (2) quality of life (QoL), and (3) behavioural-psychological (BP) outcomes. METHODS: Seventy-four non-demented PD patients were administered the MoCA and underwent motor functional - i.e., Unified Parkinson's Disease Rating Scale (UPDRS), Modified Hoehn-Yahr Scale (HY), and Schwab and England Scale (SES) -, behavioural and psychological - i.e., State- and Trait-Anxiety Inventory-Form Y (STAI-Y1/-Y2), Beck Depression Inventory (BDI), and Dimensional Apathy Scale (DAS) - and QoL evaluations - i.e., MOS 36-Item Short Form Health Survey (SF-36). Associations of interest against FI, QoL, and BP outcomes were tested via Bonferroni-corrected Pearson's/Spearman's correlations while covarying for demographics, disease duration as well as UPDRS-III, UPDRS-IV, and HY scores. Intake of psychotropic drugs was also covaried when assessing the association between the MoCA and BP/QoL measures. RESULTS: MoCA scores were significantly associated with the SES (rs(73) = 0.34; p = 0.005) and the DAS-Executive (r(67) = -0.47; p < 0.001), while not to other FI/BP outcomes and QoL measures. CONCLUSIONS: The MoCA is a valid estimate of daily life functional autonomy in non-demented PD patients, also reflecting apathetic features of a dysexecutive nature.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".