Validation of the Turkish Version of the Montreal Cognitive Assessment Scale (MoCA-TR) in Patients With Parkinson’s Disease
Bibliographic record
Abstract
The study aimed to examine the reliability and validity of the Turkish version of the Montreal Cognitive Assessment Scale (MoCA-TR) as a screening tool for cognitive dysfunction in Parkinson's disease (PD). A total of 50 patients with PD and 50 healthy controls were included. The screening instruments-MoCA-TR followed by the Mini-Mental Status Examination (MMSE-TR) and MoCA-TR retest within 1 month-and detailed neuropsychological testing were administered to the PD patients. MoCA-TR and MMSE-TR were also administered to controls. The discriminant validities of the MoCA-TR and MMSE-TR as screening and diagnostic instruments were ascertained. The concurrent and criterion validity, test-retest reliability, and internal consistency of the MoCA-TR and MMSE-TR were examined. The Cronbach's alpha of the MoCA-TR as an index of internal consistency was 0.664, and the test-retest reliability of MoCA-TR was 0.742. With a cut-off score of < 21 points, the MoCA-TR showed sensitivity of 59% and specificity of 89% in the detection of cognitive dysfunction in PD. The area under the receiver-operating characteristics curve (95% confidence interval) for MoCA-TR was 0.794 (0.670-0.918), p<.001. The present results indicated that the MoCA-TR has acceptable psychometric properties and it should be used to assess mild cognitive impairment and early dementia in PD patients, whereas the MMSE-TR should remain the instrument of choice to assess cognitive impairment in PD dementia.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".