3 Validity of the tele-administered Montreal Cognitive Assessment for identifying geriatric neurocognitive disorders
Bibliographic record
Abstract
Objective: With the emergence of the coronavirus 2019 pandemic, investigating the validity of tele-screenings for neuropsychological status has become increasingly necessary. While the telephone version of the Montreal Cognitive Assessment (MoCA-T) has been validated for use in patients with Parkinson’s and stroke/cerebrovascular disease, the clinical utility of this instrument in geriatric patients with other suspected cognitive disorders has yet to be determined. Thus, the present study aimed to examine the classification accuracy of the MoCA-T in a mixed clinical sample of patients with mild cognitive impairment (MCI) or dementia. Participants and Methods: Ninety-one older adults were administered the MoCA-T via videoconferencing technology as part of a comprehensive neurocognitive evaluation performed by a multidisciplinary treatment team within a dementia specialty clinic. Based on this evaluation, 51 (56.0%) patients were diagnosed with dementia, 27 (29.7%) with MCI, and 13 (14.3%) with no neurocognitive diagnosis (i.e., subjective cognitive complaints). In addition to MoCA-T total and item scores, we also computed subscale scores for between-group comparisons as the sum of items assessing orientation, language, attention/executive function, and memory. ANOVA/ANCOVA and ROC curve analyses were used to examine between-group differences on the MoCA-T and its psychometric properties in discriminating patients with MCI or dementia, respectively. Results: Participants had a mean age of 74.3 ± 8.7 and education of 16 ± 2.9 years. Patients with dementia were significantly older than those with MCI and no diagnosis, but there were no other significant between-group differences in clinical characteristics. MoCA-T total [F(2,86)=28.5, p<0.001] and all subscale scores (p<0.01) differed significantly between groups and in the expected direction (dementia Conclusions: The current study provides further evidence for the clinical utility of the MoCA-T as a screening instrument for neurocognitive disorders in older adults and extends prior work to include administration via videoconferencing technology. While previous studies have focused on the use of MoCA-T in specific patient populations, here, we demonstrate the validity of this screening tool in a mixed-clinical sample, which suggests its broader use in clinical settings for distinguishing between neurocognitive disorders, regardless of the underlying etiology.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".