Montreal Cognitive Assessment (MoCA) Norms for Older Patients with a Depressive Disorder
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Bibliographic record
Abstract
Background: Interpretation of cognitive performance in older patients with depression is challenging considering the association between late-life depression and (early-stage) neurodegenerative disease. The Montreal Cognitive Assessment (MoCA) is widely used to screen for mild cognitive impairment in community-dwelling older adults. Objective: The aim of the present study was to examine the need for and to develop dedicated MoCA norms for older people with depressive disorder. Methods: We used data from the Routine Outcome Monitoring for Geriatric Psychiatry & Science (ROM-GPS) study and the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, which consisted of 859 patients with a depressive disorder according to DSM-5 criteria and 320 healthy controls, aged ≥60 years. Linear regression was used to examine the relationship between late-life depression and MoCA scores, adjusted for age, sex, and education. Results: The presence of a depressive disorder was associated with lower MoCA scores, and this effect was larger for persons with 12 years or less of education than for those with more education (B = −0.76 [95% CI −0.61; −0.91] vs. −0.53 [−0.36; −0.70]). Among depressed patients, depressive symptom severity was not associated with the MoCA score. Regression-based normative data for the MoCA were computed and adjusted for age, education, sex, and type of depressive disorder. Conclusions: Our findings demonstrate that depressive disorder, but not symptom severity within depression, is associated with lower MoCA scores. Clinical interpretation of MoCA scores in depressed older persons can be facilitated by using MoCA reference tables stratified by age, sex and level of education.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it