Depressive Symptoms Negatively Impact Montreal Cognitive Assessment Performance: A Memory Clinic Experience
Bibliographic record
Abstract
OBJECTIVE: The Montreal Cognitive Assessment (MoCA) is a general cognitive screening tool that has shown sensitivity in detecting mild levels of cognitive impairment in various clinical populations. Although mood dysfunction is common in referrals to memory clinics, the influence of mood on the MoCA has to date been largely unexplored. METHOD: In this study, we examined the impact of mood dysfunction on the MoCA using a memory clinic sample of individuals with depressive symptoms who did not meet criteria for a neurodegenerative disease. RESULTS: Half of the group with depressive symptoms scored below the MoCA-suggested cutoff for cognitive impairment. As a group, they scored below healthy controls, but above individuals with Alzheimer's disease and frontotemporal dementia. A MoCA subtask analysis revealed a pattern of executive/attentional dysfunction in those with depressive symptoms. CONCLUSIONS: This observed negative impact of depressive symptomatology on the MoCA has interpretative implications for its utility as a cognitive screening tool in a memory clinic setting.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".