Influence of depression, anxiety and stress on cognitive performance in community‐dwelling older adults living in rural <scp>E</scp>cuador: Results of the <scp>A</scp>tahualpa <scp>P</scp>roject
Bibliographic record
Abstract
AIM: To assess the relationship between cognitive status and self-reported symptoms of depression, anxiety and stress of older adults living in an underserved rural South American population. METHODS: Community-dwelling Atahualpa residents aged ≥60 years were identified during a door-to-door census, and evaluated with the Depression Anxiety Stress Scale-21 (DASS-21) and the Montreal Cognitive Assessment (MoCA). We explored whether positivity in each of the DASS-21 axes was related to total and domain-specific MoCA performance after adjustment for age, sex and education. RESULTS: A total of 280 persons (59% women; mean age, mean age 70 ± 8 years) were included. Based on established cut-offs for the DASS-21, 12% persons had depression, 15% had anxiety and 5% had stress. Mean total MoCA scores were significantly lower for depressed than for not depressed individuals (15.9 ± 5.5 vs 18.9 ± 4.4, P < 0.0001). Depressed participants had significantly lower total and domain-specific MoCA scores for abstraction, short-term memory and orientation. Anxiety was related to significantly lower total MoCA scores (17 ± 4.7 vs 18.8 ± 4.5, P = 0.02), but not to differences in domain-specific MoCA scores. Stress was not associated with significant differences in MoCA scores. CONCLUSION: The present study suggests that depression and anxiety are associated with poorer cognitive performance in elderly residents living in rural areas of developing countries.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".