An assessment of the cognitive functions of the senior citizens living in the community
Bibliographic record
Abstract
Abstract Aim. The study aimed to evaluate cognitive function status in community-dwelling seniors and to establish relationships between cognitive function and selected aspects. Material and methods. The research population consisted of 330 community-dwelling respondents over the age of 60. Cognitive function was assessed using the Montreal Cognitive Test (MoCA), anxiety symptoms – using the Geriatric Anxiety Inventory (GAI), and depression symptoms – using the Geriatric Depression Scale (GDS-15). Quality of life was assessed using the Older People’s Quality of Life – Brief version (OPQOL-BRIEF). Results. The average total score in the MoCA test was 26.2 points (SD = 2.3; min. 19; max. 30), and 63.7% of respondents scored within the norm. A lower average MoCA score was recorded in those who were diagnosed with depression (p = 0.012). The same was true for those who were diagnosed with anxiety (p < 0.001). Signifi cantly worse MoCA scores were found in those who were no longer working (p = 0.027). Conclusions. Assessment of cognitive function in the elderly should not be underestimated in terms of the need for early detection of dementia. In addition to activities that may enhance cognitive function, there is a need to support activities in practice that focus on reducing the symptoms of anxiety and depression in the elderly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".