[Association between depression syndromе and functional disorders in elderly residents of the European North of Russia.]
Bibliographic record
Abstract
Depression syndrome is one of the most common syndromes among the elderly and is directly associated with functional independence and quality of life. This study aimed to investigate the association between the severity of depression syndrome and functional disorders among individuals aged 60 to 74 years. In 2023, a cross-sectional study was conducted on arandom-samplein Arkhangelsk (n=611). Participants were examined for depression syndrome using the Beck Depression Scale. Functional disorders were evaluated using hand dynamometry, the Short Physical Performance Battery, the Montreal Cognitive Assessment, visual and hearing acuity tests. Zero-inflated negative binomial regression was used to analyze the associations between the severity of depression syndrome and functional disorders. After adjustment for age, education, marital status, financial difficulties, low physical activity, and all functional disorders, higher depression syndrome severity was associated with preasthenia gravis (an early stage of frailty) in both men and women and with hearing loss in women only. These findings underscore the importance of taking a gender-sensitive approach to screening for and preventing depression syndrome in older adults, especially those with complex age-related functional disorders.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".