Prevalence of depressive symptoms and associated factors among older adults treated at a referral center
Bibliographic record
Abstract
Abstract The present study aimed to estimate the prevalence of depressive symptoms and associated factors among older adults treated at a referral center. A cross-sectional study was carried out with a sample of 360 older adults treated at a Referral Center for the Health of Older Adults in the north of Minas Gerais, Brazil. The following data were collected in 2017: demographic, socioeconomic, morbidity, hospital admission in the last year, frailty (Edmonton Frail Scale), functional capacity (Katz Index, Lawton and Brody Scale) and presence of depressive symptoms (Geriatric Depression Scale - GDS-15). Multiple analysis was performed through logistic regression. A prevalence of depressive symptoms was observed in 37.2% of the sample. The variables associated with depressive symptoms were: negative perception about one’s own health (OR=1.9, 95% CI 1.34-2.70); frailty (OR=1.94, 95% CI 1.41-2.66); having suffered falls (OR=1.24, 95% CI 1.01-1.61); having been hospitalized in the last year (OR=1.56, 95% CI, 1.11-2.27); (OR=2.56, 95% CI 1.38-4.77) and residing alone (OR=1.66, 95% CI 1.09-2.53). Thus, a high prevalence of depressive symptoms was identified among the older adults, evidencing the need for an effective and immediate approach by health professionals.
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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 | 0.002 |
| 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 | 0.000 | 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".