Depression in frail elders: impact on family caregivers
Bibliographic record
Abstract
OBJECTIVES: To examine the relationship between depression among medically ill, frail elders and family caregivers' hours of care, health status, and quality of life. DESIGN AND METHODS: A cross-sectional study of 193 family caregivers of seniors treated in the emergency department (ED) was conducted. Measures included patient depression (Geriatric Depression Scale-15), and caregivers' hours of care, mental health and physical functioning (SF-36), and quality of life (EQ-5D). RESULTS: Mean caregiver age was 60.0 +/- 16.1 years and 70.5% were female. More caregivers of depressed seniors provided more care in the previous month (37.3% vs 22.4%, p = 0.03), had poor mental health (63.5% vs 47.0%, p = 0.03), and poor perceived quality of life (63.5% vs 50.4%, p = 0.04) compared to caregivers of non-depressed seniors. Multiple logistic regression analyses indicated that patient depression was associated with poor caregiver quality of life (OR = 3.15, 95% CI 1.48, 6.73), and poor mental health in spousal and adult child caregivers (OR = 2.72, 95% CI = 0.88, 8.39, and OR = 3.29, 95% CI = 1.10, 9.86, respectively). CONCLUSIONS: Psychosocial support may be needed for caregivers of depressed seniors.
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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 | 0.004 |
| 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".