PREVALENCE AND CORRELATES OF SYMPTOMS OF ANXIETY AND DEPRESSION AT THE VERY END OF LIFE
Bibliographic record
Abstract
Abstract Rates of psychological symptoms for patients with serious illness is high, but there has been limited research investigating psychological symptoms at the very end of life. The aim of this study was to better understand the prevalence, intensity and correlates of psychological distress at the very end of life. This cross-sectional study utilized caregiver proxy interviews. Caregivers were contacted after their loved one recently died after being on home hospice and invited to participate in a brief interview with a trained research assistant. Patient, caregiver and hospice utilization data were also abstracted from electronic medical records. N = 351 caregivers were included in the study. According to caregivers, 46.4% of patients had moderate to severe anxiety, as assessed with a score of ≥4 on the Edmonton Symptom Assessment Scale (ESAS) and 43% had moderate to severe symptoms of depression in the last week of life. Symptoms of anxiety and depression were significantly associated with caregiver burden scores and inversely associated with the age of the patient. Psychological symptom management at the very end of life is essential to providing comprehensive hospice care. Our study revealed that nearly half of patients die with moderate to severe symptoms of anxiety and/or depression. Future research is needed to improve psychological symptom management at the very end of life in order to improve the quality of life for both patients and their families.
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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 | 0.003 |
| 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".