Correlates of Health Status for Family Caregivers in Bereavement
Bibliographic record
Abstract
The purpose of this retrospective cohort study was to identify aspects of caregiving associated with health status among family caregivers in bereavement. Study participants included 151 family caregivers of terminally ill patients who had died, on average, 294 days prior to the study telephone interview. The interview covered two main areas: patient characteristics and caregiver characteristics. Multivariate linear regressions revealed that as the age of the care recipient (regression coefficient [b] = -0.32; 95% confidence interval [CI] -0.48,-0.15) and caregiver (b = -0.14; 95% CI = -0.25, -0.02) increased, caregivers experienced a decline in their physical health during bereavement. Furthermore, caregivers who reported that caregiving interrupted their usual activities (b = -5.97; 95% CI = -9.79, -2.15) had a decline in physical health during bereavement. A poorer mental health status during bereavement was seen in caregivers who reported poor physical health during caregiving (b = -4.31; 95% CI = -8.17, -0.45); and that they received insufficient family support in caregiving (b = -6.01; 95% CI = -9.75, -2.27). It was also revealed that a home death was associated with higher mental health of the caregiver (b = 3.55; 95% CI = 0.26, 6.84). The practice implications of these findings are discussed in this paper.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".