Mortality communication as a predictor of psychological distress among family caregivers of home hospice and hospital inpatients with terminal cancer
Bibliographic record
Abstract
Terminally ill cancer patients and their caregivers experience significant difficulties discussing illness and impending death (herein defined as mortality communication). The current study compares response levels as well as patterns of association between mortality communication and psychological distress among caregivers of home hospice and hospital inpatients. For this study, 231 family caregivers were recruited within a year of bereavement from the south and central health regions of Israel. Contrary to our initial hypothesis, retrospectively reported levels of mortality communication did not differ between groups; however, lower levels of depressive symptomatology were reported by home hospice caregivers. Separate path analytic models indicate statistically significant inverse associations between mortality communication and psychological distress (i.e. depressive symptomatology, emotional exhaustion). Invariance analyses indicate that the strength of association between variables did not differ between path models. The results of this study are discussed in terms of self-selection biases and possible confounds associated with retrospective reporting among bereaved caregivers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".