Which has more influence on a family's assessment of the quality of dying of their long-term care resident with dementia: Frequency of symptoms or quality of communication with healthcare team?
Bibliographic record
Abstract
Abstract Objective Symptoms present at the end of life and the quality of communication with the healthcare team have both been shown to impact family assessments of the quality of dying of their loved one with dementia. However, the relative contributions of these two factors to family assessments have not yet been investigated. To address this knowledge gap, we explored which of these two factors has more influence on family assessments of the quality of dying of long-term care (LTC) residents with dementia. Method This is a secondary analysis of a mortality follow-back study. Ninety-four family members of LTC residents who had died with dementia assessed the quality of dying ( very good or not very good ), the frequency of symptoms, and the quality of communication with the healthcare team using a self-administered questionnaire mailed 1 month after the resident's death. Logistic regression analyses were performed to determine the relative contributions of the two independent variables of primary interest (frequency of symptoms and quality of communication) to the families’ assessments of the quality of dying. Results Multivariate analyses revealed that the quality of communication with the healthcare team was closely linked to the quality of dying ( p = 0.009, OR = 1.34, 95% CI = 1.09–1.65), whereas the frequency of symptoms was not ( p = 0.142, OR = 1.05, 95% CI = 0.98–1.11) after controlling for potential confounders. Significance of results Our findings show that healthcare providers’ ability to engage in the end-of-life conversations with families outweighs the frequency of symptoms in family assessments of the quality of dying of their relative with dementia. Enhancing healthcare providers’ ability to communicate with families about the end-of-life care could improve families’ perceptions of the quality of dying of their relative with dementia and, consequently, ease their grieving process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".