Evaluation of the Quality of Dying and Death Questionnaire in Kenya
Bibliographic record
Abstract
PURPOSE A culturally appropriate, patient-centered measure of the quality of dying and death is needed to advance palliative care in Africa. We therefore evaluated the Quality of Dying and Death Questionnaire (QODD) in a Kenyan hospice sample and compared item ratings with those from a Canadian advanced-cancer sample. METHODS Caregivers of deceased patients from three Kenyan hospices completed the QODD. Their QODD item ratings were compared with those from 602 caregivers of deceased patients with advanced cancer in Ontario, Canada, and were correlated with overall quality of dying and death ratings. RESULTS Compared with the Ontario sample, outcomes in the Kenyan sample (N = 127; mean age, 48.21 years; standard deviation, 13.57 years) were worse on 14 QODD concerns and on overall quality of dying and death ( P values ≤ .001) but better on five concerns, including interpersonal and religious/spiritual concerns ( P values ≤ .005). Overall quality of dying was associated with better patient experiences with Symptoms and Personal Care, interpersonal, and religious/spiritual concerns ( P values < .01). Preparation for Death, Treatment Preferences, and Moment of Death items showed the most omitted ratings. CONCLUSION The quality of dying and death in Kenya is worse than in a setting with greater PC access, except in interpersonal and religious/spiritual domains. Cultural differences in perceptions of a good death and the acceptability of death-related discussions may affect ratings on the QODD. This measure requires revision and validation for use in African settings, but evidence from such patient-centered assessment tools can advance palliative care in this region.
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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 | 0.003 | 0.008 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".