Portuguese Patient Dignity Question: A cross-sectional study of palliative patients cared for in primary care
Bibliographic record
Abstract
INTRODUCTION: The Patient Dignity Question (PDQ) is a clinical tool developed with the aim of reinforcing the sense of personhood and dignity, enabling health care providers (HCPs) to see patients as people and not solely based on their illness. OBJECTIVE: To study the acceptability and feasibility of the Portuguese version of the PDQ (PDQ-PT) in a sample of palliative care patients cared for in primary care (PC). METHOD: A cross-sectional study using 20 palliative patients cared for in a PC unit. A post-PDQ satisfaction questionnaire was developed. RESULTS: Twenty participants were included, 75% were male; average age was 70 years old. Patients found the summary accurate, precise, and complete; all said that they would recommend the PDQ to others and want a copy of the summary placed on their family physician's medical chart. They felt the summary heightened their sense of dignity, considered it important that HCPs have access to the summary and indicated that this information could affect the way HCPs see and care for them. The PDQ-PT's took 7 min on average to answer, and 10 min to complete the summary. SIGNIFICANCE OF RESULTS: The PDQ-PT is well accepted and feasible to use with palliative patients in the context of PC and seems to be a promising tool to be implemented. Future trials are now warranted.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".