The development and validation of a questionnaire to audit advance care planning (ACP)
Bibliographic record
Abstract
ACP is an established standard of care in many settings. However, no validated tool exists to evaluate patients' and their families' perspectives on ACP. The purpose of this study was to develop and validate a novel questionnaire to evaluate the quantity and quality of ACP from the perspective of a patient and their family member. To develop the questionnaire, items were generated from focus groups with health care professionals and face to face interviews with hospitalised patients. This questionnaire was then piloted and evaluated by a sample of hospitalised patients who had advanced illnesses and their family members. The questionnaire was divided into 2 parts, the first part covering ACP activities before hospital admission (6 questions) and the second part relating to' goals of care' discussions that occurred during hospitalisation (8 questions). 27 patients and 24 family members participated in the pilot. All respondents rated the language, clarity, fit, acceptability, and relevance as ‘fair’ to ‘excellent.’ On a 10 point scale where 1=“Not a burden at all” and 10= “Extremely burdensome,” the average (SD) burden score of patients was 2.2 (1.7) and for family members was 1.6 (0.9). Revisions to the questionnaire were made based on the feedback from respondents. We conclude that our questionnaire to evaluate key ACP practices has face and content validity. Our pilot study demonstrates the feasibility and acceptability of this evaluative approach. By auditing ACP practices, from the patient/family perspective, practitioners may gain key insights into how to improve ACP processes in their settings.
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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 | 0.070 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".