“Our best hope is a cure.” Hope in the context of advance care planning
Bibliographic record
Abstract
OBJECTIVE: Advance care planning (ACP) has the potential to enhance end-of-life care, yet often fails to live up to that potential. This qualitative interpretive study was designed to explore the process and outcomes of ACP using the patient-centered Advance Care Planning Interview (PC-ACP) developed by the Respecting Choices® program in Wisconsin. METHOD: Patients diagnosed with advanced lung cancer and close family members were recruited. Nine family dyads participated in the PC-ACP interview, which was audio-recorded. Follow-up interviews took place 3 and 6 months after the PC-ACP interview and were also recorded. Thematic analysis was conducted on transcribed interviews using constant comparison. RESULTS: Analysis showed that hope was a significant theme in the ACP process and this article reports on that theme. Hope for a cure was one of many hopes that supported quality of life for the participant dyads. Three themes were identified: hope is multifaceted, hope for a cure is well considered, and hope is resilient and persistent. The seeming paradox of hoping for a cure of an incurable cancer did not interfere with the process of ACP. The dyads engaged in explicit discussions of end-of-life scenarios and preferences for care. ACP did not interfere with hope and hope for a cure did not interfere with ACP. SIGNIFICANCE OF RESULTS: Concerns about false hope are called into question. The principle of honoring hope is not necessarily in conflict with the principle of truthful communication. This is clinically significant, as the findings suggest we need not disrupt hope that we think of as "unrealistic" as long as it supports the family to live well. Further, ACP can be successful even in the context of hoping for a cure.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.006 |
| 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".