Communicating prognostic uncertainty in potential end-of-life contexts: experiences of family members
Bibliographic record
Abstract
BACKGROUND: This article reports on the concept of "communicating prognostic uncertainty" which emerged from a mixed methods survey asking family members to rank their satisfaction in seven domains of hospital end-of-life care. METHODS: Open-ended questions were embedded within a previously validated survey asking family members about satisfaction with end-of-life care. The purpose was to understand, in the participants' own words, the connection between their numerical rankings of satisfaction and the experience of care. RESULTS: Our study found that nearly half of all family members wanted more information about possible outcomes of care, including knowledge that the patient was "sick enough to die". Prognostic uncertainty was often poorly communicated, if at all. Inappropriate techniques included information being cloaked in confusing euphemisms, providing unwanted false hope, and incongruence between message and the aggressive level of care being provided. In extreme cases, these techniques left a legacy of uncertainty and suspicion. Family members expressed an awareness of both the challenges and benefits of communicating prognostic uncertainty. Most importantly, respondents who acknowledged that they would have resisted (or did) knowing that the patient was sick enough to die also expressed a retrospective understanding that they would have liked, and benefitted, from more prognostic information that death was a possible or probable outcome of the patient's admission. Family members who reported discussion of prognostic uncertainty also reported high levels of effective communication and satisfaction with care. They also reported long-term benefits of knowing the patient was sick enough to die. CONCLUSION: While a patient who is sick enough to die may survive to discharge, foretelling with family members in potential end of life contexts facilitates the development of a shared and desired prognostic awareness that the patient is nearing end of life.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".