When Frail Individuals or Their Families Request Nonindicated Interventions: Usefulness of the Four‐Box Ethical Approach
Bibliographic record
Abstract
In the age of person-centered care, there is an emphasis on promoting patient autonomy and surrogate decision maker authority in making treatment decisions that are aligned with the patient's priorities and values. As technological advances offer multiple clinical options with various levels and types of risks and benefits, person-centered clinical practice encourages the incorporation of patients' and families' heterogeneous experiences into decisions regarding illness management. In caring for frail elderly adults, clinicians are sometimes faced with situations in which individuals and their surrogate decision-makers request a treatment that the clinicians feel is clinically inappropriate. This article provides a case example of a frail older adult with advanced chronic kidney disease who requests dialysis despite the advice of his nephrologist to pursue conservative management. The four-box approach, which provides clinicians with a structured ethical framework to facilitate informed and ethically justified treatment decisions, is then introduced. By considering the patient's medical indications, preferences, quality of life, and contextual factors, how each consideration plays a unique yet equally important role in informing clinically responsible and person-centered care is illustrated.
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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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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".