Dignity-based approaches in the care of terminally ill patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: Promoting dignified dying is an altruistic goal in palliative care. Until recently, what was meant by this construct was poorly understood. This review seeks to clarify what is meant by dignity at the end of life, what threatens dignity, and evidence of the domains that define dignity. A model of dignity is proposed from which interventions can be derived. RECENT FINDINGS: A paucity of research exists exploring the concept of dignity. What can be gleaned from this work is that dignity is socially constructed and mediated in our relationships with others. Research has noted that self-perceived burden, depression, hopelessness, and 'the reflection patients see of themselves in the eye of the beholder' are intimately connected to one's notion of dignity. A model of dignity in the terminally ill has been developed that outlines three areas that are most influential in shaping dignity. Interventions such as dignity therapy and critical personal reflection are proposed as tools to promote dignity. SUMMARY: Despite the fact that little research exists exploring the notion of dignity at the end of life, a robust model of dignity exists and is helpful in directing interventions aimed at improving care at the 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".