Psychotherapy at the End of Life
Bibliographic record
Abstract
, she identified a glaring gap in our understanding of how people cope with death, both on the part of the terminally ill patients that face death and as the clinicians who care for these patients. Now, 50 years later, a substantial and ever-growing body of research has identified "best practices" for end of life care and provides confirmation and support for many of the therapeutic practices originally recommended by Dr. Kübler-Ross. This paper reviews the empirical study of psychological well-being and distress at the end of life. Specifically, we review what has been learned from studies of patient desire for hastened death and the early debates around physician assisted suicide, as well as demonstrating how these studies, informed by existential principles, have led to the development of manualized psychotherapies for patients with advanced disease. The ultimate goal of these interventions has been to attenuate suffering and help terminally ill patients and their families maintain a sense of dignity, meaning, and peace as they approach the end of life. Two well-established, empirically supported psychotherapies for patients at the end of life, Dignity Therapy and Meaning Centered Psychotherapy are reviewed in detail.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".