Existential Suffering, Futility, and the Mental Stress of Moral Distress in Health Care
Bibliographic record
Abstract
This article explores the relationship of existential suffering and moral distress by examining life-threatening medical situations and the distress on persons engaged in medical ethics decision-making. The aim and focus are to articulate how existential suffering experienced by the patient and family generates moral distress in the health-care team as they perceive ongoing treatments as futile. Suffering and existential suffering pose a challenge ethically and therapeutically on a number of levels, first in terms of determining what a patient wants to be addressed or what a substitute decision-maker needs to consider in fulfilling the best interests of the patient who is suffering. Second, when there are unrelenting and intolerable sufferings, a difficult medical assessment is sometimes made that any further treatments are “futile,” which leads to conflict with the family and moral distress for the medical team. Moral distress and mental stress have physiological, psychological, social/behavioral, and existential-spiritual dimensions. Existential suffering consists of a constellation of factors, not only severe pain but also the inclusion of harms from the illness, which are irreversible, irremediable, and unrelenting, adding to the total suffering. This article argues that the existential suffering of the patient and family has a special moral status that significantly and legitimately guides decisions at the end of life, and addressing the existential suffering of the patient/family can relieve levels of moral distress for the health-care team.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| 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".