Palliative sedation: Nurses’ perceptions
Bibliographic record
Abstract
Patients with advanced illnesses suffer from a myriad of distressing symptoms. Palliative care aims to alleviate the distress caused by such symptoms. In extreme circumstances palliative sedation may be implemented to manage symptom distress that is not responsive to standard treatment modalities. Nurses are involved in the care of patients receiving palliative sedation as well as their families. To date, however, little research has been conducted examining the nurses' experiences with, and perceptions about the use of palliative sedation in end-of-life care. In order to redress this gap in the literature a descriptive-exploratory study guided by the theory of symbolic interactionism was conducted. Face-to-face interviews were conducted with 10 nurses working on an adult in-patient palliative care unit within a long-term care facility in Canada. The major theme emerging from content analysis of interview transcripts was that of 'Working your way through the quagmire'. The metaphor of the quagmire captured the difficult and complex issues nurses grappled with in instances where palliative sedation was used, and integrates the major categories into the key analytic model emerging from this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".