Forensic nursing and the palliative approach to care: an empirical nursing ethics analysis
Bibliographic record
Abstract
BACKGROUND: A movement is underway to promote a palliative approach to care in all contexts where people age and live with life-limiting conditions, including psychiatric settings. Forensic psychiatry nursing-a subfield of mental health nursing- focuses on individuals who are in conflict with the criminal justice system. We know little about the values of nurses working in forensic psychiatry, and how these values might influence a palliative approach to care for frail and aging patients. METHOD: Interviews with four nurses working on one of two forensic units of a university-affiliated mental health hospital in an urban area of eastern Canada. FINDINGS: Three specific values were found to guide forensic nurses in their care of aging patients that are commensurate with a palliative approach: hope, inclusivity, and quality of life. CONCLUSION: When we started this project, we wondered whether the culture of forensic nursing practice was antithetical to the values of a palliative approach. Instead, we found several parallels between forensic nurses' moral identities and palliative philosophy. These findings have implications for how we think about the palliative approach in contexts not typically associated with palliative care, but in which patients will increasingly age and die.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".