Would standardized best practice guidelines to help patients, families and caregivers making end-of-life decisions for care be beneficial?
Bibliographic record
Abstract
Understanding the basis of personal clinical practice and identifying a potential research questionInitiating resuscitation for an incapacitated, palliative, or neurologically deceased person can be ethically and emotionally distressing for the nurses and health care team, and family involved in these situations.When a family or caregiver refuses to initiate a do-not-resuscitate (DNR) or life support withdrawal due to lack of knowledge, understanding and support, it is upsetting to all parties involved.Maintaining life support or not implementing a DNR plan of care is not always in the best interest of the patient.Throughout my career in a regional emergency and trauma centre, and currently in the cardiac setting at the University of Ottawa Heart Institute, these situations are a daily part of my nursing experience.I have had several opportunities to meet with the families who are making these end-of-life decisions.Each circumstance, while different, revolves around making the best decision for the well-being and dignity of the person who is incapacitated.In this area of practice, there are no set guidelines besides the Canadian Nurses Association's Code of Ethics for Registered Nurses to assist the nurse in assisting people to make these end-of-life care decisions.If there was a standardized teaching initiative for nurses faced with these aspects of care and patients and families faced with these decisions, everyone involved would be ensured that the outcome would be the best decision made under the circumstances.Overall, there is a general lack of knowledge of procedure, protocols and laws that revolve around withholding or withdrawing life support and end-of-life care.There is still the belief among laypeople that withdrawing life support or consenting to a DNR order will result in the withdrawal of expert and ethical treatment of their loved ones.If a best practice standard of care guideline was developed, then nurses would have guidance on how to best prepare and assist those making end-of-life decisions.
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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 | 0.000 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".