Paradoxes, nurses’ roles and Medical Assistance in Dying: A grounded theory
Bibliographic record
Abstract
BACKGROUND: In June 2016, the Parliament of Canada passed federal legislation allowing eligible adults to request Medical Assistance in Dying (MAID). Since its implementation, there likely exists a degree of hesitancy among some healthcare providers due to the law being inconsistent with personal beliefs and values. It is imperative to explore how nurses in Quebec experience the shift from accompanying palliative clients through "a natural death" to participating in "a premeditated death." RESEARCH QUESTION/AIM/OBJECTIVES: This study aims to explore how Quebec nurses personally and professionally face the new practice of MAID and their role evolution. RESEARCH DESIGN: A grounded theory design was used. PARTICIPANTS AND RESEARCH CONTEXT: We recruited 37 nurses who participated in or coordinated at least one MAID. Semi-structured interviews and focus groups were conducted and audiotaped. Data collection and analysis followed Strauss and Corbin steps. ETHICAL CONSIDERATIONS: Ethics approval was received from the investigator's affiliated University. Participants were informed regarding the research goal, signed a written consent, and were assigned pseudonyms. FINDINGS/RESULTS: Results show that nurses experienced the wide range of paradoxe during MAID centering around the following eight elements: 1) confrontation abouth death, 2) choice, 3) time of death, 4) emotional load, 5) new Bill, 6) relationship with the person, 7) communication skills, and 8) healthcare setting. The shifting of views and values in this new role is presented by the contradiction of opposites. CONCLUSIONS: A better understanding of the paradox experienced by nurses involved with MAID paves the way for the development of interventions.
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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 | 0.028 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.008 | 0.039 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".