The rocks and hard places of MAiD: a qualitative study of nursing practice in the context of legislated assisted death
Notice bibliographique
Résumé
Abstract Background Medical Assistance in Dying (MAiD) was legalized in Canada in June, 2016. The Canadian government’s decision to legislate assisted dying, an approach that requires a high degree of obligation, precision, and delegation, has resulted in unique challenges for health care and for nursing practice. The purpose of this study was to better understand the implications of a legislated approach to assisted death for nurses’ experiences and nursing practice. Methods The study used a qualitative approach guided by Interpretive Description. Semi-structured interviews were conducted with 59 registered nurses and nurse practitioners. Interviews were audio-recorded, transcribed, and managed using qualitative analysis software. Analysis followed a procedure of data immersion, open coding, constant comparative analysis, and the construction of a thematic and interpretive account. Results Nurses in this study described great variability in how MAiD had been enacted in their work context and the practice supports available to guide their practice. The development of systems to support MAiD, or lack thereof, was largely driven by persons in influential leadership positions. Workplaces that supported a range of nurses’ moral responses to MAiD were most effective in supporting nurses’ well-being during this impactful change in practice. Participants cited the importance of teamwork in providing high quality MAiD-related care; although, many worked without the benefit of a team. Nursing work related to MAiD was highly complex, largely because of the need for patient-centered care in systems that were not always organized to support such care. In the absence of adequate practice supports, some nurses were choosing to limit their involvement in MAiD. Conclusions Data obtained in this study suggested that some workplace contexts still lack the necessary supports for nurses to confidently meet the precision required of a legislated approach to MAiD. Without accessible palliative care, sufficient providers, a supportive team, practice supports, and a context that allowed nurses to have a range of responses to MAiD, nurses felt they were legally and morally at risk. Nurses seeking to provide the compassionate care consistent with such a momentous moment in patients’ lives, without suitable supports, find themselves caught between the proverbial rock and hard place.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,019 | 0,023 |
| Communication savante | 0,008 | 0,008 |
| Science ouverte | 0,004 | 0,009 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».