Two-Dimensional Deaths? A Discourse Analysis of Patient Death in Preclinical Tutorial Cases at a Canadian Medical School
Notice bibliographique
Résumé
Introduction: The prospect of death is everywhere, but seldom directly addressed, in undergraduate medical education (UGME). Despite calls for UGME curricula to address the complex social and emotional aspects of death and dying, most curricula focus on biomedical, legal, and logistical aspects, or concentrate these topics within palliative care content and/or in simulations with simulated patients and manikins. We aimed to add to death education scholarship by exploring the complexities of death and dying within two dimensional simulations—i.e., in the text-based cases used in Case-Informed-Learning (CIL). Method: We conducted a critical discourse analysis exploring how death and dying were discursively constructed in the formal, planned curriculum at one medical school. We used two methods: (1) Document Analysis: We developed a template to analyze 127 cases regarding their discursive constructions of death and dying; (2) Longitudinal Interviewing: We conducted semi-structured interviews with a cohort of 12 medical students, twice annually throughout their medical program (total 92 interviews). We collectively analyzed data, attuning to how the format, content, and purpose of each case discursively constructed death and dying. Results: There were 127 tutorial cases included in the undergraduate, pre-clerkship case-informed curriculum. In the five (4%) cases featuring a patient who dies, death and dying were discursively constructed as: (1) predictable; (2) a plot device; (3) a cautionary tale; (4) an epilogue; (5) deliberate and careful; and (6) an absence. Very few cases highlighted death and dying in their titles, learning objectives, or questions, and where it did feature, it was framed a biomedical fact or outcome. Only one case allowed for a nuanced, in-depth and open-ended discussion of patient death and dying, but it was scheduled at a time that prevented meaningful engagement. This glossing over the complexities of death was identified as a missed opportunity by students, who, as their clinical placements loomed, were eager to broach this topic in detail with tutors and other teaching faculty. Discussion: Death was often a conspicuous absence in this CIL curriculum. In the few cases that featured the death of the main patient character, multiple discourses were mobilized that worked together to construct death as something that happens elsewhere, outside the parameters of core curriculum. In other words, death happens—predictably, slowly, as a means to an end and the result of moral failures, in the case or somewhere in the future—but was not the primary concern. To deepen engagement with these subjects in CIL, we encourage medical educators to attend to representations of patient death by considering the format, content, purpose, and timing of these cases. Conclusion: Carefully rendered cases thoughtfully embedded in the curriculum offer tremendous potential. We suggest nuanced cases featuring patient death, with plenty of space and time for discussion, reflection, and storytelling may help address gaps in formal UGME preclinical curricula addressing death and dying.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 tête enseignante, 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 ».