Teaching Palliative Care to Emergency Medicine Residents Using Gamified Deliberate Practice-Based Simulation: Palliative Gaming Simulation Study
Notice bibliographique
Résumé
BACKGROUND: Emergency departments (EDs) care for many patients nearing the end of life with advanced serious illnesses. Simulation training offers an opportunity to teach physicians the interpersonal skills required to manage end-of-life care. OBJECTIVE: We hypothesized a gaming simulation of an imminently dying patient using the LIVE. DIE. REPEAT (LDR) format, would be perceived as an effective method to teach end-of-life communication and palliative care management skills. METHODS: This was a gaming simulation replicating the experience of caring for a dying patient with advanced serious illness in the ED. The scenario involved a patient with pancreatic cancer presenting with sepsis and respiratory distress, with a previously established goal of comfort care. The gaming simulation game was divided into 4 stages, and at each level, learners were tasked with completing 1 critical action. The gaming simulation was designed using the LDR serious game scheme in which learners are allowed infinite opportunities to progress through defined stages depicting a single patient scenario. If learners successfully complete the predetermined critical actions of each stage, the game is paused, and there is a debriefing to reinforce knowledge or skills before progressing to the next stage of the gaming simulation. Conversely, if learners do not achieve the critical actions, the game is over, and learners undergo debriefing before repeating the failed stage with an immediate transition into the next. We used the Simulation Effectiveness Tool-Modified survey to evaluate perceived effectiveness in teaching end-of-life management. RESULTS: Eighty percent (16/20) of residents completed the Simulation Effectiveness Tool-Modified survey, and nearly 100% (20/20) either strongly or somewhat agreed that the gaming simulation improved their skills and confidence at the end of life in the following dimensions: (1) better prepared to respond to changes in condition, (2) more confident in assessment skills, (3) teaching patients, (4) reporting to the health care team, (5) empowered to make clinical decisions, and (6) able to prioritize care and interventions. All residents felt the debriefing contributed to learning and provided opportunities to self-reflect. All strongly or somewhat agree that they felt better prepared to respond to changes in the patient's condition, had a better understanding of pathophysiology, were more confident on their assessment skills, and had a better understanding of the medications and therapies after the gaming simulation. A total of 88% (14/16) of them feel more empowered to make clinical decisions. After completing the gaming simulation, 88% (14/16) of residents strongly agreed that they would feel more confident communicating with a patient and prioritizing care interventions in this context. CONCLUSIONS: This palliative gaming simulation using the LDR format was perceived by resident physicians to improve confidence in end-of-life communication and palliative care management.
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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 | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».