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Enregistrement W4389356530 · doi:10.11124/jbies-23-00517

Interprofessional disaster exercises in nursing curricula: a necessary inclusion

2023· editorial· en· W4389356530 sur OpenAlexaboutno aff
Thi Thuy Ha Dinh, Kathleen Tori, Sonia Hines

Notice bibliographique

RevueJBI Evidence Synthesis · 2023
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueDisaster Response and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésInclusion (mineral)CurriculumNatural disasterNursingHealth carePandemicMedical educationMedicinePsychologyCoronavirus disease 2019 (COVID-19)Political sciencePedagogyGeography

Résumé

récupéré en direct d'OpenAlex

Natural disasters (eg, floods, landslides), emergencies (eg, bombings, mass casualty incidents), and public health crises (eg, the COVID-19 pandemic) have occurred frequently in recent years,1 adversely affecting the health and well-being of many individuals. Consequently, it is imperative for health professionals to be thoroughly prepared and equipped to respond promptly and effectively when these situations arise. Our scoping review in this issue of JBI Evidence Synthesis2 explores how disaster exercises involving students from various health care disciplines, including nursing, have been organized globally. Disaster exercises are learning opportunities in a lab environment (eg, simulations) or in simulated settings (eg, drills), with the purpose of replicating a disaster situation for students to practice roles safely under supervision. Scoping review methodology was chosen to gather existing literature on the planning and implementation of these disaster exercises and to help identify the key lessons and research gaps. The review focused on understanding the roles of nursing students in simulated disaster scenarios, as nurses are often frontline personnel in such situations, as well as the lessons derived from these exercises and the outcomes measured. The review mapped 13 papers from 12 studies (1 mixed method, 1 survey, 3 pre-post test studies, and 7 studies reporting the planning of exercises without student-level data) published between 2009 and 2021. The studies were conducted in the United States (9 studies), Canada (2 studies), and Australia (1 study). The limited number of studies suggests that this topic has not received significant coverage in nursing curricula, with notable gaps in disaster management subjects across undergraduate nursing courses.3–5 The disaster exercises varied in terms of the professions and stakeholders involved, including both health professionals (eg, medicine, paramedicine) and non-health professionals (eg, police, firefighters), the contexts of disasters (eg, flood, bus crash, bombing), the methods used to conduct the exercises, and the underlying purposes. Many of the disaster exercises were designed to help students achieve specific learning goals, such as recognizing critical events and implementing initial and appropriate responses,6 evaluating interprofessional collaboration during simulated disasters, honing clinical judgment and patient safety skills, and improving communication. Several studies underscored the importance of clarifying students’ roles in these disaster exercises, either during the planning phase or at orientation, as confusion arose when students were not properly informed about their responsibilities in the exercises.7,8 Overall, there was inconsistency in how the disaster simulations were conducted, with no single model or framework to guide the training, although most reported a post-simulation timeline that included debriefing.9 The findings of the review emphasized that disaster exercises require comprehensive training of volunteer patients, briefing of participants, and ample resources and consumables to replicate real-life situations.2 The findings also stressed the importance of allocating sufficient time, not only for conducting the exercises, but also for planning beforehand, as well as for debriefing after the disaster simulation. The review highlighted that thorough exercise planning is vital to provide a positive learning experience, and all aspects of the preparatory phase must be carried out systematically to achieve the desired outcomes.2 This includes careful attention to details, such as conducting student orientation to familiarize them with the scenario and learning objectives, clearly defining roles for students and others involved, allocating necessary resources (both logistical and financial), ensuring collaborative efforts among multidisciplinary organizers, communication planning, and limiting the number of participants to a manageable level.7,8,10 The process of conducting disaster exercises should encompass defining clear goals and project scope; identifying key stakeholders, methods, and necessary resources for the exercises; conducting debriefing sessions for all participants; and conducting thorough evaluations of all aspects of the disaster exercise to ensure optimal efficiency. Educators could also consider integrating disaster-related content earlier in their courses and provide opportunities for students to consolidate the skills they learn in capstone subjects.3 It was interesting to note that there were no studies from other countries frequently affected by natural disasters, for example, those in the Asian regions. Ultimately, disaster simulation inclusion in nursing, or indeed any health professional curricula, is not only “nice to have” but a necessity to prepare students for these scenarios in their professional roles.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,016
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesIntégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,274
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,016
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0010,004
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,003

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.

Tête enseignante Opus0,027
Tête enseignante GPT0,439
Écart entre enseignants0,412 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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