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Enregistrement W2085651790 · doi:10.1111/j.1365-2923.2010.03654.x

Development of an undergraduate curriculum in obstetrical simulation

2010· article· en· W2085651790 sur OpenAlexaff
Glenn Posner, Amy Nakajima

Notice bibliographique

RevueMedical Education · 2010
Typearticle
Langueen
DomaineMedicine
ThématiqueSimulation-Based Education in Healthcare
Établissements canadiensHealth Canada
Organismes subventionnairesnon disponible
Mots-clésCurriculumObstetrics and gynaecologyMedical educationSpecialtyPresentation (obstetrics)Session (web analytics)Experiential learningMedicineObstetricsPsychologyFamily medicinePedagogyPregnancyComputer science

Résumé

récupéré en direct d'OpenAlex

Because of the sensitive nature of the specialty, medical students can often be marginalised during their obstetrics rotation. Opportunities for hands-on experience are often lacking, yet we know that experiential learning increases understanding and activates trainees. As the use of simulation becomes more common in postgraduate medical education, the question of its application to the undergraduate experience becomes relevant. A curriculum was designed for a simulation-based workshop during the first week of the obstetrics clerkship to instruct students in the diagnosis of labour and intrapartum management. Prior to the development of this curriculum, formal teaching for clerkship students in obstetrics and gynaecology at our institution consisted solely of didactic lectures. The objective of this innovation was to assess the effectiveness of a new simulator-based curriculum on learning during the obstetrics clerkship. As a secondary outcome, it was hoped that these sessions would engage the students and serve to lessen their anxiety at the start of their rotation, optimise their experiences, and foster an interest in pursuing postgraduate training in obstetrics and gynaecology. A structured simulation-based curriculum was developed in accordance with the educational objectives of the US-based Association of Professors of Gynecology and Obstetrics. A total of 110 students from the class of 2010 at our university attended a small-group session at the simulation centre, which incorporated the use of a high-fidelity obstetrical manikin. The curriculum is based on a single obstetrical patient whose clinical course is followed by the students from presentation in the obstetrics assessment unit to eventual delivery and postpartum care. The students are given the opportunity to examine the patient several times during the course of her labour to assess her dilation. During the discussion, they are able to handle forceps, vacuum extractors, amniotomy hooks and scalp electrodes. The workshop culminates in a mock delivery managed by each student. The students completed a pre-test just prior to the teaching session and a post-test immediately after the session. This test addressed definitions, risk factors and management decisions relevant to basic intrapartum care and mirrored the content of the workshop. Written feedback was solicited from the first group of students. Performance on the two tests was compared using inferential and descriptive statistics. Following the session, the median student score increased significantly from 40.0% (14/35, standard deviation [SD] = 5.5) on the pre-test to 71.4% (25/35, SD = 4.3) on the post-test (P < 0.01). Scores ranged from 2 to 29 out of 35 on the pre-test and from 9 to 33 out of 35 on the post-test. Thirty-eight students rated ‘the overall quality of the session’ and ‘the appropriateness of the topic’ on a 10-point Likert scale. Mean scores were 8.7/10 for quality and 9.1/10 for appropriateness. High-fidelity simulation can be a useful adjunct to the current education of medical students. A structured, interactive simulation curriculum in obstetrics is an effective teaching approach and is well received by medical students.

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)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,246
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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.

Tête enseignante Opus0,021
Tête enseignante GPT0,401
Écart entre enseignants0,380 · 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; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations6
Publié2010
Routes d'admission1
Résumé présentoui

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