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Enregistrement W3035292487 · doi:10.2196/17277

Evaluating the Instructional Design and Effect on Knowledge, Teamwork, and Skills of Technology-Enhanced Simulation-Based Training in Obstetrics in Uganda: Stepped-Wedge Cluster Randomized Trial

2020· article· en· W3035292487 sur OpenAlexvenueno aff
Anne Antonia Cornelia van Tetering, Maartje H.M. Segers, Peter Ntuyo, Imelda Namagambe, M. Beatrijs van der Hout‐van der Jagt, Josaphat Byamugisha, S. Guid Oei

Notice bibliographique

RevueJMIR Medical Education · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueSimulation-Based Education in Healthcare
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTeamworkInstructional designRandomized controlled trialDescriptive statisticsMedical educationComputer scienceInstructional simulationMedicinePsychologyMultimediaEducational technologyMathematics educationStatistics

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Simulation-based training is a common strategy for improving the quality of facility-based maternity services and is often evaluated using Kirkpatrick's theoretical model. The results on the Kirkpatrick levels are closely related to the quality of the instructional design of a training program. The instructional design is generally defined as the "set of prescriptions for teaching methods to improve the quality of instruction with a goal of optimizing learning outcomes." OBJECTIVE: The aim of this study is to evaluate the instructional design of a technology-enhanced simulation-based training in obstetrics, the reaction of participants, and the effect on knowledge, teamwork, and skills in a low-income country. METHODS: A stepped-wedge cluster randomized trial was performed in a university hospital in Kampala, Uganda, with an annual delivery volume of over 31,000. In November 2014, a medical simulation center was installed with a full-body birthing simulator (Noelle S550, Gaumard Scientific), an interactive neonate (Simon S102 Newborn CPR Simulator, Gaumard Scientific), and an audio and video recording system. Twelve local obstetricians were trained and certified as medical simulation trainers. From 2014 to 2016, training was provided to 57 residents in groups of 6 to 9 students. Descriptive statistics were calculated for ten instructional design features of the training course measured by the 42-item ID-SIM (Instructional Design of a Simulation Improved by Monitoring). The Wilcoxon signed rank test was conducted to investigate the differences in scores on knowledge, the Clinical Teamwork Scale, and medical technical skills. RESULTS: The mean scores on the ten instructional design features ranged from 54.9 (95% CI 48.5-61.3) to 84.3 (95% CI 80.9-87.6) out of 100. The highest mean score was given on the feature feedback and the lowest scores on repetitive practice and controlled environment. The overall score for the training day was 92.8 out of 100 (95% CI 89.5-96.1). Knowledge improved significantly, with a test score of 63.4% (95% CI 60.7-66.1) before and 78.9% (95% CI 76.8-81.1) after the training (P<.001). The overall score on the 10-point Clinical Teamwork Scale was 6.0 (95% CI 4.4-7.6) before and 5.9 (95% CI 4.5-7.2) after the training (P=.78). Medical technical skills were scored at 55.5% (95% CI 47.2-63.8) before and 65.6% (95% CI 56.5-74.7) after training (P=.08). CONCLUSIONS: Most instructional design features of a technology-enhanced simulation-based training in obstetrics in a low-income country were scored high, although intervals were large. The overall score for the training day was high, and knowledge did improve after the training program, but no changes in teamwork and (most) medical technical skills were found. The lowest-scored instructional design features may be improved to achieve further learning aims. TRIAL REGISTRATION: ISRCTN Registry ISRCTN98617255; http://www.isrctn.com/ISRCTN98617255. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12884-020-03050-3.

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)0,003
score de la tête « metaresearch » (Gemma)0,039
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,640
Score d'incertitude au seuil0,969

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,039
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,050
Tête enseignante GPT0,432
Écart entre enseignants0,382 · 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.

Devis d'étudeEssai randomisé
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

Citations11
Publié2020
Routes d'admission1
Résumé présentoui

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