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Enregistrement W2019901454 · doi:10.1111/j.1365-2929.2005.02288.x

Integration of ultrasound in the education programme in anatomy

2005· article· en· W2019901454 sur OpenAlex

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affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueMedical Education · 2005
Typearticle
Langueen
DomaineMedicine
ThématiqueUltrasound in Clinical Applications
Établissements canadiensMcMaster University Medical Centre
Organismes subventionnairesnon disponible
Mots-clésHuman anatomyContext (archaeology)MedicineUltrasoundSurface anatomySession (web analytics)Medical physicsRadiologyAnatomyMedical educationComputer science

Résumé

récupéré en direct d'OpenAlex

Context and setting Medical students invest a significant amount of time studying human structure using a variety of resources. They often find it challenging to visualise the functioning living human and to apply their learning clinically. Because ultrasound imaging provides a means of visualising structure and movement in a living person, it was proposed that it could be used to enhance and facilitate the learning of functional clinical anatomy. An ultrasound learning resource was located within the anatomy area to enable students to integrate their learning through ultrasound with the study of specimens and other resources. Why the idea was necessary The purpose of the study was to determine the effect on student learning of integrated ultrasound anatomy teaching sessions. These sessions included an introduction to the technology of ultrasound imaging and the hands-on experience of performing an examination in order to provide students with the opportunity to develop basic imaging skills, and to enhance their knowledge of surface and visceral anatomy. What was done Groups of 6 first-year medical students had an integrated clinical skills, anatomy and radiology session, followed by a series of 3 90-minute ultrasound anatomy sessions provided by a radiologist during the cardiovascular and renal subunits. The sessions included an introduction to the use of the ultrasound imaging, the setting of learning objectives, guidance on the location of landmarks and the visualisation of organs and tissues, a hands-on experience conducting an ultrasound examination on a living human, a discussion of its clinical relevance and an evaluation of the session. The objectives of the examinations were to use various approaches and scans to visualise and identify specific cardiac structures, major abdominal vessels, carotid arteries and the kidneys, as well as noting the relationships of adjacent structures. Videos of related pathologies were also discussed. The students were evaluated on their ability to perform an ultrasound examination at the end of the first and the last sessions, and received formative evaluation. For this study, a 5-point scale was used: from 1 = poor (inadequate identification of ‘acoustic window’ required for visualisation of prioritised structures) to 5 = excellent (ability to detect normal and pathological surface anatomy and functional morphology on reference standards). Approximately 490 medical students from 4 consecutive classes participated. The average score at the end of the first session was 3.25 ± 0.12, compared to the last session (4.15 ± 0.16; P < 0.005). The scores from this study were not provided to the students or incorporated into their formal evaluation. The student evaluations of the sessions were consistently excellent (score of 5/5), and included highly positive comments. Evaluation of results and impact The results of this study show that the small-group problem-based ultrasound anatomy sessions for students in the Medical Program at McMaster University, which focuses on small-group problem-based active learning, are a highly effective method for facilitating student learning and significantly enhance knowledge of living clinical anatomy. In addition, they provide students with a basic understanding of ultrasound imaging and its use in clinical practice. Finally, the students value these innovative sessions highly and find that this use of ultrasound is an exciting and engaging approach to stimulate the learning of ‘living’ clinical anatomy and enhance their clinical reasoning skills.

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.

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)0,001
score de la tête « metaresearch » (Gemma)0,007
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,832
Score d'incertitude au seuil0,851

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,007
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)0,0000,000

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 Opus0,025
Tête enseignante GPT0,407
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