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Enregistrement W4386331342 · doi:10.7759/cureus.44414

Investigating the Skill Development of Medical Students in Focused Assessment With Sonography for Trauma (FAST) Ultrasound: A Comparative Analysis Across Different Stages of Medical Training

2023· article· en· W4386331342 sur OpenAlexaff
Michael Atalla, Andrew Yacoub, Hasan Al-Ali, Bianca Lupia, Layal Ezzeddine, Shaliz Barzani, Michelle Moussa, James Coey, Tarek Alambrouk, Haider Hilal

Notice bibliographique

RevueCureus · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueUltrasound in Clinical Applications
Établissements canadiensUniversity of WaterlooUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineSession (web analytics)Focused assessment with sonography for traumaMedical educationInclusion (mineral)Family medicineSurgeryPsychology

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Focused assessment with sonography for trauma (FAST) ultrasound (US) is a valuable medical examination used in trauma settings, particularly for rapid responses to events such as natural disasters. Although the efficacy and benefits of FAST in patient care have been extensively studied, there is limited research on training medical students in FAST. Previous studies have found that medical students can proficiently perform a FAST US after two days of training. However, these studies exclusively included first-year medical students without considering variations in their medical knowledge. Particularly, the advantage of medical students having US experience before undergoing FAST training has not been previously examined. OBJECTIVES: Assess the performance and knowledge acquisition of medical students with and without prior US experience after completing a FAST training course. METHODS: The study included a total of 71 students, consisting of 33 males and 38 females, who were between the ages of 18 and 31, with an average age of 24.6 and a standard deviation of 2.4. The inclusion criteria targeted first- and second-year medical school students who participated on a volunteer basis. Students were divided into two groups: group A, consisting of those without prior US experience, and group B, made up of those who had previous US experience. All students completed a pre-training survey to share their comfort and confidence in US use and knowledge. A baseline FAST exam was conducted to establish initial performance. A comprehensive three-hour training session was then provided. Post-training, students performed another FAST exam to assess improvement, followed by a post-training survey to evaluate comfort and confidence. RESULTS: Medical students who had prior experience in the US (group B) performed significantly better (p<0.01) in both the pre- and post-training FAST exams when compared to students without previous US experience. Specifically, in locating the liver, right kidney, hepatorenal recess, and left kidney, as well as detecting fluid accumulation when in a supine position. Additionally, medical students with prior US experience (group B) exhibited higher baseline confidence (p<0.005-p<0.01) in their ability to perform a FAST exam, as indicated by the results of the pre-testing survey. CONCLUSION: Previous experience with US significantly boosted confidence and knowledge gains following FAST training. This emphasizes the value of including US training in medical school programs after earlier exposure, offering evident benefits. The study reveals the unexplored benefit of having prior US experience for medical students undergoing FAST training, thus addressing a previously unexplored area in current research. The conclusions stress the necessity of integrating US training into medical school curricula after initial exposure. This understanding can direct medical educators in refining the education process, enabling students to be better equipped for real-world medical situations involving FAST.

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)0,001
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 enseignants0,032
Score d'incertitude au seuil0,525

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
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 Opus0,123
Tête enseignante GPT0,469
Écart entre enseignants0,346 · 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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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