The Effect of Anatomical Education for First Year Medical Students in Point of Care Ultrasound Training
Notice bibliographique
Résumé
Introduction With technological progress in portable Ultrasound machines, there is a growing demand for healthcare providers to perform bedside Ultrasonography, also known as Point of Care Ultrasound (POCUS). Training health care providers to perform POCUS can complement their physical examination findings, help them reach a more accurate diagnosis, improve patient outcomes and safety measurements for various therapeutic/diagnostic procedures. Properly performing POCUS requires both technical knowledge of how to operate the equipment, as well as functional knowledge of the involved anatomy. However, it is unknown exactly how students' previous anatomical knowledge affects their ability to appreciate and learn to effectively use POCUS. Aim To assess the effect of anatomical education on students' feelings towards POCUS training. Methods First year medical students at McMaster University participate in an integrated curriculum. Each week, half of the class attends an applied radiology session, including POCUS training, while the other half studies the related anatomy in a cadaver lab. In order to assess the effect of anatomy education on POCUS training, a preliminary qualitative study was conducted. A 5 question survey was distributed to each group, asking students to rate their feelings towards their POCUS training on a scale of 1–7. Further, students were given space on the survey to provide additional comments. 68 responses were collected from students who had not yet taken the anatomy sessions, while 57 surveys were collected from the students who had. Results The questions asked were: (A) Does the orientation of the probe position make sense with patient's anatomy? (B) Does the orientation of the probe position allow you to further understand the ultrasound images? (C) Does the session help you to reinforce your anatomy knowledge? (D) Do you think having anatomy knowledge helps you to learn ultrasound scanning training session easier? And (E) Did you wish to know more anatomy prior to this session? Students who had not yet received the corresponding anatomy session responded with consistently lower scores to each of questions (A)–(D). Both groups responded similarly to question (E). Discussion and Conclusion These results illustrate the importance of prior anatomical education for medical students being trained in POCUS. Students who had not yet completed the accompanying anatomy session experienced more difficulty understanding the relation of the probe's position to the corresponding images. Understandably, those students did not feel as though the POCUS training helped reinforce their anatomy knowledge, and did not feel as though their anatomy knowledge was helpful in the session. Interestingly, both groups similarly wished to know more anatomy prior to the session. These results suggest first year medical students value having anatomical education before learning POCUS techniques. Having previous anatomy knowledge helped students to better understand their POCUS training, and this training in turn helped the students reinforce their anatomy knowledge. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».