Essential Anatomy for Clerkships and Electives–A Multi‐Site Survey of Clinical Educators
Notice bibliographique
Résumé
Introduction In the era of radical medical curriculum reform, the preclinical anatomy curriculum should not only prepare students for USMLE Step 1, but also provide sufficient knowledge for clinical clerkships and electives. Unfortunately, data regarding the anatomical knowledge considered essential for any given clerkship or elective is lacking. Aim This IRB study addresses the lack of data on the anatomical knowledge required for clinical clerkships and electives using an online survey provided to clerkship/elective educators to evaluate the importance of 98 anatomical items (tissues and structures) across all body regions using a 1‐to‐4 scale (1 = not important, 4 = essential). Methods For each clerkship/elective, the average ranking for each survey item was calculated for each body region; subsequently, an average ranking was calculated across all body regions for each clerkship/elective, as well as a “meta‐rank” for groups of clerkships/electives that were classified as Primary Care, Surgical/Procedural (further subdivided into specialties that ranked all anatomy in all regions vs. those that ranked only specific anatomy in some regions), or Non‐Surgical/Procedural. Results The initial data was from 165 clinical educators (clerkship/elective directors, attending physicians, residents, fellows) in 19 clerkships/electives at 13 medical schools. The table shows the average rankings for each clerkship/elective across all body regions, as well as a “meta‐rank” for broad practice areas. Discussion and Conclusions This expanding database represents the first comprehensive evaluation of the importance to clinical educators of specific tissues and structures in each anatomical region. While some of the average anatomy rankings for specific clerkships/electives were as might be expected (e.g., most surgical/procedural fields ranked anatomy highly whereas psychiatry ranked it very low), there were surprises (e.g., primary care fields as a whole ranked anatomy relatively highly). The rankings of specific anatomy within each region in this database (to be presented at the meeting) will provide detailed information regarding specific anatomical content that anatomists and medical schools can use to focus on in the preclinical years to prepare their students for success in their undergraduate and graduate medical clinical experiences. Average Rankings Across Body Regions image Average Rankings Across Body Regions This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».