Minding the gap: student‐led, surgically oriented anatomy electives
Notice bibliographique
Résumé
The time dedicated to teaching anatomy in the modern medical curriculum has been substantially reduced. Many anatomy programmes have adapted strategies such as the use of prosection and team-based learning (TBL) to cope with time limitations. Regardless, studies have indicated that there are deficiencies in the clinical anatomy knowledge base of medical graduates, particularly with regard to surgically relevant anatomy, which could impact patient health and safety.1 In order to bridge this knowledge gap, third-year clerkship students (M3) at our institution (featuring a representative ‘modern’, 50-hour, prosection- and TBL-based anatomy programme) developed an Advanced Surgical Anatomy Interest Group (ASAIG) elective aimed at integrating common clinical encounters (patient presentations, diagnoses and surgical interventions) and the relevant anatomy. Three sessions were developed (lower limb, upper limb and abdomen). In each 2-hour session, ASAIG M3 leaders delivered presentations, drawing from their personal clerkship experiences, and participants subsequently reviewed anatomy in small groups using cadaveric prosections. Each group included both pre-clerkship (M1, M2) and clerkship (M3) students. Small-group review was facilitated by circulating ASAIG leaders and one anatomy professor. Upon session completion, participants were surveyed for general feedback. Sixty different students (n = 22, n = 21 and n = 17 in the M1, M2 and M3 groups, respectively) attended at least one session, and 18 students (including nine M2 students) attended multiple sessions. Thirty-six survey responses were collected (n = 11, n = 19 and n = 6 for M1, M2 and M3 students, respectively). Widely cited motivations for participation included relevance to career path (24 students indicated interest in a surgical specialty), the wish to be better prepared for clerkship (n = 11), and the wish to gain clinical anatomy knowledge beyond that covered in the curriculum (n = 7). Overall, the M2 group included the largest proportion of students to note each factor as motivating. Responses given on a rating scale of 1–6 (1 = strongly disagree, 6 = strongly agree) indicated that participants agreed with the following: the sessions had improved their knowledge of surgical anatomy (mean ± standard deviation [SD] score: 5.4 ± 0.2) and better prepared them for surgical clerkship rotations (mean ± SD score: 5.1 ± 0.3); the mix of pre-clerkship and clerkship students was beneficial to their learning (mean ± SD score: 5.5 ± 0.1), and near-peer teaching created a comfortable learning environment (mean ± SD score: 5.2 ± 0.2). The majority of participants (59%) preferred having clerkship students (rather than faculty staff) lead the sessions. In response to open-ended questions, participants demonstrated particular appreciation for the integration of clinical situations with surgically oriented anatomy (n = 10) and the small-group review that promoted exposure to student perspectives not typically encountered (n = 7), especially clerkship perspectives. Suggested improvements included having more sessions (n = 11), increasing the ratio of clerkship to pre-clerkship students (n = 2), and incorporating hands-on learning of specific surgical techniques (n = 3). In summary, the didactic integration of actual clinical clerkship experiences with relevant surgical anatomy, delivered by clerks to their near-peers, resulted in a time-efficient educational elective that increased student self-perceived preparedness regarding, and helped address curricular deficiencies in, surgical anatomy knowledge. An added benefit was the facilitation of engagement between clerkship and pre-clerkship students who do not normally interact, especially in anatomy learning contexts. These benefits were most appreciated by students about to enter clerkship.
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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 | 0,000 | 0,001 |
| 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 | 0,000 |
| 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 ».