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Record W2016020766 · doi:10.1111/medu.12568

Minding the gap: student‐led, surgically oriented anatomy electives

2014· article· en· W2016020766 on OpenAlexaff
Christopher J. Ramnanan, Andrew Adamczyk, A. Martel, Andrew Stokl

Bibliographic record

VenueMedical Education · 2014
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGross anatomyCurriculumSession (web analytics)Medical educationMedicinePsychological interventionPsychologyAnatomyNursingPedagogy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.279
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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