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Anatomy Education Across the Health Professions: A Comparison of Student Perspectives on Body Donation

2020· article· en· W3017272685 on OpenAlexaffabout
Geoffroy Noël, Alexandra Claveria, Dona Bachour, Joseph B. Dubé, Rosetta Antonacci, Nicole M. Ventura

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsEmpathyCurriculumPsychologyMedical educationFeelingCompassionQualitative researchMedicinePedagogySocial psychology

Abstract

fetched live from OpenAlex

Cadaver‐based learning provides students with the opportunity to not only acquire the visual and tactile experiences necessary to properly apply anatomical knowledge but more importantly, an opportunity for students to reflect upon fundamental values of humanism, such as respect, empathy and compassion. Differences in students' perspectives across the health professions on body donation and the use of body donors as a component of their education has not yet been explored. The goal of the study was to qualitatively analyze the commonalities and differences in student perspectives on body donation across varying health professional programs including nursing, physical and occupational therapy and medicine. One‐page reflections written by nursing (N=37), physical and occupational therapy (N=49) and medical students (N=66) regarding their experiences in the McGill University anatomy laboratory were collected and qualitatively analyzed by deductive coding methods using Atlas.ti software. All of the data were thematically coded using a deductive approach, by 2 independent coders, according to the themes and sub‐themes described by Stephens et al., 2019 (How does Donor Dissection Influence Medical Students’ Perceptions of Ethics? A Cross‐Sectional and Longitudinal Qualitative Study, ASE 2019). IRB# A06‐B42‐17A. Despite the students having different curricula, there were only a few differences in what the nursing, physical and occupational therapy and medical students discussed in their reflections about body donation and cadaveric‐based learning, suggesting that the anatomy laboratory had similar effects on the different users. The nursing students were not reflective about the idea that working with different body donors provided them with unique learning experiences in the anatomy laboratory. In addition, the physical and occupational therapy students did not discuss the idea of maintaining the body donors' privacy by keeping parts of their bodies covered during the anatomy lab. The majority of the students from all three healthcare profession groups have mentioned that, as a result of their positive anatomy lab experience, they would like to give future generations the same privilege they had by donating their bodies to science. However, there were two nursing students that have concluded that they have decided not to donate their bodies to science. This qualitative study is the first of its kind because it directly compares student perspectives on body donation and cadaveric‐based learning, amongst three different health profession groups: nursing, physical and occupational therapy and medicine. This new information can help design interprofessional activities, which require mutual respect of another profession’s perspective, such commemorative services. Support or Funding Information This work was generously supported by the McGill University Faculty of Medicine Research Bursary Program.

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)0.007
metaresearch head score (Gemma)0.020
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.378
Teacher spread0.350 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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