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The anatomy course during the time of COVID‐19 ‐ students’ initiation of reflections on life's passing in dissection and non‐dissection anatomy courses

2021· article· en· W3160216318 on OpenAlexaff
Anette Wu, Rachel Utomo, Mandeep Gill Sagoo, Richard Wingate, Cecilia Brassett, C. L. Chien, Hannes Traxler, Jens Waschke, Franziska Vielmuth, Takeshi Sakurai, Mina Zeroual, Jørgen Olsen, Salma El Batti, Suvi Viranta, Yukari Yamada, Sean McWatt, Shuji Kitahara, Kevin A. Keay, Anne Kellett, Michael Skonieczny, Yinghui Mao, Ariella Lang, Carol Kunzel, Paulette Bernd, Heike Kielstein, Geoffroy Noël

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsDissection (medical)Coronavirus disease 2019 (COVID-19)Gross anatomyAnatomyPsychologyMedical educationHuman anatomyPandemicMedicinePathologyDisease

Abstract

fetched live from OpenAlex

Background During the COVID‐19 pandemic, in‐person cadaveric dissection to teach anatomy was often omitted. While knowledge‐based assessment can be evaluated via remote exams, soft skills (e.g., reflections on the topic of death) can often be overlooked. This study aims to quantitatively investigate how different anatomy course formats play a role in initiating students’ reflections on life's passing, during the COVID‐19 pandemic. Method In the fall semester of 2020, 216 medical, dental, premedical undergraduate, and health sciences students from 14 international universities discussed (in small groups) differences in their anatomy courses as part of an online exchange program. Formats of anatomy education delivery in the 14 universities ranged from dissection, hybrid dissection‐prosection, and prosection only, to no laboratory exposure during the pandemic. Students’ responses to the question, “Did/does your Anatomy course initiate your thinking on life's passing?” were collected utilizing a multiple‐choice question and a short essay. Statistical analysis was performed using Chi‐square analysis. Results 105 students dissected (group 1), 21 had a hybrid dissection‐prosection class (group 2), and 79 had no dissection (group 3). 11 students did not have an anatomy course. Within the 3 groups, 149 students had exposure to human anatomical specimens and 52 students did not. A majority of students in groups 1 and 2 reported that the anatomy course helped them to initiate reflections on the topic of death, compared to those in group 3 (75% and 71% respectively, versus 36%, p<0.05). The majority of students who had exposure to human anatomical specimens thought that the course did initiate thoughts about life's passing, compared to students who did not have this exposure (p<0.05). Students who did not dissect during the time of the pandemic felt that talking with their peers who did dissect during this period (i.e., at schools that did offer dissection) resulted in initiating thoughts about the topic of death. Discussion Anatomy dissection courses and exposure to human anatomical specimens help initiate reflection on the topic of life's passing. During the COVID‐19 pandemic interactions between students who do not dissect and their peers who do dissect help initiate thoughts about the topic of death in the non‐dissecting students, as reflected by their essays. Without exposure to human bodies there is less chance that students will think about this subject. Conclusion Anatomy dissection courses are important for the initiation of students’ feelings about the topic of death. During the COVID‐19 pandemic, dissecting students can help non‐dissecting students with initiating reflections about life's passing by discussing this subject with each other.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.311
Teacher spread0.299 · 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
Published2021
Admission routes1
Has abstractyes

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