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Record W4214618287 · doi:10.1186/s12909-021-03051-6

Virtue and care ethics & humanism in medical education: a scoping review

2022· review· en· W4214618287 on OpenAlexaff
David J. Doukas, David T. Ozar, Martina Darragh, Janet de Groot, Brian S. Carter, Nathan Stout

Bibliographic record

VenueBMC Medical Education · 2022
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Calgary
FundersArnold P. Gold Foundation
KeywordsVirtueHumanismVirtue ethicsMedical ethicsHealth careCurriculumEngineering ethicsNursing ethicsBioethicsEpistemic virtueSociologyMedicinePedagogyLawPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: This scoping review explores how virtue and care ethics are incorporated into health professions education and how these factors may relate to the development of humanistic patient care. METHOD: Our team identified citations in the literature emphasizing virtue ethics and care ethics (in PubMed, NLM Catalog, WorldCat, EthicsShare, EthxWeb, Globethics.net , Philosopher's Index, and ProQuest Central) lending themselves to constructs of humanism curricula. Our exclusion criteria consisted of non-English articles, those not addressing virtue and care ethics and humanism in medical pedagogy, and those not addressing aspects of character in health ethics. We examined in a stepwise fashion whether citations: 1) Contained definitions of virtue and care ethics; 2) Implemented virtue and care ethics in health care curricula; and 3) Evidenced patient-directed caregiver humanism. RESULTS: Eight hundred eleven citations were identified, 88 intensively reviewed, and the final 25 analyzed in-depth. We identified multiple key themes with relevant metaphors associated with virtue/care ethics, curricula, and humanism education. CONCLUSIONS: This research sought to better understand how virtue and care ethics can potentially promote humanism and identified themes that facilitate and impede this mission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.438
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.438
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0040.034
Insufficient payload (model declined to judge)0.0460.001

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 head0.417
GPT teacher head0.666
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations61
Published2022
Admission routes1
Has abstractyes

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