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Record W1557398094 · doi:10.36834/cmej.36601

Medical student reporting of factors affecting pre-clerkship changes in empathy: a qualitative study

2013· article· en· W1557398094 on OpenAlexaffvenue
Hasan Sheikh, Jennifer Carpenter, Joy Wee

Bibliographic record

VenueCanadian Medical Education Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsQueen's University
Fundersnot available
KeywordsEmpathyPsychosocialFeelingPsychologyClinical psychologyMedical schoolPerspective (graphical)MedicineMedical educationSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To isolate factors that medical students identify as possibly affecting empathy in pre-clerkship years of medical school. METHODS: 12 students in their second year of medical school at Queen's University were randomly selected and asked to participate in semi-structured interviews conducted from an ethnographic perspective. RESULTS: Students reported both negative and positive changes in empathy. Negative changes included desensitization and focusing on the disease process, decreased ability to see things from patients' perspectives, and routine responses in emotional situations. These changes occur due to time constraints, objective lessons in empathy, and a changing identity. Positive changes included an increased awareness of the impact of illness, and increased ability to read feelings. These changes result from increased exposure to patients, discussions surrounding the psychosocial impact of illness, and positive role models. CONCLUSION: Students should be made aware of the limitations of objective lessons in empathy, and non-evaluated, implicit lessons should be emphasized when possible. Students should be encouraged to maintain relationships outside of medicine. Aspects of medical school that currently promote empathy should be reinforced, including exposure to patients, opportunities to work closely with positive role models, and practical discussions surrounding the psychosocial impact of illness.

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)0.007
metaresearch head score (Gemma)0.142
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.142
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0220.000

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 head0.050
GPT teacher head0.438
Teacher spread0.389 · 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 teacher head, not a consensus.

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

Citations13
Published2013
Admission routes2
Has abstractyes

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