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Informed Consent Skills in Internal Medicine Residency: How Are Residents Taught, and What Do They Learn?

2004· article· en· W1970889779 on OpenAlexaffabout
Karen McClean, Sharon E. Card

Bibliographic record

VenueAcademic Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsRoyal University HospitalUniversity of Saskatchewan
Fundersnot available
KeywordsInformed consentComprehensionMedical educationPrivilege (computing)PsychologyMedicineFamily medicineAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: Obtaining informed consent is an essential skill in internal medicine (IM). The authors' informal observations and formal testing revealed deficiencies in residents' informed consent skills. This study evaluated how residents acquire informed consent skills and how informed consent skills are addressed in Canadian IM residency programs. METHOD: A questionnaire was delivered to all 16 IM program directors in Canada, asking how informed consent is taught and assessed. At the University of Saskatchewan IM residency program, residents were assessed through an objective structured clinical examination station, written examination, and a self-assessment questionnaire. RESULTS: No consistent approach to teaching or evaluating informed consent skills exists within Canadian IM programs. Program directors and residents identified informal mentoring by residents as an important learning modality. Although residents performed well in discussing procedural indications and techniques, discussing risks was inadequate. Residents focused on general and minor risks but avoided discussing serious risks and had difficulty discussing the frequency of complications. Residents lacked a structured approach to assessing capacity and often assessed only comprehension. Residents were unfamiliar with concepts such as material risk, implied consent, and therapeutic privilege. CONCLUSION: Explicit training in informed consent skills is urgently needed. Informal mentoring must be recognized as an important training method for informed consent and supported by appropriate teaching and evaluation strategies to ensure that resident-instructors do so effectively.

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)0.002
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.368
Teacher spread0.340 · 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 designObservational
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

Citations63
Published2004
Admission routes2
Has abstractyes

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