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Record W2396784326 · doi:10.1177/082585970301900404

Breaking Bad News: Impact of a Continuing Medical Education Workshop

2003· article· en· W2396784326 on OpenAlexaff
Roger Ladouceur, F Goulet, Robert Gagnon, Richard Boulé, Gilles Girard, André Jacques, Jacques Frenette, Robert Carrier, Viateur Lalonde, Claude Bélisle

Bibliographic record

VenueJournal of Palliative Care · 2003
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsCollege of Family Physicians of CanadaMerck Canada Inc. (Canada)Université de MontréalUniversité LavalAssociation des Médecins d'Urgence du QuébecGouvernement du QuébecUniversité du Québec à MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsMedical educationContinuing medical educationContinuing educationPsychologyPerceptionMedicineFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the impact of an interactive continuing medical education workshop designed to help physicians in breaking bad news to their patients. METHODOLOGY: Analysis of post-workshop questionnaires from 539 physicians assessing the retention of the key concepts and the perception of the potential impact of the workshop on their practice immediately after the workshop and six months later. RESULTS: The most significant concepts retained by the respondents are: the need to take into consideration the whole patient (42.7% post-workshop and 45.6% of follow-up responses), the need to be prepared for the consultation (11.6% and 15%), the importance of better guiding the interview (18.8% and 13.6%), and the value of taking more time during the consultation (5.8% and 8.3%). Analysis of paired responses on the post-workshop and the follow-up questionnaires shows that 35% of the concepts retained are identical. CONCLUSION: The majority of physicians retained the key concepts, both immediately following the workshop and in the longer term.

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.158
GPT teacher head0.506
Teacher spread0.348 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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