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Record W2680854180 · doi:10.1136/bmjopen-2017-015945

Assessing medical student knowledge and attitudes about shared decision making across the curriculum: protocol for an international online survey and stakeholder analysis

2017· article· en· W2680854180 on OpenAlexaffabout
Marie‐Anne Durand, Renata W. Yen, Paul Barr, Nan Cochran, Johanna W. M. Aarts, France Légaré, Malcolm Reed, A. James O’Malley, Peter Scalia, Geneviève Painchaud Guérard, Glyn Elwyn

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsHôpital Saint-François d'AssiseUniversité Laval
FundersNational Cancer InstituteUniversity of California, San FranciscoYale University
KeywordsMedicineCurriculumMedical educationThematic analysisChecklistStakeholderQualitative propertyData collectionThe InternetSample (material)Computer-assisted web interviewingProtocol (science)Qualitative researchAlternative medicinePublic relationsPsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Shared decision making (SDM) is a goal of modern medicine; however, it is not currently embedded in routine care. Barriers include clinicians’ attitudes, lack of knowledge and training and time constraints. Our goal is to support the development and delivery of a robust SDM curriculum in medical education. Our objective is to assess undergraduate medical students’ knowledge of and attitudes towards SDM in four countries. METHODS AND ANALYSIS: The first phase of the study involves a web-based cross-sectional survey of undergraduate medical students from all years in selected schools across the United States (US), Canada and undergraduate and graduate students in the Netherlands. In the United Kingdom (UK), the survey will be circulated to all medical schools through the UK Medical School Council. We will sample students equally in all years of training and assess attitudes towards SDM, knowledge of SDM and participation in related training. Medical students of ages 18 years and older in the four countries will be eligible. The second phase of the study will involve semistructured interviews with a subset of students from phase 1 and a convenience sample of medical school curriculum experts or stakeholders. Data will be analysed using multivariable analysis in phase 1 and thematic content analysis in phase 2. Method, data source and investigator triangulation will be performed. Online survey data will be reported according to the Checklist for Reporting the Results of Internet E-Surveys. We will use the COnsolidated criteria for REporting Qualitative research for all qualitative data. ETHICS AND DISSEMINATION: The study has been approved for dissemination in the US, the Netherlands, Canada and the UK. The study is voluntary with an informed consent process. The results will be published in a peer-reviewed journal and will help inform the inclusion of SDM-specific curriculum in medical education worldwide.

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)0.098
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.098
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.072
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.006
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0600.015

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 head0.744
GPT teacher head0.709
Teacher spread0.036 · 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 designNot applicable
Domainnot available
GenreProtocol

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
Published2017
Admission routes2
Has abstractyes

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