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Twelve myths about shared decision making

2014· review· en· 404 citations· W2061907426 on OpenAlex· 10.1016/j.pec.2014.06.014

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow), Science and technology studies
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Other designConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.963
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.176
GPT teacher head0.487
Teacher spread
0.311 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

OBJECTIVE: As shared decision makes increasing headway in healthcare policy, it is under more scrutiny. We sought to identify and dispel the most prevalent myths about shared decision making. METHODS: In 20 years in the shared decision making field one of the author has repeatedly heard mention of the same barriers to scaling up shared decision making across the healthcare spectrum. We conducted a selective literature review relating to shared decision making to further investigate these commonly perceived barriers and to seek evidence supporting their existence or not. RESULTS: Beliefs about barriers to scaling up shared decision making represent a wide range of historical, cultural, financial and scientific concerns. We found little evidence to support twelve of the most common beliefs about barriers to scaling up shared decision making, and indeed found evidence to the contrary. CONCLUSION: Our selective review of the literature suggests that twelve of the most commonly perceived barriers to scaling up shared decision making across the healthcare spectrum should be termed myths as they can be dispelled by evidence. PRACTICE IMPLICATIONS: Our review confirms that the current debate about shared decision making must not deter policy makers and clinicians from pursuing its scaling up across the healthcare continuum.

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.

The record

Venue
Patient Education and Counseling
Topic
Patient-Provider Communication in Healthcare
Field
Health Professions
Canadian institutions
Hôpital Saint-François d'AssiseUniversité Laval
Funders
not available
Keywords
ScrutinyMythologyHealth careDecision aidsPsychologyPublic relationsPolitical scienceMedicineAlternative medicineHistoryLaw
Has abstract in OpenAlex
yes