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Record W2091605506 · doi:10.1371/journal.pone.0062537

Shared Decision Making Does Not Influence Physicians against Clinical Practice Guidelines

2013· article· en· W2091605506 on OpenAlexaff
Mireille Guerrier, France Légaré, Stéphane Turcotte, Michel Labrecque, Louis‐Paul Rivest

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsTheory of planned behaviorAnalysis of covarianceMedicinePsychologyRandomized controlled trialControl (management)Family medicineClinical psychologySocial psychologyStatisticsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: While shared decision making (SDM) and adherence to clinical practice guidelines (CPGs) are important, some believe they are incompatible. This study explored the mutual influence between physicians' intention to engage in SDM and their intention to follow CPGs. METHODS: Embedded within a clustered randomized trial to assess the impact of training physicians in SDM about using antibiotics to treat acute respiratory tract infections, this study evaluated physicians' intentions to both engage in SDM and follow CPGs. A self-administered questionnaire based on the theory of planned behavior evaluated both behavioral intentions and their respective determinants (attitude, subjective norm and perceived behavioral control) at study entry and exit. We used path analysis to explore the relationships between the intentions. We conducted statistical analyses using the maximum likelihood method and the variance-covariance matrix. Goodness of fit indices encompassed the chi-square statistic, the comparative fit index and the root mean square error of approximation. RESULTS: We analyzed 244 responses at entry and 236 at exit. In the control group, at entry we observed that physicians' intention to engage in SDM (r = 0, t = 0.03) did not affect their intention to follow CPGs; however, their intention to follow CPGs (r = -0.31 t = -2.82) did negatively influence their intention to engage in SDM. At exit, neither behavioral intention influenced the other. In the experimental group, at entry neither behavioral intention influenced the other; at exit, the intention to engage in SDM still did not influence the intention to use CPGs, although the intention to follow CPGs (r = -0.15 t = -2.02) slightly negatively influenced the intention to engage in SDM, but this was not clinically significant. CONCLUSION: Physicians' intention to engage in SDM does not affect their intention to adopt CPGs even after SDM training. Physicians' intention to adopt CPGs had no clinically significant influence on intention to engage in SDM. TRIAL REGISTRATION: ClinicalTrials.gov NCT01116076.

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)0.021
metaresearch head score (Gemma)0.155
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.155
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.469
GPT teacher head0.522
Teacher spread0.053 · 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 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

Citations30
Published2013
Admission routes1
Has abstractyes

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