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Record W2065762790 · doi:10.2147/jmdh.s3553

Competing interests in development of clinical practice guidelines for diabetes management: Report from a multidisciplinary workshop

2008· article· en· W2065762790 on OpenAlexafffundabout
Anna M. Sawka

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2008
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMultidisciplinary approachBioethicsScarcityMedical educationMedicinePublic relationsPsychologyEngineering ethicsPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the complex issue of competing interests (CIs) in development of clinical practice guidelines (CPGs) in diabetes with stakeholders. METHODS: A multidisciplinary panel of 26 health, methodological, legal, and bioethical experts, trainees, and lay people from across Canada participated in a workshop on CIs in CPGs. Mixed methods were used such that qualitative themes were extracted from the discussions and quantitative survey data were collected. RESULTS: In the discussions, participants acknowledged that potential competing interests were not uncommon among sponsoring organizations and authors of CPGs. Avoidance of all potential CIs in development of CPGs was emulated as ideal, but considered probably unrealistic, given the paucity of peer-reviewed funding opportunities for development of evidence-informed CPGs and the scarcity of knowledgeable authors without CIs. An optimal approach for management of CIs in CPGs could not be agreed upon by participants. Full disclosure of any financial CIs for authors and sponsoring organizations as well as discouragement of external financial contributors from writing involvement, were endorsed by participants in the workshop and a subsequent survey. CONCLUSIONS: Complete disclosure of financial CIs of sponsoring organizations and authors of CPGs is essential, yet the optimal approach to management of potential CIs is currently undefined.

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)0.010
metaresearch head score (Gemma)0.034
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 score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.481
GPT teacher head0.593
Teacher spread0.112 · 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

Citations4
Published2008
Admission routes3
Has abstractyes

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