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Record W2976680886 · doi:10.1136/bmjopen-2019-031767

Extending the RIGHT statement for reporting adapted practice guidelines in healthcare: the RIGHT-Ad@pt Checklist protocol

2019· article· en· W2976680886 on OpenAlexaff
Yang Song, Andrea Darzi, Mónica Ballesteros, Laura Martínez García, Pablo Alonso‐Coello, Thurayya Arayssi, Soumyadeep Bhaumik, Yaolong Chen, Françoise Cluzeau, Davina Ghersi, Paulina Fuentes Padilla, Étienne V Langlois, Holger J. Schünemann, Robin W.M. Vernooij, Elie A. Akl

Bibliographic record

VenueBMJ Open · 2019
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsMcMaster UniversityImpact
FundersUniversitat Autònoma de BarcelonaWorld Health Organization
KeywordsChecklistMedicineProtocol (science)Delphi methodGuidelineMedical educationProcess (computing)WaiverHealth careStatement (logic)PsychologyAlternative medicineComputer sciencePathologyPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION: The adaptation of guidelines is an increasingly used methodology for the efficient development of contextualised recommendations. Nevertheless, there is no specific reporting guidance. The essential Reporting Items of Practice Guidelines in Healthcare (RIGHT) statement could be useful for reporting adapted guidelines, but it does not address all the important aspects of the adaptation process. The objective of our project is to develop an extension of the RIGHT statement for the reporting of adapted guidelines (RIGHT-Ad@pt Checklist). METHODS AND ANALYSIS: To develop the RIGHT-Ad@pt Checklist, we will use a multistep process that includes: (1) establishment of a Working Group; (2) generation of an initial checklist based on the RIGHT statement; (3) optimisation of the checklist (an initial assessment of adapted guidelines, semistructured interviews, a Delphi consensus survey, an external review by guideline developers and users and a final assessment of adapted guidelines); and (4) approval of the final checklist. At each step of the process, we will calculate absolute frequencies and proportions, use content analysis to summarise and draw conclusions, discuss the results, draft a report and refine the checklist. ETHICS AND DISSEMINATION: We have obtained a waiver of approval from the Clinical Research Ethics Committee at the Hospital de la Santa Creu i Sant Pau (Barcelona, Spain). We will disseminate the RIGHT-Ad@pt Checklist by publishing into a peer-reviewed journal, presenting to relevant stakeholders and translating into different languages. We will continuously seek feedback from stakeholders, surveil new relevant evidence and, if necessary, update the checklist.

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)0.033
metaresearch head score (Gemma)0.074
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.440
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.074
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 science0.0010.000
Research integrity0.0000.000
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 head0.455
GPT teacher head0.642
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

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

Citations24
Published2019
Admission routes1
Has abstractyes

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