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Development and Validation of a Tool to Assess the Quality of Clinical Practice Guideline Recommendations

2020· article· en· W3028923082 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsSt. Michael's HospitalNorth York General HospitalOttawa HospitalMcMaster UniversityUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsUsabilityGuidelineCronbach's alphaReliability (semiconductor)Scale (ratio)ExcellenceQuality (philosophy)PsychologyApplied psychologyRigourMedical educationMedicinePsychometricsComputer scienceClinical psychologyMathematics

Abstract

fetched live from OpenAlex

Importance: Clinical practice guidelines (CPGs) may lack rigor and suitability to the setting in which they are to be applied. Methods to yield clinical practice guideline recommendations that are credible and implementable remain to be determined. Objective: To describe the development of AGREE-REX (Appraisal of Guidelines Research and Evaluation-Recommendations Excellence), a tool designed to evaluate the quality of clinical practice guideline recommendations. Design, Setting, and Participants: A cross-sectional study of 322 international stakeholders representing CPG developers, users, and researchers was conducted between December 2015 and March 2019. Advertisements to participate were distributed through professional organizations as well as through the AGREE Enterprise social media accounts and their registered users. Exposures: Between 2015 and 2017, participants appraised 1 of 161 CPGs using the Draft AGREE-REX tool and completed the AGREE-REX Usability Survey. Main Outcomes and Measures: Usability and measurement properties of the tool were assessed with 7-point scales (1 indicating strong disagreement and 7 indicating strong agreement). Internal consistency of items was assessed with the Cronbach α, and the Spearman-Brown reliability adjustment was used to calculate reliability for 2 to 5 raters. Results: A total of 322 participants (202 female participants [62.7%]; 83 aged 40-49 years [25.8%]) rated the survey items (on a 7-point scale). All 11 items were rated as easy to understand (with a mean [SD] ranging from 5.2 [1.38] for the alignment of values item to 6.3 [0.87] for the evidence item) and easy to apply (with a mean [SD] ranging from 4.8 [1.49] for the alignment of values item to 6.1 [1.07] for the evidence item). Participants provided favorable feedback on the tool's instructions, which were considered clear (mean [SD], 5.8 [1.06]), helpful (mean [SD], 5.9 [1.00]), and complete (mean [SD], 5.8 [1.11]). Participants considered the tool easy to use (mean [SD], 5.4 [1.32]) and thought that it added value to the guideline enterprise (mean [SD], 5.9 [1.13]). Internal consistency of the items was high (Cronbach α = 0.94). Positive correlations were found between the overall AGREE-REX score and the implementability score (r = 0.81) and the clinical credibility score (r = 0.76). Conclusions and Relevance: This cross-sectional study found that the AGREE-REX tool can be useful in evaluating CPG recommendations, differentiating among them, and identifying those that are clinically credible and implementable for practicing health professionals and decision makers who use recommendations to inform clinical policy.

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.

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)0.018
metaresearch head score (Gemma)0.059
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.645
GPT teacher head0.624
Teacher spread0.021 · 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