Development and Validation of a Tool to Assess the Quality of Clinical Practice Guideline Recommendations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.270 | 0.484 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".