Quality assessment of clinical guidelines for the treatment of obesity in adults: application of the AGREE II instrument
Bibliographic record
Abstract
There are various guidelines for the treatment of obesity, and thus the quality of these clinical guidelines has become a matter of concern. The objective was to describe and assess the quality of clinical guidelines for treatment of obesity in adults. We collected several studies, dated from 1998 to 2016, produced by different countries. The literature search included the National Guideline Clearinghouse (NGC), Guidelines International Network (GIN), PubMed (MEDLINE), Scopus, Web of Science, webpages of health institutions from different countries, and search sites, with the criterion: "clinical guidelines for treatment of obesity in adults and published until the 2016". The guidelines were assessed with the Appraisal of Guidelines for Research & Evaluation (AGREE II), according to the domains of the instrument. The search identified 21 guidelines: nine from Europe, six from North America, three from Latin America, and one each from Asia and Oceania and a transnational association. The Australian guideline had the best assessment. Of the six guidelines with the highest scores, five had been elaborated by the government sector responsible for the country's health. The domains "scope and purpose" and "clarity of presentation" had the highest score. Except for the Canadian guideline, the three guidelines drafted before the elaboration of AGREE II had the worst quality. In the domain "stakeholder involvement", only four guidelines (Australia, Scotland, France, and England) mentioned patient participation. Guideline development and quality enhancement are ongoing processes requiring systematic appraisal of the guideline production process and existing guidelines.
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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 | 0.252 | 0.447 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.027 | 0.030 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".