The quality of four psychology practice guidelines using the Appraisal of Guidelines for Research and Evaluation (AGREE) II
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Clinical Practice Guidelines (CPGs) have been shown to improve healthcare services and clinical outcomes. However, they are useful resources only to the degree that they are developed according to the most rigorous standards. Multiple studies have demonstrated significant variability between CPGs with regard to specific indicators of quality. The Ordre des psychologues du Québec (OPQ), the College of psychologists of Quebec, has published several CPGs that are intended to provide empirically supported guidance for psychologists in the areas of assessment, diagnosis, general functioning, treatment and other decision-making support. The aim of this study was to evaluate the quality of these CPGs. METHODS: The Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument was used to assess the quality of the CPGs. RESULTS: Our results show that although there have been some modest improvements in quality of the CPGs over time, there are important methodological inadequacies in all CPGs evaluated. CONCLUSIONS: The findings of this study demonstrate the need for more methodological rigour in CPGs development as such, recommendations to improve CPG quality are discussed.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Evaluation · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.438 | 0.639 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.027 | 0.020 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".