Factors associated with higher quality of clinical practice guidelines and their recommendations for the pharmacological treatment of depression: a systematic review
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to assess the quality of clinical practice guidelines (CPGs) for the pharmacological treatment of depression along with their recommendations and factors associated with higher quality. DESIGN: We conducted a systematic review that included CPGs for the pharmacological treatment of depression in adults. DATA SOURCES: We searched for publications from 1 January 2011 to 31 December 2021, in MEDLINE, Cochrane Library, Embase, PsycINFO, BVS and 12 other databases and guideline repositories. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included CPGs containing recommendations for the pharmacological treatment of depression in adults at outpatient care setting, regardless of whether it met the U.S. National Academy of Medicine criteria, or not. If a CPG included recommendations for both children and adults, they were considered. No language restriction was applied. DATA EXTRACTION AND SYNTHESIS: Data extraction was also conducted independently and in duplicate, a process that was validated in a previous project. The quality of the CPGs and their recommendations were assessed by three independent reviewers using Appraisal of Guidelines for Research and Evaluation (AGREE II) and Appraisal of Guidelines for Research and Evaluation-Recommendations Excellence (AGREE-REX). A CPG was considered to be of high quality if AGREE II Domain 3 was ≥60%; while their recommendations were considered high if AGREE-REX Domain 1 was ≥60%. RESULTS: Seventeen out of 63 (27%) CPGs were classified as high quality, while 7 (11.1%) had high-quality recommendations. The factors associated with higher-scoring CPGs and recommendations in the multiple linear regression analyses were 'Handling of conflicts of interest', 'Multiprofessional team' and 'Type of institution'. 'Inclusion of patient representative in the team' was also associated with higher-quality recommendations. CONCLUSIONS: The involvement of professionals from diverse backgrounds, the handling of conflicts of interest, and the inclusion of patients' perspectives should be prioritised by developers aiming for high-quality CPGs for the treatment of depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.143 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, not a consensus.
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".