Is the National Guideline Clearinghouse a Trustworthy Source of Practice Guidelines for Child and Youth Anxiety and Depression?
Bibliographic record
Abstract
OBJECTIVE: Innovative strategies that facilitate the use of high quality practice guidelines (PG) are needed. Accordingly, repositories designed to simplify access to PGs have been proposed as a critical component of the network of linked interventions needed to drive increased PG implementation. The National Guideline Clearinghouse (NGC) is a free, international online repository. We investigated whether it is a trustworthy source of child and youth anxiety and depression PGs. METHOD: English language PGs published between January 2009 and February 2016 relevant to anxiety or depression in children and adolescents (≤ 18 years of age) were eligible. Two trained raters assessed PG quality using Appraisal of Guidelines for Research and Evaluation (AGREE II). Scores on at least three AGREE II domains (stakeholder involvement, rigor of development, and editorial independence) were used to designate PGs as: i) minimum quality (≥ 50%); and ii) high quality (≥ 70%). RESULTS: Eight eligible PGs were identified (depression, n=6; anxiety and depression, n=1; social anxiety disorder, n=1). Four of eight PGs met minimum quality criteria; three of four met high quality criteria. CONCLUSIONS: At present, NGC users without the time and special skills required to evaluate PG quality may unknowingly choose flawed PGs to guide decisions about child and youth anxiety and depression. The recent NGC decision to explore the inclusion of PG quality profiles based on Institute of Medicine standards provides needed leadership that can strengthen PG repositories, prevent harm and wasted resources, and build PG developer capacity.
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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 | 0.384 | 0.830 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".