An appraisal of the trustworthiness of practice guidelines for depression and anxiety in children and youth
Bibliographic record
Abstract
OBJECTIVE: Little is known about the trustworthiness of clinical practice guidelines (PGs) relevant to child and youth depression or anxiety. To address this gap, we used systematic review methods to identify all available relevant PGs, quality appraise them, and make recommendations regarding which PGs are trustworthy and should be used by clinicians. METHODS: Prespecified inclusion criteria identified eligible PGs. Two independent trained reviewers applied the Appraisal of Guidelines for Research and Evaluation (AGREE II) tool. Using three AGREE II domain scores (stakeholder involvement, rigor of development [clinical validity/trustworthiness], and editorial independence), PG quality was designated as (1) minimum (≥50%) and (2) high (≥70%). RESULTS: Of 25 eligible PGs, five met minimum quality criteria (depression, n = 4; anxiety, n = 1); three out of five met high-quality criteria (depression, n = 2; anxiety, n = 1). Among the five minimum quality PGs, developers included government (n = 2), independent expert groups (n = 2), and other (n = 1). No PGs developed by specialty societies achieved minimum or high-quality ratings; eight of 25 PGs were up-to-date. CONCLUSIONS: Trustworthy PGs are available to support clinical decisions about depression and anxiety in children and youth, but are few in number. Many existing PGs (up to 80%) may not be clinically valid. Clinicians who implement the high-quality PGs identified here can increase the number of children and youth who receive effective interventions for depression and anxiety, minimize harm, and avoid wasted resources. Clinicians, service planners, youth, and their families should encourage PG developers to increase the pool of high-quality PGs using internationally recognized PG development standards.
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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 | 0.614 | 0.897 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.028 | 0.019 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.008 | 0.008 |
| 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, 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".