Study Preregistration: Measuring What Matters: Development and Dissemination of a Core Outcome Set for Pediatric Anxiety Disorders Clinical Trials
Bibliographic record
Abstract
Pediatric anxiety disorders (AD) are prevalent disorders with an impact on all aspects of a child’s life and functioning.1 Although evidence supports commonly used treatments, there are notable concerns with the research to date.2 Heterogeneity in outcome selection, measurement, analysis, and reporting is a contributing factor to the hinderance of the translation of research into clinical practice.3 Recognition for outcome standardization in pediatric mental health disorders is evolving and there are several initiatives of importance, including the International Consortium for Health Outcomes Measurement (ICHOM), which has developed standardized outcome sets for use in the routine clinical mental health treatment of children and adolescents.4 Similarly, the International Alliance of Mental Health Research Funders5 advocate for use of 1 specific outcome measurement instrument (OMI) in the youth mental health research that they fund. Development of a Core Outcome Set (COS), a minimal set of outcomes that should be measured and reported in clinical trials, has been a solution in other areas of medicine to address heterogeneity in outcome selection and measurement across trials.6 The Core Outcomes and Measures in Pediatric Anxiety Clinical Trials (COMPACT) Initiative will develop a harmonized, evidence- and consensus-based COS that is meaningful to youth and families for use in future trials in pediatric AD.
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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 | 0.710 | 0.779 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".