Updated recommendations on measures for clinical trials in pediatric chronic pain: a multiphase approach from the Core Outcomes in Pediatric Persistent Pain (Core-OPPP) Workgroup
Bibliographic record
Abstract
ABSTRACT: Many gaps remain in finding effective, safe, and equitable treatments for children and adolescents with chronic pain and in accessing treatments in different settings. A major goal of the field is to improve assessment of pain and related experience. Valid and reliable patient-reported outcome measures are critical for advancing knowledge of clinical interventions for pediatric chronic pain. Building on the work of the Ped-IMMPACT group, we previously updated a core outcome set (COS) for pediatric chronic pain clinical trials using stakeholder feedback from providers, youth, and parents. The new COS includes 3 mandatory domains: pain severity, pain-related interference with daily living, and adverse events and 4 optional domains: overall well-being, emotional functioning, physical functioning, and sleep quality. The aim of this study was to use a multiphased approach to recommend specific measures for each of the 7 domains identified in our new COS for pediatric chronic pain. We synthesized evidence through conducting the following: (1) a Delphi study of experts to identify candidate measures for the new COS domains, (2) a review phase to gather evidence for measurement properties for candidate measures, and (3) an expert consensus conference to reach agreement on measurement recommendations. Final recommendations included 9 patient-reported measures. Important contextual considerations are discussed, and guidance is provided regarding strengths and limitations of the recommendations. Implementation of these recommendations may be enhanced by widespread dissemination and ease of access to measurement tools.
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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 | 0.522 | 0.743 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.016 | 0.017 |
| Research integrity | 0.028 | 0.032 |
| Insufficient payload (model declined to judge) | 0.015 | 0.013 |
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".