MétaCan
Menu
Back to cohort

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

2023· article· en· W4389947678 on OpenAlexaff
Tonya M. Palermo, Rui Li, Kathryn A. Birnie, Geert Crombez, Christopher Eccleston, Susmita Kashikar‐Zuck, Amanda Stone, Gary A. Walco

Bibliographic record

VenuePain · 2023
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Calgary
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsWorkgroupMedicineCore (optical fiber)Chronic painClinical trialPhysical therapyInternal medicineComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.170
metaresearch head score (Gemma)0.084
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1700.084
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.307
GPT teacher head0.438
Teacher spread0.131 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePainSame topicPediatric Pain Management TechniquesFrench-language works237,207