Pediatric chronic pain programs: current and ideal practice
Bibliographic record
Abstract
INTRODUCTION: The treatment of youth with chronic pain has improved in recent years. However, because pediatric chronic pain programs are not governed by international standards, the development and implementation of new initiatives may be limited. OBJECTIVES: The objectives of this study were to identify the features of programs as they exist at present and to determine what features they should have in an ideal state. METHODS: A web-based international survey was used to collect information. The survey contained 86 questions seeking respondent professional demographic data and information about the pain program with which the respondent was affiliated at the time (program organization, types of pain problem treated, professionals involved, services provided, size of the program, research, professional training, public education and advocacy, and funding sources). RESULTS: Respondents were 136 pediatric pain experts representing different specialties located in 12 countries. Most respondents indicated that ideal programs would have a multidisciplinary staff; provide a wide range of treatments for different chronic pain problems; integrate research, formal clinical training of specialists, and public education and advocacy into their activities; and be an accredited part of the public health system. CONCLUSIONS: The results of this survey may be useful for health care professionals interested in treating chronic pain in children and adolescents and for policy makers concerned with improving the care given to these children and their families.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".