Evaluating Treatment Outcome in an Interdisciplinary Pediatric Pain Service
Bibliographic record
Abstract
OBJECTIVE: To provide descriptive data evaluating outcome and treatment satisfaction among former pediatric patients and their parents seen in an interdisciplinary treatment program for complex pain syndromes. DESIGN: Retrospective telephone interview. SETTING: Pediatric academic health care centre. SUBJECTS AND METHODS: A semistructured interview designed for this study was administered by phone with 24 former patients (mean age 15.63 years) and parents, seen over the previous three years in the Complex Pain Consultation Service. Participants provided both qualitative and quantitative information about pre‐ and post‐treatment levels of pain and functioning, achievement of treatment goals and satisfaction with the treatment program. RESULTS: Findings indicated significantly lower frequency and intensity of pain, as rated by patients, when current pain levels were compared with recalled pretreatment levels. As well, improvements were reported in strategies for managing pain and participation in regular activities of daily living. Satisfaction with the team treatment was generally very high, and most felt that their goals were partially to completely met. Child and parent ratings of outcome and satisfaction were consistent. CONCLUSIONS: These descriptive data provide preliminary support for the application of an interdisciplinary model to treating disabling complex pain syndromes in children and youths.
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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 | 0.001 | 0.011 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".