The effect domains, measures, and methods reported in pediatric‐specialized multidisciplinary outpatient rehabilitation programs: An integrated review
Bibliographic record
Abstract
OBJECTIVES: Specialized pain rehabilitation is recognized as the treatment of choice for youth with pain-related disability. Appropriate outcomes for program evaluation are critical. This study aimed to summarize the effect domains and methods used to evaluate pediatric-specialized outpatient pain rehabilition programs, map them to the PedIMMPACT statement, and highlight future directions. METHODS: An integrated review framework, incorporating stakeholders, was used. Academic Search Complete, CINAHL, ERIC, MEDLINE, PsycINFO, and Google Scholar were searched for studies published in 1999-2021 featuring the treatment effects of specialized outpatient pain rehabilitation on youth with pain-related disability and their parents. Selected studies were critically appraised using the Quality Assessment Tool for Studies of Diverse Design, organized by study characteristics, and analyzed using constant comparison. RESULTS: From the 1951 potentially relevant titles, 37 studies were selected. Twenty-five effects targeted youth and 24 focused on parents, with a maximum of 15 youth and 11 parent effect domains (median = 5 domains per study). Although most studies measured a combination of effect domains and were inclusive of some recommended in the PedIMMPACT statement, no effect was measured consistently across studies. Youth physical functioning and parent emotional functioning were measured most often. Eighty-five instruments were used to assess youth outcomes and 59 for parents, with self-report questionnaires dominating. DISCUSSION: A lack of standardization exists associated with the domains and methods used to evaluate the effects of pediatric-specialized outpatient pain rehabilitation programs, hindering comparisons. Future program evaluations should be founded on their theory, aim, and anticipated outcomes.
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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 | 0.043 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.023 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".