Pain in Children With Developmental Disabilities
Bibliographic record
Abstract
INTRODUCTION: Pain in children with intellectual disabilities (ID) is common and complex, yet there is no standard pain training for their secondary caregivers (ie, respite staff). OBJECTIVES: Determine perceived pain training needs/preferences of children's respite staff (phase 1) and, use this information combined with extant research and guidelines to develop and pilot a training (phase 2). METHODS: In phase 1, 22 participants responded to questionnaires and engaged in individual interviews/focus groups about their experiences with pain in children with ID, and perceived training needs/preferences. In phase 2, 50 participants completed knowledge measures and rated the feasibility of, and their own confidence and skill in, pain assessment and management for children with ID immediately before and after completing a pain training. They also completed a training evaluation. RESULTS: Participants viewed pain training as beneficial. Their ideal training involved a half-day, multifaceted in-person program with a relatively small group of trainees incorporating a variety of learning activities, and an emphasis on active learning. Phase 2 results suggested that completion of the 3 to 3.5-hour pain training significantly increased respite workers' pain-related knowledge (effect sizes: r=0.81 to 0.88), as well as their ratings of the feasibility of, and their own confidence and skill in, pain assessment and management in children with ID (effect sizes: r=0.41 to 0.70). The training was rated favorably. DISCUSSION: Training can positively impact respite workers' knowledge and perceptions about pain assessment and management. As such, they may be better equipped to care for children with ID in this area.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".