Making needle procedures comfortable for autistic children: Caregiver perspectives
Bibliographic record
Abstract
Background Autistic children are at greater risk for having difficulty undergoing needle procedures and poor management of their needle pain and fear. While there are general clinical practice guidelines (CPGs) available for managing pediatric needle pain and fear, it is unclear whether these strategies are appropriate for autistic children and their caregivers. Method The objective of this study was to explore caregiver perspectives on what is needed for needle procedures to be comfortable and CPGs to be appropriate for them and their autistic child. Twenty Canadian caregivers of autistic children were interviewed, including open-ended questions and ratings of how helpful CPG strategies would be for autistic children. Results Using reflexive thematic analysis , four themes were identified: 1) autistic children’s sense of autonomy is important; 2) external factors impact autistic children’s comfort (e.g., environment, familiarity, healthcare providers); 3) caregivers play a key role by preparing themselves and others before needle procedures and 4) it is essential to tailor CPG strategies to children’s needs. Conclusions Findings indicate that a child and family-centered approach is imperative to making needle procedures comfortable for autistic children. Practical recommendations for healthcare providers and caregivers are provided.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".