Picturing Bravery: A Rapid Review of Needle Procedures Depicted in Children’s Picture Books
Bibliographic record
Abstract
Existing research has identified evidence-based strategies for mitigating fear and pain during needle procedures; yet, families often experience limited access to health professionals who deliver these interventions. Children may benefit from learning about such strategies in a developmentally appropriate and accessible format such as a picture book. This review aimed to summarize content related to needle procedures represented in picture books for 5- to 8-year-old children. Key terms were searched on Amazon, and the website was used to screen for relevant eligibility criteria. Three levels of screening and exclusions resulted in a final sample of 48 books. Quantitative content analysis was used to apply a coding scheme developed based on relevant Clinical Practice Guidelines and systematic reviews. Cohen's Kappa indicated strong reliability, and frequencies were calculated to summarize the content. The books were published between 1981 and 2022. All 48 books included at least one evidence-based coping strategy. Distressing aspects such as scary visuals were often included (27.1%), as well as specific expressions of fear (52.1%) and pain (16.7%). Overall, this study paves the way for researchers interested in evaluating the effectiveness of picture books on children's knowledge and self-efficacy, as well as creating interventions for coping.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".