Children's fear during procedural pain: Preliminary investigation of the Children's Fear Scale.
Bibliographic record
Abstract
UNLABELLED: Many children consider getting a needle to be one of their most feared and painful experiences. Differentiating between a child's experience of fear and pain is critical to appropriate intervention. There is no gold standard one-item self-report measure of fear for use with children. OBJECTIVE: To conduct an initial investigation of the psychometric properties of the Children's Fear Scale (CFS; based on the adult Faces Anxiety Scale) with young school-age children. METHOD: Children and their parents were filmed during venipuncture and completed pain and fear ratings immediately after the procedure (n = 100) and 2 weeks later (n = 48). Behavioral coding of the procedures was conducted. RESULTS: Support was found for interrater reliability (Time 1: rs = .51, p < .001) and test-retest reliability (rs = .76, p < .001) of the CFS for measuring children's fear during venipuncture. Assessment of construct validity revealed high concurrent convergent validity with another self-report measure of fear (Time 1: rs = .73, p < .001) and moderate discriminant validity (e.g., Time 1: rs = -.30, p < .005 with child coping behavior; rs = .41, p < .001 with child distress behavior). CONCLUSIONS: The CFS holds promise for measuring pain-related fear in children. In addition to further investigation into the psychometric properties of the CFS during acute pain with a wider age range, future research could validate this measure in other contexts. The utility of a one-item measure of fear extends beyond the field of pediatric pain to other contexts including intervention for anxiety disorders and children in hospital.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".