Impact of parent-directed education on parental use of pain treatments during routine infant vaccinations
Bibliographic record
Abstract
Educating parents about ways to minimize pain during routine infant vaccine injections at the point of care may positively impact on pain management practices. The objective of this cluster randomized trial was to determine the impact of educating parents about pain in outpatient pediatric clinics on their use of pain treatments during routine infant vaccinations. Four hospital-based pediatric clinics were randomized to intervention or control groups. Parents of 2- to 4-month-old infants attending the intervention clinics reviewed a pamphlet and a video about vaccination pain management on the day of vaccination, whereas those in the control clinics did not. Parent use of specific pain treatments (breastfeeding, sugar water, topical anesthetics, and/or holding of infants) on the education day and at subsequent routine vaccinations 2 months later was the primary outcome. Altogether, 160 parent-infant dyads (80 per group) participated between November 2012 and February 2014; follow-up data were available for 126 (79%). Demographics did not differ between groups (P > 0.05). On the education day and at follow-up vaccinations, use of pain interventions during vaccinations was higher in the intervention group (80% vs 26% and 68% vs 32%, respectively; P < 0.001 for both analyses). Educating parents about pain management in a hospital outpatient setting leads to higher use of pain interventions during routine infant vaccinations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".