Impact of prenatal education on maternal utilization of analgesic interventions at future infant vaccinations: A cluster randomized trial
Bibliographic record
Abstract
Analgesic interventions are not routinely used during vaccine injections in infants. Parents report a desire to mitigate injection pain, but lack the knowledge about how to do so. The objective of this cluster-randomized trial was to evaluate the effect of a parent-directed prenatal education teaching module about vaccination pain management on analgesic utilization at future infant vaccinations. Expectant mothers enrolled in prenatal classes at Mount Sinai Hospital in Toronto were randomized to a 20-30minute interactive presentation about vaccination pain management (experimental group) or general vaccination information (control group). Both presentations included a PowerPoint (Microsoft Corporation, Redmond, WA, USA) and video presentation, take-home pamphlet, and "Question and Answer" period. The primary outcome was self-reported utilization of breastfeeding, sugar water, or topical anaesthetics at routine 2-month infant vaccinations. Between October 2012 and July 2013, 197 expectant mothers from 28 prenatal classes participated; follow-up was obtained in 174 (88%). Maternal characteristics did not differ (P>0.05) between groups. Utilization of one or more prespecified pain interventions occurred in 34% of participants in the experimental group, compared to 17% in the control group (P=0.01). Inclusion of a pain management module in prenatal classes led to increased utilization of evidence-based pain management interventions by parents at the 2-month infant vaccination appointment. Educating parents offers a novel and effective way of improving the quality of pain care delivered to infants during vaccination. Additional research is needed to determine if utilization can be bolstered further using techniques such as postnatal hospital reinforcement, reminder cards, and clinician education.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".