The impact of an educational intervention on knowledge about infant crying and abusive head trauma
Bibliographic record
Abstract
BACKGROUND: Infants follow a predictable trajectory of increased early crying. Frustration with crying is reported to be a trigger for abusive head trauma (AHT). OBJECTIVE: To evaluate the impact of postpartum delivery of the educational program, the Period of PURPLE Crying (PURPLE), in a group of first-time mothers. The primary objective was to determine whether there was a change in knowledge about infant crying and shaking after exposure to PURPLE. Factors associated with change in knowledge were also examined. METHOD: A total of 93 participants were recruited over a four-month period at a tertiary care hospital in Nova Scotia. Pre- and postintervention data were collected. RESULTS: Knowledge about infant crying increased significantly after program delivery (P=0.001). Low baseline crying knowledge was a significant predictor of increased knowledge about infant crying (P≤0.01). There was an insignificant decrease in shaking knowledge (P=0.5), which may have been the consequence of high baseline knowledge. CONCLUSION: An educational program for new parents appears to be warranted, especially with respect to improving knowledge about infant crying. This may have a positive benefit in AHT prevention. Additional studies are required to evaluate the impact of the program on other caregivers and on rates of AHT.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".