Parental Language and Dosing Errors After Discharge From the Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVES: Safe and effective care after discharge requires parental education in the pediatric emergency department (ED). Parent-provider communication may be more difficult with parents who have limited health literacy or English-language fluency. This study examined the relationship between language and discharge comprehension regarding medication dosing. METHODS: We completed a prospective observational study of the ED discharge process using a convenience sample of English- and Spanish-speaking parents of children 2 to 24 months presenting to a single tertiary care pediatric ED with fever and/or respiratory illness. A bilingual research assistant interviewed parents to ascertain their primary language and health literacy and observed the discharge process. The primary outcome was parental demonstration of an incorrect dose of acetaminophen for the weight of his or her child. RESULTS: A total of 259 parent-child dyads were screened. There were 210 potential discharges, and 145 (69%) of 210 completed the postdischarge interview. Forty-six parents (32%) had an acetaminophen dosing error. Spanish-speaking parents were significantly more likely to have a dosing error (odds ratio, 3.7; 95% confidence interval, 1.6-8.1), even after adjustment for language of discharge, income, and parental health literacy (adjusted odds ratio, 6.7; 95% confidence interval, 1.4-31.7). CONCLUSIONS: Current ED discharge communication results in a significant disparity between English- and Spanish-speaking parents' comprehension of a crucial aspect of medication safety. These differences were not explained purely by interpretation, suggesting that interventions to improve comprehension must address factors beyond language alone.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".