“MY CHILD CAN’T KEEP ANYTHING DOWN!”: INTERVIEWING PARENTS WHO BRING THEIR PRESCHOOLERS TO THE EMERGENCY DEPARTMENT FOR DIARRHEA AND VOMITING
Bibliographic record
Abstract
Introduction Viral gastroenteritis with dehydration is one of the most frequent reasons for visits to pediatric Emergency Departments (ED). Worldwide dehydration is among the top causes of mortality in preschool children. Parental intervention at home can make a difference in the course of a child’s illness. Objectives This project is part of a program of research to design an educational tool for parents of preschoolers with gastroenteritis. The primary objective of this phase was to validate an interview guide. From initial data, the researchers explored parental motivations for bringing their children to the ED. Methods Ten families were recruited from the pediatric ED. Included were families of children under 4 with vomiting, diarrhea and dehydration. Telephone interviews were recorded and transcribed. The interview guide was edited for face and content validity. To ensure rigor, thematic analysis was done by all investigators. Results The interview guide was validated. Probes were added, and likert scale questions were standardized. Thematic analysis focused on parents’ decision to take their child to the ED. Making this decision is complex, involving community-level, family-level, and child factors. Access to medical care, including perceived urgency, travel time and mode of transport, impacts parents’ decision. Conclusions A model outlines the most important factors our sample of parents report when deciding to take their ill child to the ED. Making the decision about an ill child is more complex than when individuals decide for themselves. The interview guide developed will facilitate collection of further information to test our model.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".