Asthma-Related Educational Needs of Families With Children With Asthma in an Urban Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to identify the educational needs of inner-city children with persistent asthma and their caregivers who utilize the emergency department (ED) for asthma care as well as determine their guideline adherence, factors associated with ED use, and comfort with computers. METHODS: Cross-sectional survey of children aged 2 to 18 years with previous diagnosis of asthma presenting with asthma-related complaints or acute asthma exacerbations to an urban pediatric ED. Data on demographics, families' response to acute asthma, approach to asthma prevention, access to care, educational topics of interest, and sources of health information were collected. RESULTS: Of approximately 1500 asthma-related visits, 218 caregivers were approached, and 200 completed the survey. In the past 12 months, 31% had experienced at least 1 asthma-related hospitalization, and 55.5% had had at least 3 ED visits. Although 184 (92.9%) of 198 caregivers were able to identify a primary physician, 37% reported they were more likely to take their child to the ED in response to acute asthma during the day as opposed to their physician (17%). Approximately half of patients were not on any preventive medication, with 57% not having had received an Asthma Action Plan. Caregivers expressed the most interest in learning about long-term controller medications (44.2%), use of metered dose inhalers or nebulizers (44.2%), and trigger avoidance (35.2%). Most caregivers (approximately 68%) reported ease of use with computers and the Internet. CONCLUSION: There was discordance between caregivers' reports of primary care provider teaching on asthma management and the use of the controller medications and possession of the Asthma Action Plans for persistent asthma. Education could focus on caregiver concerns of the safety and benefits of the controller medications.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| 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".