Improvement of Rural Children’s Asthma Self‐Management by Lay Health Educators
Bibliographic record
Abstract
BACKGROUND: The purpose of the present analysis is to examine changes in rural children's asthma self-management after they received lay health educator (LHE)-delivered classes. METHODS: Elementary schools were randomly assigned to the treatment or attention-control condition and their participating students received either asthma education or general health promotion education, respectively. The triethnic sample was composed of 183 children (46% Hispanic, 29.5% non-Hispanic white, 22% African American, and 2.6% other categories) who had a mean age of 8.78 years (SD = 1.24). The time frame from baseline to postintervention was 12 weeks. RESULTS: Repeated measures analysis of variance found main effects in changes in scores for children's asthma knowledge, asthma self-management, self-efficacy for managing asthma symptoms, and metered dose inhaler (MDI) technique and significant group interaction effects for the treatment intervention on the measures of children's asthma knowledge, asthma self-management, and MDI technique. CONCLUSIONS: The delivery of an asthma health education intervention by trained LHEs to school-aged children was an effective means for improving children's knowledge and skills in asthma self-management.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".