Health Professionals’ Preparation for Supporting Children and Parents Affected by Asthma and Allergies
Bibliographic record
Abstract
Background: The objective of this study was to assess health professionals’ learning needs and preferences pertinent to the support and education of children with asthma and allergies. Method: A 26-item online survey (n = 47) and qualitative interviews (n = 10) elicited information from health professionals about the perceived support and education needs of children with asthma and allergies, health professionals experience and educational needs regarding support of children. Results: Health professionals believed that children needed professional education, support, and strategies to reduce effects of asthma and allergies. Time (66%) and cost (80.9%) were significant barriers to non-webbased education. Although these health professionals were interested in learning from and connecting with their own peers; promoting peer support for children with asthma and allergies received a lower rating on their list of education needs. Conclusions: This needs assessment study confirms that health professionals have limited time, funds, and options for asthma-and allergy-related professional development activities. It emphasizes the need for web-based education, group discussions, inclusion of information, and practical skills for teaching children. Understanding the value of incorporating peer support and social support into health programs may be limited.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".