Recent innovations to improve asthma outcomes in vulnerable children
Bibliographic record
Abstract
PURPOSE OF REVIEW: Despite overall improvements in asthma care through an increasing evidence base, disparities in outcomes of children of ethnic minorities and low socioeconomic status are well documented across healthcare systems. New interventions to reduce gaps in outcomes among these children are continually being evaluated. This article reviews the most relevant and influential recent studies. RECENT FINDINGS: A number of interventions aimed at vulnerable children with asthma have been successful. Most of these include a component of education and self-management. There is some evidence that culturally competent care produces improved outcomes, whereas stronger evidence exists for multifaceted programs and community health workers providing home visits for education and environmental allergen reduction. Targeting children and families through school-based programs may be an effective outreach strategy. Use of novel technologies such as educational messages on MP3 players shows promise in reaching at-risk adolescents. SUMMARY: There are promising strategies proven to significantly decrease disparities in asthma among vulnerable children. Further research must be performed to elucidate the interventions that produce the greatest impact on asthma-related outcomes while being feasible, sustainable, and cost-effective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".