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Record W2046954536 · doi:10.1289/ehp.8989

Childhood Asthma and Environmental Interventions

2007· review· en· W2046954536 on OpenAlexaff
Felicia Wu, Tim K. Takaro

Bibliographic record

VenueEnvironmental Health Perspectives · 2007
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAsthmaEnvironmental healthPsychological interventionMedicineImmunologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Contaminants encountered in many households, such as environmental tobacco smoke, house dust mite, cockroach, cat and dog dander, and mold, are risk factors in asthma. Young children are a particularly vulnerable subpopulation for environmentally mediated asthma, and the economic burden associated with this disease is substantial. Certain mechanical interventions are effective both in reducing allergen loads in the home and in improving asthmatic children's respiratory health. RESULTS: Combinations of interventions including the use of dust mite-impermeable bedding covers, improved cleaning practices, high-efficiency particulate air vacuum cleaners, mechanical ventilation, and parental education are associated with both asthma trigger reduction and improved health outcomes for asthmatic children. Compared with valuated health benefits, these combinations of interventions have proven cost effective in studies that have employed them. Education alone has not proven effective in changing parental behaviors such as smoking in the home. CONCLUSIONS: Future research should focus on improving the effectiveness of education on home asthma triggers, and understanding long-term children's health effects of the interventions that have proven effective in reducing asthma triggers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.036
GPT teacher head0.374
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations128
Published2007
Admission routes1
Has abstractyes

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