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Record W3047141155 · doi:10.1186/s13223-020-00470-w

Improving detection of work-related asthma: a review of gaps in awareness, reporting and knowledge translation

2020· review· en· W3047141155 on OpenAlexafffundvenue
Madison MacKinnon, Teresa To, Clare D. Ramsey, Catherine Lemière, M. Diane Lougheed

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2020
Typereview
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversity of ManitobaHealth Sciences CentreCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalSickKids FoundationUniversity of TorontoHospital for Sick ChildrenKingston Health Sciences CentreQueen's University
FundersFaculty of Health Sciences, Queen's UniversityWorkers Compensation Board of Manitoba
KeywordsKnowledge translationMedicineAsthmaMEDLINEDiseaseHealth careFamily medicineKnowledge managementPathologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Work-related asthma (WRA) accounts for up to 25% of all adults with asthma. Early diagnosis is key for optimal management as delays in diagnosis are associated with worse outcomes. However, WRA is significantly underreported and the median time to diagnosis is 4 years. The objective of this review is to identify the gaps in awareness and reporting of WRA and identify gaps in current knowledge translation strategies for chronic disease in general, and asthma specifically. This will identify reasons for delays in WRA diagnosis, as well inform suggestions to improve knowledge translation strategies for dissemination and implementation of WRA prevention and management guidelines. METHODS: Non-systematic literature reviews were conducted on PubMed with a focus on work-related asthma screening and diagnosis, and knowledge translation or translational medicine research in asthma and chronic disease. In total, 3571 titles and abstracts were reviewed with no restriction on date published. Of those, 207 were relevant and fully read. Another 37 articles were included and reviewed after citation reviews of articles from the initial search and from suggestions from editors. In total, 63 articles were included in the final review. RESULTS: Patients, employers, and healthcare professionals lack awareness and under-report WRA which contribute to the delayed diagnosis of WRA, primarily through lack of education, stigma associated with WRA, and lack of awareness and screening in primary care. Knowledge translation strategies for asthma research typically involve the creation of guidelines for diagnosis of the disease, asthma care plans and tools for education and management. While there are some prevention programs in place for certain industries, gaps in knowledge translation strategies including lack of screening tools currently available for WRA, poor education of employers and physicians in identifying WRA, and education of patients is often done post-diagnosis and focuses on management rather than prevention or screening. CONCLUSION: Future knowledge translation strategies should focus on educating employees and employers well before potential exposure to agents associated with WRA and screening for WRA in primary care to enable health care providers to recognize and diagnose WRA.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.397
Teacher spread0.323 · 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

Citations23
Published2020
Admission routes3
Has abstractyes

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