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Record W4366602365 · doi:10.1177/10482911231165975

Barriers and Facilitators in the Creation of a Surveillance System for Solar Radiation-Induced Skin Cancers

2023· article· en· W4366602365 on OpenAlexaff
Nicole Slot, Thomas Tenkate, Lindsay Forsman-Phillips, Victoria H Arrandale, Sunil Kalia, D. Linn Holness, Cheryl Peters

Bibliographic record

VenueNEW SOLUTIONS A Journal of Environmental and Occupational Health Policy · 2023
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsUniversity of CalgaryBC Centre for Disease ControlSt. Michael's HospitalProvincial Health Services AuthorityVancouver Coastal Health Research InstituteVancouver Coastal HealthToronto Metropolitan UniversityUniversity of TorontoWorld Wildlife Fund CanadaPublic Health OntarioUniversity of British ColumbiaAlberta Health Services
Fundersnot available
KeywordsMedicineStakeholderHealth surveillanceEnvironmental healthMedical surveillanceStakeholder engagementDisease surveillancePopulationMedical emergencyDiseasePublic relationsPathologyPolitical science

Abstract

fetched live from OpenAlex

Outdoor workers are exposed to many hazards, including solar ultraviolet radiation (UVR). Identifying, reporting, analyzing and tracking the exposures or health outcomes of outdoor workers have not generally been formally considered. This article aims to summarize the best practices/strategies for creating an occupational sun exposure or skin cancer surveillance system for outdoor workers and to understand the key barriers and facilitators to the development of such a system. For the design of a successful occupational safety and health (OSH) surveillance system five occupational surveillance strategies are summarized: exposure registry, disease registry, disease screening/medical surveillance, sentinel event surveillance, and disease surveillance via data linkage. Ten key considerations are identified, including identifying a clear goal, a defined target population and stakeholder involvement, five critical barriers are highlighted including underreporting and funding, and five vital facilitators are recognized including communication/collaboration and a simple reporting process.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.344
Teacher spread0.315 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNEW SOLUTIONS A Journal of Environmental and Occupational Health PolicySame topicSkin Protection and AgingFrench-language works237,207