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Record W2126116403 · doi:10.1177/1090198111420287

Sustainability of the Dissemination of an Occupational Sun Protection Program in a Randomized Trial

2011· article· en· W2126116403 on OpenAlexaboutno aff
David B. Buller, Barbara J. Walkosz, Michael D. Scott, Mark Dignan, Gary Cutter, Xiao Zhang, Ilima Kane

Bibliographic record

VenueHealth Education & Behavior · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
FundersNational Cancer InstituteSanofi
KeywordsRandomized controlled trialSustainabilityDisseminationMedicineInformation DisseminationEnvironmental healthEngineeringSurgeryTelecommunications

Abstract

fetched live from OpenAlex

Sustainability of an occupational sun safety program, Go Sun Smart (GSS), was explored in a randomized trial, testing dissemination strategies at 68 U.S. and Canadian ski areas in 2004-2007. All ski areas received GSS from the National Ski Areas Association through a Basic Dissemination Strategy (BDS) using conference presentations and free materials. Half of the ski areas were randomly assigned to a theory-based Enhanced Dissemination Strategy (EDS) with personal contact supporting GSS use. GSS use was assessed at immediate and long-term follow-up posttests by on-site observation. Use of GSS declined from immediate (M = 6.24) to long-term follow-up (M = 4.72), F(1, 62) = 6.95, p = .01, but EDS ski areas (M = 6.53) continued to use GSS more than BDS ski areas (M = 4.49), F(1, 62) = 5.75, p = .02, regardless of timing of posttest, strategy × observation F(1, 60) = 0.05, p = .83. Despite declines over time, a group of ski areas had sustained high program use and active dissemination methods had sustained positive effects on implementation.

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 imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.036
GPT teacher head0.371
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations20
Published2011
Admission routes1
Has abstractyes

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