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Record W2020453410 · doi:10.3134/ehtj.09.008

The public's acceptance of novel vaccines during a pandemic: A focus group study and its application to influenza H1N1

2008· article· en· W2020453410 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEmerging Health Threats Journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsSimon Fraser UniversityCentre for Advancing Health OutcomesSt. Paul's Hospital
FundersGenome British ColumbiaGenome Canada
KeywordsPandemicPublic healthRisk perceptionPandemic influenzaFocus groupEnvironmental healthVaccinationMedicineH1N1 influenzaOutbreakDiseasePerceptionBusinessInfectious disease (medical specialty)Coronavirus disease 2019 (COVID-19)ImmunologyPsychologyMarketingVirologyNursing

Abstract

fetched live from OpenAlex

As influenza H1N1 spreads around the world, health officials are considering the development and use of a new vaccine to protect the public and help control the outbreak. Acceptance of novel vaccines during health crises, however, is influenced by perceptions of a range of risks, including the risk of infection, risk of becoming severely ill or dying if infected, as well as the risk of serious side and long-term effects of the vaccine. A study on 11 focus groups was conducted with the public in Vancouver, Canada in 2006 and 2007 to explore how people assess these risks and how these assessments relate to their willingness to use novel vaccines in a pandemic. Concerns about using new vaccines during a pandemic differ from concerns about using established products in a non-crisis situation. Participants were hesitant to use novel vaccines because of a low perception of the early risk of infection in a pandemic, coupled with the many uncertainties that surround new vaccines and the emerging infectious disease, and owing to the concern that unsafe pharmaceuticals may be rushed to market during a health crisis. Understanding the public´s assessment of the risks related to, and willingness to use, novel vaccines during a pandemic can help officials promote disease-control measures in ways that improve the likelihood of acceptance by the public and may increase uptake of an H1N1 vaccine.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
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 head0.096
GPT teacher head0.407
Teacher spread0.312 · 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