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Record W2514857846 · doi:10.9778/cmajo.20160050

Trends in influenza vaccine coverage and vaccine hesitancy in Canada, 2006/07 to 2013/14: results from cross-sectional survey data

2016· article· en· W2514857846 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCMAJ Open · 2016
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsVaccinationMedicineInfluenza vaccineEnvironmental healthCross-sectional studyDemographyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Past studies have reported influenza vaccination coverage below national targets, but up-to-date estimates are needed to understand trends and to identify areas for intervention. The objective of this study was to describe recent trends in influenza vaccination in Canada, timing of uptake and reasons for not receiving the vaccine. METHODS: We pooled data from the 2007 to 2014 cycles of the Canadian Community Health Survey. Using bootstrapped survey weights, we examined influenza vaccine coverage by various groups, including by age and by presence of chronic medical conditions. RESULTS: The overall sample included 481 526 respondents. Across all survey cycles combined, 29% of respondents reported receiving seasonal influenza vaccination in the past 12 months. Coverage levels were fairly consistent during the study period, but varied by province or territory. Vaccination coverage decreased over time among those aged 65 years and older. Among those who received a vaccination, it was most common to do so in October or November. Among those not vaccinated, the most frequently cited reason was believing it was unnecessary. INTERPRETATION: Influenza vaccination coverage continues to fall below national targets, with substantial declines seen among those aged 65 years and older, a group for which vaccination is particularly important. More intensive efforts are needed to improve coverage in Canada, particularly for high-risk groups.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
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 head0.159
GPT teacher head0.419
Teacher spread0.259 · 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