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Record W2042906106 · doi:10.2190/iq.31.1.f

Implementing HPV Vaccines: Public Knowledge, Attitudes, and the Need for Education

2011· review· en· W2042906106 on OpenAlexafffund
Amrita Mishra

Bibliographic record

VenueInternational Quarterly of Community Health Education · 2011
Typereview
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsHPV vaccinesMedicineFamily medicineCervical cancerStigma (botany)Public healthMisinformationQualitative researchMEDLINESocial stigmaEnvironmental healthHPV infectionNursingHuman immunodeficiency virus (HIV)Political sciencePsychiatryCancer

Abstract

fetched live from OpenAlex

This article reviews qualitative research on public knowledge and attitudes to HPV vaccines, focusing on socio-economically challenged populations. Keyword searches were conducted on MEDLINE and ISI Web of Science for relevant peer-reviewed literature in English. A high acceptance of HPV vaccines was found despite low knowledge about HPV (types, prevalence, transmission, health risks, and cervical screening). Facilitators of HPV vaccine uptake included fear of cancer and desire to protect children's health. Barriers included low knowledge levels, perception of HPV vaccines as potential causes of sexual disinhibition, concerns about vaccine costs, social stigma, adverse effects, and parental unwillingness to permit vaccination of pre-adolescent children. Despite acceptance of HPV vaccines, implementation in low-resource settings faces social and economic difficulties. To pursue and strengthen cervical screening in these settings, public education about HPV is key.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.175
GPT teacher head0.526
Teacher spread0.351 · 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 designNot applicable
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

Citations15
Published2011
Admission routes2
Has abstractyes

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