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Record W4406675033 · doi:10.3390/cancers17030344

An Assessment of Young Adults’ Awareness and Knowledge Related to the Human Papillomavirus (HPV), Oropharyngeal Cancer, and the HPV Vaccine

2025· article· en· W4406675033 on OpenAlexaff
Eric N Davis, Philip C. Doyle

Bibliographic record

VenueCancers · 2025
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsGenital wartsMedicineCervical cancerHPV infectionHuman papillomavirusAnal cancerHPV vaccinesFamily medicineIncidence (geometry)VaccinationYoung adultCervixCancerGynecologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND/OBJECTIVES: The human papillomavirus (HPV) is a prevalent sexually transmitted infection that is a known cause of morbidities such as genital warts and cancers of the cervix, anus, and oropharynx. Non-cervical HPV-related cancers have been a developing problem in North America, increasing in incidence by up to 225% in some instances over a span of two decades. METHODS: = 1005) aged 18-30 completed a 42-item questionnaire that included demographic information, awareness questions, and a series of "true/false/I don't know" knowledge questions. RESULTS: The data gathered revealed that participants had relatively high levels of awareness. However, many respondents had significant gaps in their knowledge of HPV, OPC, and the HPV vaccine. Collectively, the data indicate that awareness and knowledge of HPV and the value of vaccination may place younger individuals at risk for HPV-related infections. CONCLUSIONS: Although a relatively high level of awareness concerning HPV was observed, the gaps in knowledge suggest that further efforts are necessary to educate young adults. While all risk factors cannot be reduced, the present data may guide future efforts directed toward better education on HPV and related health concerns and associated risks.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.018
GPT teacher head0.377
Teacher spread0.359 · 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 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

Citations13
Published2025
Admission routes1
Has abstractyes

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