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Record W2399311237 · doi:10.1080/07448481.2016.1192542

The role of human papillomavirus (HPV)-related stigma on HPV vaccine decision-making among college males

2016· article· en· W2399311237 on OpenAlexaffabout
Georden Jones, Samara Perez, Veronika Huta, Zeev Rosberger, Sophie Lebel

Bibliographic record

VenueJournal of American College Health · 2016
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsJewish General HospitalMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychosocialHuman papillomavirusStigma (botany)MedicineEthnic groupHPV infectionResidenceYoung adultDemographyClinical psychologyCervical cancerPsychologyGerontologyInternal medicinePsychiatryCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: The goals of the present study are (1) to identify sociodemographic and psychosocial predictors of human papillomavirus (HPV)-related stigma and (2) to examine the relationship between HPV-related stigma in predicting HPV vaccine decision-making among college males. PARTICIPANTS: Six hundred and eighty college males aged 18-26 from 3 Canadian universities were recruited from September 2013 to April 2014. METHODS: Participants completed a self-report survey assessing HPV-related stigma, psychosocial predictors of HPV-related stigma, and HPV vaccine decision-making. The results were analyzed using variance analyses and linear regressions. RESULTS: Ethnicity, province of residence, and perceived severity of HPV were found to significantly influence HPV-related stigma. In addition, HPV-related stigma was higher in those unaware of the availability of the HPV vaccine for males. CONCLUSIONS: Promotion efforts should concentrate on Asian minorities and should avoid HPV severity messaging, as these may lead to higher HPV-related stigma, which in turn may act as a barrier to vaccination.

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)0.001
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 score0.081
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.360
Teacher spread0.343 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

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