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Record W2746586139 · doi:10.1177/0956462417727690

Women’s willingness to experiment with condoms and lubricants: A study of women residing in a high HIV seroprevalence area

2017· article· en· W2746586139 on OpenAlexaff
Stephanie A. Sanders, Richard A. Crosby, Robin R. Milhausen, Cynthia A. Graham, Amir Tirmizi, William L. Yarber, Laura Beauchamps, Leandro Mena

Bibliographic record

VenueInternational Journal of STD & AIDS · 2017
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCondomMedicinePleasureDemographyFamily medicineHuman immunodeficiency virus (HIV)GynecologyPsychologySyphilis

Abstract

fetched live from OpenAlex

The objective of this study was to investigate women's willingness to experiment with new condoms and lubricants, in order to inform condom promotion in a city with high rates of poverty and HIV. One hundred and seventy-three women (85.9% Black) sexually transmitted infection clinic attendees in Jackson, Mississippi, United States completed a questionnaire assessing willingness to experiment with condoms and lubricants and sexual pleasure and lubrication in relation to last condom use. Most women were willing to: (1) experiment with new types of condoms and lubricants to increase their sexual pleasure, (2) touch/handle these products in the absence of a partner, and (3) suggest experimenting with new condoms and lubricants to a sex partner. Previous positive sexual experiences with lubricant during condom use predicted willingness. The role women may play in male condom use should not be underestimated. Clinicians may benefit women by encouraging them to try new types of condoms and lubricants to find products consistent with sexual pleasure.

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)0.003
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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
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 head0.089
GPT teacher head0.433
Teacher spread0.344 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of STD & AIDSSame topicAdolescent Sexual and Reproductive HealthFrench-language works237,207