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Record W3209989824 · doi:10.1007/s10461-022-03596-7

Color, Scent and Size: Exploring Women's Preferences Around Design Characteristics of Drug-Releasing Vaginal Rings

2022· article· en· W3209989824 on OpenAlexfundno aff
Xinyu Zhao, Cecilia Milford, Jenni Smit, Bongiwe Zulu, Peter D. W. Boyd, Karl Malcolm, Mags Beksinska

Bibliographic record

VenueAIDS and Behavior · 2022
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsFlexibility (engineering)Vaginal ringHuman immunodeficiency virus (HIV)SiliconeMedicinePsychologyAdvertisingEnvironmental healthPopulationFamily medicineChemistryResearch methodologyOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

Steroid-releasing vaginal rings are available for contraception and estrogen replacement therapy, and a new antiretroviral-releasing ring was recently approved for HIV prevention. Marketed rings are white or transparent in appearance, non-scented, and supplied as one-size-fits-all devices with diameters ranging from 54 to 56 mm. In this study, drug-free silicone elastomer rings were manufactured in different sizes, colors and scents, and the opinions/preferences of 16 women (eThekwini District, South Africa; 20-34 years) assessed through focus group discussions and thematic analysis. Opinions varied on ring color and scent, with some women preferring specific colors or scent intensities, while for others these attributes were unimportant. Concerns about color and scent were linked to perceptions around vaginal health and safety related to chemical composition. There was greater agreement on preferred ring size; flexibility and width were considered important factors for insertion and comfort. Greater choice with ring products could facilitate acceptability and overall uptake.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.081
GPT teacher head0.304
Teacher spread0.223 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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