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Record W1998100694 · doi:10.3138/cjhs.2013.2201

University students' attitudes toward purchasing condoms

2013· article· en· W1998100694 on OpenAlexaffvenue
Scott T. Ronis, Daniel M. LeBouthillier

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2013
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of ReginaUniversity of New Brunswick
Fundersnot available
KeywordsPurchasingPsychologyFeelingSocial psychologyPersonalityNeuroticismHuman sexualityDevelopmental psychologyMarketingSociologyBusiness

Abstract

fetched live from OpenAlex

This study assessed participants' attitudes regarding purchasing condoms as well as factors associated with emotional comfort in purchasing them. Participants were 244 university students who were asked about their educational, cultural, and family backgrounds; previous experiences and attitudes in purchasing (or otherwise obtaining) condoms; experience and knowledge about topics directly relevant to sexuality; personality traits; and parent-child sexual communication. Zero-order correlation and multiple regression analyses were used to identify predictors of emotional comfort in purchasing condoms. Regression results demonstrated that lower religiosity, more favourable attitudes toward birth control, lower neuroticism, and greater parent-child sexual communication predicted comfort in purchasing condoms. Qualitative analyses revealed that individuals who purchased condoms typically reported either feeling embarrassed and concerned about being exposed or that they had acted appropriately and responsibly. Findings from this study provide key information about emerging adults' comfort in purchasing condoms and have important implications for enhancing sexual education programs.

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 score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.180
GPT teacher head0.446
Teacher spread0.266 · 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
Published2013
Admission routes2
Has abstractyes

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