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Record W2028740088 · doi:10.1037/a0015986

The role of sexuality in cervical cancer screening among Chinese women.

2009· article· en· W2028740088 on OpenAlexaffabout
Jane S. T. Woo, Lori A. Brotto, Boris B. Gorzalka

Bibliographic record

VenueHealth Psychology · 2009
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAcculturationHuman sexualityPap testMedicineEmbarrassmentCervical cancerPsychologyClinical psychologyDemographyEthnic groupGynecologySocial psychologyCancerCervical cancer screeningGender studiesInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Chinese women have significantly lower rates of Papanicolaou (Pap) testing than Euro-Canadian women despite efforts to promote testing. Evidence suggests that Chinese women's reluctance to undergo Pap testing may be related to culture-linked discomfort with sexuality. The purpose of this study was to explore the role of sexuality in the interaction between acculturation and Pap testing. DESIGN: Euro-Canadian (n = 213) and Chinese (n = 260) female university students completed a battery of questionnaires. MAIN OUTCOME MEASURES: Questionnaires assessing sexual knowledge, sexual function, acculturation, and Pap testing frequency. RESULTS: Euro-Canadian women had significantly more accurate sexual knowledge, higher levels of sexual functioning, a broader repertoire of sexual activities, and higher Pap testing rates. Chinese women were more likely to cite embarrassment as a barrier to Pap testing. Heritage acculturation, but not mainstream acculturation, predicted Chinese women's Pap testing behavior. Mainstream acculturation was associated with more accurate sexual knowledge and greater sexual desire and satisfaction. CONCLUSION: The findings provide support for the hypothesis that low Pap testing rates in Chinese women may be associated with heritage acculturation, although the hypothesis that sexual function would predict Pap testing behavior was not supported.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.132
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.468
Teacher spread0.404 · 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 teacher head, 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

Citations32
Published2009
Admission routes2
Has abstractyes

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