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Record W2133827207 · doi:10.7314/apjcp.2013.14.11.6445

Factors Associated with Underscreening for Cervical Cancer among Women in Canada

2013· article· en· W2133827207 on OpenAlex
Nour Schoueri‐Mychasiw, Paul McDonald

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAsian Pacific Journal of Cancer Prevention · 2013
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
Fundersnot available
KeywordsCervical cancerMedicinePap testLogistic regressionTest (biology)DemographyCross-sectional studyCancerPopulationGerontologyGynecologyFamily medicineCervical cancer screeningEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Cervical cancer is the second most common cancer among women worldwide. Failure to prevent cervical cancer is partly due to non-participation in regular screening. It is important to plan and develop screening programs directed towards underscreened women. In order to identify the factors associated with underscreening for cervical cancer among women, this study examined Pap test participation and factors associated with not having a time-appropriate (within 3 years) Pap test among a representative sample of women in Ontario, Canada using Canadian Community Health Survey (CCHS) data. MATERIALS AND METHODS: Univariate analyses, cross-tabulations, and logistic regression modeling were conducted using cross-sectional data from the 2007-2008 CCHS. Analyses were restricted to 13,549 sexually active women aged 18-69 years old living in Ontario, with no history of hysterectomy. RESULTS: Almost 17% of women reported they had not had a time-appropriate Pap test. Not having a time-appropriate Pap test was associated with being 40-69 years old, single, having low education and income, not having a regular doctor, being of Asian (Chinese, South Asian, other Asian) cultural background, less than excellent health, and being a recent immigrant. CONCLUSIONS: Results indicate that disparities still exist in terms of who is participating in cervical cancer screening. It is crucial to develop and implement cervical cancer screening programs that not only target the general population, but also those who are less likely to obtain a Pap tests.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.041
GPT teacher head0.319
Teacher spread0.279 · 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