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Record W4221115375 · doi:10.1101/2022.03.28.22272903

Ensuring a successful transition from Pap to HPV-based primary screening in Canada: a study protocol to investigate the psychosocial correlates of women’s screening intentions

2022· preprint· en· W4221115375 on OpenAlexafffundabout
Gabrielle Griffin-Mathieu, Ben Haward, Ovidiu Tatar, Patricia Zhu, Samara Perez, Gilla K. Shapiro, Emily McBride, Erika L. Thompson, Laurie Smith, Aïsha Lofters, Ellen M. Daley, Juliet Guichon, Jo Waller, Marc Steben, Kathleen Decker, Marie‐Hélène Mayrand, Julia Brotherton, Gina Ogilvie, Gregory D. Zimet, Teresa Norris, Zeev Rosberger

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsB.C. Women's Hospital & Health CentreUniversity of British ColumbiaSanté MontérégieUniversity of ManitobaUniversité de MontréalWomen's College HospitalBC Cancer AgencyUniversity of CalgaryPrincess Margaret Cancer CentreMcGill UniversityMcGill University Health CentreUniversity of TorontoCancerCare ManitobaUniversity Health NetworkCentre Hospitalier de l’Université de MontréalJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsPsychosocialCervical cancerMedicineFamily medicineCervical screeningTest (biology)Public healthLogistic regressionMultinomial logistic regressionGynecologyClinical psychologyCancerNursingPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction The Human Papillomavirus (HPV) test has emerged as a significant improvement over cytology for primary cervical cancer screening. In Canada, provinces and territories are moving towards implementing HPV testing in cervical cancer screening programs. While an abundance of research exists on the benefits of HPV-based screening, there is a dearth of research examining women’s understanding of HPV testing. In other countries, failure to adequately address women’s concerns about changes has disrupted implementation of HPV-based screening. This study protocol describes a multi-step approach to develop psychometrically valid measures and to investigate psychosocial correlates of women’s intentions to participate in HPV-based cervical cancer screening. Materials and Methods We conducted a web-based survey of Canadian women to assess the acceptability and feasibility of a questionnaire, including validation of scales examining: cervical cancer knowledge, HPV testing knowledge, HPV testing attitudes and beliefs, and HPV test self-sampling attitudes and beliefs. Preferences for cervical cancer screening were assessed using Best-Worst Scaling methodology. A second web-based survey will be administered to a national sample of Canadian women in June-July of 2022 using the validated scales. Differences in the knowledge, attitudes, beliefs, and preferences of women who are currently either underscreened or adequately screened for cervical cancer will be examined through bivariate analyses. Multinomial logistic regression will be used to estimate the associations between psychosocial and sociodemographic factors and intentions to screen using HPV-based screening. Study Impact and Dissemination Findings will provide direction for Canadian public health authorities to align guidelines to address women’s concerns and optimize acceptability and uptake of HPV-based primary screening. Validated scales can be used by other researchers to improve and standardize measurement of psychosocial factors impacting HPV test acceptability. Study results will be disseminated through peer-reviewed journal articles, conference presentations, and direct communication with researchers, clinicians, policymakers, media, and specialty organizations.

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)0.030
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.220
Threshold uncertainty score0.564

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.015
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.005
Science and technology studies0.0140.003
Scholarly communication0.0040.002
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0310.004

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 head0.049
GPT teacher head0.339
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations3
Published2022
Admission routes3
Has abstractyes

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