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Abstract 90: Understanding the Self-Collection Preferences of Women Living in Rwanda

2023· article· en· W4378983023 on OpenAlexaff
Varun Nair, Hallie Dau, Marianne Vidler, Maryam AboMoslim, Barbra Mutamba, Zoey Nesbitt, Nadia Mithani, Laurie Smith, Stephen Rulisa, Gina Ogilvie

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2023
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsBC Centre for Disease ControlWomen's Health Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsMedicineData collectionRural areaCervical cancerFeelingDescriptive statisticsDemographicsDemographySocioeconomicsGerontologyCancerPsychology

Abstract

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Abstract Purpose: Cervical cancer is a leading cause of cancer death among women in low- and middle-income countries. Women in Rwanda have high rates of cervical cancer due to limited access to effective screening methods. Research in low-resource settings similar to Rwanda has shown that self-collection for cervical cancer screening is an effective method. This study aimed to compare the preferences of Rwandan women in urban and rural settings toward self-collection and to report on factors related to self-collection amenability. Methods: A cross-sectional survey was conducted from June 1-9, 2022. Women were recruited from an urban and rural clinic in Rwanda. Women were eligible for the study if they were ≥ 18 years and spoke Kinyarwanda or English. The survey consisted of 51 questions investigating demographics and attitudes towards self-collection for cervical cancer screening. All results were stratified by clinic site. We performed descriptive statistics stratified by urban and rural sites. Results: In total, 374 Rwandan women completed the survey (urban n=169 and rural n=205). The mean age was 33.09 years for urban and 32.89 years for rural respondents. The majority of respondents at both sites had a primary school or less education and were in a relationship. Both urban and rural respondents were open to self-collection; however, rates were higher in the rural site (79.9% urban and 95.6% rural; p-value<0.001). Similarly, women in rural areas were more likely to report feeling unembarrassed about self-collection (65.3% of urban, 76.8% of rural; p-value<0.001). Both urban (87.6%) and rural (90.2%) respondents were similarly unafraid of social stigma around cervical cancer. Notably, almost all urban and rural respondents (97.6% urban and 98.5% rural) stated they would go for a cervical cancer pelvic examination to a nearby health center if their self-collected results indicated any concern (p-value=0.731). Conclusion: Rwandan women in both urban and rural areas largely support the implementation and integration of self-collection for cervical cancer screening. Further research is needed to better understand how to implement self-collection screening services. Expanding self-collection for cervical cancer screening in Rwanda will contribute the global elimination of cervical cancer. Citation Format: Varun Nair, Hallie Dau, Marianne Vidler, Maryam AboMoslim, Barbra Mutamba, Zoey Nesbitt, Nadia Mithani, Laurie Smith, Stephen Rulisa, Gina Ogilvie. Understanding the Self-Collection Preferences of Women Living in Rwanda [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 90.

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)0.004
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.154
GPT teacher head0.418
Teacher spread0.264 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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