P830 Feasibility of an online HPV self-collection screening program in canada: digital health literacy in south asian women
Bibliographic record
Abstract
Background Women who do not regularly attend cervical cancer screening are at increased risk for cervical cancer. In British Columbia (BC), approximately 30% of women aged 21–69 years are under-screened. As cervical cancer screening in BC moves towards the use of primary HPV testing, there is an opportunity to address screening barriers women face through self-collected, rather than clinician collected specimens. CervixCheck is an internet-based program for HPV self-collection being piloted in communities across BC with low screening rates. To inform the implementation of CervixCheck, we investigated digital health literacy (DHL) in South Asian women. Methods A cross-sectional anonymous survey was administered July-August 2018 through collaborating primary care clinics in predominantly South Asian communities in the Fraser Health Region of BC. The study population was a convenience sample of women 30–65 years of age, presenting at a primary care clinic. Women were administered the survey on a tablet, which collected demographic, screening history, and internet use information. DHL was measured using the validated eHEALS and Digital Health Literacy Instruments. Results 51 women participated from four family practices where 30% of women were 50 years or older. 29.4% of women self-reported not having had a Pap test in the last 3 years. English (86%) and Punjabi (58%) were the most common languages participants reported reading and speaking. Majority of women reported using the internet daily (82.4%), with mobile phones being the most common device (72.6%). DHL was higher in under-screened women. Over 80% of women responded that they would be likely to very likely to participate in self-collected screening using CervixCheck. Conclusion The survey revealed CervixCheck is a promising digital health platform to increase cervical cancer screening uptake among under-screened South Asian women. Findings were used to inform CervixCheck website design and program resources in preparation for its launch. Disclosure No significant relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".