Correlates of women’s intentions to be screened for human papillomavirus for cervical cancer screening with an extended interval
Bibliographic record
Abstract
BACKGROUND: High-risk HPV DNA testing has been proposed as a primary tool for cervical cancer screening (HPV-CCS) as an alternative to the Papanicolaou cytology- method. This study describes factors associated with women's intentions to attend cervical cancer screening if high-risk HPV DNA testing (HPV-CCS) was implemented as a primary screening tool, and if screening were conducted every 4 years starting after age 25. METHODS: This online survey was designed using the Theory of Planned Behaviour to assess factors that impact women's intentions to attend HPV-CCS among women aged 25-69 upon exit of the HPV FOCAL trial. Univariate and regression analyses were performed to compare the demographic, sexual history, and smoking characteristics between women willing and unwilling to screen, and scales for intention to attend HPV-CCS. A qualitative analysis was performed by compiling and coding the comments section of the survey. RESULTS: Of the 981 women who completed the survey in full, only 51.4 % responded that they intended to attend HPV-CCS with a delayed start age and extended screening interval. Women who intended to screen were more likely to have higher education (AOR 0.59, 95 % CI [0.37, 0.93]), while both positive attitudes (AOR 1.26, 95 % CI [1.23, 1.30]) and perceived behavior control (AOR 1.06, 95 % CI [1.02, 1.10]) were significant predictors of intention to screen. Among women who provided comments in the survey, a large number of women expressed fears about not being checked more than every 4 years, but 12 % stated that these fears may be alleviated by having more information. CONCLUSIONS: Acceptability of increased screening intervals and starting age could be improved through enhanced education of benefits. Program planners should consider measures to assess and improve women's knowledge, attitudes and beliefs prior to the implementation of new screening programs to avoid unintended consequences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".