Acceptability and validity of <scp>HPV</scp> self‐sampling for cervical cancer screening among women living in different ecological settings in <scp>India</scp>
Bibliographic record
Abstract
India records one fifth of global cervical cancer burden. Unlike human papillomavirus (HPV) self-sampling, other screening methods may cause discomfort and embarrassment. This study aimed to investigate attitudes, acceptability, barriers, predictors, effective modality of instructions, and validity of HPV self-sampling among Indian women residing in varied settings and different literacy levels. This is community-based interventional study among Indian women 30-55 years, residing in urban slums (500), urban non-slums (500), and rural (600) settings with varied washroom facilities and privacy, to collect self-samples. Each group was subdivided into two arms; in one women received education with pamphlets and other with health education program (HEP). Study involved enlisting eligibles, obtaining informed consents and conducting personal interviews to collect baseline data. Self-samplers were distributed with instructions (pictorial pamphlets in one group and HEP in other) regarding usage, storage and return. Willingness to use self-samplers, refusals, experiences, and so forth were captured. Post-intervention knowledge, attitudes, practices was recorded. HPV reports were distributed. Women with positive result on either test were offered further management. Acceptance rate of self-sampling was 99.2%, 97%, and 98.8% and HPV positivity was 7%, 7.8%, and 8.5%, respectively among urban non-slum, urban slum and rural women. Agreement rate between health personnel collected and self-collected samples was 96.5% in pamphlet and 93.2% in HEP arm. Major barriers of self-sampling were lack of confidence about performing self-test correctly, fear that test would be painful and anxiety about test results. HPV self-sampling has good acceptability among Indian women and good agreement with health personnel collected samples.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".