Effectiveness of family-centred sexual health education and HPV self-sampling in promoting cervical cancer screening among hard-to-reach indian women in rural and tribal areas: a community-based pilot study
Bibliographic record
Abstract
BACKGROUND: While cervical cancer deaths have declined steeply in high-income countries due to the widespread use of the Papanicolaou test (Pap test), the same trend has not emerged in low or middle-income countries (LMICs). Access to screening in LMICs like India is limited due to barriers such as limited healthcare infrastructures, lack of sexual health education, and stigma demarcating sexually transmitted infections (STIs). HPV self-sampling (HPV-SS), a woman-centered and at-home method for screening, can be utilized as a unique screening tool to overcome some of these barriers. Our study examined the effectiveness of HPV-SS, supported by family-centred arts-based sexual health literacy on the uptake of cervical cancer screening among hard-to-reach women in rural and remote areas in India. METHODS: Our community-based mixed methods pilot study recruited 240 participants (120 women and 120 male partners or family members) through female Accredited Social Health Activists (ASHA) across 3 Indian villages of Shirgoan, Khodala, and Jamsar in Palghar district. Inclusion criteria included women ages 30-69 who were under or never screened (UNS) and their male partners/family members aged 18 or over. Knowledge and attitudes about cervical cancer and screening and their perceived stigma surrounding STI were assessed using validated scales prior to and after attending a 2-hour arts-based sexual health education (SHE). In addition, participants' uptake of cervical cancer screening was assessed after attendance in SHE. FINDINGS: Results revealed significant improvement in knowledge and attitudes about cervical cancer and screening, and a reduction in the STI stigma after participation in SHE sessions (overall mean difference in Knowledge: z = 6.1 ± 2.4, P < 0.001; attitudes about Pap-test and VIA: z = 2.2 ± 8.4, P < 0.001 and z = 2.9 ± 8.2, P < 0.001; STI stigma: z = 2.8 ± 12.4, P < 0.001). 118 out of 120 female participants chose to be screened and 115 opted for HPV-SS. CONCLUSIONS: The implementation of HPV-SS coupled with family-centered arts-based and culturally appropriate SHE is highly promising in promoting cervical cancer screening among hard-to-reach women. Evidence from our study can be used to advance public health policies and inform the scale-up of similar initiatives in other villages and states across rural India and other LMICs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".