Family-Centered Sexual Health Intervention to Promote Cervical Cancer Screening Uptake Among Low-income Rural Women in India: A Community-Based Protocol study (Preprint)
Bibliographic record
Abstract
BACKGROUND Human papillomavirus (HPV) is the primary cause of cervical cancer, which is preventable through screening and early treatment. The Papanicolaou (Pap) test and visual inspection with acetic acid (VIA), traditionally performed at the clinical setting, have been used effectively to screen for cervical cancer and pre-cancerous changes, and reduce cervical cancer mortality in high-income countries for many decades. However, these screening methods are not easily accessible to women living in low- and middle- income countries (LMIC), especially women living in rural areas. OBJECTIVE Preventing Cervical Cancer in India through Self-Sampling (PCCIS) is a community-based family-centered research project that aims to reduce avoidable cervical cancer disparities in rural area in India. The project will use HPV self-sampling, supported by a sexual health literacy intervention to increase rural women’s participation in cervical cancer screening. The objectives are to determine the effectiveness of this program in: (a) increasing sexual health literacy; (b) reducing gendered stigma of HPV and cervical cancer; (c) promoting cervical cancer screening using HPV self-sampling. METHODS We will recruit 120 women aged 30-69, who are under or never screened (UNS) for cervical cancer along with 120 supportive male relatives or friends from 3 impoverished rural / tribal villages in Palghar district in the state of Maharashtra, India. Participants will attend gender-specific sexual health education (SHE) followed by a Movie Matinee. Data will be collected though an interviewer-administered questionnaire before and after SHE. The questionnaire will include items on social demographics, medical history, attitudes, sexual health stigma, cervical cancer knowledge, and screening practices. Women will self-select whether to use HPV self-sampling. Those who do not may or may not undergo Pap test/VIA. Participants’ views regarding barriers and facilitators and suggestions to improve access and uptake will also be elicited. RESULTS PCCIS was funded in January 2020 for 15 months. Due to the COVID19 pandemic, the project was extended by one year. The protocol was approved by the research ethics boards of Ryerson University (REB 2020-104) and Tata Memorial Center (OIEC/3786/2021 /00003). Study outcome measures will include changes in knowledge/attitudes about cervical cancer screening, proportion of participants who self-select into each cohort, proportion of positive test result in each cohort- and proportion of participants with confirmed cervical cancer. Women’s experiences related to barriers and facilitators associated with the screening uptake will be captured. CONCLUSIONS This multi-faceted work could lead to reduced cervical cancer mortality and morbidity, and increased community capacity in sexual health promotion and cervical cancer prevention. Insights and lessons learned from this project can be used to inform the adaptation and scale-up of HPV self-sampling among women across India and in other countries, promote collective commitment to family-centred wellness, and support women to make healthful, personalized cervical screening decisions. CLINICALTRIAL Not Applicable
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".