Abstract 35: Examining Levels of Awareness, Barriers and Enablers Regarding the Cervical Cancer Prevention and Treatment Pathway for Patients and Health Providers in Tanzania: A Qualitative Study
Bibliographic record
Abstract
Abstract Purpose: Cervical cancer is the fourth most common cancer in women around the globe. It has been identified as the most common cancer in Tanzania, resulting in about 9772 new cases and 6695 deaths each year. Several research studies have identified lack of awareness, low screening uptake and several other barriers as significant contributors to the striking number of deaths in the nation. While prior studies on the effects of both awareness levels and barriers/enablers in rural Tanzania have been explored, there is scant literature on the perspectives across all stakeholders (e.g., patients, key informants, healthcare providers, and non-healthcare providers). Our study aims to better understand the cervical cancer screening cascade in rural Tanzania to inform relevant policies and guidelines and overall, improve health outcomes. Methods: We leveraged a framework for conducting a health systems assessment to identify healthcare providers’ perspectives on effective cervical cancer screening, prevention and control in Tanzania. We adapted interview topic guides for cervical cancer screening using the health systems assessment framework conceptualized by Risso-Gill and colleagues designed initially for evaluating hypertension control. Study participants (71) were interviewed between 2014-2018. This included key stakeholders, patients, healthcare providers and non-healthcare providers. Results: Through the interviews and focus group discussions that were conducted, three major themes emerged: 1) awareness, 2) barriers, and 3) enablers. Awareness sub-themes included education (healthcare providers), education (patients), beliefs on cervical cancer screening, traditional medicine, risk factors, and symptoms and signs. Barriers sub-themes included access to seeking care, stigma, fear of seeking care, transportation methods, lack of communication between healthcare providers, lack of resources for patients, and disadvantaged populations. Enablers sub-themes included previous use of services, use of referrals, mass screening programs, and family support (including male involvement). Conclusion: It is evident that there is a low level of awareness of cervical cancer amongst patients and healthcare providers in rural Tanzania and a multitude of barriers and enablers that alter the prevention and treatment cascade. There is a critical need to implement more initiatives and programs to increase uptake and allow for informed-decision making among women. Citation Format: Sanchit Kaushal, Melinda Chelva, Nicola West, Erica Erwin, Prisca Dominic Marandu, Safina Yuma, Donna Shelley, Karen Yeates. Examining Levels of Awareness, Barriers and Enablers Regarding the Cervical Cancer Prevention and Treatment Pathway for Patients and Health Providers in Tanzania: A Qualitative Study [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 35.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".