Abstract 85: The Social and Economic Impact of a Cervical Cancer Diagnosis on Women and Children in Uganda
Bibliographic record
Abstract
Abstract Purpose: Cervical cancer is the second most common cancer for women living in low- and middle-income countries (LMIC). In Uganda 40% of all female cancer cases are cervical cancer. There is a need for more research on the social and economic impacts of cervical cancer in LMICs in order to provide evidence for expanded cervical cancer screening programs. The goal of this study is the understand the economic impact of cervical cancer on women and children in Uganda. Methods: Data collection for this study began in September and will continue until December 2022. Participants were recruited by nurses at two clinics at the Uganda Cancer Institute in Kampala and Jinja. Participants were eligible if they are being treated for cervical cancer and speak either English, Lusoga, Luo, Runyankore, or Luganda. Each participant completed a 45-minute orally administered survey on REDCap. Descriptive statistics using counts and frequencies were used to describe primary outcomes which include changes in a child’s education and a family’s economic status. Ethical approval was obtained from the University of British Columbia, Uganda Cancer Institute, and Uganda National Council for Science & Technology. Results: To date 67 participants have completed the survey and 57 indicated that they had children living in their household. The mean age of participants is 49 years. The majority of participants are married, have a primary school education or less, and were diagnosed with stage II or stage III cancer. Women reported traveling up to 14 hours to receive cancer treatment and 28% (n=19) brought their child with them to the clinic because they could not find childcare. In all, 93% (n=62) of women indicated that they have paid out of pocket for some type of medical care with 15% (n=9) of women noting that they stopped at least one treatment because of the cost. Approximately 15% of women reported that they cut down on food consumed and withdrew their child from school to help pay for cancer care. Conclusion: We found that a cervical cancer diagnosis has not only on women, but their children as well, confirming that while largely preventable, cervical cancer has far-reaching impact beyond the woman diagnosed. The results of this study can be used to provide further evidence of the urgent need expand cervical cancer screening programs not only in Uganda, but similar countries as well. This in turn will help contribute to the eventual global elimination of cervical cancer. Citation Format: Hallie Dau, Shamim Nakyazze, Priscilla Naguti, Avery McNair, Beth Payne, Marianne Vidler, Joel Singer, Laurie Smith, Jackson Orem, Carolyn Nakisige, Gina Ogilvie. The Social and Economic Impact of a Cervical Cancer Diagnosis on Women and Children in Uganda [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 85.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".