The Economic Burden of Cervical Cancer on Women and Families in Uganda
Bibliographic record
Abstract
PURPOSE There is little research on how a cervical cancer diagnosis financially impacts women and their families in low-and middle-income countries, including the burden of out-of-pocket costs. The objective of this analysis is to describe the economic burden of cervical cancer treatment, including how this differs by socio-economic status (SES) in Uganda. METHODS We conducted a cross-sectional study from September 19, 2022 to January 17, 2023. Women were recruited from the Uganda Cancer Institute and Jinja Regional Referral Hospital and were eligible for this study if they were ≥ 18 years, being treated for cervical cancer, and provided consent. Participants completed a 45-minute survey which included questions about their out-of-pocket costs, unpaid labor, and changes in their family’s economic situation. A wealth index was constructed from the participant’s ownership of household items to determine their SES. Descriptive statistics were reported. RESULTS Of the 338 participants who completed the survey, 183 were from the lower SES. Women from the lower SES were significantly more likely to be older, have primary school education, and have a more advanced stage of cervical cancer. Both groups of women reported paying out-of-pocket for cervical cancer care (higher SES 95.5%, lower SES 92.3%). Only 15/338 participants stopped treatment because they could not afford it. Women of a lower SES were significantly more likely to report borrowing money (p-value=0.004) and selling possessions to pay for cancer care (p-value=0.006). With regards to unpaid labor, women from both groups reported decreasing the amount of time that they spent caring for their children since their cervical cancer diagnosis. CONCLUSION Regardless of their SES, women in Uganda incur out-of-pocket costs related to their cervical cancer treatment. However, there are inequities as women from the lower SES groups were more likely to borrow funds to afford treatment. Alternative payment models and further financial support could help alleviate the financial burden of cervical cancer care on women and families in Uganda. The results of this analysis can be used to demonstrate the indirect economic impact that a cervical cancer diagnosis has on not only women but their families as well. This in turn can be as evidence to expand global cervical cancer screening programs and eliminate cervical cancer worldwide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".