The role of daughters in relation to their mother’s cervical cancer diagnosis and treatment in Guatemala: a descriptive study
Bibliographic record
Abstract
PURPOSE: There is currently no information on how caregivers for women diagnosed with cervical cancer in Guatemala, particularly daughters, are affected by their supportive role. This study's objective was to describe the support role of caregivers in the country, with a focus on daughters with a mother diagnosed with cervical cancer. METHODS: This analysis utilizes data from a cross-sectional study which aimed to understand pathways to cervical cancer care. Women seeking cervical cancer treatment at the Instituto de Cancerologia (INCAN) in Guatemala City, Guatemala and their companions were surveyed. Descriptive statistics were calculated. RESULTS: One hundred forty-five women seeking treatment and 71 companions participated in the study. Patient's daughters were most frequently reported as the person who provided the most support (51%) and as the most reported to have encouraged the patient to seek care. Furthermore, daughters were noted as the person most reported to fulfill the major household and livelihood roles of the patient while they were seeking or receiving treatment (38.0%). Most daughters reported that they were missing housework (77%), childcare (63%), and income-earning activities (60%) to attend the appointment with their mothers. CONCLUSION: Our study suggests that in Guatemala cervical cancer patient's daughters have a significant support role in their mother's cancer diagnosis. Furthermore, we found that while caring for their mothers, daughters in Guatemala are often unable to participate in their primary labor activities. This highlights the additional burden that cervical cancer has on women in Latin America.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".