Recognizing Endometrial Cancer Risks in Perimenopausal and Postmenopausal Experiences: Insights From Community Qualitative Interviews and Workshop
Bibliographic record
Abstract
OBJECTIVES: To evaluate the experiences of perimenopausal and postmenopausal women in British Columbia, their perceptions of expected reproductive aging, and potential concerns about endometrial cancer (EC). METHODS: We interviewed 31 midlife community women of diverse backgrounds and hosted a workshop for more in-depth discussion. We summarized relayed experiences and beliefs through a thematic and descriptive analysis of participant stories and workshop feedback. RESULTS: Participants demonstrated a somewhat simplistic understanding of midlife changes, facing this phase of life with a "tough-it-out" attitude rather than seeking medical help for arising symptoms. Awareness of EC and EC-specific risk factors, such as obesity, was low. Confusion between cervical and EC was common. Although abnormal bleeding was seen as potentially of concern, many opted to wait before seeking medical help. Workshop participants stressed the need to include awareness about EC in a broader conversation about perimenopause and menopause and suggested strategies for disseminating EC awareness. CONCLUSIONS: Community women in British Columbia demonstrated low awareness of EC-associated symptoms and risk factors. There is little information to help distinguish when perimenopausal abnormal uterine bleeding is of concern and when to seek help. This highlights the need to enhance knowledge of EC and its risk factors in perimenopause among the public and among health care providers.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| 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".