Gynecologic cancer screening among women with Lynch syndrome: Information and healthcare access needs
Bibliographic record
Abstract
Screening recommendations for gynecologic cancers (GC) associated with Lynch syndrome (LS) are diverse. The objectives of this study were to examine among women with LS: 1) psychosocial factors that influence thoughts and choices about GC screening, and 2) information and unmet healthcare access needs when making GC screening decisions. This study used a qualitative design. Interviews were analyzed using thematic analysis. Participants were women with LS (N = 20) recruited from Toronto, Canada. Fourteen participants had or were participating in GC screening and six had never undergone screening, however were or would be eligible for screening in the future. Five main themes were identified: understanding level of risk, women’s experiences of GC screening, interactions with the health care system, considerations about risk-reducing surgery, and improving LS care. Participants had many unmet healthcare needs and lacked information about screening and pain management. Self-advocacy was an important strategy for managing care. Psychoeducational interventions are important to manage uncertainty associated with LS, increasing social and informational support, and informing health care providers about best practices with this population. • Unmanaged pain and discomfort related to endometrial biopsy were common. • Providers should discuss pain management options for endometrial biopsy. • Self-advocacy in navigating LS-related care was common. • Women with LS desire more specific recommendations about screening. • Women with LS desire more information about menopausal symptoms and HRT.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".