Sexual Function, Quality of Life, and Experiences of Women with Ovarian Cancer: A Mixed-Methods Study
Bibliographic record
Abstract
INTRODUCTION: Ovarian cancer impacts approximately 1 in 75 women. Sexual health is receiving increasing attention as a critical aspect of gynecologic cancer treatment and a component of quality of life. Therefore, investigating how women with ovarian cancer experience and express sexuality is an important area of inquiry. AIMS: To evaluate how women with ovarian cancer experience and express sexuality, a major determinant of quality of life, in the context of their illness. METHODS: In a mixed-methods approach, 6 validated self-report questionnaires (n = 64) and an in-depth focus group (n = 3) were used to gather data. RESULTS: The quantitative phase of the study showed that women with ovarian cancer have a poorer quality of life and higher rates of sexual dysfunction and sexual distress compared with published norms from the general population. They also have lower levels of relationship satisfaction and increased rates of depression. The qualitative phase of the study revealed 6 themes: (i) changes to relationship satisfaction; (ii) sexual difficulties; (iii) challenges with body image; (iv) gaps in communication with healthcare providers; (v) feelings of guilt, grief, resentment, anxiety, and fear; and (vi) strategies used for coping. CONCLUSIONS: Ovarian cancer impacts women's lives beyond mere survival, including their sexual function and quality of life. Healthcare providers are urged to prepare women with ovarian cancer for these challenges and offer information and resources to help improve their quality of life and sexuality. Fischer OJ, Marguerie M, Brotto LA. Sexual Function, Quality of Life, and Experiences of Women with Ovarian Cancer: A Mixed-Methods Study. Sex Med 2019;7:530-539.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".