Sociocultural and Clinical Determinants of Sexual Dysfunction in Perimenopausal Women with and Without Breast Cancer
Bibliographic record
Abstract
Breast cancer survivorship is a recognized risk factor for sexual dysfunction, with various clinical, sociocultural, and psychological factors potentially interacting differently across populations. This study compared sexual dysfunction, anxiety, and depression between females with breast cancer and those without, aiming to identify associated factors. A total of 362 females participated, including 227 with sexual dysfunction and 135 controls. Among them, 195 are breast cancer survivors, while 167 have no personal history of cancer. Key variables were analyzed using Student’s t-test for quantitative data and Fisher’s exact test for categorical data, while logistic regression models were used to assess the association between sexual dysfunction and various factors. Multivariate analysis revealed that, in sexually active females, breast cancer survivorship increased the odds of sexual dysfunction 2.7-fold (95% CI: 1.17–6.49; p = 0.020). Anxiety was significantly associated with sexual dysfunction, regardless of cancer status (AdOR 6.00; 95% CI: 2.50–14.43; p < 0.001). The interaction between cancer survival and anxiety further increased the odds of sexual dysfunction by more than 11-fold (AdOR 11.55; 95% CI: 3.81–35.04; p < 0.001). Additionally, obesity was found to be a protective factor among cancer survivors (AdOR 0.149; 95% CI: 0.027–0.819; p = 0.029). In conclusion, breast cancer has a significant impact on sexual function, with psychological factors like anxiety playing a crucial role. Addressing these issues requires a holistic, patient-centered approach that considers the complex interplay of physical, emotional, and sociocultural factors.
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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 | 0.000 |
| 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) | 0.001 | 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".