A qualitative study of sexual health and function of females with pelvic cancer
Bibliographic record
Abstract
Background: Pelvic cancers are among the most common cancers, impacting millions of individuals worldwide annually. However, little is known about the impact of more rare pelvic cancers on the sexual health of females. Aim: In this study we explored sexual health experiences of female pelvic cancer survivors (FPCS) and their healthcare providers (HCP) in order to identify the most salient impacts of pelvic cancer on sexual function. Methods: = 9). For data analysis, qualitative framework analysis was used. Outcomes: We used the collected data and analysis of findings to establish recommendations including ways to improve sexual health and function in female survivors of pelvic cancer. Results: Most FPCS experienced negative impacts on their sexual health and function through increased pain and dryness, bleeding due to atrophy, decreased libido, and psychosocial issues such as body dysmorphia. Females with the rarer vulvar and vaginal cancers faced additional challenges to their sexual health such as shortening of vaginal canals, high levels of neuropathy, lack of sexual activity with their partners, and suicidal ideation. FPCS had unmet sexual health needs, which can be attributed to lack of appropriate training by HCPs and lack of resources and availability of services. Although HCPs recognized the importance of providing sexual healthcare, they lacked confidence in their ability to facilitate a conversation on sexual health with their patients, and often avoided this topic. Clinical implications: The sexual health outcomes of FPCS can be improved by providing targeted training for HCPs, developing standard resources for sexual health, and integrating tiers of support, including group interventions and counseling. Strengths and limitations: The main strength of this study is that data were collected from HCPs as well as FPCS, thus providing a more in-depth overall picture of the current strengths and weaknesses of the resources for sexual health support available for this patient population. A limitation of this study is that the experiences of transgender men were not captured. Conclusions: Sexual difficulties are very common in all FPCS, particularly survivors of vulvar and vaginal cancers. Improvement of sexual health outcomes is needed in this patient population, which can be achieved by providing more training for HCPs, developing robust resources for FPCS and their sexual health, and providing more opportunities for tiered support.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".