Implementation of a sexual health clinic in an oncology setting: patient and provider perspectives
Bibliographic record
Abstract
BACKGROUND: Sexual dysfunction is prevalent among cancer survivors, significantly impacting patient and partner quality of life. Despite this, sexual health clinics (SHCs) remain rare in cancer centres across Canada. An innovative clinic was developed at Princess Margaret Cancer Centre in Toronto, Canada to address this significant gap in survivorship care. This study examines factors affecting the provision of sexual healthcare and the implementation of a sexual health clinic within a large urban centre. METHODS: The Quality Implementation Framework was used to explicate patient and provider experience and identify barriers and facilitators to integrating sexual healthcare into routine cancer care workflows. Healthcare providers and patients representing selected cancer types (prostate, cervical, ovarian, testicular, bladder, kidney, and head and neck cancer) participated in semi-structured interviews. Interviews were transcribed and analyzed using the Framework qualitative analysis protocol. RESULTS: The analysis identified three organizing domains and ten themes that describe the unique aspects of the sexual healthcare experience and critical factors for sexual health implementation. Both patients and providers described a lack of sexual health support in the oncology setting and emphasized the need for comprehensive and personalized care. Limitations of current care provision included mutual silence between patients and providers due to discomfort in discussing sexual issues, insufficient provider confidence in delivering optimal sexual healthcare, and constraints related to space and time. Key Factors for implementing a sexual health clinic in oncology emphasized the importance of having a dedicated clinic, flexibility in service delivery, proactive patient engagement, and ongoing staff education. CONCLUSIONS: Findings highlight significant challenges in addressing sexual health in an oncology setting, underscoring the need for specialized sexual health clinics that are integrated with, but distinct from, routine oncology care. This study further emphasizes the need for incorporating sexual healthcare in survivorship programs as well as the necessity of conducting thorough implementation research, involving multiple stakeholders, prior to launching new programs.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".