(079) IMPLEMENTATION OF A HYBRID VIRTUAL/IN-PERSON SEXUAL HEALTH CLINIC IN A HIGH- VOLUME CANCER CENTRE
Bibliographic record
Abstract
Abstract Introduction Sexual health concerns are some of the most prevalent and challenging side effects of cancer treatment. A hybrid virtual and in-person Sexual Health Clinic (SHC) was recently established within a high-volume Cancer Centre to provide patients with comprehensive sexual health assessment and intervention. Previous research has highlighted the importance of implementation in the achievement of successful outcomes. As part of a robust program evaluation, implementation research methods were used to support the integration of the SHC. Objective The objective of this study was to employ a systematic framework to guide the implementation of an innovative hybrid virtual and in-person SHC within an oncology setting. Methods The study setting was a high-volume oncology Centre situated in a large urban setting. Participants were purposefully sampled to ensure involvement of relevant stakeholders, including healthcare providers (HCPs) and patient participants representing each identified cancer site (eg, prostate, testicular, bladder, kidney, cervical, ovarian and head & neck cancers). The Quality Implementation (QI) Framework was used to guide the knowledge translation and implementation strategy. The procedure involved conducting 30-minute, semi-structured interviews with patients, clinic personnel, and oncologists. The interviews were transcribed and analyzed using Framework Analysis methodology. The goal of the interviews was to determine ideal SHC implementation methods directly from the perspectives of both patients and HCPs. Results In total, 20 semi-structured interviews were conducted (6 patients and 14 HCPs) transcribed and analysed. After employing the Framework Analysis Method, 3 main themes and 10 subthemes were determined. The 3 main themes and associated sub themes include: 1) Recognized Need (Current Gap in Care, Common Concerns Across Populations, and Unique Needs by Population); 2) Confinements of Current Care (Mutual Avoidance/Silence, Concern of Providing Inadequate Care, and Lack of Time); and 3) Strategic Implementation (Need for a Unique Space and Team, Need for Flexibility, Need for Patient Awareness, and Multiple and Ongoing Engagement into Patient Workflow). Conclusions This study successfully identified the barriers and facilitators to implementing a hybrid in-person/virtual SHC within a high-volume urban oncology Centre. These findings offer practical insights into integrating sexual health programming into patient workflows, enhancing patient accessibility and engagement. Disclosure No.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".