Challenges having conversations about sexuality in ambulatory settings: Part I—Patient perspectives
Bibliographic record
Abstract
INTRODUCTION: A cancer diagnosis and treatment can have a significant impact on an individual's quality of life. In particular, body image and sexuality can be compromised. However, there is increasing evidence that conversations about these consequences are not happening often between cancer patients and their health care providers. This is especially the case in busy ambulatory settings. PURPOSE: This study was undertaken to explore the perspectives of cancer patients concerning the conversations that happen about sexuality following a cancer diagnosis in daily practice. There was a desire to understand more about the barriers that exist with regards to having this type of conversation. METHODS: Thirty-two cancer patients participated in interviews that explored their experiences with having conversations about sexuality. Transcripts of the interviews were subjected to a standard qualitative content and theme analysis. FINDINGS: Patients described many changes in their bodies following cancer treatment that had the potential to impact on sexuality, but actual concerns or problems about sexuality were highly individualized. Few had had conversations about sexuality with their health care providers. Most thought it was the responsibility of the cancer care team to "open the door" to the topic area. CONCLUSION: The results support the idea that few conversations are taking place between cancer patients and their providers about sexuality. Innovative approaches are required to better meet patient needs.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".