Approaching sexuality in LGBTQIAP + patients with cancer: scoping review
Bibliographic record
Abstract
BACKGROUND: When individuals in the SGM group are diagnosed with cancer and undergo treatment, they experience changes in physical, mental, sexual and spiritual dimensions, which can negatively impact sexual desire, as well as satisfaction and sexual health as a whole. This study aims to examine the existing scientific literature on how healthcare professionals approach sexuality in cancer patients who belong to the SGM group. The SGM group is particularly vulnerable, and the challenges they face in terms of psychosocial and emotional health are further exacerbated by the oncological treatment they receive. Therefore, specialized attention and support are necessary to address their unique needs. METHOD: To conduct this study, a scoping review was performed following the guidelines established by the Joanna Briggs Institute. By synthesizing the available evidence, this study aims to provide insights and recommendations for healthcare professionals to improve the care and support provided to SGM individuals with cancer. Guiding question: "how do health professionals approach sexuality in cancer patients in a minority group?". The search was carried out in PubMed, Science Direct, Scopus, Web of Science, Virtual Health Library, Embase databases and Google Scholar in addition. Specific criteria were used for Evidence source selection, Data mapping, assurance, analysis, and presentation. RESULTS: Fourteen publications were included in this review for the final synthesis, which indicated that the approach to the sexuality of sexual and gender minority groups is based on research whose character is limited in terms of producing care and health care that is congruent in gender and sexuality. The analysis of scientific articles showed that one of the biggest challenges and priorities of health services today is to reduce disparities and promote equity in health for SGM people. CONCLUSIONS: This study reveals a significant gap in addressing the sexuality of SGM groups within cancer care. Inadequate research impedes the provision of consistent and inclusive care for SGM individuals, which has a negative impact on their overall wellbeing. Reducing disparities and promoting healthcare equity for SGM individuals must be a top priority for health services.
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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 | 0.012 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".