Exploring lesbian, gay, bisexual, and queer (LGBQ) people’s experiences with disclosure of sexual identity to primary care physicians: a qualitative study
Bibliographic record
Abstract
BACKGROUND: It has been demonstrated that health disparities between lesbian, gay, bisexual and queer (LGBQ) populations and the general population can be improved by disclosure of sexual identity to a health care provider (HCP). However, heteronormative assumptions (that is, assumptions based on a heterosexual identity and experience) may negatively affect communication between patients and HCPs more than has been recognized. The aim of this study was to understand LGBQ patients' perceptions of their experiences related to disclosure of sexual identity to their primary care provider (PCP). METHODS: One-on-one semi-structured telephone interviews were conducted, audio-recorded, and transcribed. Participants were self-identified LGBQ adults with experiences of health care by PCPs within the previous five years recruited in Toronto, Canada. A qualitative descriptive analysis was performed using iterative coding and comparing and grouping data into themes. RESULTS: Findings revealed that disclosure of sexual identity to PCPs was related to three main themes: 1) disclosure of sexual identity by LGBQ patients to a PCP was seen to be as challenging as coming out to others; 2) a solid therapeutic relationship can mitigate the difficulty in disclosure of sexual identity; and, 3) purposeful recognition by PCPs of their personal heteronormative value system is key to establishing a strong therapeutic relationship. CONCLUSION: Improving physicians' recognition of their own heteronormative value system and addressing structural heterosexual hegemony will help to make health care settings more inclusive. This will allow LGBQ patients to feel better understood, willing to disclose, subsequently improving their care and health outcomes.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".