Lived Experiences of Sexual and Gender Minorities in Solid Organ Transplantation: A Best-Fit Framework Synthesis and Inductive Thematic Analysis
Bibliographic record
Abstract
Background: Organ and tissue donation and transplantation (OTDT) policies and practices lead to differential care for sexual and gender minorities (SGMs). The experiences of SGM patients and caregivers in the transplantation system have not been published. The perspectives of SGMs on how to best address existing inequities are not understood. Objective: To characterize the lived experiences of SGM patients and caregivers in solid-organ transplant health systems, as well as the perspectives and priorities of these individuals regarding SGM-relevant policies, practices and targets for system improvements. Methods: We conducted a series (N = 12) of one-on-one semi-structured interviews with a convenience sample of SGMs with lived experience of the OTDT system. We transcribed interviews verbatim and performed a formal qualitative analysis combining a best-fit framework synthesis and inductive thematic analysis. Results: We revealed novel targets for action to improve inclusive care in the transplantation system directly informed by the lived experiences of SGM patients and caregivers. Targets for improvement included (1) enhancements to shared decision-making between OTDT providers and patients, (2) transparent communication from OTDT organizations, (3) data-driven donor risk assessments, (4) expanded healthcare worker training, (5) inclusive physical care spaces, (6) recommendations for transgender and gender-diverse health system planning, (7) integrated sexual and reproductive healthcare services for transplant recipients, (8) increased SGM representation in medical education and care settings, (9) SGM and OTDT intersectional support networks, and (10) structural facilitation of SGM community advocacy efforts. Limitations: While thematic saturation was achieved with our sample, we recognize that not all SGM identities were represented. It remains likely that additional experiences, beliefs, and priorities exist in the SGM community. Conclusions: The emergent priorities and perspectives of SGMs with lived experience of transplant systems should inform patient-centered equitable health system advancements.
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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 | 0.034 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".