Operationalizing the Women-Centred HIV Care Model for trans women and persons with transfeminine experience living with and affected by HIV: A qualitative study
Bibliographic record
Abstract
Background: The Women-Centered HIV Care (WCHC) Model and associated toolkits were created to address the health care barriers and disparities that women and gender diverse people living with HIV experience. Since trans women and transfeminine people experience disproportionately high rates of HIV acquisition (in comparison to their cisgender peers) amidst biologic, social, political, and historical factors that affect their general care experiences negatively, more research is needed. Aim: We aimed to obtain feedback on the WCHC Model regarding the acceptability, applicability, usability, gaps, and potential adaptations needed to meet the needs of trans women and gender diverse people with transfeminine experience. Methods: Our study was grounded in community-based research principles and intersectionality frameworks. We conducted semi-structured interviews with 17 trans women and transfeminine people residing in Ontario, Canada. We analyzed the data using a descriptive qualitative content analysis approach. Results: Participants were largely satisfied with the WCHC Model. However, participants were concerned with the model's implementation due to a lack of knowledge among healthcare providers regarding trans women's experiences within broader social contexts. Simultaneously, participants affirmed the need for care providers to offer person-centered care - a central component of the WCHC Model. Lastly, participants spoke to the healthcare system limitations and failures that disproportionately affected trans women and posed significant barriers to WCHC access and engagement. Discussion: Our findings demonstrate that trans women perceive successful healthcare delivery as combining holistic care frameworks - like the WCHC Model - with healthcare providers' understanding of individual and community needs. There is a need for policy reform to improve the healthcare system. We offer reflections and recommendations for improving healthcare for trans women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".