Stigma and patient work: Understanding cumulative inequities for gay and bisexual men in accessing HIV healthcare services
Bibliographic record
Abstract
Patient work refers to the quotidian labour undertaken by individuals to manage health, often unrecognised by health systems. This article argues that anticipated and received stigma and inclusivity labour comprise additional forms of patient work specific to minority populations. We draw on a case study of gay and bisexual men's experiences accessing healthcare services related to HIV prevention and testing in New South Wales (NSW), Australia's most populous state. Although new HIV diagnoses have reduced in NSW, these declines have not been uniformly observed. This study aimed to understand experiences of stigma related to accessing healthcare amongst two priority populations identified in the state's HIV strategy: gay and bisexual men who are young or who are living in regional and outer metropolitan suburbs. We interviewed 32 participants in 2023, recruited via social media advertisements and email invitations, and analysed data thematically. Our findings emphasise how disclosure of sexual orientation and/or HIV status operates as a form of inclusivity labour, in which patients look for cues from health providers that disclosure will be safe and respected. Other forms of patient work required to navigate access to HIV prevention services included finding appropriate providers likely to prescribe HIV pre-exposure prophylaxis (PrEP) and managing service refusal from general practitioners. Patient work appeared to also be compounded by intersecting issues of anticipated and vicarious stigma, unavailability of sexual health services in regional areas, long waiting times, and increased costs of healthcare services. Although experiences of enacted stigma in healthcare were infrequently reported, interview accounts suggested that participants undertook extensive patient work to minimise or avoid stigmatising encounters with health providers. Focusing on patient work in the context of stigma illuminates the labour of underserved populations required to access safe and culturally competent healthcare services (including HIV prevention and testing), suggesting areas of unmet need from health systems.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.005 |
| 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".