“To do so in a patient-centred way is not particularly lucrative”: The effects of neoliberal health care on PrEP implementation and delivery
Bibliographic record
Abstract
BACKGROUND: HIV pre-exposure prophylaxis (PrEP) is a highly effective biomedical intervention used by HIV-negative people to prevent HIV acquisition. Despite increased use of PrEP worldwide, several barriers to PrEP implementation have resulted in insufficient uptake, inadequate adherence, and frequent discontinuation. Our objective was to interrogate the social, political, and economic conditions shaping PrEP implementation and delivery among gay, bisexual, queer and other men who have sex with men (GBQM) in Ontario, Canada. METHODS: Six focus groups and three interviews with 20 stakeholders in Ontario (e.g., healthcare professionals, clinicians, community-based organization staff, and government staff) were conducted between July and October 2021. Participants were asked about the personal, workplace, and structural factors shaping PrEP delivery strategies for GBQM. Transcripts were analyzed using reflexive thematic analysis informed by the political economy of PrEP and employed a critique of neoliberalism. RESULTS: Participants critiqued the problematic arrangements of the current healthcare system in Canada. Neoliberal governmentality and policies have resulted in inequitable PrEP care by establishing funding structures prioritizing profit and requiring patients and providers to function as individual entrepreneurs. Consequently, healthcare disparities are compounded for marginalized peoples who lack the resources and capacity to navigate existing healthcare systems. Participants identified several pathways to improve the implementation of PrEP, including greater institutional and governmental supports for PrEP and healthcare, leveraging communities and collaboration, and moving beyond risk-based health frameworks. CONCLUSION: Socio-political-economic changes reflecting post-neoliberal principles are needed to overcome existing barriers to PrEP care, and sexual and reproductive healthcare more broadly.
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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 | 0.033 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 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".