Open Access Barriers to gender-equitable HIV testing: going beyond routine screening for pregnant women in
Bibliographic record
Abstract
Background: Women and men face different gender-based health inequities in relation to HIV, including HIV testing as well as different challenges in accessing HIV care, treatment and support programs and services when testing HIV-positive. In this article, we discuss the findings of a mixed methods study exploring the various individual and structural barriers and facilitators to HIV counselling and testing experienced among a sample of adult women and men living in Nova Scotia, Canada. Methods: Drawing from testing demographics, qualitative interview data and a review of existing testing policies and research, this paper focuses on understanding the gendered health inequities and their implications for HIV testing rates and behaviours in Nova Scotia. Results: The findings of this research serve as the basis to further our understanding of gender as a key determinant of health in relation to HIV testing. Recognizing gender as a key determinant of health in terms of both vulnerability to HIV and access to testing, this paper explores how gender intersects with health equity issues such as access to HIV testing, stigma and discrimination, and sexual behaviours and relationships. Conclusions: Drawing on the current gender and HIV literatures, in conjunction with our data, we argue that an enhanced, gender-based, context-dependent approach to HIV counselling and testing service provision is required in order to address the health equity needs of diverse groups of women and men living in various settings. Further, we argue that enhanced HIV testing efforts must be inclusive of both men and women, addressing uniquely gendered barriers to accessing HIV counselling and testing services and in the process moving beyond routine HIV testing for pregnant women.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".