Disparities in access to and use of HIV-related health services in the Netherlands by migrant status and sexual orientation: a cross-sectional study among people recently diagnosed with HIV infection
Bibliographic record
Abstract
BACKGROUND: Migrants often face barriers to accessing healthcare. We examined disparities in access to and use of HIV-related health services between migrant and non-migrant people recently diagnosed with HIV living in the Netherlands, taken into account sexual orientation. Also, we examined differences in experiences in living with HIV between these groups. METHODS: We used a questionnaire and clinical data collected between July 2013 and June 2015 among migrant and non-migrant participants of the European cross-sectional aMASE (Advancing Migrant Access to health Services in Europe) study in the Netherlands. Using univariable logistic regression analyses, we compared outcomes on between migrants and non-migrants, stratified by sexual orientation (with non-migrant men having sex with men [MSM] as the reference group). RESULTS: We included 77 migrant MSM, 115 non-migrant MSM, 21 migrant heterosexual men, 14 non-migrant heterosexual men and 20 migrant women. In univariable analyses, all heterosexual groups were less likely to ever have had an HIV-negative test before their diagnosis and were more likely to be diagnosed late than non-migrant MSM. All migrant groups were more likely to have experienced difficulties accessing general healthcare in the Netherlands and were less likely to have heard of post-exposure prophylaxis than non-migrant MSM. Migrants frequently reported uncertainty about their rights to healthcare and language barriers. Most (93%) participants visited a healthcare facility in the 2 years before HIV diagnosis but only in 41% an HIV test was discussed during that visit (no statistical difference between groups). Migrant heterosexuals were more likely to have missed appointments at their HIV clinic due to the travel costs than non-migrant MSM. Migrant MSM and women were more likely to have experienced HIV discrimination in the Netherlands than non-migrant MSM. CONCLUSION: Disparities in access to and use of HIV-related health services and experiences exist by migrant status but also by sexual orientation. Our data suggests heterosexual men and women may particularly benefit from improved access to HIV testing (e.g., through provider-initiated testing), while migrant MSM may benefit from improved access to HIV prevention interventions (e.g., pre-exposure prophylaxis).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".