Impact of HIV knowledge and stigma on the uptake of HIV testing – Results from a community-based participatory research survey among migrants from sub-Saharan Africa in Germany
Bibliographic record
Abstract
Background: In 2015, 3,674 new HIV diagnoses were notified in Germany; 16% of those newly diagnosed cases originated from sub-Saharan Africa (sSA). One quarter of the newly diagnosed cases among migrants from sSA (MisSA) are notified as having acquired the HIV infection in Germany. In order to reach MisSA with HIV testing opportunities, we aimed to identify which determinants influence the uptake of HIV testing among MisSA in Germany. Methods: To identify those determinants, we conducted a quantitative cross-sectional survey among MisSA in Germany. The survey was designed in a participatory process that included MisSA and other stakeholders in HIV-prevention. Peer researchers recruited participants to complete standardized questionnaires on HIV knowledge and testing. We conducted multivariable analyses (MVA) to identify determinants associated with ever having attended voluntary HIV testing; and another MVA to identify determinant associated with having had the last voluntary HIV test in Germany. Results: Peer researchers recruited 2,782 participants eligible for inclusion in the MVA. Of these participants, 59.9% (1,667/2,782) previously had an HIV test. For each general statement about HIV that participants knew prior to participation in the study, the odds of having been tested increased by 19% (OR 1.19; 95%-CI: 1.11–1.27). Participants reporting that HIV is a topic that is discussed in their community had 92% higher odds of having been tested for HIV (OR 1.92; 95%-CI: 1.60–2.31). Migrants living in Germany for less than a year had the lowest odds of having had their last HIV test in Germany (OR 0.17; 95%-CI: 0.11–0.27). Additionally, MisSA 18 to 25 years (OR 0.55; 95%-CI: 0.42–0.73) and participants with varied sexual partners and inconsistent condom use (OR 0.75; 95%-CI: 0.44–0.97) had significantly lower odds of having had their last HIV test in Germany. Discussion: Through participatory research, we were able to show that knowledge about HIV and discussing HIV in communities increased the odds of having attended HIV testing among MisSA. However, recent migrants and young sexually active people are among the least reached by testing offers in Germany. Community-based interventions may present opportunities to reach such migrants and improve knowledge and increase discussion about HIV.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".