Evaluating experiences of HIV-related stigma among people living with HIV diagnosed in different treatment eras in British Columbia, Canada
Bibliographic record
Abstract
There is mixed evidence on whether experiences of HIV-related stigma are mitigated with lived experience. We sought to examine whether people living with HIV (PLWH) with longer living experience reported varying levels of HIV-related stigma. Between January 2016-September 2018, we used purposive sampling to enrol PLWH aged ≥19 across British Columbia, Canada, where participants completed the 10-item Berger HIV Stigma Scale. We conducted bivariate analyzes examining key sociodemographic characteristics and HIV-related stigma scores. Multivariable linear regression modelled the association between year of HIV diagnosis by treatment era and HIV-related stigma scores. We enrolled 644 participants; median age at enrolment was 50 years (Q1–Q3: 42–56), with 37.4% (n = 241) diagnosed before the year 2000. The median HIV-stigma scores of all participants (19.0, Q1–Q3: 13–25, range 0–40) stratified by treatment era were: 17.0 (pre-1996), 20.0 (1996–1999), 20.0 (2000–2009), 19.0 (2010–2018) (p = 0.03). While there was a significant association at the univariate level, year of HIV diagnosis by treatment era was not associated with stigma scores after controlling for age, gender, HIV key populations, ethnicity, relationship status, social support, and ever having a mental health disorder diagnosis. This suggests that PLWH still experience HIV-related stigma today, compared to those diagnosed in earlier time periods.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".