A longitudinal study of associations between HIV‐related stigma, recent violence and depression among women living with HIV in a Canadian cohort study
Bibliographic record
Abstract
INTRODUCTION: Women living with HIV (WLHIV) experience stigma and elevated exposure to violence in comparison with HIV-negative women. We examined the mediating role of experiencing recent violence in the relationship between stigma and depression among WLHIV in Canada. METHODS: We conducted a cohort study with WLHIV in three Canadian provinces. Recent violence was assessed through self-reported experiences of control, physical, sexual or verbal abuse in the past three months. At Time 1 (2013-2015) three forms of stigma were assessed (HIV-related, racial, gender) and at Time 2 (2015-2017) only HIV-related stigma was assessed. We conducted structural equation modelling (SEM) using the maximum likelihood estimation method with Time 1 data to identify direct and indirect effects of gender discrimination, racial discrimination and HIV-related stigma on depression via recent violence. We then conducted mixed effects regression and SEM using Time 1 and Time 2 data to examine associations between HIV-related stigma, recent violence and depression. RESULTS: At Time 1 (n = 1296), the direct path from HIV-related stigma (direct effect: β = 0.200, p < 0.001; indirect effect: β = 0.014, p < 0.05) to depression was significant; recent violence accounted for 6.5% of the total effect. Gender discrimination had a significant direct and indirect effect on depression (direct effect: β = 0.167, p < 0.001; indirect effect: β = 0.050, p < 0.001); recent violence explained 23.15% of the total effect. Including Time 1 and Time 2 data (n = 1161), mixed-effects regression results indicate a positive relationship over time between HIV-related stigma and depression (Acoef: 0.04, 95% CI: 0.03, 0.06, p < 0.001), and recent violence and depression (Acoef: 1.95, 95% CI: 0.29, 4.42, p < 0.05), controlling for socio-demographics. There was a significant interaction between HIV-related stigma and recent violence with depression (Acoef: 0.04, 95% CI: 0.01, 0.07, p < 0.05). SEM analyses reveal that HIV-related stigma had a significant direct and indirect effect on depression over time (direct effect: β = 0.178, p < 0.001; indirect effect: β = 0.040, p < 0.001); recent violence experiences accounted for 51% of the total effect. CONCLUSIONS: Our findings suggest that HIV-related stigma is associated with increased experiences of recent violence, and both stigma and violence are associated with increased depression among WLHIV in Canada. There is an urgent need for trauma-informed stigma interventions to address stigma, discrimination and violence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".