Brief Report: Internalized Poverty-Related Stigma and Interpersonal Violence Among Women Living With HIV in the United States
Bibliographic record
Abstract
BACKGROUND: Interpersonal violence (IPV) affects half of women living with HIV (WLHIV) in the United States and has important consequences for mental health and HIV outcomes. Although different types of stigmas (eg, HIV- or sexual identity-related) are associated with increased risk of IPV, the relationship between poverty-related stigma and IPV is unclear, even though poverty frequently co-occurs with IPV. METHODS: Data from up to 4 annual visits (2016-2020) were collected from 374 WLHIV enrolled in a substudy of the Women's Interagency HIV Study (now known as Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study) at 4 sites across the United States. A validated measure of the perceived stigma of poverty was used, along with questions on recent experiences of IPV. We used a mixed-effects model to assess the association between internalized poverty stigma and IPV. RESULTS: The unadjusted model with internalized poverty stigma and recent IPV as independent and dependent variables, respectively, suggested that the 2 were associated (prevalence ratio 1.29 [95% CI: 1.02 to 1.62, P = 0.033]). After adjusting for income and education, we found an independent association between internalized poverty-related stigma and recent IPV, with a prevalence ratio of 1.35 (95% CI: 1.07 to 1.71, P = 0.011). CONCLUSION: Our findings suggest that reducing the psychologic consequences of poverty may better situate WLHIV to escape or avoid IPV. The usefulness of screening WLHIV who may be experiencing poverty-related stigma for IPV should be investigated. Interventions that address internalized poverty-related stigma may provide an avenue for reducing the harms caused by IPV in addition to interventions aiming to reduce violence itself.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".