HIV-Related Stigma Affects Cognition in Older Men Living With HIV
Bibliographic record
Abstract
BACKGROUND: Stigma remains a reality for many people living with HIV. Stigma bears on mental health, but we hypothesized that it might also affect cognition, in turn affecting function. METHODS: We estimated the impact of HIV-related stigma on brain health and everyday functioning among 512 older white men living with HIV in Canada, using the International Classification of Functioning, Disability and Health as a comprehensive framework to integrate biopsychosocial perspectives. Experience of HIV-related stigma, as indicated by a single self-report item, was related to cognitive test performance, cognitive symptoms, and mood. Structural equation modeling was used to estimate the relationships between these variables. FINDINGS: A comprehensive structural equation model was built including personal, environmental, and biological factors, measures of mental and cognitive health, activity limitations, and participation restrictions. HIV-related stigma contributed to lower cognitive test performance and worse mental health. These in turn affected real-world function. The paths from stigma to cognition and mood had distinct downstream effects on physical, cognitive, and meaningful activities. INTERPRETATION: This provides evidence that HIV-related stigma is a threat to cognitive as well as mental health, with a negative impact on everyday function in men aging with HIV. This argues for direct links between the psychosocial and biological impacts of HIV at the level of the brain. Stigma reduction may be a novel route to addressing cognitive impairment in this population. FUNDING: Operating support was provided by the Canadian Institutes of Health Research (TCO-125272) and by the CIHR HIV Clinical Trials Network (CTN-273).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".