Impact of Loneliness on Brain Health and Quality of Life Among Adults Living With HIV in Canada
Bibliographic record
Abstract
BACKGROUND: People aging with HIV are at risk for loneliness, with stigmatization and economic marginalization added to the health challenges arising from chronic infection. This study provides evidence for the extent, contributors, and consequences of loneliness in people living with HIV, focusing on brain health and quality of life. SETTING: Cross-sectional data from 856 middle-aged and older adults living with HIV recruited from 5 urban specialty clinics in Canada were drawn from the inaugural visit of the Positive Brain Health Now cohort study. METHODS: Participants completed an extensive assessment of biopsychosocial variables. The prevalence, severity, and quality of life impact of self-reported loneliness were described. Clinical and environmental factors hypothesized as contributing to loneliness, and the consequences of loneliness on health and function were identified using logistic, ordinal, and linear regression. RESULTS: Eighteen percent reported being "quite often" and 46% "sometimes" lonely. Those with more loneliness were younger, less mobile, suffered more financial hardship, and were more likely to use opioids. HIV symptoms, pain, fatigue, low motivation, stigma, and unemployment were related to loneliness. Loneliness increased the odds of cognitive impairment, low mood, stress, and poor physical health. Those who were "quite often" lonely were over 4 times more likely to report poor or very poor quality of life than those who were "almost never" lonely. CONCLUSION: Loneliness is common in middle-aged and older people living with HIV in Canada. Many of the associated factors are modifiable, offering novel targets for improving brain health, general health, and quality of life in HIV.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".