Four-Year Trajectories of Health-Related Quality of Life in People Living with HIV: Impact of Unmet Basic Needs across Age Groups in Positive Spaces, Healthy Places
Bibliographic record
Abstract
Despite significant advances in antiretroviral therapy, unmet basic needs can negatively impact health-related quality of life (HRQoL) in people living with HIV, especially as they age. We aimed to examine the effect of unmet basic needs across age groups on changes in HRQoL over a 4-year period in persons with HIV. Physical and mental HRQoL scores from the Positive Spaces, Healthy Spaces cohort interviewed in 2006 (n = 538), 2007 (n = 506), and 2009 (n = 406) were examined across three age groups according to their unmet needs for food, clothing, and housing. Individual growth curve model analyses were used to investigate changes over time, adjusting for demographics, employment, living conditions, social supports, HIV status, and health behavior risks. Low scores on physical and mental HRQoL were positively associated with higher number of unmet basic needs (β = −6.40, standard error (SE) = 0.87, p < 0.001 and β = −7.39, SE = 1.00, p < 0.001, respectively). There was a slight improvement in physical and mental HRQoL over 4 years in this HIV cohort, but the burden of unmet basic needs took its toll on those over 50 years of age. Regularly assessing unmet basic needs is recommended given the impact these can have on HRQOL for people living with HIV. Recognition of unmet needs is vital, as is the development of timely interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".