Health-Seeking Behavior and Quality of Life of People Living With HIV: Novel Evidence From Ghana
Bibliographic record
Abstract
The health and economic burdens of HIV/AIDS in low-and-middle-income countries are enormous despite global and local efforts to prevent and mitigate its effect. This study seeks to assess cadres' (or people living with HIV [PLHIV]) health-seeking behavior and its effects on their quality of life (QoL). We collected cross-sectional data from 218 HIV community cadres and 255 noncadres in 11 out of the 16 political regions in Ghana based on a modified WHOQOL-HIV-Brief and EQ-5D questionnaires. We used descriptive statistics to describe the sample and calculate the QoL scores. We also used regression analysis (ordered logit and ordinary least squares) to analyze the factors associated with the QoL of our respondents. We found that women (77%) are still disproportionally affected by HIV. Similarly, the youth, less educated and informal sector employees continue to be affected most by HIV. Factors related to QoL of PLHIV include being a community cadre, health-seeking behavior, comorbidities, and employment type. We recommend that alternative health providers be educated on the basic science of HIV/AIDS to help them offer appropriate support to PLHIV who visit them for care. Additionally, PLHIV should be supported to engage in less energy demanding employment options.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".