Health-Related Quality of Life and Associated Factors Among People Living with HIV Infection at a Comprehensive Hospital in Ethiopia
Bibliographic record
Abstract
Abstract Background: Antiretroviral therapy (ART) has significantly reduced mortality and morbidity of people living with HIV/AIDS (PLWHA); however, the nature of infection and treatment associated with adverse drug reactions often adversely affect patient's health-related quality of life (HRQoL). The purpose of this study was to assess the HRQoL and its associated factors among PLWHA in Ethiopia. Methods: A hospital-based cross-sectional study was conducted among patients taking HAART at Zewditu Memorial General Hospital in Addis Ababa. A face-to-face interview was performed using the HIV/AIDS targeted quality of Life (HAT-QoL) instrument. Patients who met eligibility criteria were approached consecutively while they came to the pharmacy for a medication refill. Descriptive statistics were used to present patient characteristics and HRQoL profiles. Independent t-test and one-way ANOVA were carried out to identify predictors for HRQoL. All statistical tests considered significant at p-value < 0.05. Results: A total of 300 participants were interviewed. The mean age of patients was 41.47 ± 9.45 years and the majority (63.13% ) were females. More than two-thirds (69.7%) of patients were adherents to their medication. The highest HAT-QoL mean score was observed in the overall function domain (84.96±19.87) followed by life satisfaction (83.02±14.61) and physician trust (80.53±20.79). Moderate mean scores were reported in the domains of health worries (71.90±27.00), medication worries (69.44±21.53) and disclosure worries (63.65±30.94) had moderate mean scores, while HIV mastery (56.94±32.52), financial worries (48.81±44.64), and sexual function (12.57±45.56) recorded lower mean scores. Being female, higher educational status, older age, low household income, taking prophylactic therapy, low CD4+ count, and non-adherence were significantly associated with HAT-QoL domains. Conclusions: Overall, HIV/AIDS patients in Addis Ababa had an average level of HRQoL. This study demonstrated that several sociodemographic and clinical variables contribute to reduced HRQoL. Hence, healthcare providers should be paid attention to associated factors that contributed to reduced HRQoL.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".