Prevalence of Depression Among People Living with HIV on Antiretroviral Therapy in Africa: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: HIV is a global health issue, with the highest number of infected individuals found in sub-Saharan Africa. The coexistence of HIV with depression is a huge challenge. This study aimed to investigate the prevalence of depression in people living with HIV (PLWHIV) who are on antiretroviral therapy (ART) in Africa. Method: PubMed, Scopus, and bibliographic screening were used to identify suitable literature. The study adhered to guidelines outlined by Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The Newcastle–Ottawa guideline was used to assess the quality of the included cross-sectional studies. Subgroup analysis and meta-regression were subsequently conducted following the meta-analyses, based on heterogeneity. A meta-analysis software online tool and Jamovi software (version 2.4.8.0) were used to analyse the data, and the results were presented as prevalence and 95% confidence intervals. Results: Thirty-four cross-sectional studies identified from the databases were deemed relevant. The overall sample size was 21,143 PLWHIV on ART in African countries. The analysed data showed the prevalence of depression to be 36%, with 95% CI (27% to 40%), p < 0.01, in Africa. However, the subgroup showed that the highest prevalence was in Northern Africa, with a prevalence of 41% with 95% CI (20% to 50%), p < 0.01, followed by those in Southern and Eastern Africa, with a prevalence of 38% with 95% CI (27% to 49%) and 39% with 95% CI (26% to 50%), p < 0.01, respectively. The lowest prevalence was observed in Western Africa, with a prevalence of 20% with 95% CI (14% to 27%), p < 0.01. Conclusions: Our findings show that there is a higher prevalence of depression among PLWHIV who are on ART in Africa. It is crucial to correctly recognise and provide proper care for depression to optimise HIV treatment and enhance treatment adherence in this population.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".