The prevalence and outcomes of depression in older HIV-positive adults in Northern Tanzania: a longitudinal study
Bibliographic record
Abstract
Abstract Studies of depression and its outcomes in older people living with HIV (PLWH) are currently lacking in sub-Saharan Africa. This study aims to investigate the prevalence of psychiatric disorders in PLWH aged ≥ 50 years in Tanzania focussing on prevalence and 2-year outcomes of depression. PLWH aged ≥ 50 were systematically recruited from an outpatient clinic and assessed using the Mini-International Neuropsychiatric Interview (MINI). Neurological and functional impairment was assessed at year 2 follow-up. At baseline, 253 PLWH were recruited (72.3% female, median age 57, 95.5% on cART). DSM-IV depression was highly prevalent (20.9%), whereas other DSM-IV psychiatric disorders were uncommon. At follow-up (n = 162), incident cases of DSM-IV depression decreased from14.2 to 11.1% (χ2: 2.48, p = 0.29); this decline was not significant. Baseline depression was associated with increased functional and neurological impairment. At follow-up, depression was associated with negative life events (p = 0.001), neurological impairment (p < 0.001), and increased functional impairment (p = 0.018), but not with HIV and sociodemographic factors. In this setting, depression appears highly prevalent and associated with poorer neurological and functional outcomes and negative life events. Depression may be a future intervention target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".