The prevalence and outcomes of depression in older HIV-positive adults in Northern Tanzania: a longitudinal study
Bibliographic record
Abstract
Abstract Background: Studies of depression and its outcomes in older people living with HIV (PLWH) are currently lacking in sub-Saharan Africa Objectives: To investigate prevalence of psychiatric disorders in PLWH aged ≥50 years in Tanzania focussing on prevalence and two-year outcomes of depression.Method: PLWH aged ≥50 were systematically recruited from an outpatient clinic and assessed using the Mini-International Neuropsychiatric interview (MINI). Neurological and functional impairment were assessed at year two follow-up. Results: 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) DSM-IV depression non-significantly decreased (14.2% -11.1%) x2 :2.48 p=0.29). Baseline depression, was associated with increased functional (p=0.018), and neurological impairment (p<0.001) and negative life events (p=0.001) at follow-up, but HIV and sociodemographic factors were not.Conclusions: In this setting, depression appears highly prevalent and associated with poorer outcomes. This may be a future intervention target.
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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 | 0.001 |
| 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".