Adequacy of Mental Health Services for HIV-Positive Patients with Depression: Ontario HIV Treatment Network Cohort Study
Bibliographic record
Abstract
BACKGROUND: Major depression can profoundly impact clinical and quality-of-life outcomes of people living with HIV, and this disease is underdiagnosed and undertreated in many HIV-positive individuals. Here, we describe the prevalence of publicly funded primary and secondary mental health service use and antidepressant use, as well as mental health care for depression in accordance with existing Canadian guidelines for HIV-positive patients with depression in Ontario, Canada. METHODS: We conducted a prospective cohort study linking data from the Ontario HIV Treatment Network Cohort Study with administrative health databases in the province of Ontario, Canada. Current depression was assessed using the Center for Epidemiologic Depression Scale or the Kessler Psychological Distress Scale. Multivariable regressions were used to characterize prevalence outcomes. RESULTS: Of 990 HIV-positive patients with depression, 493 (50%) patients used mental health services; 182 (18%) used primary services (general practitioners); 176 (18%) used secondary services (psychiatrists); and 135 (14%) used both. Antidepressants were used by 407 (39%) patients. Patients who identified as gay, lesbian, or bisexual, as having low income or educational attainment, or as non-native English speakers or immigrants to Canada were less likely to obtain care. Of 493 patients using mental health services, 250 (51%) received mental health care for depression in accordance with existing Canadian guidelines. CONCLUSIONS: Our results showed gaps in delivering publicly funded mental health services to depressed HIV-positive patients and identified unequal access to these services, particularly among vulnerable groups. More effective mental health policies and better access to mental health services are required to address HIV-positive patient needs and reduce depression's impact on their lives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".