“Our needs, our priorities, listen to us!” recommendations for improving HIV prevention and the cascade of care from people living with HIV in Manitoba, Canada: a qualitative study
Bibliographic record
Abstract
BACKGROUND: The Canadian province of Manitoba has reported a 52% increase in HIV diagnoses during the past 5 years. Females are disproportionately affected by HIV and multiple intersecting health and social challenges, including houselessness, injection drug use, sexually transmitted and blood borne infections, and mental health conditions. Program and service development often ignore people's complex lived experiences. Our aim was to describe recommendations made by people living with HIV (PLHIV) to inform a person-centred HIV cascade of care valuing the needs and ideas from PLHIV. METHODS: This qualitative study was conducted between October 2022 and May 2023. Thirty-two women, men, and gender-diverse participants completed a semi-structured interview. Interviews were recorded, transcribed, and analyzed using NVivo 12, deploying thematic analysis to understand major themes related to recommendations to care. This manuscript focuses on questions related to recommendations for the HIV cascade of care. RESULTS: Recommendations fell within two major themes: 'Meeting people where they are at' and an HIV educational strategy. The first theme included three main categories to make HIV services more accessible. (1) psychological (social programming, peer support during diagnosis, increased mental health services), (2) biomedical (HIV outreach, HIV services outside 9 -5 h, specialized care outside metropolitan areas, universal coverage for HIV medicines), and (3) social (transportation support, emergency housing, financial support) supports. The HIV educational strategy included five major categories: (1) physical posters and billboards in highly transited areas; (2) community meetings with peer-led education; (3) comprehensive sex education in schools; (4) training primary healthcare providers on stigma and discrimination; (5) and social media campaigns to reach younger audiences. We report on gender differences for recommendations where they arose. The themes described by PLHIV suggest a need to implement HIV care delivery models that will connect and maintain people in HIV care in Manitoba. CONCLUSIONS: This study provides practical and person-centred strategies that could bridge the barriers PLHIV face when accessing and remaining in HIV care and expanding education and prevention about HIV in Manitoba.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".