Social and structural barriers and facilitators to HIV healthcare and harm reduction services for people experiencing syndemics in Manitoba: study protocol
Bibliographic record
Abstract
INTRODUCTION: In Manitoba, Canada, there has been an increase in the number of people newly diagnosed with HIV and those not returning for regular HIV care. The COVID-19 pandemic resulted in increased sex and gender disparities in disease risk and mortalities, decreased harm reduction services and reduced access to healthcare. These health crises intersect with increased drug use and drug poisoning deaths, houselessness and other structural and social factors most acutely among historically underserved groups. We aim to explore the social and structural barriers and facilitators to HIV care and harm reduction services experienced by people living with HIV (PLHIV) in Manitoba. METHODS AND ANALYSIS: Our study draws on participatory action research design. Guiding the methodological design are the lived experiences of PLHIV. In-depth semi-structured face-to-face interviews and quantitative questionnaires will be conducted with two groups: (1) persons aged ≥18 years living or newly diagnosed with HIV and (2) service providers who work with PLHIV. Data collection will include sex, gender, sociodemographic information, income and housing, experiences with the criminal justice system, sexual practices, substance use practices and harm reduction access, experiences with violence and support, HIV care journey (since diagnosis until present), childhood trauma and a decision-making questionnaire. Data will be analysed intersectionally, employing grounded theory for thematic analysis, sex-based and gender-based analysis and social determinants of health and syndemic framework to understand the experiences of PLHIV in Manitoba. ETHICS AND DISSEMINATION: We received approval from the University of Manitoba Health Ethics Research Board (HS25572; H2022:218), First Nations Health and Social Secretariat of Manitoba, Nine Circles Community Health Centre, Shared Health Manitoba (SH2022:194) and 7th Street Health Access Centre. Findings will be disseminated using community-focused knowledge translation strategies identified by participants, peers, community members and organisations, and reported in conferences, peer-reviewed journals and a website (www.alltogether4ideas.org).
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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 | 0.021 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.061 | 0.008 |
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".