“Another thing to live for”: Supporting HCV treatment and cure among Indigenous people impacted by substance use in Canadian cities
Bibliographic record
Abstract
BACKGROUND: Colonization and colonial systems have led to the overrepresentation of Indigenous people impacted by substance use and HCV infection in Canada. It is critical to ensure Indigenous people's equitable access to new direct acting antiviral HCV treatments (DAAs). Identifying culturally-safe, healing-centered approaches that support the wellbeing of Indigenous people living with HCV is an essential step toward this goal. We listened to the stories and perspectives of HCV-affected Indigenous people and HCV treatment providers with the aim of providing pragmatic recommendations for decolonizing HCV care. METHODS: Forty-five semi-structured interviews were carried out with Indigenous participants affected by HCV from the Cedar Project (n = 20, British Columbia (BC)) and the Canadian Coinfection Cohort (n = 25, BC; Ontario (ON); Saskatchewan (SK)). In addition, 10 HCV treatment providers were interviewed (n = 4 BC, n = 4 ON, n = 2 SK). Interpretive description identified themes to inform clinical approaches and public health HCV care. Themes and related recommendations were validated by Indigenous health experts and Indigenous participants prior to coding and re-contextualization. RESULTS: Taken together, participants' stories and perceptions were interpreted to coalesce into three overarching and interdependent themes representing their recommendations. First: treatment providers must understand and accept colonization as a determinant of health and wellness among HCV-affected Indigenous people, including ongoing cycles of child apprehension and discrimination within the healthcare system. Second: consistently safe attitudes and actions create trust within HCV treatment provider-patient relationships and open opportunities for engagement into care. Third: treatment providers who identify, build, and strengthen circles of care will have greater success engaging HCV-affected Indigenous people who have used drugs into care. CONCLUSION: There are several pragmatic ways to integrate Truth and Reconciliation as well as Indigenous concepts of whole-person wellness into the HCV cascade of care. By doing so, HCV treatment providers have an opportunity to create greater equity and support long-term wellness of Indigenous patients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".