Factors influencing the acceptability of hepatitis C screening among people with experience of incarceration in Quebec, Canada: A qualitative descriptive study guided by the Theoretical Domains Framework
Bibliographic record
Abstract
BACKGROUND: For hepatitis C virus (HCV) elimination to occur in carceral settings, opt-out screening on admission, the first step in the HCV care cascade, is recommended. As screening strategies in Quebec provincial prisons vary, we aimed to identify factors influencing the acceptability of HCV screening among people with experience of incarceration (PWEI). METHODS: A theory-based qualitative descriptive study was used to conduct semi-structured interviews. Interview guides and analyses were guided by the Theoretical Domains Framework (TDF). Directed content analysis was used to identify domains within the TDF reflecting barriers and facilitators to HCV screening. RESULTS: Nineteen interviews were conducted from January-December 2022. Most (58 %) participants identified as cisgender men, and the median age was 48 years. Social influences was the most frequently coded domain indicating the importance of peer networks in influencing HCV screening uptake. This was followed by Environmental context and resources, underscoring the prison environment's role as both a barrier and facilitator to HCV screening, and Beliefs about consequences, pointing to perceived outcomes of a positive test, underpinned by a lack of knowledge, stigma, and fear/anxiety, on HCV screening uptake. CONCLUSIONS: The TDF was useful in identifying factors associated with the acceptability of HCV screening among PWEI. Future interventions should seek to leverage peer networks, integrate point-of-care HCV testing, and provide whole-of-sector education and wrap-around services to better support PWEI and contribute to broader efforts to eliminate HCV among incarcerated populations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".