Understanding Perceptions of Hepatitis C and Its Management Among People with Experience of Incarceration in Quebec, Canada: A Qualitative Study Guided by the Common Sense Self-Regulation Model
Bibliographic record
Abstract
Hepatitis C virus (HCV) disproportionately affects certain sub-populations, including people with experience of incarceration (PWEI). Little is known about how perceptions of HCV and treatment have changed despite simplifications in testing and treatment in carceral settings. Nineteen semi-structured interviews were conducted with people living with or having a history of HCV infection released from Quebec provincial prison. Interviews were guided by the Common Sense Self-Regulation Model (CS-SRM) and aimed to explore cognitive and emotional representations of HCV and coping strategies. Among the 19 participants, seven (37%) were diagnosed with HCV in prison and 14 (74%) had previously received HCV treatment. Participants' HCV illness perceptions were influenced by fear (of HCV transmission, death, and the well-being of family) and stigma (related to HCV, injection drug use, and incarceration). While some sought education and social and professional support, others self-isolated or engaged in high-risk behaviors to cope. Despite advances in HCV treatment, PWEI continue to experience various forms of stigma and fear surrounding their HCV diagnosis, resulting in delayed HCV care. These findings provide insights into how prison-based healthcare providers can better utilize HCV illness perceptions to evaluate willingness to engage in HCV care among PWEI.
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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 | 0.001 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".