P5-S6.23 Barriers to accessing hepatitis C treatment for individuals who have experience with injection drug use
Bibliographic record
Abstract
In Canada, approximately 10 000 people are living with both hepatitis C and HIV; 20% of individuals living with HIV are co-infected with hepatitis C. Many individuals who inject drugs are at a higher risk for contracting both hepatitis C and HIV because they engage in high risk activities that increase their chances of being in contact with infected blood Individuals living with hepatitis C are at risk of contracting HIV. Being co-infected with both diseases complicates both hepatitis C and HIV; it is therefore critical to provide treatment for hepatitis C. Although those living with hepatitis C often report high interested in treatment, uptake remains low. The purpose of this research project is to identify the factors which influence decisions around hepatitis C treatment. A mixed methods approach was used; 60 individuals participated in a cross sectional questionnaire, while 6 engaged in in-depth interviews. All participants were currently accessing methadone maintenance treatment for opioid addiction and had experience with injection drug use. The questionnaires explored characteristics, knowledge, attitude and willingness to access hepatitis C treatment. Interviews delved deeper into the issues uncovered in the questionnaires and explored life experiences and their influence around treatment decisions. Results indicated that 70% of participants were interested in starting hepatitis C treatment within the next 6 months, while 30% were undecided or uninterested. Analysis of the questionnaire results have suggested that it may not be factual knowledge which influences individuals' decisions around treatment, but life conditions (ie, housing, employment) and experiences. The interviews supported this finding though a thematic analysis. The results of this study suggest that efforts to increase interest in treatment should focus on improving life conditions that support accessing treatment (eg, providing supportive housing). Future studies would include a larger sample size and a more refined questionnaire.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".