Barriers to and facilitators of hepatitis C virus screening and testing: A scoping review
Bibliographic record
Abstract
BACKGROUND: As part of the global effort to eliminate hepatitis C virus (HCV), it is important to understand the barriers to and facilitators of HCV screening and testing. OBJECTIVE: To examine the barriers and facilitators experienced by health care providers offering HCV screening and testing and patients seeking HCV testing. METHODS: A literature search was conducted using Embase, Medline and Scopus databases to collect studies published between January 2012 and July 2017. We extracted the following data: author, year of publication, study design, population, setting, country, method of data collection, and knowledge and awareness outcomes. RESULTS: A total of 16 articles were identified. Barriers to HCV screening and testing among patients included low self-perceived risk of acquiring HCV, perceived stigma and fear of a positive result. Facilitators of HCV screening and testing, as reported by patients, included increased knowledge of transmission and manifestations of HCV infection and having HCV testing included as part of routine care with or without HIV testing. Barriers to offering HCV screening and testing included time constraints, lack of specific knowledge about HCV and discomfort in asking about risk behaviours. Facilitators of offering HCV screening and testing included testing reminders and working in locations with a higher HCV caseload. CONCLUSION: Lack of knowledge and fear of stigma and discrimination remain barriers to HCV testing at the patient level and lack of time, knowledge and discomfort in asking about risk behaviours remain barriers to offering HCV testing by health care providers. This identifies potential areas for future public health action.
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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 | 0.016 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".