Using the barriers and facilitators to linkage to HIV care to inform hepatitis C virus (HCV) linkage to care strategies for people released from prison: Findings from a systematic review
Bibliographic record
Abstract
Elimination of hepatitis C virus (HCV) among short-term sentenced prison populations will require improved access to HCV care and specific strategies dedicated to linkage upon release. Prison-based HCV care has lagged behind HIV care, but much can be learned from HIV studies. We performed a systematic review to identify individual-, provider- and system-level barriers and facilitators to linkage to HCV and HIV care among released inmates. We searched MEDLINE, Scopus, the Cochrane Central Register of Controlled Trials and Embase, and performed a grey literature search for English articles published up to November 2018. Two searches were conducted, one each for HCV and HIV; 323 and 684 unique articles were identified of which two and 27 studies were included, respectively. Facilitators to linkage to HCV care included social support, having an existing primary care provider, and receipt of methadone, whereas barriers included a perceived lack of healthcare information and a lack of specialized linkage to care programs. The principal facilitators to linkage to HIV care included social support, treatment for substance use and mental illness, the provision of education, case management, discharge planning and transportation assistance. Important barriers were unstable housing, age <30 years, HIV-related stigma, poor providers' attitudes and the lack of post-release reintegration assistance. While HCV care-specific studies are needed, much can be learned from linkage to HIV care studies. Ultimately, a multi-pronged approach, addressing several individual-level social determinants of health, and key provider- and system-level barriers may be an appropriate starting point for the development of HCV linkage to care strategies.
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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 | 0.024 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".