Illness perceptions and explanatory models of viral hepatitis B and C among immigrants and refugees: a narrative systematic review.
Bibliographic record
Abstract
BACKGROUND: Hepatitis B and C (HBV, HCV) infections are associated with high morbidity and mortality. Many countries with traditionally low prevalence (such as UK) are now planning interventions (screening, vaccination, and treatment) of high-risk immigrants from countries with high prevalence. This review aimed to synthesise the evidence on immigrants' knowledge of HBV and HCV that might influence the uptake of clinical interventions. The review was also used to inform the design and successful delivery of a randomised controlled trial of targeted screening and treatment. METHODS: Five databases (PubMed, CINHAL, SOCIOFILE, PsycINFO and Web of Science) were systematically searched, supplemented by reference tracking, searches of selected journals, and of relevant websites. We aimed to identify qualitative and quantitative studies that investigated knowledge of HBV and HCV among immigrants from high endemic areas to low endemic areas. Evidence, extracted according to a conceptual framework of Kleinman's explanatory model, was subjected to narrative synthesis. We adapted the PEN-3 model to categorise and analyse themes, and recommend strategies for interventions to influence help-seeking behaviour. RESULTS: We identified 51 publications including quantitative (n = 39), qualitative (n = 11), and mixed methods (n = 1) designs. Most of the quantitative studies included small samples and had heterogeneous methods and outcomes. The studies mainly concentrated on hepatitis B and ethnic groups of South East Asian immigrants residing in USA, Canada, and Australia. Many immigrants lacked adequate knowledge of aetiology, symptoms, transmission risk factors, prevention strategies, and treatment, of hepatitis HBV and HCV. Ethnicity, gender, better education, higher income, and English proficiency influenced variations in levels and forms of knowledge. CONCLUSION: Immigrants are vulnerable to HBV and HCV, and risk life-threatening complications from these infections because of poor knowledge and help-seeking behaviour. Primary studies in this area are extremely diverse and of variable quality precluding meta-analysis. Further research is needed outside North America and Australia.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".