Hepatitis B testing and vaccination in immigrants attending English as a second language classes in British Columbia, Canada.
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) is a growing health issue in Canada, especially given that population growth is now largely the result of immigration. Immigrants from countries with high HBV prevalence and low levels of HBV vaccination have an excess risk of liver disease and there is a need for increased diligence in HBV blood testing and possibly vaccination among these populations. OBJECTIVE: This study describes the sociodemographic characteristics associated with a history of HBV testing and HBV vaccination in immigrants from several countries with high HBV prevalence who are attending English classes. METHODS: 759 adult immigrants attending English as a Second Language classes completed a self-administered questionnaire asking about sociodemographic characteristics and history of HBV testing and HBV vaccination. Descriptive statistics and adjusted ORs were calculated to explore these associations. RESULTS: 71% reported prior HBV testing, 8% reported vaccination without testing, and 21% reported neither testing nor vaccination. Age, education and country of birth all showed significant effects for both testing and vaccination. CONCLUSIONS: Health care practitioners need to be cognizant of HBV testing, and possibly vaccination, in some of their patients, including immigrants from countries with endemic HBV infection. Infected persons need to be identified by blood testing in order receive necessary care to prevent or delay the onset of liver disease as well as to adopt appropriate behaviours to reduce the risk of transmission to others. Close contacts of infected persons also require HBV testing and subsequent vaccination (if not infected) or medical management (if infected).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".