Cross-sectional study of Hepatitis B Awareness among Chinese and Southeast Asian Canadians in the Vancouver-Richmond community
Bibliographic record
Abstract
BACKGROUND: Hepatitis B (HBV) is endemic and a leading cause of morbidity and mortality in Asia. British Columbia has the highest proportion of Chinese and Southeast Asians among all Canadian provinces. The present study was designed to evaluate the degree of concern for and knowledge of HBV in this high-risk community. METHODS: Unselected patrons of two large Asian commercial centres in Richmond, British Columbia were surveyed. The variables studied were population demographics, concern for HBV, level of HBV knowledge and awareness of HBV-related cirrhosis or hepatocellular carcinoma (HCC). Associations were assessed using c2 testing and multiple logistic regression analysis. RESULTS: A total of 1008 individuals participated in the survey. Fifteen incomplete surveys were excluded. Only 7.7% felt that HBV was not a concern for the community. Only 13% of respondents felt that HBV education was adequate in the community. The main sources of community health education were their doctor's office (56.3%) and media (49.1%). A high number stated they were "aware" of HBV (68%) but over 60% were unaware that HBV could cause HCC or cirrhosis and only 61.3% scored a 'reasonable' level of HBV knowledge. Higher HBV knowledge was significantly associated with increasing age (P<0.001), higher education (P<0.001) and the use of media for health education (P<0.001). Awareness that HBV may cause HCC and cirrhosis was significantly associated with age (P<0.001), education (P=0.006) and birthplace (P=0.001). INTERPRETATION: HBV education is necessary in this local Asian community. Programs should target younger, less educated adults and elaborate on the potential serious health consequences of HBV. Vehicles for public education should include the physicians' offices and local media.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".