Hepatitis B Learning Needs Assessment of Family Medicine Trainees in Canada: Results of a Nationwide Survey
Bibliographic record
Abstract
BACKGROUND: An estimated 350 million people worldwide have chronic hepatitis B (CHB), which is a major cause of cirrhosis and hepatocellular carcinoma. OBJECTIVE: To assess the level of knowledge among family medicine trainees regarding the identification and management of CHB. METHODS: questionnaire to assess knowledge regarding screening and management of patients with CHB and cirrhosis was developed. The questionnaire was pilot tested among primary care physicians, subsequently revised and distributed to family medicine trainees across Canada through an online survey program (QuestionPro). RESULTS: A total of 158 trainees completed the questionnaire. Of these, 54% to 56% routinely offered vaccination against hepatitis A or hepatitis B virus (HBV), and 42% regularly screened patients for HBV risk factors. The percentage who recognized the need to screen highrisk populations for CHB, ie, individuals from an HBV-endemic country, men who have sex with men, or intravenous drug users was 73%, 66% and 74%, respectively. While less than 50% of respondents used the appropriate HBV screening tests, 86% to 91% correctly interpreted various HBV serological patterns. Only 3% recognized cirrhosis in our case scenario. Almost 80% of respondents inappropriately preferred prescribing a narcotic or nonsteroidal anti-inflammatory drug over acetaminophen (4%) for pain control in a patient with cirrhosis. While less than 60% recognized HBeAg negative CHB as an indication for referral and treatment, 90% would have referred a patient in the immune-tolerant phase, even though treatment is not indicated. CONCLUSIONS: Knowledge gaps regarding CHB among family medicine trainees in the areas of primary prevention, disease recognition and management of cirrhosis were identified. Results suggest that opportunities to prevent potentially life-threatening complications are being missed.
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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 | 0.001 | 0.003 |
| 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) | 0.001 | 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".