Liver Transplant Recipients Speak Out on Public Awareness and Education Surrounding Alcohol-Related Health Effects: A Survey Study
Bibliographic record
Abstract
BACKGROUND: Compared to other recreational substances in Canada, alcohol consumption incurs the highest healthcare costs. Liver transplant recipients are unique stakeholders as members of the general public with lived experiences of liver disease. We sought to explore their perspectives on the current state of public education on alcohol-related health effects. METHODS: The most recent 400 liver transplant recipients at Vancouver General Hospital, Canada, were invited to participate in an anonymous online survey on alcohol-related health effects by mail, email, and phone. RESULTS: Of 372 contacted patients, 212 (57%) completed the survey. Most patients were between 60-79 years, 63% were male, and 69% were Caucasian. The most common liver conditions leading to transplant were viral hepatitis (33%), alcohol-related liver disease (16%), autoimmune liver disease (14%), and non-alcoholic fatty liver disease (15%). Most patients knew that alcohol leads to liver failure (85%), but fewer knew about alcohol leading to cancer (54%), heart disease (50%), and damage to other organs (58%). Most common sources of information included public media (61%), family and friends (52%), and physicians (49%), with narrative comments about learning of alcohol-related health effects after liver diagnosis. Most patients believed that public health education at a middle/high school level would have long-term efficacy (72%) compared to health warning labels (33%) and safety messaging in commercials (39%). Current public education was felt to be adequate by only 20% of patients and 73% of patients supported health warning labels. CONCLUSIONS: Liver transplant patients reported a high, but not universal, awareness of alcohol-related health effects. A majority thought that current public health efforts were inadequate; it is critical to implement public health interventions to ensure consumers are able to make an informed decision on alcohol consumption.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".