The Effectiveness of a Liver Disease Education Class for Providing Information to Patients and Their Families
Bibliographic record
Abstract
BACKGROUND: We have been conducting liver disease education classes regularly in our hospital for the purpose of providing health information to patients and their families. METHODS: In order to evaluate the effectiveness of these classes, we conducted a questionnaire survey of patients and family members who attended the classes held three times in 2012. The cumulative total number of participants was 80 (49 patients, 26 family members, and five others). The classes focused on the following areas: 1) prevention of hepatic cancer; 2) treatment of hepatic cancer; 3) iron restriction diet for hepatitis C patients; and 4) importance of branched-chain amino acid preparations. Self-evaluation of knowledge in these areas was based on a four-point scale. RESULTS: A comparison of knowledge levels between the patients and their family members revealed no statistically significant differences. Therefore, subsequent analyses were performed by combining the patients and their families into one group. The knowledge level of the participants increased with the number of class attendances; that is, the more often they attended, the more they accumulated knowledge (Kruskal-Wallis test: P < 0.0001; P = 0.0368; P = 0.0021; and P < 0.0001). In addition, the results of the questionnaire administered immediately before and after the education class showed significant improvement in the knowledge level for each area. CONCLUSION: The results of this study indicate the liver disease education class to be effective for improving the knowledge of patients and their families. The importance of repeated information provision was also demonstrated.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".