An educational video increases disease-related knowledge in hospitalized patients with decompensated cirrhosis
Bibliographic record
Abstract
Background: The Cirrhosis Care Alberta (CCAB) Project has created an expert-guided educational video for patients with decompensated cirrhosis. The effect of this video on improving disease-related knowledge in patients with decompensated cirrhosis has yet to be determined. Methods: In-patients with decompensated cirrhosis were prospectively recruited between November 2022 and August 2023. A pre-post-intervention design employing a questionnaire on managing complications of decompensated cirrhosis was used to evaluate whether the CCAB educational video was effective in improving disease-related knowledge, the primary outcome. Baseline knowledge was defined as preintervention questionnaire scores. Learning was defined as the difference between postintervention and preintervention questionnaire scores. Follow-up occurred 30 days when the same questionnaire was readministered. Univariate and multivariate regression analyses evaluated if any participant demographics and disease-related characteristics predicted baseline knowledge or learning. Results: Fifty participants were included. Study participants were predominantly biologically male (62%), aged 40–75 (78%), and had an average of 2.4 (SD: 2.8) prior cirrhosis-related hospitalizations. The mean baseline knowledge score among participants was 62% (SD: 17.3). The mean questionnaire scores following the educational video rose to 72.5% (SD: 20.2%, p < 0.001). Sixteen (32%) participants completed the 30-day follow-up questionnaire with a mean score of 78.8% (SD: 14.7, p = 0.02). Univariate analysis demonstrated that age, number of prior cirrhosis-related hospitalizations, and number of decompensating events predicted baseline knowledge scores ( p values < 0.05). Conclusion: The CCAB educational video is effective in improving disease-related knowledge scores. Further investigation evaluating this effect on clinical outcomes is needed.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".