Collaborating with patients and caregivers to create web-based educational resources for people affected by cirrhosis
Bibliographic record
Abstract
Objective: To describe the development of multimodal, web-based educational resources about cirrhosis alongside patients and caregivers. Methods: We used an iterative process that was guided by the Strategy for Patient Oriented Research (SPOR) patient engagement framework in describing patient engagement activities to partner with a team of 16 patients and caregivers (Patient Advisory Team (PAT)). This process included five phases: a) Prioritize and gather content, b) design and build the website and videos, c) gather and integrate feedback, d) improve user accessibility, and e) assess usability and knowledge uptake for users. Results: This 2-year process resulted in a 55-page website and 78 animated and live-action videos on cirrhosis complications, procedures, nutrition, and exercise. We implemented usability testing through pre-defined tasks and a think-aloud method from individuals with no previous exposure to the website to assess navigation, appearance, and content issues. Following usability testing, we have been gathering quantitative data from each unique page about relevance and ease of use, as well as qualitative data on the value of the content itself. Conclusions: Collaboration between clinicians, patients, and caregivers is key to developing high-quality digital educational resources. Lessons from our process may help other organizations looking to address disease-specific knowledge gaps. Next steps with www.cirrhosiscare.ca will be continued iterative refinement and structured impact evaluation. Innovation: This project used a patient-centered approach to develop a comprehensive online educational resource for patients with cirrhosis. By having patients with cirrhosis as a key part of our team, we ensured that the site met the needs of this unique population.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".