The use of technology platforms for nutrition education in cirrhosis: A cross-sectional study of patients’ acceptability and capabilities
Bibliographic record
Abstract
Background: Few nutrition education strategies using technology have been developed and evaluated for patients with cirrhosis. This study aims to describe the receptivity of these patients to technology-based nutrition education, specifically assessing their interest, preferences, Internet attitudes, technological skills with computers and mobile devices, and factors associated with their interest in such educational approaches. Methods: A cross-sectional study was conducted among patients with cirrhosis. Questionnaires included participant characteristics, interest, preferences and ownership of technology, Internet Attitude Scale (IAS), Computer Proficiency Questionnaire-12 (CPQ-12), Mobile Device Proficiency Questionnaire-16 (MDPQ-16), and Household Food Security Survey Module (HFSSM). Results: 77 patients were included (mean age 63.1, 57.1% male); 68.8% had post-secondary education, and 11.7% were food insecure. The primary etiologies were mixed (27.3%), metabolic dysfunction-associated steatohepatitis (MASH) (24.7%), and alcoholic liver disease (ALD) (19.5%). Most patients (72.7%) were interested in receiving nutrition education through technology. Interested patients showed higher proficiency and better attitude toward the Internet. ALD was more prevalent among patients not interested in technological nutritional education. Univariate analysis identified proficiency, attitude toward the Internet, ALD diagnosis, and tablet ownership as predictors of interest. Multivariate analysis confirmed tablet ownership and Internet attitude as significant factors. Preferred educational formats were documents (59.7%) and video clips (57.1%) by email, and pre-recorded online courses (57.1%). Conclusion: Patients with cirrhosis are generally receptive to technology-based nutrition education, though barriers may include lower technological proficiency and a negative attitude toward the Internet. Enhancing patients' technological skills could increase their willingness to use technology for educational purposes, particularly among ALD patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".