New Patient Education Video on Colonoscopy Preparation: Development and Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Although several patient education materials on colonoscopy preparation exist, few studies have evaluated or compared them; hence, there is no professional consensus on recommended content or media to use. OBJECTIVE: This study aims to address this need by developing and evaluating a new video on colonoscopy preparation. METHODS: We developed a new video explaining split-dose bowel preparation for colonoscopy. Of similar content videos on the internet (n=20), the most favorably reviewed video among patient and physician advisers was used as the comparator for the study. A total of 232 individuals attending gastroenterology or urology clinics reviewed the new and comparator videos. The order of administration of the new and comparator videos was randomly counterbalanced to assess the impact of presentation order. Respondents rated each video on the following dimensions: information amount, clarity, trustworthiness, understandability, new or familiar information, reassurance, information learned, understanding from the patient's point of view, appeal, and the likelihood of recommending the video to others. RESULTS: Overall, 71.6% (166/232) of the participants preferred the new video, 25.0% (58/232) preferred the comparator video, and 3.4% (8/232) were not sure. Furthermore, 64.0% (71/111) of those who viewed the new video first preferred it, whereas 77.7% (94/121) of the participants who viewed the new video second preferred it. Multivariable logistic regression analysis also demonstrated that participants were more likely to prefer the new video if they had viewed it second. Participants who preferred the new video rated it as clearer and more trustworthy than those who preferred the comparator video. CONCLUSIONS: This study developed and assessed the strengths of a newly developed colonoscopy educational video.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".