Internet-Based Patient Education Prior to Colonoscopy: Prospective, Observational Study of a Single Center’s Implementation, with Objective Assessment of Bowel Preparation Quality and Patient Satisfaction
Bibliographic record
Abstract
BACKGROUND: Nonpharmacologic factors, including patient education, affect bowel preparation for colonoscopy. Optimal cleansing increases quality and reduces repeat procedures. This study prospectively analyzes use of an individualized online patient education module in place of traditional patient education. AIMS: To determine the effectiveness of online education for patients, measured by the proportion achieving sufficient bowel preparation. Secondary measures include assessment of patient satisfaction. METHODS: Prospective, single-center, observational study. Adults aged 19 years and over, with an e-mail account, scheduled for nonurgent colonoscopy, with English proficiency (or someone who could translate for them) were recruited. Demographics and objective bowel preparation quality were collected. Patient satisfaction was assessed via survey to assess clarity and usefulness of the module. RESULTS: Nine hundred consecutive patients completed the study. 84.6% of patients achieved adequate bowel preparation as measured by Boston bowel preparation score ≥ 6 and 90.1% scored adequately using Ottawa bowel preparation score ≤7. 94.2% and 92.1% of patients rated the web-education module as 'very useful' and 'very clear', respectively (≥8/10 on respective scales). CONCLUSIONS: Our analysis suggests that internet-based patient education prior to colonoscopy is a viable option and achieves adequate bowel preparation. Preparation quality is comparable to previously published trials. Included patients found the process clear and useful. Pragmatic benefits of a web-based protocol such as time and cost savings were not formally assessed but may contribute to greater satisfaction for endoscopists and patients.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".