A Multi-Center Randomized Controlled Trial on the Impact of Disease Subtype-Based Active Video Education on Bowel Preparation Quality in Patients With Inflammatory Bowel Disease
A Multi-Center Randomized Controlled Trial on the Impact of Disease Subtype-Based Active Video Education on Bowel Preparation Quality in Patients With Inflammatory Bowel Disease
This multi-center, prospective, randomized controlled trial evaluates whether disease subtype-based active video education improves bowel preparation quality in patients with inflammatory bowel disease (IBD) undergoing colonoscopy. A total of 600 IBD patients from 13 centers will be randomized 1:1 to standard education plus subtype-specific video education (intervention group) or standard education alone (control group). The primary outcome is the Boston Bowel Preparation Scale (BBPS) score.
Inflammatory bowel disease (IBD) patients often have suboptimal bowel preparation before colonoscopy due to chronic inflammation, strictures, and poor adherence to preparation protocols. Conventional written and verbal education has shown limited effectiveness in this population. This multi-center trial will develop and test an active video education intervention tailored to IBD subtypes (ulcerative colitis or Crohn's disease), delivered via WeChat before colonoscopy. A total of 600 patients from 13 participating hospitals across China will be randomized 1:1 to either the intervention group or the control group. Randomization will be stratified by center using a computer-generated sequence with allocation concealment (sealed, opaque envelopes). The primary endpoint is bowel preparation quality measured by the total BBPS score. Secondary outcomes include adequate/excellent preparation rates, cecal intubation rate and time, patient compliance, knowledge scores, adverse events, anxiety levels, and satisfaction. Outcome assessors will be blinded to group assignment to reduce bias. Statistical analyses will account for center effects (e.g., using mixed-effects models or including center as a covariate) and will be performed using appropriate methods based on data distribution.
Inclusion Criteria:
Exclusion Criteria:
liangjie@fmmu.edu.cn029-84771535
Beijing, BeijingBeijing 100730, China
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Shanghai, Shanghai Municipality 200025, China
Shanghai, Shanghai Municipality 200127, China
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