Multimodal AI-Assisted Bowel Preparation for Colonoscopy
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age20+
SponsorChiayi Christian Hospital
About this trial
This randomized controlled trial aims to evaluate the effectiveness of a multimodal artificial intelligence (AI)-assisted smartphone application in improving bowel preparation outcomes among hospitalized adults undergoing colonoscopy. A total of 140 participants will be randomly assigned in a 1:1 ratio to either an experimental group or a control group. The control group will receive conventional written and verbal nursing education, while the experimental group will receive the same standard education plus a multimodal AI-assisted application delivered through the LINE platform. The application provides structured bowel preparation education, interactive AI-based question-and-answer support, dietary image recognition, stool image analysis, and individualized feedback. Study outcomes will include bowel preparation knowledge, satisfaction with nursing education, and bowel cleansing quality assessed using the Aronchick Scale.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Hospitalized adults scheduled to undergo colonoscopy.
Age 20 years or older.
Able to read.
Conscious and able to communicate in Mandarin or Taiwanese.
Disqualifiers
Patients receiving hemodialysis or peritoneal dialysis.
Patients unable to take bowel cleansing medication orally.
Patients unable to consume a large volume of fluids.
Patients with intestinal stenosis, bowel obstruction, or obstructing intestinal tumors.
Trial design
Design model
Parallel
Treatments tested in this trial
Multimodal AI-Assisted Bowel Preparation Education
BehavioralParticipants in the experimental group receive conventional bowel preparation education plus a multimodal AI-assisted application delivered through the LINE platform. The application provides structured education on bowel preparation, dietary restrictions, bowel cleansing medication, and examination procedures; interactive AI-based question-and-answer support; dietary image recognition; stool image analysis; and individualized feedback throughout the bowel preparation process. Food images are analyzed to classify dietary patterns as clear liquid, low-residue, or regular diet, while stool images are analyzed using multimodal AI and a convolutional neural network model to assess bowel cleansing status and provide feedback.
Treatment groups
140 Participants
are divided into 2 treatment groupsGroup A: Multimodal AI-Assisted Education GroupExperimental treatment 1 intervention
Group B: Conventional Nursing Education GroupActive comparator 1 intervention
Trial outcomes
Primary outcomes
1
Bowel Cleansing Quality Assessed Using the Aronchick Scale
Bowel cleansing quality will be assessed by the endoscopist using the Aronchick Scale, which classifies bowel preparation as Excellent, Good, Fair, Poor, or Inadequate. Excellent and Good ratings will be considered adequate bowel preparation.
Time frame
During colonoscopy, approximately 2-3 days after enrollmentSponsors and contacts
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Source ClinicalTrials.gov