The Effectiveness of Bowel Preparation in Colonoscopy Patients Using Artificial Intelligence-assisted Nursing Education
The Effectiveness of Bowel Preparation in Colonoscopy Patients Using Artificial Intelligence-assisted Nursing Education
Background: Colonoscopy is a critical diagnostic and screening tool for colorectal cancer, and its effectiveness largely depends on bowel preparation quality. Traditionally, bowel preparation education has been provided by nurses using written materials and verbal instructions. However, clinical workload pressures and staffing shortages frequently result in inadequate patient comprehension and poor adherence, negatively impacting bowel cleanliness, polyp or adenoma detection rates, examination quality, and overall medical efficiency. Recent advancements in artificial intelligence (AI) suggest potential improvements in patient education and adherence through AI-based interventions. Nevertheless, systematic studies assessing the effectiveness of AI smartphone applications (APPs) specifically tailored for bowel preparation education within local cultural and clinical contexts remain limited.
Objective: This study aims to evaluate the effectiveness of an AI-integrated smartphone application designed for bowel preparation education before colonoscopy, focusing on patient cognition regarding bowel preparation, satisfaction with nursing education, and bowel cleanliness outcomes.
Methods: A randomized controlled trial was conducted in the gastroenterology ward of a regional hospital in southern Taiwan. A total of 140 hospitalized patients scheduled for colonoscopy were enrolled and randomly assigned to either the experimental group (n=70) or the control group (n=70). The experimental group received multimodal education through an AI-based smartphone application, featuring visual and textual information, educational videos, and interactive chatbot dialogues. In contrast, the control group received conventional written and verbal nursing instructions. Demographic data were collected prior to colonoscopy. Post-examination evaluations included bowel cleanliness assessment (using the Aronchick Scale), nursing education satisfaction, and bowel preparation cognition questionnaires administered before and after the intervention. The overall effectiveness of the APP-based intervention was analyzed.
Keywords: Artificial Intelligence, Bowel Preparation, Colonoscopy, Smartphone Application
Inclusion Criteria:
Hospitalized patients scheduled for colonoscopy who are aged 20 years or older. Able to read and write. Conscious and able to communicate in Mandarin Chinese. Own a smartphone and have basic skills in using the LINE application.
Exclusion Criteria:
Patients undergoing hemodialysis or peritoneal dialysis. Unable to read or write. Patients receiving an enema during the bowel preparation process. Patients unable to take oral bowel preparation agents. Patients unable to consume a large volume of fluids. Individuals who do not meet the inclusion criteria. Patients scheduled for colonoscopy on the day before or the same day as the procedure without prior scheduling.
Patients with intestinal stricture, bowel obstruction, or obstruction caused by an intestinal tumor.
Patients with moderate or severe active gastrointestinal bleeding (>100 mL/day).
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