Artificial Intelligence (AI) Technology May Help Patients to Understand Bowel Preparation Better Before They go for Colonoscopy.This Study Attempts to Leverage AI Chatbot in Counselling Patients to Improve Bowel Cleanliness, Reduce Anxiety as Well as Increase Procedural Satisfaction

March 24, 2025 updated by: Nabil Mohammad Azmi, National University of Malaysia

Prospective Single Blinded Randomized Control Trial on the Effectiveness of Using Large Language Model Artificial Intelligence Chatbot to Improve Boston Bowel Preparation Score (BBPS) for Colonoscopy Preparation

Traditional pre-colonoscopy counselling requires significant time from healthcare workers to explain procedures, limiting efficiency and patient turnover. Inadequate bowel preparation exacerbates this issue, leading to repeat procedures and increased costs. However, no study has yet evaluated the effectiveness of AI in improving the Boston Bowel Preparation Scale (BBPS) for colonoscopy preparation. By addressing this gap, AI chatbots could provide personalized guidance, reduce healthcare worker burden, improve preparation quality, and enhance patient experience.This research attempts to evaluate the effectiveness of using Artificial intelligence (AI) chat bot to improve bowel preparation, anxiety level and patient's satisfaction among colonoscopy patients in Hospital Tuanku Muhriz (HCTM), compared to conventional instructions

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

96

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Nabil Mohammad Azmi, Doctor in General Surgery
  • Phone Number: +60122177050
  • Email: nabil@ukm.edu.my

Study Locations

  • Malaysia
    • Kuala Lumpur
      • Cheras, Kuala Lumpur, Malaysia, 56000
        • Faculty of Medicine, The National University of Malaysia
        • Contact:
          • Nabil Mohammad Azmi, Doctor of General Surgery
          • Phone Number: +60122177050
          • Email: nabil@ukm.edu.my

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • All scheduled colonoscopy with indication
  • Adequate digital literacy
  • Adequate language literacy with Malay and English language

Exclusion Criteria:

  • Patients with memory impairment due to previous stroke, dementia or Alzheimer's disease
  • Diagnosed with clinical anxiety

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Artificial Intelligence (AI) Chatbot
Patient's who will be interacting with AI chatbot for bowel preparation counselling
Procedure: AI chatbot study arm
Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)
Procedure: Traditional counselling study arm
Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)
Other: Conventional counselling by healthcare workers
Patients receiving conventional way of counselling for bowel preparation before colonoscopy
Procedure: AI chatbot study arm
Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)
Procedure: Traditional counselling study arm
Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
To determine the effectiveness of artificial intelligence (AI) chat bot in improving bowel preparation among colonoscopy patients in Hospital Tuanku Mukhriz (HCTM), compared to conventional instructions
Time Frame: 1 year
Patients in interventional arm will be receiving counselling via interaction with AI chatbot.Each interaction session were limited to 15 minutes maximum. The quality of bowel preparation will be graded by the masked endoscopists using Boston Bowel Preparation Score (BBPS). Each of the three colon segments (right, transverse and left) will be assigned scores (0 - 3) . 0 - unprepared colon while 3 indicates the best possible preparation.A total score will range from 0 to 9, where higher scores indicate better bowel preparation.
1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
To determine the effectiveness of AI chat bot in relieving anxiety among colonoscopy patients in HCTM, compared to conventional instructions.
Time Frame: 1 year
Anxiety level for both arms will be measured before and after colonoscopy using the validated Depression Anxiety and Stress Scale 21 (Anxiety Scale). Is a self-reporting scale that measure the the anxiety.DASS interpretation ;Normal 0-7, Mild 8-9, Moderate 10-14, Severe 15-19 and Extremely severe 20+
1 year
To determine the effectiveness of AI chat bot in improving satisfaction among colonoscopy patients in HCTM, compared to conventional instructions.
Time Frame: 1 year
Patients from both arms will be interviewed after colonoscopy using the validated Patient Satisfaction Questionnaire (PSQ).PSQ are a set of questionnaires that help researchers to understand patient experiences and identify areas of improvement.Patients will be evaluated on multiple domains- general satisfaction, technical quality, interpersonal aspect, clarity of communication,access to care and confidence in healthcare provider. Each domain will be given scores according to the Likert scale ranging from 1 to 5. 1 means very dissatisfied while 5 means very satisfied.
1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

National University of Malaysia

Investigators

  • Principal Investigator: Nabil Mohammad Azmi, Doctor of General Surgery, Faculty of Medicine, The National University of Malaysia

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 1, 2025

Primary Completion (Estimated)

February 2, 2026

Study Completion (Estimated)

February 2, 2026

Study Registration Dates

First Submitted

March 15, 2025

First Submitted That Met QC Criteria

March 24, 2025

First Posted (Actual)

April 1, 2025

Study Record Updates

Last Update Posted (Actual)

April 1, 2025

Last Update Submitted That Met QC Criteria

March 24, 2025

Last Verified

March 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • JEP-2025-035

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Study Protocol , Informed Consent Form, Clinical Study Report upon considerable request

IPD Sharing Time Frame

APRIL 2025 - FEBRUARY 2026

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • ICF
  • CSR

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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