NCT06905782

Brief Summary

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

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
96

participants targeted

Target at P50-P75 for not_applicable

Timeline
Completed

Started Apr 2025

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

March 15, 2025

Completed
17 days until next milestone

First Posted

Study publicly available on registry

April 1, 2025

Completed
Same day until next milestone

Study Start

First participant enrolled

April 1, 2025

Completed
10 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 2, 2026

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

February 2, 2026

Completed
Last Updated

April 1, 2025

Status Verified

March 1, 2025

Enrollment Period

10 months

First QC Date

March 15, 2025

Last Update Submit

March 24, 2025

Conditions

Keywords

colorectal cancercolon polypcolonoscopybowel preparationBoston Bowel Preparation Score (BBPS)artificial intelligenceAIChatbotlarge language modelpatient satisfactioncancer screening

Outcome Measures

Primary Outcomes (1)

  • 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

    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 Outcomes (2)

  • To determine the effectiveness of AI chat bot in relieving anxiety among colonoscopy patients in HCTM, compared to conventional instructions.

    1 year

  • To determine the effectiveness of AI chat bot in improving satisfaction among colonoscopy patients in HCTM, compared to conventional instructions.

    1 year

Study Arms (2)

Artificial Intelligence (AI) Chatbot

EXPERIMENTAL

Patient's who will be interacting with AI chatbot for bowel preparation counselling

Procedure: AI chatbot study armProcedure: Traditional counselling study arm

Conventional counselling by healthcare workers

OTHER

Patients receiving conventional way of counselling for bowel preparation before colonoscopy

Procedure: AI chatbot study armProcedure: Traditional counselling study arm

Interventions

Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)

Artificial Intelligence (AI) ChatbotConventional counselling by healthcare workers

Intervention arm will have to undergo bowel preparation using standard polyethylene glycol solution (Fortrans)

Artificial Intelligence (AI) ChatbotConventional counselling by healthcare workers

Eligibility Criteria

Age18 Years - 75 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Faculty of Medicine, The National University of Malaysia

Cheras, Kuala Lumpur, 56000, Malaysia

Location

Related Publications (1)

  • Mohammad Azmi N, Abdul Jalal MI, Mohd Ashar SH, Mohd Nazri MI, Jie Y, Ganeson N, Augustine JK, Qian YS. A prospective single-masked, non-inferiority, parallel-group randomized controlled trial of the efficacy of a ChatGPT-based AI chatbot to improve Boston bowel preparation scores for colonoscopy preparation: A trial protocol. PLoS One. 2025 Oct 15;20(10):e0334349. doi: 10.1371/journal.pone.0334349. eCollection 2025.

MeSH Terms

Conditions

Colonic PolypsAdenomaColorectal NeoplasmsPatient Satisfaction

Condition Hierarchy (Ancestors)

Intestinal PolypsPolypsPathological Conditions, AnatomicalPathological Conditions, Signs and SymptomsNeoplasms, Glandular and EpithelialNeoplasms by Histologic TypeNeoplasmsIntestinal NeoplasmsGastrointestinal NeoplasmsDigestive System NeoplasmsNeoplasms by SiteDigestive System DiseasesGastrointestinal DiseasesColonic DiseasesIntestinal DiseasesRectal DiseasesTreatment Adherence and ComplianceHealth BehaviorBehavior

Study Officials

  • Nabil Mohammad Azmi, Doctor of General Surgery

    Faculty of Medicine, The National University of Malaysia

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Nabil Mohammad Azmi, Doctor in General Surgery

CONTACT

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
CARE PROVIDER
Masking Details
Endoscopist performing the colonoscopy will be masked
Purpose
DIAGNOSTIC
Intervention Model
PARALLEL
Model Details: Prospective, single-masked, randomized control trial
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
General Surgeon & Lecturer

Study Record Dates

First Submitted

March 15, 2025

First Posted

April 1, 2025

Study Start

April 1, 2025

Primary Completion

February 2, 2026

Study Completion

February 2, 2026

Last Updated

April 1, 2025

Record last verified: 2025-03

Data Sharing

IPD Sharing
Will share

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

Shared Documents
STUDY PROTOCOL, ICF, CSR
Time Frame
APRIL 2025 - FEBRUARY 2026

Locations