Assessing Knowledge, Attitudes, Trust, Perceived Usefulness, and Barriers to Using Artificial Intelligence (AI) in Gastroenterology Among Clinicians and Patients

June 21, 2026 updated by: Amr Hamed, Sohag University

-Introduction Innovative technological developments in medical image interpretation, diagnostic support, risk assessment for different illnesses, outcome prognostication, and, in some cases, treatment recommendation have all been made possible by artificial intelligence (AI) (Goh et. al., 2024).

The number of machine learning and artificial intelligence (AI) applications intended to enhance the caliber, efficacy, and efficiency of our clinical practice has increased dramatically in gastroenterology over the last 10 years.

(Leggett et. al., 2024). Research on clinicians' acceptance and confidence in AI is becoming more and more crucial. This is due to the perception that healthcare workflow integration requires trust and acceptance of AI technology. Numerous studies have already shown that trust is one of the key factors influencing the use of AI in healthcare. Although there is growing clinical evidence of AI's accuracy in diagnosis and prognosis, more focus needs to be placed on physicians' level of acceptance and trust (Goh et. al., 2024).

More and more patients want to take a more active role in their medical care. As a result, patients' usage of digital health care tools-both online and mobile-has skyrocketed. As of right now, it's unclear if people use symptom checkers to enhance medical guidance or if they use them to replace in-person medical care by only seeking it when directed by AI (Meyer et. al., 2022).

-Aim of the work: Primary: To measure knowledge, attitudes, trust, perceived usefulness, risk perception, and willingness to use AI in gastroenterology among (a) gastroenterology clinicians and (b) GI patients.

Secondary:

  • To compare perspectives between clinicians and patients.
  • To explore factors associated with higher acceptance/trust (age, prior AI exposure, digital literacy, years of practice).

Patient and Methods:

We will conduct a cross-sectional study. We will conduct a survey using a structured questionnaire for two parallel target populations: clinicians and patients. The questionnaire will be created by a multidisciplinary team (authors) with expertise in patient experience, cognitive psychology, psychometrics, internal medicine, and diagnostic errors. Items in the questionnaire for testing risk perception, acceptance, and trust were adapted from various other studies [Hah et. al., 2021; Kader et. al., 2022; Goh et. al., 2024]

  • Participants

    • Clinicians: - practicing gastroenterologists.

  • Ability and willingness to sign the consent form

    • Patients: Inclusion: -adult patients (≥18) attending GI clinics/units (inpatient or outpatient), cognitively able to complete questionnaire

  • Ability and willingness to sign the consent form

  • Ethical consideration:

    • The study will be approved by the local ethical committee.
    • Informed consent will be obtained from patients.

    • voluntary participation, confidentiality, right to withdraw. Questionnaire Development

      1. Item generation: Based on literature and brief interviews with 8-10 clinicians and 8-10 patients.
      2. Content validity: Review by a small expert panel (3-5 experts).
      3. Cognitive testing: 10-15 participants from each group to ensure clarity and comprehension.
      4. Pilot testing: Small sample (clinicians: ~50; patients: ~100) to refine items.

  • Questionnaire Domains

    • Demographics
    • Knowledge (self-rated ± short objective items)
    • Attitudes toward AI in GI
    • Trust & risk perception
    • Perceived usefulness
    • Willingness to use AI
    • Barriers & facilitators
  • Data Collection:

Clinicians: Online survey (Google Forms). Patients: Paper or tablet-based survey in clinics. Consent obtained before participation; responses are anonymous.

Statistical analysis:

Statistical analysis will be conducted by SPSS. Parametric data will be expressed as mean ± standard deviation (SD), such as age, and will be evaluated statistically by means of Student t-test, while non-parametric data will be expressed as proportions, like male and female, and will be analyzed using chi-square. A p-value < 0.05 will be considered significant.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

100

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

N/A

Sampling Method

Probability Sample

Study Population

  • Clinicians: - practicing gastroenterologists.

    • Ability and willingness to sign the consent form
  • Patients:

Inclusion: -adult patients (≥18) attending GI clinics/units (inpatient or outpatient), cognitively able to complete questionnaire

  • Ability and willingness to sign the consent form

Description

Inclusion Criteria:

  • Inclusion: -adult patients (≥18) attending GI clinics/units (inpatient or outpatient), cognitively able to complete questionnaire
  • Ability and willingness to sign the consent form

Exclusion Criteria:

-

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

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Patients
Other: Questionnaire
Questionnaire
Clinicians
Other: Questionnaire
Questionnaire

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Knowledge of Artificial Intelligence in Gastroenterology Questionnaire Score
Time Frame: 1 day

Title: Knowledge of Artificial Intelligence in Gastroenterology Questionnaire Score

Description: Participants' knowledge regarding applications of AI in gastroenterology, measured using the Knowledge Domain of the AI in Gastroenterology Questionnaire.

Unit of Measure: Total knowledge score (points) Total score ranges from 5-25, with higher scores indicating greater knowledge
1 day

Collaborators and Investigators

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

Sponsor

Sohag University

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)

June 10, 2026

Primary Completion (Estimated)

December 1, 2026

Study Completion (Estimated)

December 1, 2026

Study Registration Dates

First Submitted

June 4, 2026

First Submitted That Met QC Criteria

June 21, 2026

First Posted (Actual)

June 25, 2026

Study Record Updates

Last Update Posted (Actual)

June 25, 2026

Last Update Submitted That Met QC Criteria

June 21, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Soh-Med-26-4-4PD

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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