Exploring the Effectiveness of AI Generative Models for Diabetic Patients

June 2, 2023 updated by: Pakistan Council of Scientific and Industrial Research
We plan to explore the usability of Generative AI-Chatbot for Diabetic Patient

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Diabetes is rapidly spreading, affecting a significant number of adults, with a staggering total of 537 million diabetic individuals. This condition gives rise to various complications that can lead to diabetic retinopathy, foot ulcers, cardiac problems, and kidney damage. However, many of these complications can be mitigated by providing patients with accurate information concerning their diet, stress management, and weight control.

The recent advancements in Generative Artificial Intelligence-based chatbots have demonstrated their efficacy as intelligent assistants across various aspects of human life. In this study, we aim to assess the effectiveness of these Language Models in assisting patients. Our research plan entails the interaction between patients and chatbots like ChatGPT, both with and without human support, followed by evaluations of these interactions by specialists. Additionally, we will gather feedback from patients regarding their experiences and perceptions of the chatbot interactions.

Study Type

Observational

Enrollment (Estimated)

300

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

Study Locations

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

No

Sampling Method

Non-Probability Sample

Study Population

People affected with diabetes in Pakistan

Description

Inclusion Criteria:

  • Present physically in Pakistan
  • Adults (18 years or older)
  • Diabetic Patient

Exclusion Criteria:

  • Adults unable to consent
  • Individuals who are not yet adults (infants, children, teenagers)
  • Prisoners

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
Intervention
Patients will be provided access to Chatbot to enquire their querries regarding diabetic complications.
Behavioral: Exploring AI-Chatbot
All participants will be provided access to AI-Chatbot and will be asked to enquire their daily life problems related to diabetes. They will also be asked to review the replies of the Chatbot after their interaction.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Usability of the Chatbot for diabetic patient
Time Frame: One time
To assess the usability of the Chatbot, we will employ the mHealth App Usability Questionnaire (MAUQ) to gather feedback from patients following their interaction. Our study will utilize Table 4 of this questionnaire, which consists of three sections: ease of use, interface, and satisfaction and usefulness. Specifically, we will focus our evaluation on 10 out of the 18 questions presented in this table. The selected questions are S1, S2, S6, S7, S9, S11, S12, S13, S14, and S18. Patients will provide their responses on a scale of 1 to 5, where "1" indicates very poor and "5" denotes very good.
One time
Internet Speed
Time Frame: One time
Minimum downloading speed of internet will be measured during the chat. This will be recorded in Mega bits per second.
One time

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Analyzing Chat response generated by AI Chatbot
Time Frame: One time

Likert scale will be used to evaluate the chat response of Chatbot. The following parameters will be evaluated by the specialists for each response namely Clear, Complete and Correct. Clear and Completeness will be evaluated on a range of 1-5, where 1 means poor quality and 5 means very good quality response.

The correctness of each response will be further analyzed as Safe and latest. It will be evaluated in binary terms i.e. Yes or No.
One time

Collaborators and Investigators

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

Sponsor

Pakistan Council of Scientific and Industrial Research

Investigators

  • Principal Investigator: Ghulam Mustafa, Pakistan Council of Scientific and Industrial Research

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 (Actual)

January 5, 2023

Primary Completion (Estimated)

December 30, 2024

Study Completion (Estimated)

December 31, 2026

Study Registration Dates

First Submitted

March 9, 2023

First Submitted That Met QC Criteria

May 22, 2023

First Posted (Actual)

May 31, 2023

Study Record Updates

Last Update Posted (Actual)

June 5, 2023

Last Update Submitted That Met QC Criteria

June 2, 2023

Last Verified

June 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AI Chatbot Evaluation

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

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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