Exploring the Effectiveness of AI Generative Models for Diabetic Patients

Recruiting

• Conditions: Diabetic Retinopathy; Diabetes Mellitus, Type 2; Diabetes
• Interventions: Behavioral: Exploring AI-Chatbot

• Registration Number: NCT05883072
• Lead Sponsor: Pakistan Council of Scientific and Industrial Research

Brief Summary

We plan to explore the usability of Generative AI-Chatbot for Diabetic Patient

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 Timeline

• Study Start: 2023-01-05
• Study First Submitted: 2023-03-09
• Study First Submitted QC: 2023-05-22
• Study First Posted: 2023-05-31
• Status Verified: 2023-06
• Last Update Submitted: 2023-06-02
• Last Update Posted: 2023-06-05
• Primary Completion: 2024-12-30
• Study Completion: 2026-12-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 300

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 & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Intervention	Exploring AI-Chatbot	Patients will be provided access to Chatbot to enquire their querries regarding diabetic complications.

Primary Outcome Measures

Name	Time	Method
Usability of the Chatbot for diabetic patient	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.
Internet Speed	One time	Minimum downloading speed of internet will be measured during the chat. This will be recorded in Mega bits per second.

Secondary Outcome Measures

Name	Time	Method
Analyzing Chat response generated by AI Chatbot	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.

Trial Locations

Locations (1)

CDLE, PCSIR Lbas Complex; 🇵🇰 Karachi, Sindh, Pakistan