| CTRI Number |
CTRI/2024/10/075937 [Registered on: 25/10/2024] Trial Registered Prospectively |
| Last Modified On: |
25/10/2024 |
| Post Graduate Thesis |
No |
| Type of Trial |
Observational |
|
Type of Study
|
Cross Sectional Study |
| Study Design |
Other |
|
Public Title of Study
|
AI Chatbots in Indian Healthcare – Improving Patient Care, Ethical Issues, and Challenges |
|
Scientific Title of Study
|
Artificial Intelligence Chatbots in Indian Healthcare System and Therapeutics – Transforming Patient Experience, Ethical Implications and The Challenges Faced |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Akshay Balakrishna |
| Designation |
Junior resident |
| Affiliation |
Kasturba Medical College, Manipal |
| Address |
Department of Pharmacology
Ground floor Physiology Pharmacology Building
Kasturba Medical College Manipal
Madhav Nagar
Manipal
Udupi
KARNATAKA
576104
India |
| Phone |
08747828873 |
| Fax |
|
| Email |
akshay.bala1996@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Dr Jeffrey Pradeep Raj |
| Designation |
Associate Professor |
| Affiliation |
Kasturba Medical College Manipal |
| Address |
Division of Clinical Pharmacology
Department of Pharmacology
Ground floor Physiology Pharmacology Building
Kasturba Medical College Manipal
Madhav Nagar
Manipal
Udupi
KARNATAKA
576104
India |
| Phone |
8095464464 |
| Fax |
|
| Email |
jpraj.m07@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Dr Jeffrey Pradeep Raj |
| Designation |
Associate Professor |
| Affiliation |
Kasturba Medical College Manipal |
| Address |
Division of Clinical Pharmacology
Department of Pharmacology
Ground floor Physiology Pharmacology Building
Kasturba Medical College Manipal
Madhav Nagar
Manipal
KARNATAKA
576104
India |
| Phone |
8095464464 |
| Fax |
|
| Email |
jpraj.m07@gmail.com |
|
|
Source of Monetary or Material Support
|
| Kasturba Medical College Manipal
Madhav Nagar
Manipal
Karnataka 576104 |
|
|
Primary Sponsor
|
| Name |
Kasturba Medical College Manipal |
| Address |
Madhav Nagar
Manipal-576104
Karnataka
India |
| Type of Sponsor |
Private medical college |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Akshay Balakrishna |
Kasturba Medical College, Manipal |
Department of Pharmacology
Ground Floor Physiology Pharmacology Building
Kasturba Medical College Manipal
Madhav nagar
Manipal - 576104
Udupi
KARNATAKA |
08747828873
akshay.bala1996@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Kasturba Medical college and Kasturba Hospital, Institutional Ethics Comittee-2 |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Healthy Human Volunteers |
Healthy human volunteers |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Nil |
| Comparator Agent |
Nil |
Nil |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
99.00 Year(s) |
| Gender |
Both |
| Details |
1) Indian healthcare professionals of any biological sex over the age of 18 yrs and above.
2) Willing to give written informed consent.
|
|
| ExclusionCriteria |
| Details |
1) Incompletely filled forms
2) Those who failed to answer the trap question (The trap question would be a repeat of one of the previous questions. Any discordance in the answer option chosen will be considered as failed).
3) Participants who have been working abroad in the last 6 months.
|
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| The proportion of individuals using AI chatbots |
Baseline |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| Attitudes, perceptions and challenges in the use of AI |
Baseline |
|
|
Target Sample Size
|
Total Sample Size="400"
Sample Size from India="400"
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" |
|
Phase of Trial
|
N/A |
|
Date of First Enrollment (India)
|
07/11/2024 |
| Date of Study Completion (India) |
Applicable only for Completed/Terminated trials |
| Date of First Enrollment (Global) |
Date Missing |
| Date of Study Completion (Global) |
Applicable only for Completed/Terminated trials |
|
Estimated Duration of Trial
|
Years="1"
Months="0"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Applicable |
| Recruitment Status of Trial (India) |
Open to Recruitment |
|
Publication Details
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
This study explores the transformative potential of AI chatbots in the Indian healthcare system, emphasizing their ability to enhance patient care, streamline services, and address the challenges of accessibility in a resource-constrained environment. The 24/7 availability of chatbots can help manage routine queries and alleviate the workload of healthcare professionals. However, ethical concerns such as patient data privacy, accuracy of medical advice, and varying levels of technology acceptance across diverse populations are also addressed. The primary objective is to estimate the proportion of individuals using AI chatbots in routine patient care, while secondary objectives focus on understanding attitudes, perceptions, and challenges related to AI use in healthcare. The study employs a cross-sectional online survey design, requiring approval from the Institutional Ethics Committee and adherence to ethical guidelines. It includes Indian healthcare professionals aged 18 and above who provide informed consent, with an estimated sample size of 400 participants. Data collection will occur through digital questionnaires distributed via various online platforms. Statistical analyses will summarize demographics and perceptions, while further analysis will identify predictors of AI usage. Ensuring participant confidentiality is paramount, with no personal identifiers collected. Ultimately, the study aims to provide insights into how AI chatbots can improve patient interactions, access to medical information, and overall healthcare experiences in India, while examining ethical implications and identifying challenges in integrating chatbots into existing frameworks, leading to actionable recommendations for optimizing their use in healthcare settings |