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CTRI Number  CTRI/2025/10/095667 [Registered on: 07/10/2025] Trial Registered Prospectively
Last Modified On: 30/04/2026
Post Graduate Thesis  No 
Type of Trial  Observational 
Type of Study   Cross Sectional Study 
Study Design  Other 
Public Title of Study   How Doctors and Nurses Accept AI Tools in Healthcare 
Scientific Title of Study   Acceptability of Clinical Care Enhanced by Predictive Technologies - AI Evaluating Doctors’ and Nurses’ Acceptance of AI-Driven Clinical Tools Using the Unified Theory of Acceptance and Use of Technology (UTAUT) 
Trial Acronym   
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Dr Sushila Kataria 
Designation  Vice chairman 
Affiliation  Medanta The Medicity 
Address  Room 30,Department of Internal Medicine,9th floor OPD,Medanta The Medicity, CH Baktawar Singh Rd, Medicity, Islampur Colony, Sector 38, Gurugram

Gurgaon
HARYANA
122001
India 
Phone  09818828078  
Fax    
Email  Sushila.Kataria@medanta.org  
 
Details of Contact Person
Scientific Query
 
Name  Dr Sushila Kataria 
Designation  Vice chairman 
Affiliation  Medanta The Medicity 
Address  Room 30,Department of Internal Medicine,9th floor OPD,Medanta The Medicity, CH Baktawar Singh Rd, Medicity, Islampur Colony, Sector 38, Gurugram


HARYANA
122001
India 
Phone  09818828078  
Fax    
Email  Sushila.Kataria@medanta.org  
 
Details of Contact Person
Public Query
 
Name  Dr Sushila Kataria 
Designation  Vice chairman, Department of Internal Medicine 
Affiliation  Medanta The Medicity 
Address  Room 30,Department of Internal Medicine,9th floor OPD,Medanta The Medicity, CH Baktawar Singh Rd, Medicity, Islampur Colony, Sector 38, Gurugram


HARYANA
122001
India 
Phone  09818828078  
Fax    
Email  Sushila.Kataria@medanta.org  
 
Source of Monetary or Material Support  
Medanta – The Medicity CH Baktawar Singh Road, Sector 38, Gurugram, Haryana 122001 India 
 
Primary Sponsor  
Name  Medanta- The Medicity 
Address  CH Baktawar Singh Road, Sector 38 Near Bakhtawar Chowk Gurugram, Haryana 122001 India 
Type of Sponsor  Private hospital/clinic 
 
Details of Secondary Sponsor  
Name  Address 
NIL  NIL 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 1  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Dr Sushila Kataria  Medanta The Medicity  Department of Internal Medicine, CH Baktawar Singh Rd, Medicity, Islampur Colony, Sector 38, Gurugram
Gurgaon
HARYANA 
09818828078

Sushila.Kataria@medanta.org 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Medanta Institutional Ethics Committee  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Healthy Human Volunteers  Not Applicable – Healthcare professionals’ perceptions of AI in clinical decision-making 
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  Nil  Nil 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  50.00 Year(s)
Gender  Both 
Details  MBBS doctors and registered nurses working full-time.
Minimum 1 year of clinical experience.
Willingness to give informed consent.
 
 
ExclusionCriteria 
Details  Healthcare workers in administrative/non-clinical roles.
Those unwilling to participate or incomplete responses.
 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
Mean scores and proportions of high responses across the four UTAUT constructs (Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions) among doctors and nurses.  At baseline (single time point – during questionnaire administration) 
 
Secondary Outcome  
Outcome  TimePoints 
• Comparison of mean UTAUT scores between professional groups (doctors vs. nurses) using tests, as appropriate based on data distribution.
• Correlation analyses between UTAUT construct scores and independent variables such as age, years of experience, prior AI/HIS exposure, and AI training.
• Descriptive statistics (frequencies, percentages) for reported barriers and enablers to AI adoption.
• Thematic content analysis of open-ended responses to identify qualitative insights and recurring themes, mapped to the UTAUT domains.
 
At baseline (single time point – during questionnaire administration) 
 
Target Sample Size   Total Sample Size="240"
Sample Size from India="240" 
Final Enrollment numbers achieved (Total)= "0"
Final Enrollment numbers achieved (India)="0" 
Phase of Trial   N/A 
Date of First Enrollment (India)   15/10/2025 
Date of Study Completion (India) Date Missing 
Date of First Enrollment (Global)  Date Missing 
Date of Study Completion (Global) Date Missing 
Estimated Duration of Trial   Years="0"
Months="5"
Days="0" 
Recruitment Status of Trial (Global)
Modification(s)  
Not Yet Recruiting 
Recruitment Status of Trial (India)  Completed 
Publication Details
Modification(s)  
Kataria S, Aggarwal R, Ardhapure A, et al. (February 22, 2026) Determinants of AI Adoption in Healthcare: Insights From a Unified Theory of Acceptance and Use of Technology (UTAUT) Study Among Doctors and Nurses in a Tertiary Care Hospital in North India. Cureus 18(2): e104086. doi:10.7759/cureus.104086 
Individual Participant Data (IPD) Sharing Statement

Will individual participant data (IPD) be shared publicly (including data dictionaries)?  

Response - NO
Brief Summary   The study aims to evaluate the acceptance of AI-based clinical decision-making tools among doctors and nurses in North India using the UTAUT framework.
We hypothesize that healthcare professionals with greater knowledge and favorable attitudes toward AI are more likely to adopt and utilize AI tools in clinical practice. 
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