Date of Award

10-13-2025

Degree Type

Thesis

Degree Name

MSc in Nursing

First Advisor

Dr Syeda Naghma Rizvi

Second Advisor

Ms. Shamsa Samani

Third Advisor

Ms. Shanaz Cassum

Department

School of Nursing and Midwifery, Pakistan

Abstract

Background: Artificial Intelligence (AI) is transforming healthcare by improving diagnostic accuracy, decision-making, and patient management, particularly in cardiology. However, nurses’ readiness to adopt AI remains crucial for its effective integration into clinical practice. Despite global progress, limited evidence exists from low -and middleincome countries (LMICs) like Pakistan, where disparities in infrastructure and training may affect technology adoption.
Purpose: This study assessed the levels of AI readiness among cardiac nurses in a tertiary care cardiac hospital in Karachi, Pakistan. It examined the influence of demographic factors such as age, gender, education, and professional experience on AI readiness and explored nurses’ identified educational and training needs for AI utilization in cardiac care.
Methodology: A descriptive-analytical, cross-sectional design was used. Data were collected from 316 cardiac nurses through a self-administered questionnaire comprising the validated Medical Artificial Intelligence Readiness Scale (MAIRS) and a researcher-developed section on educational and training needs. Descriptive statistics, t-tests, one-way ANOVA, Pearson’s correlation, and multiple linear regression analyses were performed using SPSS version 26. Ethical approvals were obtained from Aga Khan University and the participating institution.
Results: The overall mean AI readiness score was 70 (range 22-110), indicating readiness near the moderate level. Among participants, 25% showed poor, 25.3% low, 25.9% moderate, and 23.7% high readiness. Younger nurses and those with fewer years of experience exhibited higher readiness (r = -0.31, p < 0.001; r = -0.38-p < 0.001). Educational qualification was a significant predictor (F (2,313) = 13.18, p < 0.001), with graduate-prepared nurses scoring highest. Most nurses identified the need for foundational AI knowledge (67.1%), practical skills training (64.6%), and ethical awareness (79.3%); 84.2% preferred hands-on workshops.
Conclusion: Cardiac nurses demonstrated moderate readiness for AI integration, with gaps in technical competence and cognitive understanding. Findings highlight the need for structured AI education, continuous professional development, and institutional support to enhance nurses’ digital competencies in Pakistan’s healthcare system.

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1

Last Page

158

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