When AI intervene clinical decision-making: the influence of organisational support, cognitive load, and perceived autonomy

Isparan, Shanthi and Ai-Na, Seow (2025) When AI intervene clinical decision-making: the influence of organisational support, cognitive load, and perceived autonomy. Malaysia Journal of Invention and Innovation, 4 (3): 4. pp. 33-39. ISSN 2976-2170

Official URL: https://journal.academicapress.org/aps/index.php/m...

Identification Number (DOI): 10.64382/mjii.v4i3.112

Abstract

The integration of Artificial Intelligence (AI) in healthcare holds the potential to optimise clinical decisionmaking. However, the effectiveness of AI intervention in clinical decision-making can influence the ability of healthcare professionals to effectively process and apply AI-generated recommendations. This research examines the influence of organisational support (OS) on cognitive load (CL) and its impact on the effectiveness of AI-assisted clinical decision-making. The study further investigates the mediating role of cognitive load and explores the moderating effect of perceived autonomy (PA). Organisational Support Theory (OST), Cognitive Load Theory (CLT), and Self-Determination Theory (SDT) are used to support these dynamics. The targeted respondents are medical doctors in Malaysia, and data are analysed using Partial Least Squares Structural Equation Modeling (PLSSEM). It is expected that the increased OS will reduce CL, leading to improved AI-assisted clinical decision-making, with PA strengthening this relationship. The findings offer actionable insights for healthcare institutions, suggesting strategies to strengthen AI implementation, streamline workflows, and enhance clinical decision-making.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Isparan, Shanthi
shanthi98@1utar.my
Ai-Na, Seow
seowan@utar.edu.my
Subjects: H Social Sciences > HM Sociology > Social structure
R Medicine > R Medicine (General) > Medical technology
Divisions: Universiti Teknologi MARA, Kelantan > Machang Campus > Faculty of Information Management
Journal or Publication Title: Malaysia Journal of Invention and Innovation
ISSN: 2976-2170
Volume: 4
Number: 3
Page Range: pp. 33-39
Related URLs:
Keywords: Artificial intelligence, Cognition and learning, Medical personnel
Date: 5 May 2025
URI: https://ir.uitm.edu.my/id/eprint/128911
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