Nurses' Personality Traits as a Mediator between their Artificial Intelligence Perception and Innovative Work Behaviors
Year: 2025
Type: article
Study design: Observational Study
Abstract: • Background: Personality traits and technology may affect how well nursing utilize their abilities and strategies to achieve their objectives and innovations at the place of work. So, nurses' personalities have a great influence on their creativity and innovative behavior involved using artificial intelligence. The study aimed to assess the nurses' personality traits as a mediator between their artificial intelligence perception and innovative work behaviors. Research design: A descriptive correlational research design was applied. Setting: The research was conducted on different hospitals in Minia City. Sample: A Purposive sample with a total number of 329 nurses. Tools of data collection: Three tools were used, 1st tool was Big Five Inventory, 2nd tool was Perception of Artificial Intelligence Scale and the 3rd tool was Innovative Work Behaviors scale. Results Revealed that the highest mean scores of nurses were for conscientiousness traits, followed by openness and agreeableness personality. Moreover, under fifty percent of nurses had a high as well as moderate level of perception of artificial intelligence. Also, approximately three quarters of nurses had high level of innovative work behaviors. Conclusion: There was a significant positive correlation between nurses' total perception of artificial intelligence as well as their innovative work behaviors and all dimensions of personality traits except neuroticism dimension. Recommendations: Training programs should emphasize the benefits and practical applications of AI in nursing to alleviate fears and resistance, particularly among those with high neuroticism personality.
Authors: Shherifa Rabea Mohamed, Tahany Shaaban Mohammed, Ebtsam Ahmed, Heba Dacrory
Institution: Minia University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $340
OpenAlex ID: W4408625494