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Nursing Students’ Perception and Attitudes toward Utilization of Artificial Intelligence in Health Care

Author

Listed:
  • Samira Ahmed Alsenany
  • Obay A. AlMaraira
  • Suzan El-Said Mansour

Abstract

The aim of the study was to evaluate nursing students’ perception and attitudes toward utilization of Artificial Intelligence in Health care. Descriptive design was applied. The study was carried out at Vision Medical College, Jeddah. KSA. Two hundred and six students registered in the nursing program were included in the study by using convenience sampling. Three instruments were employed to gather data, Self-Administered questionnaire, covering student nurses' demographic characteristics, Questionnaire to assess the perception and attitudes regarding artificial intelligence. Results revealed that majority of participants (79.6%) were familiar with artificial intelligence, and their attitudes toward using it were significantly correlated with their demographic characteristics (living location, educational attainment, self-assessment of technological competence, and familiarity with artificial intelligence). Also, it showed that 64% of the participants had a positive attitude regarding using artificial intelligence. Both the attitude and perception scales had mean scores of 3.29±0.76 and 3.43±0.69. Likewise, a statistically significant positive correlation (β = 0.855, p< 0.001) showed between the students’ perception and attitudes. Conclusion. The current study concluded that the students most likely held positive attitudes and had a favorable perception toward utilization of artificial intelligence in health care. Arranging frequent workshops and training sessions for healthcare personnel and student nurses to enhance their knowledge about artificial intelligence and its developments.

Suggested Citation

  • Samira Ahmed Alsenany & Obay A. AlMaraira & Suzan El-Said Mansour, 2024. "Nursing Students’ Perception and Attitudes toward Utilization of Artificial Intelligence in Health Care," Edelweiss Applied Science and Technology, Learning Gate, vol. 8(6), pages 663-670.
    • Handle: RePEc:ajp:edwast:v:8:y:2024:i:6:p:663-670:id:2138
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