Perceived impact of artificial intelligence on nursing practice and patient care delivery among nurses at Federal Medical Centre, Idi Aba Abeokuta Ogun state
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ID: 309413
2025
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Abstract
Artificial intelligence (AI) is a field of computer science that allows machines to perform some nursing tasks and allowing the delivery of more individualized and evidence-based Nursing care. This study assessed the impact of Artificial intelligence on nursing practice and patient care delivery at Federal Medical Center, Idi-Aba Abeokuta Ogun State, Nigeria. A descriptive cross-sectional was used to assess this study with the population consist of 354 registered nurses and 188 respondents was through Taro Yamane's Formula and simple random sampling technique. A validated and self-developed structured questionnaire was constructed to elicit information on research specific objectives, instrument's internal consistency were measured using Cronbach’s Alpha of not less than 0.65 for each section. The distributed questionnaire was analyzed using SPSS 26.0 version. The result showed revealed 176(93.6%) of the Nurses were female while about 123(65.4%) of the nurses have 1 to 10 years experiences in clinical settings. The finding showed that majority 113 (60.1%) of the Nurses have good knowledge of artificial intelligence to provide patient care. Large proportion 125(66.5%) of the respondents have positive attitudes towards Artificial Intelligence and about 125(66.5%) of the respondents claimed that Artificial Intelligence have positive impact in providing patient care. Conclusively, majority 100(53.2%) of the clinical Nurses agreed that lack of sufficient technological gadgets can confine the usage of artificial intelligence in some clinical settings. The study recommended that the healthcare providers and policymakers should support the implementation of policies that facilitate the deployment of Artificial intelligence in healthcare delivery.
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| Authors | Opeyemi Hamdallah Abolore |
| Journal | Aminu Kano Academic Scholars Association Multidisciplinary Journal |
| Year | 2025 |
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| Keywords | Keywords not found |
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