Adopting Artificial Intelligence (ai) in Nursing Care: the Interplay of Attitudes, Self-belief, and Clinical Reasoning at Nishtar Hospital, Multan
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Artificial intelligence (AI) is increasingly influencing clinical practice by enhancing diagnostic precision, improving patient safety, and facilitating informed decision-making. However, successful adoption in nursing depends on both professional attitudes toward AI and competencies such as creative self-efficacy and clinical reasoning. Aim: This study examined the relationship between nurses’ AI-related attitudes, creative self-efficacy, and clinical reasoning performance at Nishtar Hospital, Multan. Methods: A descriptive cross-sectional design was used with 130 nurses working in intensive and critical care units. Three validated instruments were applied: The Nurses’ AI Attitude Scale, the Creative Self-Efficacy Scale, and the Clinical Reasoning Competency Scale. Data were analyzed using SPSS 26 with descriptive, correlational, and regression statistics. Results: Most participants showed favorable attitudes toward AI and strong clinical reasoning abilities, while moderate levels of creative self-efficacy were observed. AI-related attitudes correlated positively with creative self-efficacy (r = 0.53, p < 0.001) and clinical reasoning (r = 0.71, p < 0.001). Regression models indicated AI attitudes explained 35% of the variance in creative self-efficacy and 54% in clinical reasoning. Educational level and years of professional experience had a significant influence on outcomes. Conclusion: Nurses’ positive perceptions of AI enhance their creative confidence and reasoning performance. Hospital administrators and educators should prioritize AI-oriented training and supportive work environments to build confidence in AI adoption and strengthen clinical judgment.
DOI: 10.62019/b74f5z64
Authors: Dawood Masih, Anum Pervaiz, Sumbal Rafiq, Nabila Parosh, Hina Zahra
Institutions: Nishtar Medical College and Hospital, Al-Sabah Hospital
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4414584261
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