Relationship Between Individual Innovativeness Levels and Attitudes Toward Artificial Intelligence Among Nursing and Midwifery Students.

IF 1.3 4区 医学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cin-Computers Informatics Nursing Pub Date : 2024-11-01 DOI:10.1097/CIN.0000000000001170
Şeyma Kilci Erciyas, Ebru Cirban Ekrem, Elif Keten Edis
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Abstract

The aim of this study is to explore the connection between individual innovativeness levels and attitudes toward artificial intelligence among nursing and midwifery students. Data were collected from 500 nursing and midwifery students studying at a university in Türkiye. The data gathered between November and December 2023 involved a Personal Information Form, the Individual Innovation Scale, and the General Attitudes toward Artificial Intelligence Scale. Data analysis used descriptive statistics, independent-samples t test, analysis of variance, Bonferroni test, and logistic regression models. Students' average Individual Innovativeness Scale score was 59.47 ± 7.23. Consequently, it was determined that students' individual innovativeness levels were inadequate, placing them in the questioning group. Students demonstrated positive attitudes toward artificial intelligence, with General Attitudes toward Artificial Intelligence Scale-positive scores at a good level (42.67 ± 7.10) and negative attitudes at an average level (24.08 ± 5.81). A significant, positive relationship was found between Individual Innovation Scale and General Attitudes toward Artificial Intelligence Scale total scores ( P < .001). The individual innovation level of students proved to be a significant predictor of attitudes toward artificial intelligence ( P < .001). Students' individual innovativeness levels positively influence their attitudes toward artificial intelligence. However, it was identified that students' individual innovativeness levels are not sufficient and require improvement.

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护理和助产专业学生的个人创新水平与对人工智能的态度之间的关系。
本研究旨在探讨护理和助产专业学生的个人创新水平与对人工智能的态度之间的联系。数据收集对象为 500 名在土耳其一所大学就读的护理和助产专业学生。数据收集时间为 2023 年 11 月至 12 月,涉及个人信息表、个人创新量表和对人工智能的总体态度量表。数据分析采用了描述性统计、独立样本 t 检验、方差分析、Bonferroni 检验和逻辑回归模型。学生的个人创新能力量表平均得分为 59.47±7.23 分。因此,确定学生的个人创新能力水平不足,将他们归入质疑组。学生对人工智能表现出积极的态度,对人工智能的一般态度量表的积极得分处于良好水平(42.67 ± 7.10),消极态度处于一般水平(24.08 ± 5.81)。个体创新量表与对人工智能的总体态度量表总分之间存在明显的正相关关系(P < .001)。事实证明,学生的个人创新水平对人工智能态度有重要的预测作用(P < .001)。学生的个人创新水平对他们对人工智能的态度有积极影响。然而,研究发现,学生的个人创新水平还不够充分,需要改进。
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来源期刊
Cin-Computers Informatics Nursing
Cin-Computers Informatics Nursing 工程技术-护理
CiteScore
2.00
自引率
15.40%
发文量
248
审稿时长
6-12 weeks
期刊介绍: For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.
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