{"title":"Relationship Between Individual Innovativeness Levels and Attitudes Toward Artificial Intelligence Among Nursing and Midwifery Students.","authors":"Şeyma Kilci Erciyas, Ebru Cirban Ekrem, Elif Keten Edis","doi":"10.1097/CIN.0000000000001170","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cin-Computers Informatics Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CIN.0000000000001170","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
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.
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.