Ae Ran Kim, Ae Young Park, Soojin Song, Jeong Hee Hong, Kyeongsug Kim
{"title":"A Microlearning-Based Self-directed Learning Chatbot on Medication Administration for New Nurses: A Feasibility Study.","authors":"Ae Ran Kim, Ae Young Park, Soojin Song, Jeong Hee Hong, Kyeongsug Kim","doi":"10.1097/CIN.0000000000001119","DOIUrl":null,"url":null,"abstract":"<p><p>New nurses must acquire accurate knowledge of medication administration, as it directly affects patient safety. This study aimed to develop a microlearning-based self-directed learning chatbot on medication administration for novice nurses. Furthermore, the study had the objective of evaluating the chatbot feasibility. The chatbot covered two main topics: medication administration processes and drug-specific management, along with 21 subtopics. Fifty-eight newly hired nurses on standby were asked to use the chatbot over a 2-week period. Moreover, we evaluated the chatbot's feasibility through a survey that gauged changes in their confidence in medication administration knowledge, intrinsic learning motivation, satisfaction with the chatbot's learning content, and usability. After using the chatbot, participants' confidence in medication administration knowledge significantly improved in all topics ( P < .001) except \"Understanding a concept of 5Right\" ( P = .077). Their intrinsic learning motivation, satisfaction with the learning content, and usability scored above 5 out of 7 in all subdomains, except for pressure/tension (mean, 2.12; median, 1.90). They scored highest on ease of learning (mean, 6.69; median, 7.00). A microlearning-based chatbot can help new nurses improve their knowledge of medication administration through self-directed learning.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":"343-353"},"PeriodicalIF":1.3000,"publicationDate":"2024-05-01","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.0000000000001119","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
New nurses must acquire accurate knowledge of medication administration, as it directly affects patient safety. This study aimed to develop a microlearning-based self-directed learning chatbot on medication administration for novice nurses. Furthermore, the study had the objective of evaluating the chatbot feasibility. The chatbot covered two main topics: medication administration processes and drug-specific management, along with 21 subtopics. Fifty-eight newly hired nurses on standby were asked to use the chatbot over a 2-week period. Moreover, we evaluated the chatbot's feasibility through a survey that gauged changes in their confidence in medication administration knowledge, intrinsic learning motivation, satisfaction with the chatbot's learning content, and usability. After using the chatbot, participants' confidence in medication administration knowledge significantly improved in all topics ( P < .001) except "Understanding a concept of 5Right" ( P = .077). Their intrinsic learning motivation, satisfaction with the learning content, and usability scored above 5 out of 7 in all subdomains, except for pressure/tension (mean, 2.12; median, 1.90). They scored highest on ease of learning (mean, 6.69; median, 7.00). A microlearning-based chatbot can help new nurses improve their knowledge of medication administration through self-directed learning.
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.