Cin-Computers Informatics Nursing最新文献

{"title":"Adaptation of a Synergy Model-based Patient Acuity Tool for the Electronic Health Record: Proof of Concept.","authors":"Mei Lin Chen-Lim, Halley Ruppel, Walter Faig, Eloise Flood, Daniel Mead, Darcy Brodecki","doi":"10.1097/CIN.0000000000001262","DOIUrl":"10.1097/CIN.0000000000001262","url":null,"abstract":"<p><p>Nurse staffing decisions are often made without input from high-quality, reliable patient acuity measures, especially in medical-surgical settings. Staffing decisions not aligned with patient care needs can contribute to inadequate patient-to-nurse ratios and nurse burnout, potentially resulting in preventable patient harm and death. We conducted a proof-of-concept study to explore the feasibility of adapting an evidence-based patient acuity tool for use in the EHR. A retrospective cohort of pediatric medical-surgical inpatients was used to map electronic patient data variables. We developed an algorithm to calculate the score for one domain of the tool and validated it by comparing it with a score based on a manual chart review. Through multiple rounds of testing and refinement of the variables and algorithm, we achieved 100% concordance between scores generated by the algorithm and the manual chart review. Our proof-of-concept study demonstrates the feasibility and challenges of adapting an evidence-based patient acuity score for automation in the EHR. Further collaboration with data scientists is warranted to operationalize the tool in the EHR and achieve an automated acuity score that can improve staffing decisions, support nursing practice, and enhance team collaboration.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Interactive Virtual Reality Simulation Developed to Teach Oral Care Application Skills on Unconscious Patients: Effect on the Knowledge Level of Nursing Students.","authors":"Asuman Çobanoğlu, Tarık İçten","doi":"10.1097/CIN.0000000000001222","DOIUrl":"10.1097/CIN.0000000000001222","url":null,"abstract":"<p><p>A quasi-experimental one-group pretest-posttest research design was used in this study. For the purpose of the research, a computer-based and interactive virtual reality simulation for applying oral care on an unconscious patient was developed to be integrated into the existing nursing curriculum. It was concluded that the computer-based, interactive virtual reality simulation design developed for teaching oral care application on an unconscious patient had a high impact on education and the sense of presence. It was further determined that the virtual reality simulation, developed herein, improved the students' knowledge level on the subject ( P < .05). It was concluded that the computer-based, interactive virtual reality simulation prepared for applying oral care on an unconscious patient is an effective and usable method in nursing education.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142958339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Visits at Intensive Care Units Post-COVID-19: A Mixed-Methods Implementation Evaluation Study.","authors":"Linea Høyer, Anna Holm, Pia Dreyer, Anette Bjerregaard Alrø, Erika G Spaich","doi":"10.1097/CIN.0000000000001252","DOIUrl":"10.1097/CIN.0000000000001252","url":null,"abstract":"<p><p>Due to visiting restrictions at intensive care units during the COVID-19 pandemic, a digital video technology was developed and implemented. This study evaluated the use of digital visits at four intensive care units after COVID-19. Nurses' use of the technology and managerial perspectives on implementation were examined in an explanatory sequential mixed-methods study. Data were explored by inferential statistics (quantitative data) and content analysis (qualitative data). Results revealed that 52.9% of nurses had not used digital visits. Users indicated that the technology supported the patient-relative-nurse relationship, but needs reimplementation, aligning it with the post-COVID-19 setting.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143081953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidance Regarding the Use of Artificial Intelligence in Nursing Journal Author Guidelines.","authors":"Heather Carter-Templeton, Marilyn H Oermann, Jacqueline K Owens, Gabriel M Peterson, Joy Mbadiwe, Mohammed Quazi, Hannah E Bailey","doi":"10.1097/CIN.0000000000001286","DOIUrl":"10.1097/CIN.0000000000001286","url":null,"abstract":"","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"UXpedite Learning Design: Bridging Instructional Design and Software Engineering for Effective Augmented Reality Learning Environments.","authors":"Hector Cardona-Reyes, Carlos Lara-Alvarez, Alexis Edmundo Gallegos-Acosta","doi":"10.1097/CIN.0000000000001301","DOIUrl":"10.1097/CIN.0000000000001301","url":null,"abstract":"<p><p>The demands of contemporary everyday contexts have accelerated the deployment and adoption of emerging technologies, such as augmented reality, to enhance the learning experience. Traditionally, AR learning environments have been designed according to established instructional design principles. Now, it has become essential to update this approach by addressing the current demands of modern teaching and learning methods (eg, face-to-face and online learning) alongside technical issues related to augmented reality (eg, virtual scenarios). Additionally, the inclusion of software engineering methodologies can contribute to increased precision in the design process. In this sense, the current research presents a blended learning design model named UXpedite Learning Design, which integrates both instructional design and software engineering design approaches to facilitate the development of AR environments. The model comprises six phases: (i) needs assessment, (ii) ideation, (iii) prototyping, (iv) development, (v) technical testing, and (vi) user evaluation. A case study was conducted to demonstrate the implementation of the proposed model in developing the Virtual-Beat application, a tool designed to teach the interpretation of human vital sign measurements. Our tests indicate that using the Virtual-Beat application leads to slightly better learning outcomes compared with conventional classroom education, as evidenced by a statistically significant difference in examination scores between the experimental group (M = 7.53) and the control group (M = 7.08), t73 = 2.96, P = .004. Additionally, the User Experience Questionnaire completed by participants who used the application yielded positive results, highlighting a favorable overall experience (M = 1.465) and excellent attractiveness (M = 1.667). However, the assessment also identified a need for improvement in user interaction control. In conclusion, the findings suggest that the UXpedite Learning Design model shows promise for creating high-quality learning environments that align with the evolving needs of higher education.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Deep Learning Approach for Infant Pain Assessment Using Facial Expressions Through Convolutional Neural Network.","authors":"Long Zhang, Ting Yan Zhu, Ying Zhang","doi":"10.1097/CIN.0000000000001302","DOIUrl":"10.1097/CIN.0000000000001302","url":null,"abstract":"<p><p>This study presents a deep learning-based approach for assessing infant pain through facial expression analysis using Convolutional Neural Networks (CNNs). Given infants' inability to verbally articulate pain, reliable assessment methods are crucial in clinical nursing. To address this need, we developed a CNN model utilizing the COPE (Classification of Pain Expression) database. Our model achieved a test accuracy of 90.24%, with an average precision and recall of 87.58%, and an F1 score of 0.8758. Additionally, the model demonstrated high performance with an area under the curve of 0.9818 on the receiver operating characteristic curve. These results underscore the potential utility of CNNs for providing an objective pain assessment in clinical settings. However, the study acknowledges limitations, including a small sample size, the need for external validation, and ethical considerations. Future research should focus on expanding the dataset, conducting external validation, refining model architectures, and addressing ethical considerations to enhance performance and applicability. These efforts will advance infant pain management, ensure ethical integrity, and improve the overall quality of care.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of eHealth Literacy With Cervical Cancer and Human Papillomavirus Awareness Among Women in Türkiye: A Cross-sectional Study.","authors":"Gülbahar Korkmaz Aslan, Eda Kılınç İşleyen, Asiye Kartal","doi":"10.1097/CIN.0000000000001314","DOIUrl":"10.1097/CIN.0000000000001314","url":null,"abstract":"<p><p>Internet is women's primary source of information about cervical cancer and human papillomavirus. The aim of this study was to determine the associations of electronic health literacy with cervical cancer and human papillomavirus awareness among women of reproductive age. This is a cross-sectional study. The research sample consisted of 330 women of reproductive age (15-49 years), who were admitted to family health centers. The data were collected between July and August 2023 using eHealth Literacy Scale and the Cervical Cancer and Human Papillomavirus Awareness Questionnaire. Multiple linear regression analysis was performed to explore the predictors of cervical cancer and human papillomavirus awareness. In this study, the mean score of women's knowledge about cervical cancer and human papillomavirus was found to be low (4.54 ± 3.94), and the mean score of threat perception was found to be moderate (45.60 ± 6.54). eHealth literacy was found to be a predictor of women's knowledge about cervical cancer and human papillomavirus and threat perception. This result suggests that eHealth literacy should be considered for interventions to increase knowledge and awareness of women about cervical cancer and human papillomavirus.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nurses' Experiences of Using Nursing Care Plans in the Electronic Medical Record in an Acute Medical Setting: A Mixed-Methods Study.","authors":"Rebecca Miriam Jedwab, Isabella McDonald, Bernice Redley, Naomi Dobroff, Alemayehu Mekonnen","doi":"10.1097/CIN.0000000000001316","DOIUrl":"10.1097/CIN.0000000000001316","url":null,"abstract":"<p><p>Nursing care plans within electronic medical record systems have the potential to support nurses in planning and prioritizing patient care; however, there is a gap in the literature related to nurses' experiences of how this may occur. The aims of this mixed-methods study included exploring nurses' documentation adherence, identifying barriers and enablers to care plans documentation, and making recommendations to enhance nurses' use of care plans within electronic medical records. An audit of 142 patients revealed the majority had at least one care plan initiated in the electronic medical record (n = 120, 84.5%), 63 patients had a care plan initiated within 24 hours of admission (n = 63, 44.4%), and only three had care plans documented against in the previous 48 hours (2.11%). Data from six focus groups were developed into two themes (each with two subthemes): \"Mind the Gap\" and \"Making It Work for Us.\" Barriers and enablers were identified and mapped to 10 of the 14 domains of the Theoretical Domains Framework. There was large variability in nurses' knowledge and understanding related to the need for care plans documentation. Assessment of usability and/or redesign of care plans within electronic medical records must align to nursing workflows to support clinical care delivery.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144051457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nurse Educators' Perceptions and Experiences of Generative Artificial Intelligence: A Cross-Sectional Study Analysis.","authors":"Minjoo Hong, Hyewon Shin, Sang Suk Kim, Jennie C De Gagne","doi":"10.1097/CIN.0000000000001273","DOIUrl":"10.1097/CIN.0000000000001273","url":null,"abstract":"<p><p>As technology continues to transform education, the adoption of generative artificial intelligence is increasing in nursing education. However, concerns regarding the accuracy of AI-generated content and ethical issues exist. This study explores the perceptions/experiences of nurse educators in South Korea regarding the use of generative artificial intelligence. Using a cross-sectional survey, data were gathered from 120 nurse educators, and descriptive statistical analysis was applied to the data. Significantly 38.9% of participants reported no prior engagement with generative artificial intelligence. Meanwhile, 32.5% identified ChatGPT as their preferred source. The perceived usefulness of generative artificial intelligence was evaluated on average as 3.11 (SD = 0.31) on a 4-point scale, suggesting a generally favorable view of its potential to diversify learning resources, enhance student learning experiences, and improve educational quality. Despite these positive perceptions, the average engagement score with generative artificial intelligence was 2.76 (SD = 0.40), reflecting moderate actual use. This study contributes to the literature on generative artificial intelligence integration in education, revealing an overall positive attitude among nurse educators. It underscores the need for increased application and familiarity with such technologies to maximize teaching strategy benefits, student outcomes, and the efficacy of nursing education.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143605580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opportunities and Challenges for Digital Health and Artificial Intelligence to Support Nurses: Results of a Survey of Nursing Informaticists.","authors":"Meghan Reading Turchioe, Robin Austin, Kay Lytle","doi":"10.1097/CIN.0000000000001279","DOIUrl":"10.1097/CIN.0000000000001279","url":null,"abstract":"<p><p>Artificial intelligence and other digital health technologies may optimize nurses' work. Therefore, we aimed to examine the roles of nurses in facilitating the adoption of digital health technologies and identify opportunities for these technologies to reduce burnout. We conducted a cross-sectional survey study focused on nurses' use of digital health and artificial intelligence technology with nursing informaticists. Data collection was guided by the implementation science framework, Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability. Participants were recruited electronically through professional nursing informatics organizations. Survey data were analyzed using basic descriptive statistics. Fifty-two participants from across the United States completed the survey. Telehealth (73%), patient portals (71%), and medical-grade devices (69%) were most frequently used, whereas artificial intelligence was frequently used by only 38%. Staffing shortages (88%), low staff retention (81%), and inadequate support when adopting new technologies (52%) were among the key drivers of nursing burnout. Participants endorsed most nursing tasks as being supported by digital health, especially patient assessment and evaluating outcomes, and especially artificial intelligence. Engaging nurses early in the process of developing and deploying digital health, especially artificial intelligence, may help address burnout by producing more nursing-centered technologies and providing technology-enabled nursing work alternatives to bedside care.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}