Computers, informatics, nursing : CIN最新文献_第3页

Effect of a Web-based Decision Support System on Nursing Students' Care Plan Preparation: A Post-test Control Group Experimental Study. 基于网络的决策支持系统对护生护理计划编制的影响：测试后对照组实验研究。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-03 DOI: 10.1097/CIN.0000000000001498

Meltem Özduyan Kiliç, Fatoş Korkmaz, Oumout Chousei̇noglou

{"title":"Effect of a Web-based Decision Support System on Nursing Students' Care Plan Preparation: A Post-test Control Group Experimental Study.","authors":"Meltem Özduyan Kiliç, Fatoş Korkmaz, Oumout Chousei̇noglou","doi":"10.1097/CIN.0000000000001498","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001498","url":null,"abstract":"Care plans are critical tools for guiding health care decisions. Integrating technology-based educational tools may enhance students' ability to prepare these plans effectively. This study aimed to evaluate the impact of a web-based decision support system on nursing students' skills in preparing care plans. This is an experimental study. Students in the control group used traditional paper-based methods. In contrast, those in the intervention group used a web-based decision support system to develop care plans based on provided case scenarios (Supplemental Digital Content 1, http://links.lww.com/CIN/A515). Data were collected using an inte rview form, a datasheet, a Nursing Care Plan Evaluation Case, and an N-Care evaluation form. Thematic analysis was used for qualitative data, and descriptive statistics were applied to analyze quantitative data. The experimental group achieved significantly higher care planning scores (Z = -3.041, P = .002, r = 0.475) and total scores (Z = -2.284, P = .022, r = 0.357) than the control group. Students reported positive experiences using the N-Care system and expressed interest in continued use while suggesting minor improvements. Compared to traditional teaching methods, a web-based decision support significantly improved nursing students' ability to prepare care plans.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147617305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Generative Artificial Intelligence (GenAI) to Co-Design Digital Health Technologies: Some Lessons Learned. 使用生成式人工智能（GenAI）协同设计数字健康技术：一些经验教训。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-03 DOI: 10.1097/CIN.0000000000001537

Mengying Zhang, David Woodcock, Siobhan O'Connor

引用次数: 0

AI-Assisted Virtual Reality Simulation for Therapeutic Ambient Communication: An Integrative Review. 人工智能辅助虚拟现实模拟治疗环境交流：综合综述。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-02 DOI: 10.1097/CIN.0000000000001540

Kerry L O'Brien, Jennifer Emilie Mannino

{"title":"AI-Assisted Virtual Reality Simulation for Therapeutic Ambient Communication: An Integrative Review.","authors":"Kerry L O'Brien, Jennifer Emilie Mannino","doi":"10.1097/CIN.0000000000001540","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001540","url":null,"abstract":"Background: Artificial intelligence-enabled ambient speech recognition technology is an emerging innovation poised to transform how nurses care for and engage with patients through conversational narration of care. The purpose of this integrative literature review is to examine the current evidence of artificial intelligence-enabled virtual reality simulation as a tool for developing competencies in therapeutic communication and health assessment.Methods: A systematic search of EBSCOhost CINAHL, PubMed, and OVID was conducted. Data were extracted and synthesized to identify themes and patterns.Results: A total of 8 studies met the inclusion criteria; none were conducted with practicing nurses. Findings revealed a mixed association between the use of artificial intelligence-enabled virtual reality patient simulation and communication and physical assessment skill development in nursing students. Three key domains were examined, including therapeutic communication outcomes, learning effectiveness measured by confidence and self-efficacy, and virtual reality usability.Discussion: A literature gap exists around virtual reality's efficacy for conversational assessment training, particularly for practicing nurses. Ambient voice technology is rapidly evolving and will become standard nursing practice. Future nursing research on virtual patient simulation should be conducted to understand its role in the success of ambient technology and establish a foundation for future nursing practice and education.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

2026 HIMSS-ANI Nursing Informatics Leadership Award Announced. 宣布2026年HIMSS-ANI护理信息学领导奖。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001538

Nancy Beale

引用次数: 0

Nurses' Perspective of Barrier Structure and Promotion Strategies for Digital Health Transformation: An Interpretive Structural Modeling Approach. 护士视角下的数字健康转型障碍结构与促进策略：一种解释结构建模方法。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001470

Naotaka Sugimura, Kazuki Ohashi, Tomoki Kuribara, Machiko Ukai, Kenji Hirata, Katsuhiko Ogasawara

{"title":"Nurses' Perspective of Barrier Structure and Promotion Strategies for Digital Health Transformation: An Interpretive Structural Modeling Approach.","authors":"Naotaka Sugimura, Kazuki Ohashi, Tomoki Kuribara, Machiko Ukai, Kenji Hirata, Katsuhiko Ogasawara","doi":"10.1097/CIN.0000000000001470","DOIUrl":"10.1097/CIN.0000000000001470","url":null,"abstract":"Potentially complex structures underlie the barriers to digital health transformation. This study aimed to identify the elements of barriers to digital health transformation and clarify the relationships among them using Interpretive Structural Modeling and Cross Impact Matrix-Multiplication Applied to Classification. We identified 11 barriers through a brainstorming session conducted by 3 nursing researchers in Japan. These elements were analyzed via mathematical processing, and a hierarchical structural diagram was constructed. The characteristics of each element were classified using the Cross Impact Matrix-Multiplication Applied to Classification analysis. The results demonstrated consistency with those of previous studies, thus indicating content validity. Furthermore, this study succeeded in systematically organizing the multilayered barriers and visualizing a comprehensive model that even individuals unfamiliar with the cultural context of health care could easily understand. These findings suggest that the organizational culture of nursing plays a fundamental role in the promotion of digital health transformation and emphasize the importance of collaboration among stakeholders at the clinical, developmental, and policy levels. Future strategies for digital health transformation should incorporate more flexible approaches using SWOT analysis and the Decision-Making Trial and Evaluation Laboratory technique.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145914616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of Nursing Documentation Quality: Enabling the Secondary Use of Data. 护理文件质量评估：允许数据的二次使用。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001488

Minna Mykkänen, Johanna Ikonen, Ulla-Mari Kinnunen, Kaija Saranto, Tuulikki Vehko

{"title":"Assessment of Nursing Documentation Quality: Enabling the Secondary Use of Data.","authors":"Minna Mykkänen, Johanna Ikonen, Ulla-Mari Kinnunen, Kaija Saranto, Tuulikki Vehko","doi":"10.1097/CIN.0000000000001488","DOIUrl":"10.1097/CIN.0000000000001488","url":null,"abstract":"The high quality of nursing documentation is a prerequisite for the secondary use of data. Poor-quality data can lead to incorrect decision-making. This study aimed to describe the assessment of nursing documentation quality and the utilization of this assessment data in the knowledge-based management and development of daily nursing practices. Using a cross-sectional study design, an online survey of information systems for registered nurses in Finland was conducted in spring 2023. A total of 2970 nurses responded. Descriptive methods were used to characterize the frequency of the secondary use of nursing data. Across units, nursing documentation quality was not assessed in 51% of cases, results were not reviewed in 66% of units, and nursing data were not used for knowledge-based management in 58% of units. In private health care and social services, nursing documentation reviews occurred in 21% of units, and 24% reported using nursing data for knowledge-based management. In contrast, public hospitals demonstrated lower engagement, with only 17% of units reviewing nursing documentation and 13% utilizing nursing data for management purposes. The private sector led in the secondary use of nursing data compared with other sectors. Nursing managers consistently provided more positive responses than nurses across all aspects of secondary use of data. This difference may stem from the fact that nursing managers use secondary data for daily management.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influencing Factors for Postembolization Fever in Patients Undergoing Transarterial Chemoembolization Based on Machine Learning: A Retrospective Study. 基于机器学习的经动脉化疗栓塞患者栓塞后发热影响因素的回顾性研究

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001414

Won-Du Chang, Myoung Soo Kim

{"title":"Influencing Factors for Postembolization Fever in Patients Undergoing Transarterial Chemoembolization Based on Machine Learning: A Retrospective Study.","authors":"Won-Du Chang, Myoung Soo Kim","doi":"10.1097/CIN.0000000000001414","DOIUrl":"10.1097/CIN.0000000000001414","url":null,"abstract":"Although there is no framework for prediction models for postembolization fever, potential influencing factors include demographic, clinical, laboratory, and radiologic data. We aim to develop and validate machine learning-based prediction models for postembolization fever after transarterial chemoembolization. Data from 1495 patients who underwent transarterial chemoembolization at a tertiary hospital were reviewed retrospectively. Seven machine learning-based algorithms were used to develop prediction models of postembolization fever occurrence after transarterial chemoembolization using SPSS WIN 27.0 and Python. The proposed ensemble method was the best algorithm for predicting postembolization fever. Variables positively correlated with postembolization fever occurrence were posttransarterial chemoembolization aspartate aminotransferase, C-reactive protein, alanine aminotransferase, and bilirubin levels, and international normalized ratio and platelet counts; pretransarterial chemoembolization aspartate aminotransferase and alpha-fetoprotein levels and platelet count; lipiodol and doxorubicin amounts; and a >5 cm tumor. Conversely, variables negatively correlated with postembolization fever were posttransarterial chemoembolization lymphocyte and monocyte counts and albumin levels; pretransarterial chemoembolization albumin levels and lymphocyte count; and probably hepatocellular carcinoma. Oncology clinicians should monitor demographic, clinical, laboratory, and radiologic data before and after transarterial chemoembolization to assess postembolization fever. In addition, health care professionals should be aware of the potential side effects of transarterial chemoembolization and management strategies, such as medications.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146032621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Large Language Models to Detect Anxiety and Nausea/Vomiting Documentation in Clinical Notes of Patients With Cancer. 使用大型语言模型检测癌症患者临床记录中的焦虑和恶心/呕吐文件。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001418

Nahid Zeinali, Alaa Albashayreh, Weiguo Fan, Stephanie Gilbertson White

{"title":"Using Large Language Models to Detect Anxiety and Nausea/Vomiting Documentation in Clinical Notes of Patients With Cancer.","authors":"Nahid Zeinali, Alaa Albashayreh, Weiguo Fan, Stephanie Gilbertson White","doi":"10.1097/CIN.0000000000001418","DOIUrl":"10.1097/CIN.0000000000001418","url":null,"abstract":"Large language models (LLMs) are increasingly utilized for named entity recognition (NER) in health care, with significant potential to enhance symptom detection within electronic health records (EHRs). This study explores the application of LLMs to identify symptoms of anxiety and nausea/vomiting documented in the clinical notes of patients with cancer. We analyzed clinical notes from 8,490 patients diagnosed with various cancer types. Bio Clinical BERT and Bio GPT models were further pretrained on clinical text from this dataset. Two modeling strategies, fine-tuning and prompt-based learning, were implemented using Symptom-BERT and Symptom-GPT frameworks. Model performance was evaluated using F1 scores, emphasizing recognizing psychological symptoms (anxiety) and physical symptoms (nausea/vomiting). Fine-tuning with Symptom-BERT achieved the highest F1 scores, 0.989 for nausea/vomiting and 0.912 for anxiety, significantly outperforming Symptom-GPT in detection accuracy. While prompt-based learning with Symptom-GPT surpassed that of a few-shot learning, it remained less effective than fine-tuning. Fine-tuning excelled in identifying well-documented symptoms, particularly physical ones like nausea/vomiting. Using named entity recognition (NER), the study analyzed the entire dataset, detecting anxiety in 2,436 patients (28.69%) and nausea/vomiting in 3,338 patients (39.31%). While both fine-tuning and prompt-based learning approaches offer utility, fine-tuning demonstrates superior accuracy in recognizing symptoms from clinical narratives, particularly physical ones. LLM-based symptom detection can support oncology nurses and care teams by enabling earlier recognition of patient-reported symptoms documented in narrative notes. These tools offer practical value in improving symptom monitoring, care planning, and timely intervention, thereby enhancing patient-centered care in oncology settings.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Validity Evidence of an Educational Video on Cardiac Catheterization for Older Adults. 老年人心导管插入术教育录像的有效性证据。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001483

Adriana M T Nepomuceno, Rayana P Feitosa, Francilene Jane R Pereira, Alex T Meira, Mailson M Sousa, Maria Adelaide S P Moreira

{"title":"Validity Evidence of an Educational Video on Cardiac Catheterization for Older Adults.","authors":"Adriana M T Nepomuceno, Rayana P Feitosa, Francilene Jane R Pereira, Alex T Meira, Mailson M Sousa, Maria Adelaide S P Moreira","doi":"10.1097/CIN.0000000000001483","DOIUrl":"10.1097/CIN.0000000000001483","url":null,"abstract":"Cardiovascular diseases represent a significant public health challenge, especially among older adults. Educational strategies that provide clear and accessible information can positively influence outcomes for older patients undergoing invasive procedures such as cardiac catheterization. This methodological study aimed to evaluate the evidence of content and appearance (face) validity of an educational video for older adults undergoing cardiac catheterization. The research was conducted in 3 stages: development of the video based on the 12 principles of the Cognitive Theory of Multimedia Learning; content validation by 11 multidisciplinary experts using the Suitability Assessment of Materials (SAM) instrument; and face validation with 10 older adults assisted in the hemodynamics unit of a university hospital, using the Health Educational Technology Appearance Validation Instrument. The final video consisted of 49 scenes, lasted 5 minutes and 55 seconds, and achieved a global SAM score of 97.1 and an Appearance Validity Index of 0.97. It was considered an appropriate and accessible educational resource by participants. The video constitutes an innovative tool to support health education for older adults and contributes to professional practice in interventional cardiology. Future research should evaluate its effectiveness and verify its impact on hemodynamic parameters, anxiety levels, and adherence to therapeutic guidelines.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146069301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transforming Trauma Care: Interactive Dashboard Boosts Trauma Center Verification and Performance. 转变创伤护理：交互式仪表板促进创伤中心的验证和性能。

IF 1.9

Computers, informatics, nursing : CIN Pub Date : 2026-04-01 DOI: 10.1097/CIN.0000000000001480

Elisa Szydziak, Nwe Oo Mon, Sara Cardozo-Stolberg, Gabriela Santos-Revilla, Gabrielle Augustin, L D George Angus

{"title":"Transforming Trauma Care: Interactive Dashboard Boosts Trauma Center Verification and Performance.","authors":"Elisa Szydziak, Nwe Oo Mon, Sara Cardozo-Stolberg, Gabriela Santos-Revilla, Gabrielle Augustin, L D George Angus","doi":"10.1097/CIN.0000000000001480","DOIUrl":"10.1097/CIN.0000000000001480","url":null,"abstract":"Managing and analyzing trauma registry data is critical for optimizing trauma care and maintaining verification by organizations such as the American College of Surgeons. However, the volume and complexity of these data can be challenging to hone in on what is important. This study describes the design, implementation, and evaluation of an interactive trauma registry dashboard developed for enhancing compliance with trauma center verification standards. Developed using R programming, the dashboard consolidates trauma metrics into a layered, web-based interface featuring interactive visualizations and modular components tailored to performance improvement and compliance tracking. The primary data source is the trauma registry, with optional integration of external files. Implementation of the dashboard streamlined reporting processes by eliminating the need for multiple static reports, reducing analysis time, and enhancing communication among trauma team members. Monthly reviews of performance indicators supported real-time monitoring of compliance with American College of Surgeons standards. By transforming raw data into actionable insights, the dashboard improved operational efficiency and facilitated data-driven decision-making. This project demonstrates how applied informatics tools can enhance trauma program performance and verification readiness while supporting broader quality improvement efforts in clinical practice.","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146069296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0