Computers, informatics, nursing : CIN最新文献

{"title":"Video-Based Fall Risk Assessment Using Multimodal Large Language Models in Home Health Care: A Proof-of-Concept Feasibility Study.","authors":"Pallavi Gupta, Zhihong Zhang, Meijia Song, Martin Michalowski, Xiao Hu, Gregor Stiglic, Laura-Maria Peltonen, Maxim Topaz","doi":"10.1097/CIN.0000000000001485","DOIUrl":"10.1097/CIN.0000000000001485","url":null,"abstract":"<p><p>Falls cause millions of injuries and deaths annually, making prevention a key priority in home health care (HHC). Traditional fall risk assessments often overlook the complex interaction of personal, environmental, and behavioral factors. This study addresses these limitations by introducing a novel approach that leverages multimodal data, specifically visual frames and structured prompts, to assess fall risk in in-home patients. Using the multimodal large language model (MLLM), LLaVA-NeXTVideo-7B-hf, we analyze simulated in-home patients' video data to enable a more comprehensive and dynamic evaluation of fall risk, paving the way for intelligent, video-based fall prevention in home health care. Preliminary validation using simulated video data demonstrates the feasibility of using MLLMs for such tasks. Simulated in-home patient video data were processed into 24 equally spaced frames. Twelve visually observable fall risk factors extracted from the literature search, categorized as intrinsic, extrinsic, or behavioral, guided the creation of prompts for the MLLM. Standardized prompts were developed by testing the model with concise prompts for simple inferences and elaborated prompts for complex ones. Each prompt was run 3 times, and consensus results were compared with expert evaluations. The model achieved 85.71% accuracy with concise prompts on 7 simple risk factors and 100% accuracy with elaborated prompts on two complex ones. However, the model consistently failed for 2 risk factors that required clinical judgment or had limited visual data. MLLMs like LLaVA-NeXTVideo 7B-hf show strong potential for augmenting fall risk assessment in HHC when guided by well-structured prompts. The approach focuses on visually inferable factors and is intended to complement, rather than replace, clinical evaluation. This proof-of-concept feasibility study shows that MLLMs can support preliminary fall risk analysis using simulated home health care video data and lays the groundwork for future video-based research in this setting, where existing work remains limited. To our knowledge, this is the first study to evaluate the feasibility of MLLM-based video analysis for fall risk assessment in home health care.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129078","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}

{"title":"Machine Learning-assisted Prediction of Fluid Overload and Its Nursing Implications in Patients With Acute Pancreatitis.","authors":"Lu Zhou, Chengli Zhou, Jing Deng, Xiaoling Zhu, Ting Li","doi":"10.1097/CIN.0000000000001528","DOIUrl":"10.1097/CIN.0000000000001528","url":null,"abstract":"<p><p>Fluid overload (FO) is a critical complication in acute pancreatitis (AP), contributing to prolonged hospital stays and increased mortality. Traditional scoring systems like BISAP lack predictive accuracy for FO, placing a burden on nurses managing fluid therapy. Machine learning (ML) offered potential for early FO prediction, yet its integration into nursing practice remains underexplored. Using the MIMIC-IV database, we analyzed 3458 adult AP patients, with 22.8% experiencing FO (net fluid balance >2 L/24h plus clinical signs). Three ML models-Random Forest (RF), XGBoost, and Long Short-Term Memory (LSTM)-were developed to predict FO using clinical and nursing-derived features (eg, BUN, net fluid balance, and documentation frequency). Models were evaluated for accuracy, precision, recall, F1 score, and ROC AUC, with SHAP analysis for feature importance. A Gradio-based clinical decision support system (CDSS) was prototyped for nursing integration. LSTM outperformed RF and XGBoost, achieving an AUC of 0.92 (95% CI [0.90, 0.94]), accuracy of 0.85, and F1 score of 0.82, significantly surpassing BISAP (AUC 0.74, P <.001). Key predictors included BUN, hematocrit, and net fluid balance. Subgroup analysis showed improved performance in patients >65 years (AUC 0.95) but reduced accuracy in CKD patients (AUC 0.88). The CDSS provided real-time FO risk scores, enhancing nurse decision-making. ML models, particularly LSTM, enabled accurate FO prediction in AP, with potential to transform nursing practice through proactive fluid management. Integration into CDSS supports early interventions, reducing nurse workload and improving patient outcomes.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147611635","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}

{"title":"Enhancing Accuracy of LLM in Nursing Education Through RAG and Thought Chains.","authors":"Juan Wang, Fengrong Lu, Liang Zhang, Li Zhang","doi":"10.1097/CIN.0000000000001409","DOIUrl":"10.1097/CIN.0000000000001409","url":null,"abstract":"<p><p>The penetration of large language models (LLMs) into all walks of life requires finding effective ways to improve the accuracy of their practical application in nursing scenarios. This study investigates the potential of retrieval-augmented generation (RAG) technology and the chain of thought (CoT) reasoning process in addressing the limitations of LLMs in professional knowledge and complex problem reasoning. Leveraging a knowledge base derived from the Chinese National Nursing Licensure Examination question bank, researchers first evaluated the baseline performance of LLMs. Subsequently, the CoT reasoning process was systematically compared with official exam parsing methods to assess the model's ability to interpret nursing-related questions. Experimental results demonstrated that integrating the knowledge base significantly improved LLM accuracy from 84.58% to 93.33%. Furthermore, the CoT reasoning process achieved a 91.33% accuracy rate in parsing question options, highlighting its robust logical reasoning capabilities. These findings underscore that the synergistic integration of RAG and CoT enhances the precision of LLMs in knowledge retrieval and clinical reasoning, offering an innovative technical pathway for developing intelligent nursing education tools. The study not only validates the effectiveness of combining knowledge augmentation with advanced reasoning mechanisms but also provides methodological insights for improving the reliability of AI applications in health care.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812603","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}

{"title":"Pilot Study on the Usefulness of Tele-Yoga in Patients With Heart Failure.","authors":"Diana Achury-Saldaña, Mayra Alejandra Sánchez, Angie Angarita, Johan Ayala-Gutiérrez, Marian Thiriat-Infante, Angela Daniela Yepes, Lizeth Hasbleidy Mora, Luisa Fernanda Garcia","doi":"10.1097/CIN.0000000000001529","DOIUrl":"10.1097/CIN.0000000000001529","url":null,"abstract":"<p><p>This study aimed to evaluate the feasibility and benefits of tele-yoga in promoting mindfulness. A cross-sectional pilot study was conducted on patients (n=24) with heart failure at a tertiary referral hospital. The tele-yoga intervention was implemented in 6 group sessions over 8 weeks. Feasibility was assessed using indicators of adherence, retention, and user experience, whereas mindfulness was measured using the Mindful Attention Awareness Scale with a Cronbach's alpha of 0.92. The statistical software RStudio was used for analysis. The results showed that most participants were women, with an average age of 47.4 years, middle-aged, and recently diagnosed. The attendance rate was 100%, and participants were highly satisfied with the experience. The average mindfulness score was 60, with a median of 59 and a SD of 17.81. This intervention proved to be feasible and acceptable, promoting concentration, emotional self-awareness, and stress management, thereby improving quality of life and disease management.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148152988","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}

{"title":"A Digital Diabetes Clinic Intervention for Individuals Starting Insulin Therapy: Randomized Controlled Trial.","authors":"Dilek Büyükkaya Besen, Merve Dervişoğlu, Merve Günbaş, Gülsüm Yildiz, Abdurrahman Çömlekçi, Sema Gül, Fidan Nasrullayeva, Mehmet Çağri Ünal, Gökçen Güngör Semiz, Özgül Vatansever","doi":"10.1097/CIN.0000000000001439","DOIUrl":"10.1097/CIN.0000000000001439","url":null,"abstract":"<p><p>This randomized controlled trial evaluated the effects of a digital diabetes clinic continuous support program on metabolic, psychological, and social outcomes in individuals with type 2 diabetes who were recently initiated on insulin therapy. The study included 67 participants, with 35 in the intervention group and 32 in the control group. Data were collected at baseline, and at the third and sixth months using various instruments, including the Diabetes Individual Diagnosis Form, Hypoglycemic Confidence Scale (HCS), Hypoglycemia Fear Survey (HFS), Diabetes Empowerment Scale-Short Form (DES-SF), Psychological Insulin Resistance Scale (PIRS), Insulin Treatment Assessment Scale (ITAS), Perceived Social Support Scale (PSSS), and the Visual Analog Scale (VAS) for stress. The intervention group received digital education, counseling, continuous follow-up, and a structured daily self-management program over a 3-month period. 99% CIs were calculated for key outcome measures to support the interpretation and robustness of the results. The findings revealed significant improvements in the intervention group, including reductions in the frequency of hypoglycemia and hyperglycemia, emergency admissions, HbA1c, and lipid levels ( P <.001). Furthermore, hypoglycemia fear and psychological insulin resistance decreased, while hypoglycemic confidence, diabetes empowerment, perceived social support, and stress levels significantly improved ( P <.001). These results demonstrate that digital support programs delivered through a digital diabetes clinic can enhance treatment adherence, reduce anxiety, and improve self-management in individuals newly started on insulin, highlighting the effectiveness of telehealth in diabetes care. Newly initiated on insulin therapy, underscoring the potential of telehealth in diabetes care.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145867271","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}

{"title":"New England Nursing Informatics Consortium 2026 Annual Symposium Member Highlights.","authors":"Julie Murphy, Denise Goldsmith, Rita D Zielstorff","doi":"10.1097/CIN.0000000000001605","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001605","url":null,"abstract":"","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":"44 8","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681977","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}

{"title":"Collaboration, Intellectual Basis, and Emerging Trends in Smart Senior Care Research: A Scientometric Analysis.","authors":"Le-Ye Yao, Kai-Yi Chen, Qiao-Yun Yang, Peng-Hui Lyu","doi":"10.1097/CIN.0000000000001437","DOIUrl":"10.1097/CIN.0000000000001437","url":null,"abstract":"<p><p>As the global population ages and the demand for high-quality care rises, smart senior care, underpinned by digital and information technologies, has garnered increasing attention as a vital approach to elderly health management. This paper conducts a systematic bibliometric analysis of smart senior care from 1981 to 2023, examining 3 dimensions: publication output and academic collaboration, intellectual basis and structure, alongside research frontiers and evolving trends. International research efforts in smart senior care have grown increasingly diverse and interconnected. However, significant regional disparities persist, particularly in knowledge production and academic impact. The research frontiers and intellectual basis of smart senior care demonstrate interdisciplinary characteristics, with a focus on 2 primary directions: technological innovation and humanistic care. Research priorities in smart senior care vary across countries, while research hotspots have undergone notable shifts in recent years.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145852197","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}

{"title":"High-fidelity Simulation in Newborn Care: Effects on Midwifery Students' Learning Outcomes.","authors":"Sümeyye Bal, Yasemin Sökmen","doi":"10.1097/CIN.0000000000001410","DOIUrl":"10.1097/CIN.0000000000001410","url":null,"abstract":"<p><p>Simulation-based training at various levels contributes significantly to the professional development of midwifery students. The purpose of this study was to evaluate the midwifery students' experiences with simulation-based education, to evaluate the knowledge, skills, and attitudes they acquire through this method, and to assess the impact of simulation on their professional self-confidence and clinical competence. This randomized controlled trial examined the effect of high-fidelity simulation on midwifery students' competencies in newborn first care. Conducted with 64 students in May to June 2024, data were collected through a student information form, a newborn first care knowledge and skills assessment, and a learning satisfaction and self-confidence scale. Post-test knowledge scores were significantly higher in the experimental group ( P <.001) but the experimental group achieved slightly better newborn care skill scores, the difference was not statistically significant ( P =.737) and experimental group reported significantly higher satisfaction with the learning experience ( P =.048), but no significant difference was observed in self-confidence levels ( P =.470). High-fidelity simulation is effective in enhancing knowledge acquisition and learning satisfaction, though it may have limited impact on clinical skill development and self-confidence.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902204","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}

{"title":"Validating the Effectiveness of a VR-based and Haptic Technology-based Operating Room Simulation Program Among Nursing Students.","authors":"Hyeon-Young Kim","doi":"10.1097/CIN.0000000000001452","DOIUrl":"10.1097/CIN.0000000000001452","url":null,"abstract":"<p><p>This study aimed to validate the effectiveness of a virtual reality (VR) and haptic technology-based simulation program for operating room nursing education among undergraduate nursing students. Providing students with hands-on experience in the operating room is challenging due to safety, ethical, and logistical constraints. Therefore, this study explored immersive simulation as a viable alternative. We used a nonequivalent control group pretest-posttest design, with 78 nursing students divided into an experimental and a control group. The intervention group engaged in a simulation program that involved VR headsets and haptic gloves, allowing hands-on practice of perioperative nursing tasks in a virtual setting, while the control group received online-based perioperative nursing education reflecting the standard instructional approach used at the participating institution. Outcome measures included knowledge acquisition, confidence in performing nursing tasks, learning presence, learning flow, and learning satisfaction. Results showed that the simulation program significantly improved participants' confidence, presence, flow, and satisfaction, compared to the control group; however, no significant difference was observed in knowledge acquisition. These findings suggest that integrating haptic-enhanced VR simulation education into nursing curricula can effectively foster immersive, experiential learning and improve key educational outcomes. Further studies are recommended to optimize feedback mechanisms and assess knowledge improvement through alternative evaluation tools.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822604","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}

{"title":"Virtual Reality as a Supportive Technology for Pediatric Intravenous Procedures: Effects on Fear and Autonomic Responses.","authors":"Pei-Shan Hsieh, Hui-Ming Hou, Chieh-Mao Chuang, Wei-Ling Lin","doi":"10.1097/CIN.0000000000001608","DOIUrl":"https://doi.org/10.1097/CIN.0000000000001608","url":null,"abstract":"<p><p>Children undergoing intravenous procedures often experience substantial fear and discomfort, which can make these procedures more difficult to perform. This study examined whether virtual reality could serve as a supportive technology during pediatric intravenous procedures. A randomized, parallel-group design was used with 50 children assigned to either a virtual reality group or a comparison group. Pain and fear were assessed using self-report measures, and physiological responses were evaluated using heart rate variability, heart rate, and blood pressure indicators. Children in the virtual reality group reported significantly lower fear than those in the comparison group, whereas pain scores did not differ significantly between groups. The virtual reality group also showed significant differences in heart rate variability-related indices, suggesting a less pronounced sympathetic-dominant autonomic pattern, which may be clinically meaningful in the context of lower fear during intravenous procedures. These findings support the potential role of VR as a supportive technology in pediatric nursing care during intravenous procedures.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148671944","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}