Cin-Computers Informatics Nursing最新文献

Abnormal uterine bleeding is a common clinical concern for adolescent women. This research study aims to improve the clinical reasoning skills of advanced practice nursing students instructed in blended Objective Simulation Competency Assessment clinical experiences by enhancing feedback loops given to students during simulated experiences. A sequential explanatory mixed-methods study design was conducted with two cohorts of first-year women's health nurse practitioner graduate nursing students enrolled in the Women's Health Program at a large Midwestern university. Data were collected across 2 years from two separate cohorts, and analyses included data from 15 participants. The Abnormal Uterine Bleeding module designed with decision pathways was a worthy effort, and faculty value using data analytics from the e-learning module to evaluate student learning. This study describes how nursing faculty created abnormal uterine bleeding content in an online module format that can aid the diagnostic reasoning process and enable feedback to students.

Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier intervention and better outcomes. Three prediction models (logistic regression, random forest, and naive Bayes) were constructed and evaluated. A total of 459 people were involved, including 156 participants (34.0%) with high fall risk. Seven independent predictors (frail status, age, smoking, heart attack, cerebrovascular disease, arthritis, and osteoporosis) were selected to develop the models. Among the three machine learning models, the logistic regression model had the best model fit, with the highest area under the curve (0.856) and accuracy (0.797) and sensitivity (0.735) in the test set. The logistic regression model had excellent discrimination, calibration, and clinical decision-making ability, which could aid in accurately identifying the high-risk groups and taking early intervention with the model.

Core nursing procedures are essential for nursing students to master because of their high frequency in nursing practice. However, the experience of performing procedures in actual hospital settings decreased during the coronavirus disease 2019 pandemic, necessitating the development of various contents to supplement procedural training. This study investigated the effects of a straight catheterization program utilizing an immersive virtual reality simulation on nursing students' procedural performance, self-confidence, and immersion. The study employed a nonequivalent control group pretest-posttest design with 29 participants in the experimental group and 25 in the control group. The experimental group received training through a computer-based immersive virtual reality program installed in a virtual reality hospital, with three weekly sessions over 3 weeks. The control group underwent straight catheterization using manikin models. The research findings validated that virtual reality-based straight catheterization education significantly improved students' procedural skills, self-confidence, and flow state. Therefore, limited practical training can be effectively supplemented by immersive virtual reality programs.

Unplanned readmission endangers patient safety and increases unnecessary healthcare expenditure. Identifying nursing variables that predict patient readmissions can aid nurses in providing timely nursing interventions that help patients avoid readmission after discharge. We aimed to provide an overview of the nursing variables predicting readmission of patients with a high risk. The authors searched five databases-PubMed, CINAHL, EMBASE, Cochrane Library, and Scopus-for publications from inception to April 2023. Search terms included "readmission" and "nursing records." Eight studies were included for review. Nursing variables were classified into three categories-specifically, nursing assessment, nursing diagnosis, and nursing intervention. The nursing assessment category comprised 75% of the nursing variables; the proportions of the nursing diagnosis (25%) and nursing intervention categories (12.5%) were relatively low. Although most variables of the nursing assessment category focused on the patients' physical aspect, emotional and social aspects were also considered. This study demonstrated how nursing care contributes to patients' adverse outcomes. The findings can assist nurses in identifying the essential nursing assessment, diagnosis, and interventions, which should be provided from the time of patients' admission. This can mitigate preventable readmissions of patients with a high risk and facilitate their safe transition from an acute care setting to the community.

Low adherence to hospital-based cardiac rehabilitation has been observed in patients after percutaneous coronary intervention. The effectiveness of home-based cardiac telerehabilitation in this setting is unclear. This study aimed to investigate the impact of home-based cardiac telerehabilitation on exercise endurance, disease burden status, cardiac function, and quality of life in patients after percutaneous coronary intervention. A total of 106 patients after percutaneous coronary intervention were randomly assigned to either the intervention group (receiving routine rehabilitation care and home-based cardiac telerehabilitation) or the control group (receiving routine care only), with 53 patients in each group. The 6-minute walking test, anerobic threshold, physical component summary score, mental component summary score, V o2max , and left ventricular ejection fraction were measured in both groups before and 3 months after the intervention. Additionally, the Short-Form 12 scale and Family Burden Interview Schedule were used to assess quality of life and disease burden status. The intervention group demonstrated significant improvements in 6-minute walking test, anerobic threshold, V o2max , physical component summary score, mental component summary score, Short-Form 12 scale, and Family Burden Interview Schedule scale scores compared with the control group ( P <0.05). Results suggest that home-based cardiac telerehabilitation may improve exercise endurance and quality of life and reduce disease burden status in patients after percutaneous coronary intervention.

Although the potential of natural language processing and an increase in its application in nursing research is evident, there is a lack of understanding of the research trends. This study conducts text network analysis and topic modeling to uncover the underlying knowledge structures, research trends, and emergent research themes within nursing literature related to natural language processing. In addition, this study aims to provide a foundation for future scholarly inquiries and enhance the integration of natural language processing in the analysis of nursing research. We analyzed 443 literature abstracts and performed core keyword analysis and topic modeling based on frequency and centrality. The following topics emerged: (1) Term Identification and Communication; (2) Application of Machine Learning; (3) Exploration of Health Outcome Factors; (4) Intervention and Participant Experience; and (5) Disease-Related Algorithms. Nursing meta-paradigm elements were identified within the core keyword analysis, which led to understanding and expanding the meta-paradigm. Although still in its infancy in nursing research with limited topics and research volumes, natural language processing can potentially enhance research efficiency and nursing quality. The findings emphasize the possibility of integrating natural language processing in nursing-related subjects, validating nursing value, and fostering the exploration of essential paradigms in nursing science.