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No abstract available This study aimed to explore digital literacy among community-dwelling older adults in urban South Korea. A semistructured interview guide was developed using the Digital Competence ( 2.0 framework, which emphasizes the competencies for full digital participation in five categories: information and data literacy, communication and collaboration, content creation, safety, and problem-solving. The data were analyzed using combined inductive and deductive content analysis. Inductive analysis identified three main categories: perceived ability to use digital technology, responses to digital technology, and contextual factors. In the results of deductive analysis, participants reported varying abilities in using digital technologies for information and data literacy, communication or collaboration, and problem-solving. However, their abilities were limited in handling the safety or security of digital technology and lacked in creating digital content. Responses to digital technology contain subcategories of perception (positive or negative) and behavior (trying or avoidance). Regarding contextual factors, aging-related physical and cognitive changes were identified as barriers to digital literacy. The influence of families or peers was viewed as both a facilitator and a barrier. Our participants recognized the importance of using digital devices to keep up with the trend of digitalization, but their digital literacy was mostly limited to relatively simple levels. Game-based virtual reality simulation programs can capitalize on the advantages of non–face-to-face education while effectively stimulating the interest of trainees and improving training efficiency. This study aimed to develop a game-based virtual reality simulation program for nervous system assessment and to evaluate the effects of the program on the learning attitudes of nursing students. Using a one-group pretest-posttest design, 41 senior nursing students were enrolled, and their learning attitudes (self-directed learning attitude, academic self-efficacy, flow-learning experience, and learning presence) were evaluated. The effect of the program was statistically significant in self-directed learning attitude (t = −2.27, P = .027) and learning presence (t = −3.07, P = .003), but the difference was not statistically significant in academic self-efficacy (t = −1.97, P = .054) and learning flow (t = −0.74, P = .459). The virtual gaming simulation program can be used to effectively replace field training in situations wherein field training is limited, such as during the COVID-19 pandemic. Decision support systems have been widely used in healthcare in recent years; however, there is lack of evidence on global trends and hotspots. This descriptive bibliometric study aimed to analyze bibliometric patterns of decision support systems in nursing. Data were extracted from the Web of Science Core Collection. Published research articles on decision support systems in nursing were identified. Co-occurrence and co-citation analysis was performed using CiteSpace version 6.1.R2. In total, 165 articles were analyzed. A total of 358 authors and 257 institutions from 20 countries contributed to this research field. The most productive authors were Andrew Johnson, Suzanne Bakken, Alessandro Febretti, Eileen S. O'Neill, and Kathryn H. Bowles. The most productive country and institution were the United States and Duke University, respectively. The top 10 keywords were “care,” “clinical decision support,” “clinical decision support system,” “decision support system,” “electronic health record,” “system,” “nursing informatics,” “guideline,” “decision support,” and “outcomes.” Common themes on keywords were planning intervention, national health information infrastructure, and methodological challenge. This study will help to find potential partners, countries, and institutions for future researchers, practitioners, and scholars. Additionally, it will contribute to health policy development, evidence-based practice, and further studies for researchers, practitioners, and scholars. Paramount to patient safety is the ability for nurses to make clinical decisions free from human error. Yet, the dynamic clinical environment in which nurses work is characterized by uncertainty, urgency, and high consequence, necessitating that nurses make quick and critical decisions. The aim of this study was to examine the influence of human and environmental factors on the decision to administer among new graduate nurses in response to alert generation during bar code–assisted medication administration. The design for this study was a descriptive, longitudinal, observational cohort design using EHR audit log and administrative data. The study was set at a large, urban medical center in the United States and included 132 new graduate nurses who worked on adult, inpatient units. Research variables included human and environmental factors. Data analysis included descriptive and inferential analyses. This study found that participants continued with administration of a medication in 90.75% of alert encounters. When considering the response to an alert, residency cohort, alert category, and previous exposure variables were associated with the decision to proceed with administration. It is important to continue to study factors that influence nurses' decision-making, particularly during the process of medication administration, to improve patient safety and outcomes. The poor usability of electronic health records contributes to increased nurses' workload, workarounds, and potential threats to patient safety. Understanding nurses' perceptions of electronic health record usability and incorporating human factors engineering principles are essential for improving electronic health records and aligning them with nursing workflows. This review aimed to synthesize studies focused on nurses' perceived electronic health record usability and categorize the findings in alignment with three human factor goals: satisfaction, performance, and safety. This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five hundred forty-nine studies were identified from January 2009 to June 2023. Twenty-one studies were included in this review. The majority of the studies utilized reliable and validated questionnaires (n = 15) to capture the viewpoints of hospital-based nurses (n = 20). When categorizing usability-related findings according to the goals of good human factor design, namely, improving satisfaction, performance, and safety, studies used performance-related measures most. Only four studies measured safety-related aspects of electronic health record usability. Electronic health record redesign is necessary to improve nurses' perceptions of electronic health record usability, but future efforts should systematically address all three goals of good human factor design. Hospitals are experiencing a nursing shortage crisis that is expected to worsen over the next decade. Acute care settings, which manage the care of very complex patients, need innovations that lessen nurses' workload burden while ensuring safe patient care and outcomes. Thus, a pilot study was conducted to evaluate the feasibility of implementing a large-scale acute care telenurse program, where a hospital-employed telenurse would complete admission and discharge processes for hospitalized patients virtually. In 3 months, almost 9000 (67%) of patient admissions and discharges were conducted by an acute care telenurse, saving the bedside nurse an average of 45 minutes for each admission and discharge. Preliminary benefits to the program included more uninterrupted time with patients, more complete hospital admission and discharge documentation, and positive patient and nurse feedback about the program. Knowledge models inform organizational behavior through the logical association of documentation processes, definitions, data elements, and value sets. The development of a well-designed knowledge model allows for the reuse of electronic health record data to promote efficiency in practice, data interoperability, and the extensibility of data to new capabilities or functionality such as clinical decision support, quality improvement, and research. The purpose of this article is to describe the development and validation of a knowledge model for healthcare-associated venous thromboembolism prevention. The team used FloMap, an Internet-based survey resource, to compare metadata from six healthcare organizations to an initial draft model. The team used consensus decision-making over time to compare survey results. The resulting model included seven panels, 41 questions, and 231 values. A second validation step included completion of an Internet-based survey with 26 staff nurse respondents representing 15 healthcare organizations, two electronic health record vendors, and one academic institution. The final knowledge model contained nine Logical Observation Identifiers Names and Codes panels, 32 concepts, and 195 values representing an additional six panels (groupings), 15 concepts (questions), and the specification of 195 values (answers). The final model is useful for consistent documentation to demonstrate the contribution of nursing practice to the prevention of venous thromboembolism. No abstract available Vulnerable populations face challenges gaining access to quality healthcare, which places them at a high risk for poor health outcomes. Using patient portals and secure messaging can improve patient activation, access to care, patient follow-up adherence, and health outcomes. Developing and testing quality improvement strategies to help reduce disparities is vital to ensure patient portals benefit all, especially vulnerable populations. This quality improvement initiative aimed to increase enrollment in a patient portal, use secure messages, and adhere to follow-up appointments. Before the project, no patients were enrolled in the portal at this practice site. Over 8 weeks, 61% of invited patients were enrolled in the patient portal. Eighty-five percent were Medicaid recipients, and the others were underinsured. Eight patients utilized the portal for secure messaging. The follow-up appointment attendance rate was better in the enrolled patients than in those who did not enroll. The majority of survey respondents reported satisfaction in using the patient portal. Patient portal utilization and adoption in vulnerable groups can improve when a one-on-one, hands-on demonstration and technical assistance are provided. Mobile healthcare has emerged as a prominent technological solution for self-management of health. However, the development and utilization of tailored mobile healthcare applications for older adults with diabetes mellitus remain limited. This study examined the relationship between social support and mobile healthcare use and further explored how this relationship varies with eHealth literacy and application design among older adults with diabetes mellitus. A descriptive cross-sectional trial was conducted with a structured self-report questionnaire, surveying 252 South Korean older adults with diabetes mellitus via offline and online modes. The mediating effect and moderated mediating effect were analyzed with the PROCESS macro of SPSS. eHealth literacy mediated the relationship between social support and mobile healthcare use. High levels of eHealth literacy and social support may increase mobile healthcare use among older adults with diabetes. Application design aesthetics facilitated mobile healthcare use. Future researchers, healthcare providers, and developers can contribute to the development of tailored mobile healthcare applications for older adults with diabetes mellitus by considering application design aspects such as font size, color, and menu configuration. This study aims to develop a virtual reality–based education program for managing behavioral and psychological symptoms of dementia for family carers of persons living with dementia and investigate the feasibility for users. The program was developed through literature review, interviews with family carers, surveys, and expert content validity assessment. User feasibility was evaluated quantitatively through a questionnaire on usefulness, ease of use, and satisfaction, and qualitatively through participant interviews. The program was produced in two parts, Type 1 and Type 2, consisting of three and six episodes, respectively. Participants showed a high level of satisfaction with overall program scores of 4.28 ± 0.66 and 4.34 ± 0.41 for the two evaluations. Participants also expressed that both programs were helpful, Type 1 for achieving changes in attitude associated with more understanding of persons living with dementia and Type 2 for acquiring coping methods through communication training. Use of the virtual reality device was not inconvenient and was identified as helpful due to the high immersion experience. Results of this study confirmed that family carers had no resistance to education using new technologies such as virtual reality devices and that virtual reality–based education could be effective for training family carers. The aim of this study was to describe medication administration and alert patterns among a cohort of new graduate nurses over the first year of practice. Medical errors related to clinical decision-making, including medication administration errors, may occur more frequently among new graduate nurses. To better understand nursing workflow and documentation workload in today's clinical environment, it is important to understand patterns of medication administration and alert generation during barcode-assisted medication administration. Study objectives were addressed through a descriptive, longitudinal, observational cohort design using secondary data analysis. Set in a large, urban medical center in the United States, the study sample included 132 new graduate nurses who worked on adult, inpatient units and administered medication using barcode-assisted medication administration. Data were collected through electronic health record and administration sources. New graduate nurses in the sample experienced a total of 587 879 alert and medication administration encounters, administering 772 unique medications to 17 388 unique patients. Nurses experienced an average medication workload of 28.09 medications per shift, 3.98% of which were associated with alerts, over their first year of practice. In addition to high volume of medication administration, new graduate nurses administer many different types of medications and are exposed to numerous alerts while using barcode-assisted medication administration. Documenting surgical supply items in the operating room can be a burdensome task for circulating nurses because of manual input within the electronic medical record. This can lead to documentation fatigue and contribute to nursing burnout. The aim of this quality improvement project was to design and implement a supply item scanning process and evaluate the effect on intraoperative documentation completion time, room turnover time, picklist documentation accuracy, nurse satisfaction, and burnout. The sample included nine acute care hospitals throughout the United States, with 189 total circulating nurses and 31 718 procedures occurring during the study timeframe of 8 months. Results indicated that nurses were able to complete documentation on average 37.33 minutes sooner, and the operating room turnover time decreased by 1.88 minutes. Although nurses reported that their perceived picklist documentation accuracy did not improve, and the presence of new scanning technology did not influence their hospital employment decision, subjective feedback was mostly positive, with most responses citing the helpfulness of scanning for documentation. This study shows that an interdisciplinary team can effectively work to optimize documentation efficiency and performance improvement using a scanning intervention. Lessons learned through this process can translate into optimizations elsewhere in the electronic medical record. Nonadherence to therapy negatively impacts mortality and quality of life and results in suboptimal efficacy of treatment regimens, threats to patient safety, and increased healthcare costs for disease management. Mobile health solutions can offer users instruments that can promote therapeutic adherence. The objective of this review is to investigate the impact mobile health systems have on therapeutic adherence. Specifically, we want to map the main systems used, the functions implemented, and the different methods of adherence detection used. For this purpose, a scoping review was conducted. The following databases were consulted: PubMed, Cochrane Library, EBSCO (including APA PsycINFO, CINAHL Plus with Full Text, ERIC), including English-language studies published in the last 10 years (2012–2022). The main mobile health systems used are as follows: applications, automated messaging, interactive voice response, and mobile video games. The main features implemented to support medication management were as follows: reminders, self-monitoring instruments, educational support, and caregiver involvement. In conclusion, the use of interactive mobile health instruments intended for use by the patient and/or caregiver can improve objectively and subjectively detected therapeutic adherence. The use of these systems in the therapeutic pathway of users, with a special focus on people with comorbidities and in polypharmacy treatment, represents a challenge to improve caregiver health. No abstract available Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and prioritizing injuries and illnesses on the frontlines of the emergency room. This study aims to create an Emergency Medical Rapid Triage and Prediction Assistance model using electronic medical records and machine learning techniques. Patient information was retrieved from the emergency department of a large regional teaching hospital in Taiwan, and five supervised learning techniques were used to construct classification models for predicting critical outcomes. Of these models, the model using logistic regression had superior prediction performance, with an F1 score of 0.861 and an area under the receiver operating characteristic curve of 0.855. The Emergency Medical Rapid Triage and Prediction Assistance model demonstrated superior performance in predicting intensive care and hospitalization outcomes compared with the Taiwan Triage and Acuity Scale and three clinical early warning tools. The proposed model has the potential to assist emergency nurses in executing challenging triage assessments and emergency teams in treating critically ill patients promptly, leading to improved clinical care and efficient utilization of medical resources. Computer-based technologies have been widely used in nursing education, although the best educational modality to improve documentation and nursing diagnostic accuracy using electronic health records is still under investigation. It is important to address this gap and seek an effective way to address increased accuracy around nursing diagnoses identification. Nursing diagnoses are judgments that represent a synthesis of data collected by the nurse and used to guide interventions and to achieve desirable patients' outcomes. This current investigation is aimed at comparing the nursing diagnostic accuracy, satisfaction, and usability of a computerized system versus a traditional paper-based approach. A total of 66 nursing students solved three validated clinical scenarios using the NANDA-International terminologies traditional paper-based approach and then the computer-based Clinical Decision Support System. Study findings indicated a significantly higher nursing diagnostic accuracy (P This retrospective bibliometric analysis was conducted to explore research trends and identify studies in fields of nursing, virtual reality, and cancer. Data were obtained from the Web of Science database using an advanced search strategy. The study data were analyzed using the R Studio software and visualized using VOSviewer. A total of 594 studies were retrieved and analyzed from January 1995 to December 2021. It was determined that 59.4% of the studies were research articles and that these studies had been conducted by 2771 authors. The reviewed studies were produced by researchers from 25 countries and were published in 29 different journals. Of these, 169 were conducted by researchers in the United States. “Virtual reality” and “nursing” were found to be prominent topics. Studies on virtual reality in patients with cancer in the field of nursing have increased over the past 8 years. Researchers have actively conducted studies in this field. Prominent studies have covered various patients with cancer in all age groups and palliative care processes. It was seen that the majority of the studies were randomized controlled trials, reviews, and systematic reviews. In addition, studies have used virtual reality as a distraction method in the management of symptoms in patients with breast, lung, and pediatric cancers undergoing chemotherapy treatment. This study provides a detailed and up-to-date analysis of the findings obtained from the Web of Science database by emphasizing bibliometric models of virtual reality technologies in nursing patients with cancer. We believe that the current data on the use of virtual reality applications in patients with cancer will guide the clinical practice and scientific studies of healthcare professionals. The International Classification for Nursing Practice is a comprehensive terminology representing the domain of nursing practice. A categorization of the diagnoses/outcomes and interventions may further increase the usefulness of the terminology in clinical practice. The aim of this study was to categorize the precoordinated concepts of the International Classification for Nursing Practice into subsets for nursing diagnoses/outcomes and interventions using the structure of an established documentation model. The aim was also to investigate the distribution of the precoordinated concepts of the International Classification for Nursing Practice across the different areas of nursing practice. The method was a descriptive content analysis using a deductive approach. The VIPS model was used as a theoretical framework for categorization. The results showed that all the precoordinated concepts of the International Classification for Nursing Practice could be categorized according to the keywords in the VIPS model. It also revealed the parts of nursing practice covered by the concepts of the International Classification for Nursing Practice as well as the parts that needed to be added to the International Classification for Nursing Practice. This has not been identified in earlier subsets as they covered only one specific area of nursing. 
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