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There is an increasing need for highly accessible health management platforms for comprehensive symptoms of Parkinson disease. Mobile apps encompassing nonmotor symptoms have been rarely developed since these symptoms are often subjective and difficult to reflect what individuals actually experience. The study developed an app for comprehensive symptom management and evaluated its usability and feasibility. A single-group repeated measurement experimental design was used. Twenty-two participants used the app for 6 weeks. Monitoring of nonmotor symptoms, games to address motor symptoms, and medication management were incorporated in the app. Quantitative outcomes were self-assessed through an online questionnaire, and one-on-one telephone interviews were conducted to understand the user's point of view. The successful experience of self-monitoring had improved participants' self-efficacy (Z = −3.634, P 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. No abstract available 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. 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 No abstract available No abstract available Clinical practice nurses need adequate digital competence to use technologies appropriately at work. Questionnaires measuring clinical practice nurses' digital competence lack content validity because attitude is not included as a measure of digital competence. The aim of the current study was to identify items for an item pool of a questionnaire to measure clinical practice nurses' digital competence and to evaluate the content validity. A normative Delphi study was conducted, and the content validity index on item and scale levels was calculated. In each round, 21 to 24 panelists (medical informatics specialists, nurse informatics specialists, digital managers, and researchers) were asked to rate the items on a 4-point Likert scale ranging from “not relevant” to “very relevant.” Within three rounds, the panelists reached high consensus and rated 26 items of the initial 37 items as relevant. The average content validity index of 0.95 (SD, 0.07) demonstrates that the item pool showed high content validity. The final item pool included items to measure knowledge, skills, and attitude. The items included represent the international recommendations of core competences for clinical nursing. Future research should conduct psychometric testing for construct validity and internal consistency of the generated item pool. This study aimed to evaluate the effect of virtual reality simulation in nursing education in five domains: knowledge, skill performance, self-confidence, self-efficacy, and satisfaction. Randomized controlled trials were obtained from the databases SCOPUS, Web of Science, PubMed, and EBSCO from inception until September 2021. The standardized mean differences with 95% confidence intervals were determined for the main variables, and heterogeneity was analyzed using the I2 test. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Checklist was used. Meta-analysis was performed using the Stata 15.0 software. Among the 2074 records identified, 18 trials were included. The meta-analysis of these trials indicated that virtual reality simulation caused a significant improvement in knowledge with a moderate effect, skill performance with a moderate effect, and satisfaction with a moderate effect compared with the control group. However, virtual reality simulation did not significantly influence self-confidence and self-efficiency. The findings of this study suggested that virtual reality simulation might significantly benefit knowledge, skill performance, and satisfaction but not self-confidence and self-efficiency. Further well-designed randomized controlled trials with a larger sample size are recommended to confirm these findings. 
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