Cin-Computers Informatics Nursing最新文献

Episodes of decompensation are the main cause of hospital admissions in patients with heart failure. For this reason, the use of mobile apps emerges as an excellent strategy to improve coverage, real-time monitoring, and timeliness of care. ControlVit is an electronic application for early detection of complications studied within the context of a tertiary university hospital. Patients were randomized to the use of ControlVit versus placebo, during a 6-month follow-up. The primary outcome was the difference in numbers of readmissions and deaths for heart failure between both groups. One hundred forty patients were included (intervention = 71, placebo = 69), with an average age of 66 years old; 71% were men. The main etiology of heart failure was ischemic (60%), whereas the main comorbidities were arterial hypertension (44%), dyslipidemia (42%), hypothyroidism (38%), chronic kidney disease (38%), and diabetes mellitus (27%). The primary outcome occurred more frequently in the control group: readmission due to decompensation for heart failure (control group n = 14 vs intervention group n = 3; P = .0081), and death (control group n = 11 vs intervention group n = 3; P = .024). In heart failure patients, ControlVit is a useful and supplementary tool, which reduces hospital admissions due to episodes of decompensation.

COVID-19 has provided a unique boost to the use of digital healthcare technology, putting many vulnerable people at risk of digital exclusion. To promote digital healthcare equity, it is important to identify the challenges that may inhibit cancer patients and family caregivers from benefiting from such technology. This study explored the challenges that cancer patients and family caregivers experience in using digital healthcare technology platforms during the COVID-19 pandemic. A qualitative descriptive study using face-to-face semistructured individual interviews was carried out. A purposive sample of 21 participants was recruited from a public cancer hospital in Saudi Arabia. Qualitative content analysis with an inductive approach was utilized. The factors that challenged the ability of participants to benefit from digital healthcare technology were similar. Four themes related to the challenges the two groups experienced emerged: access to platforms, use of platforms for cancer health-related purposes, attitudes toward these platforms, and individual user preferences. This study identified numerous areas for improvement regarding digital healthcare technology platform implementation, which could increase future benefits and equal use. This study's findings also provide useful information to investigators who intend to create digital nursing interventions for both groups amid COVID-19 and other worldwide health crises.

Health literacy requires skills of reading, understanding, and analyzing text, numbers, graphs, and diagrams to make well-informed decisions. The increase advancement in technologies has made health information accessible in electronic format. Individuals must apply health literacy in navigating through health information resources on the Internet. Filipino Americans originating from a diverse background are often underreported and underrepresented in health research. The study aim was to examine electronic health literacy among Filipino Americans using the Electronic Health Literacy Scale survey. The descriptive study recruited 103 participants. Overall Filipino Americans are electronic health literate, with a mean of 32.4 ( SD = 4.6). Females ( P = .017), those with graduate or professional degrees ( P = .004) and working in healthcare ( P = .040) tend to have higher electronic health literacy. The study provided valuable insight on electronic health literacy on a population that is underrepresented in research. The descriptive data gained from the study lays foundational work to help decrease health inequities experienced by Filipino Americans.

Empathy is significant in nursing, and showing empathy toward a patient positively impacts a patient's health. Learning empathy through immersive simulations is effective. Immersion is an essential factor in virtual reality. This study aimed to describe nursing students' experiences of empathy in a virtual reality simulation game. Data were collected from nursing students (n = 20) from May 2021 to January 2022. Data collection included individual semistructured interviews; before the interviews, the virtual reality gaming procedure was conducted. Inductive content analysis was used. Nursing students experienced compassion and a feeling of concern in the virtual reality simulation game. Students were willing to help the virtual patient, and they recognized the virtual patient's emotions using methods such as listening and imagining. Students felt the need to improve the patient's condition, and they responded to the virtual patient's emotions with the help of nonverbal and verbal communication and helping methods. Empathy is possible to experience by playing virtual reality simulation games, but it demands technique practicing before entering the virtual reality simulation game.

Family-centered care is an approach to promote the health and well-being of children with chronic diseases and their families. This study aims to explore the knowledge components, structures, and research trends related to family-centered care for children with chronic conditions. We conducted the keyword network analysis in three stages using the keywords provided by the authors of each study: (1) search and screening of relevant studies, (2) keyword extraction and refinement, and (3) data analysis and visualization. The core keywords were child, adolescence, parent, and disabled. Four cohesive subgroups were identified through degree centrality. Research trends in the three phases of a recent decade have been changed. With the systematic understanding of the context of the knowledge structure, the future research and effective strategy establishment are suggested based on family-centered care for children with chronic disease.

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.

Electronic health record proficiency is critical for health professionals to deliver and document patient care. There is scarce research on this topic within undergraduate nursing student populations. The purpose of this study is to describe the psychometric evaluation of the Digital Literacy, Usability, and Acceptability of Technology Instrument for Healthcare. A cross-sectional pilot study for psychometric evaluation of the instrument was conducted using data collected through an emailed survey. Exploratory factor analysis, inter-item and adjusted item-total correlations, and Cronbach's α calculated subscale reliability. A total of 297 nursing students completed the survey. A seven-factor structure best fit the data: technology use-engagement, technology use-confidence, technology use-history, electronic health record-ease of use, electronic health record-comparability, and electronic health record-burden. Cronbach's α indicated good to very good internal consistency (α = .68 to .89). The instrument effectively measured digital literacy, acceptance, and usability of an electronic health record and may be implemented with good to very good reliability across varied healthcare simulation and training experiences.