Cin-Computers Informatics Nursing最新文献

The study aimed to determine the effects of game-based technology use in a first-aid lesson on knowledge and motivation. The study had a two-stage explanatory mixed-methods design. Quantitative data were collected as a randomized controlled trial. Qualitative data were collected through purposive sampling. A total of 202 nursing students were included and evaluated with a knowledge test and a teaching materials motivation questionnaire. A puzzle was applied to the intervention group before the first-aid lesson, and a Kahoot! was applied after the lesson. Four structured questions were asked to understand the students' thoughts about the game-based technology used. The students' pretest knowledge scores were similar. The mean posttest knowledge scores of the intervention group were significantly higher. However, the mean scores of the teaching materials motivation questionnaire were not high. The qualitative data analysis categorized students' opinions about the teaching materials as effective learning, enjoyable learning, and motivating learning. In conclusion, game-based technology methods in nursing practical lessons can enable students to apply the knowledge they learn in practice.

Zoom fatigue may affect nursing students, as there has been an increase in the use of videoconferencing for academic as well as clinical applications. Fatigue can negatively interfere with clinical decision-making and lead to clinical errors. This study aimed to explore the association between Zoom fatigue and perceived clinical decision-making ability of nursing students. This cross-sectional study assessed self-reported sociodemographic characteristics, Zoom fatigue, and clinical decision-making. Nursing students reported a medium level of Zoom fatigue (2.50 ± 0.78) and moderate effects on clinical decision-making (150.924 ± 12.561). Statistically significant differences were found between Zoom fatigue, the number of videoconferences held in the last month (rs = 0.065, P = .030), prolonged use of electronic devices (χ23 = 12.817, P = .005), and sex of the participants (U = 4043.500, P = .046). In addition, a negative relationship was observed between Zoom fatigue and clinical decision-making (rs = -0.519, P < .001). Nursing students have shown a moderate level of Zoom fatigue. The number of videoconferences attended as well as the prolonged use of electronic devices could increase students' level of Zoom fatigue. Students' perception of their clinical decision-making is moderate. As the Zoom fatigue levels of nursing students increased, their perception of clinical decision-making ability decreased. In the academic and clinical settings, there is a need to develop strategies to prevent Zoom fatigue in nursing students and improve the quality of care provided to patients.

This study aimed to compare Generations X, Y, and Z in terms of anxiety and readiness levels regarding artificial intelligence and investigate the relationship between anxiety and readiness levels regarding artificial intelligence in midwives across generations. This study is cross-sectional and comparative with a study sample of 218 midwives working in a province in the east of Turkey. Data were collected with the "Personal Information Form," "Artificial Intelligence Anxiety Scale," and "Medical Artificial Intelligence Readiness Scale." The evaluation of the data was carried out using the IBM SPSS Statistics version 22.0 (IBM Inc., Armonk, NY, USA) package program. Descriptive statistics, a one-way analysis of variance test, Pearson correlation, and regression analysis were used to analyze the data. The total mean score of midwives from the Artificial Intelligence Anxiety Scale was 47.07 ± 12.10 in Generation X, 43.91 ± 12.63 in Generation Y, and 36.16 ± 12.61 in Generation Z (P < .05), and the difference between the groups was significant. Generation X had a higher level of artificial intelligence anxiety than Generation Y, and Generation Y had higher levels of artificial intelligence than Generation Z. The total mean score of midwives from the Medical Artificial Intelligence Readiness Scale was 67.43 ± 14.28 in Generation X, 66.78 ± 17.83 in Generation Y, and 74.73 ± 16.15 in Generation Z (P < .05), and the difference between the groups was significant. Generation Z is more ready for medical artificial intelligence than Generation X, and Generation X is more ready for medical artificial intelligence than Generation Y. In addition, in the regression analysis, there was a weakly negative and significant relationship between the mean scores of Artificial Intelligence Anxiety Scale and Medical Artificial Intelligence Readiness Scale in Generation Z midwives, and as artificial intelligence anxiety levels increased, medical artificial intelligence readiness levels decreased. The artificial intelligence anxiety levels of midwives differed by generation, being highest in Generation X and lowest in Generation Z, and the level of medical artificial intelligence readiness was highest in Generation Z and lowest in Generation Y. As artificial intelligence anxiety increased in Generation Z midwives, the level of medical artificial intelligence readiness decreased.

Chatbots can change health behaviors by generating conversations about health. A well-designed health-related chatbot can encourage people to be physically active by creating a therapeutic relationship. This study aimed to develop and evaluate the feasibility and usability of a chatbot-based physical activity self-management application to promote physical activity among community-dwelling older adults. The physical activity self-management application was designed based on the five stages of the ADDIE model (analysis, design, development, implementation, and evaluation). The mobile application (app) includes a chatbot and physical activity videos as key components to provide support and guidance for physical activity enhancement and self-management. Quantitative pilot testing demonstrated that participants were highly satisfied with the app's usability, convenience, and overall satisfaction across all measures. Qualitative data analysis revealed that participants found it easy to watch and follow the videos as needed throughout the day and reported that the guidance and support from the chatbot helped motivate them to be more physically active. The findings suggest that it may be beneficial to expand the use of the chatbot-based physical activity self-management application to promote physical activity among older adults with chronic diseases and offer promising evidence for the feasibility of increasing mHealth accessibility for lifestyle modification interventions.

Given the significant global burden of congenital heart disease, there is an urgent need for innovative solutions to support and educate parents facing this challenge. This study aimed to construct and validate a virtual reality software, called CardioVR, to support congenital heart disease counseling. The process involved collaboration with 18 experts and 30 parents in three carefully managed stages, closely following the rigorous criteria outlined in the International Organization for Standardization/International Electrotechnical Commission 25010 standards. Remarkably, CardioVR achieved a remarkable content validity coefficient of 0.91 and exceeded the International Organization for Standardization/International Electrotechnical Commission criteria with more than 70% consensus. It excelled in key areas such as organization, clarity, visual appeal, self-efficacy enhancement, cultural appropriateness, and effectiveness. In addition, the System Usability Scale evaluation yielded a commendable score of 73.3%, confirming its ease of use and comprehension. The CardioVR software was considered valid and appropriate by experts and the target audience and can be used in the future as a support instrument for healthcare professionals assisting parents and caregivers of children with congenital heart diseases.

Through virtual reality technology, users experience challenging situations in a virtual world without physical experiences. This study aims to develop educational content using virtual reality to help patients undergoing magnetic resonance imaging and evaluate its usability. This pilot study developed virtual reality educational content using the ADDIE (analysis, design, development, implementation, and evaluation) model. An educational needs assessment targeted 20 experts and patients at a tertiary hospital. The content developed included pre-magnetic resonance imaging nursing, the magnetic resonance imaging process, and post-magnetic resonance imaging nursing. In pre-magnetic resonance imaging nursing, patients completed consent forms and received preparation instructions. The magnetic resonance imaging process included the environment, vision, and noise experienced during the examination. Post-magnetic resonance imaging nursing included precautions. An additional 12 experts and patients subsequently participated in virtual reality implementation and evaluation. Virtual reality evaluation included survey and semistructured face-to-face individual interviews. It scored 96.5 points out of 100 in usability, with little difference between experts' and patients' evaluations. In the qualitative evaluation, virtual reality educational content was revealed to be a useful approach, and the final virtual reality educational content was completed by reflecting the improvements suggested by participants. The findings offer tangible benefits for both healthcare professionals and patients by addressing the challenges associated with magnetic resonance imaging procedures through innovative educational interventions using virtual reality technology. Virtual reality educational content can be used as a practical training method in clinical settings.

Nurse burnout remains a significant problem affecting the nursing workforce today. However, despite calls for changes that could reduce clinician administrative burdens due to their relationship with burnout, minimal opportunities for improvement have been identified. Therefore, the purpose of this study was to investigate the relationship between nurse burnout and nurse satisfaction with the electronic health record (EHR). A cross-sectional survey was administered in 2018 to nurses practicing in the state of Alabama in the United States (N = 950). The survey inquired about participants' burnout, EHR satisfaction, and the nurse work environment. In multiple regression models, years of experience, nurse satisfaction with the EHR, and the nurse work environment explained 20%-34% of the variation in nurses' work-related burnout. Although additional research is needed, the EHR may be one actionable area that organizations could modify to help reduce nurse burnout.

The purpose of this study was to describe the development of a health literacy-focused heart failure self-care intervention (H2Lit Web-based app) and assess its usability using an online testing platform. We used an iterative approach, wherein participants evaluated more refined versions of H2Lit over four rounds of testing. Healthy participants were recruited for the earlier rounds of testing, and participants with heart failure were recruited for the final round. A total of 44 participants (10 participants with heart failure) were enrolled in the study. The participants had a mean age of 47.6 years, 57% were female, 70% identified as White, 70% were college-educated, and 34% had low health literacy. Using the System Usability Scale (score range of 0 to 100), the participants gave H2Lit a mean usability score of 74.1 in round 1, 54.3 in round 2, 85.3 in round 3, and 82.5 in round 4. H2Lit's usability score did not significantly differ between participants with adequate health literacy and those with low health literacy after controlling for age, sex, education level, and computer use duration. Further research is needed to determine the effect of the H2Lit intervention on heart failure self-care and heart failure-related outcomes.

This retrospective study of an electronic medical record database evaluated a modified training program aimed at improving documentation completion percentages in eight skilled nursing facilities across Tennessee, Ohio, Florida, and Wisconsin. The program involved a weeklong curriculum tailored to increase proficiency with the electronic medical record system, focusing on five key documentation forms: Admission Assessment, Morse Fall Risk Assessment, Braden Risk Assessment, Elopement Risk Assessment, and Weekly Skin Check. Data were collected between February 2023 and July 2023. A 3-month preimplementation phase served as the baseline control, representing the period prior to the nurses undergoing the modified training program. Data from the 3-month period after implementation was used for comparison. The sample included 47 nurses. Data analysis consisted of descriptive and inferential statistics, with two-tailed paired t tests showing significant mean improvements (P < .001) in documentation completion percentages ranging from 42% to 70% across all five forms. Although causality could not be inferred, significant improvements were observed following the training program.