Cin-Computers Informatics Nursing最新文献

Due to visiting restrictions at intensive care units during the COVID-19 pandemic, a digital video technology was developed and implemented. This study evaluated the use of digital visits at four intensive care units after COVID-19. Nurses' use of the technology and managerial perspectives on implementation were examined in an explanatory sequential mixed-methods study. Data were explored by inferential statistics (quantitative data) and content analysis (qualitative data). Results revealed that 52.9% of nurses had not used digital visits. Users indicated that the technology supported the patient-relative-nurse relationship, but needs reimplementation, aligning it with the post-COVID-19 setting.

The demands of contemporary everyday contexts have accelerated the deployment and adoption of emerging technologies, such as augmented reality, to enhance the learning experience. Traditionally, AR learning environments have been designed according to established instructional design principles. Now, it has become essential to update this approach by addressing the current demands of modern teaching and learning methods (eg, face-to-face and online learning) alongside technical issues related to augmented reality (eg, virtual scenarios). Additionally, the inclusion of software engineering methodologies can contribute to increased precision in the design process. In this sense, the current research presents a blended learning design model named UXpedite Learning Design, which integrates both instructional design and software engineering design approaches to facilitate the development of AR environments. The model comprises six phases: (i) needs assessment, (ii) ideation, (iii) prototyping, (iv) development, (v) technical testing, and (vi) user evaluation. A case study was conducted to demonstrate the implementation of the proposed model in developing the Virtual-Beat application, a tool designed to teach the interpretation of human vital sign measurements. Our tests indicate that using the Virtual-Beat application leads to slightly better learning outcomes compared with conventional classroom education, as evidenced by a statistically significant difference in examination scores between the experimental group (M = 7.53) and the control group (M = 7.08), t73 = 2.96, P = .004. Additionally, the User Experience Questionnaire completed by participants who used the application yielded positive results, highlighting a favorable overall experience (M = 1.465) and excellent attractiveness (M = 1.667). However, the assessment also identified a need for improvement in user interaction control. In conclusion, the findings suggest that the UXpedite Learning Design model shows promise for creating high-quality learning environments that align with the evolving needs of higher education.

This study presents a deep learning-based approach for assessing infant pain through facial expression analysis using Convolutional Neural Networks (CNNs). Given infants' inability to verbally articulate pain, reliable assessment methods are crucial in clinical nursing. To address this need, we developed a CNN model utilizing the COPE (Classification of Pain Expression) database. Our model achieved a test accuracy of 90.24%, with an average precision and recall of 87.58%, and an F1 score of 0.8758. Additionally, the model demonstrated high performance with an area under the curve of 0.9818 on the receiver operating characteristic curve. These results underscore the potential utility of CNNs for providing an objective pain assessment in clinical settings. However, the study acknowledges limitations, including a small sample size, the need for external validation, and ethical considerations. Future research should focus on expanding the dataset, conducting external validation, refining model architectures, and addressing ethical considerations to enhance performance and applicability. These efforts will advance infant pain management, ensure ethical integrity, and improve the overall quality of care.

Internet is women's primary source of information about cervical cancer and human papillomavirus. The aim of this study was to determine the associations of electronic health literacy with cervical cancer and human papillomavirus awareness among women of reproductive age. This is a cross-sectional study. The research sample consisted of 330 women of reproductive age (15-49 years), who were admitted to family health centers. The data were collected between July and August 2023 using eHealth Literacy Scale and the Cervical Cancer and Human Papillomavirus Awareness Questionnaire. Multiple linear regression analysis was performed to explore the predictors of cervical cancer and human papillomavirus awareness. In this study, the mean score of women's knowledge about cervical cancer and human papillomavirus was found to be low (4.54 ± 3.94), and the mean score of threat perception was found to be moderate (45.60 ± 6.54). eHealth literacy was found to be a predictor of women's knowledge about cervical cancer and human papillomavirus and threat perception. This result suggests that eHealth literacy should be considered for interventions to increase knowledge and awareness of women about cervical cancer and human papillomavirus.

Nursing care plans within electronic medical record systems have the potential to support nurses in planning and prioritizing patient care; however, there is a gap in the literature related to nurses' experiences of how this may occur. The aims of this mixed-methods study included exploring nurses' documentation adherence, identifying barriers and enablers to care plans documentation, and making recommendations to enhance nurses' use of care plans within electronic medical records. An audit of 142 patients revealed the majority had at least one care plan initiated in the electronic medical record (n = 120, 84.5%), 63 patients had a care plan initiated within 24 hours of admission (n = 63, 44.4%), and only three had care plans documented against in the previous 48 hours (2.11%). Data from six focus groups were developed into two themes (each with two subthemes): "Mind the Gap" and "Making It Work for Us." Barriers and enablers were identified and mapped to 10 of the 14 domains of the Theoretical Domains Framework. There was large variability in nurses' knowledge and understanding related to the need for care plans documentation. Assessment of usability and/or redesign of care plans within electronic medical records must align to nursing workflows to support clinical care delivery.

As technology continues to transform education, the adoption of generative artificial intelligence is increasing in nursing education. However, concerns regarding the accuracy of AI-generated content and ethical issues exist. This study explores the perceptions/experiences of nurse educators in South Korea regarding the use of generative artificial intelligence. Using a cross-sectional survey, data were gathered from 120 nurse educators, and descriptive statistical analysis was applied to the data. Significantly 38.9% of participants reported no prior engagement with generative artificial intelligence. Meanwhile, 32.5% identified ChatGPT as their preferred source. The perceived usefulness of generative artificial intelligence was evaluated on average as 3.11 (SD = 0.31) on a 4-point scale, suggesting a generally favorable view of its potential to diversify learning resources, enhance student learning experiences, and improve educational quality. Despite these positive perceptions, the average engagement score with generative artificial intelligence was 2.76 (SD = 0.40), reflecting moderate actual use. This study contributes to the literature on generative artificial intelligence integration in education, revealing an overall positive attitude among nurse educators. It underscores the need for increased application and familiarity with such technologies to maximize teaching strategy benefits, student outcomes, and the efficacy of nursing education.

Artificial intelligence and other digital health technologies may optimize nurses' work. Therefore, we aimed to examine the roles of nurses in facilitating the adoption of digital health technologies and identify opportunities for these technologies to reduce burnout. We conducted a cross-sectional survey study focused on nurses' use of digital health and artificial intelligence technology with nursing informaticists. Data collection was guided by the implementation science framework, Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability. Participants were recruited electronically through professional nursing informatics organizations. Survey data were analyzed using basic descriptive statistics. Fifty-two participants from across the United States completed the survey. Telehealth (73%), patient portals (71%), and medical-grade devices (69%) were most frequently used, whereas artificial intelligence was frequently used by only 38%. Staffing shortages (88%), low staff retention (81%), and inadequate support when adopting new technologies (52%) were among the key drivers of nursing burnout. Participants endorsed most nursing tasks as being supported by digital health, especially patient assessment and evaluating outcomes, and especially artificial intelligence. Engaging nurses early in the process of developing and deploying digital health, especially artificial intelligence, may help address burnout by producing more nursing-centered technologies and providing technology-enabled nursing work alternatives to bedside care.

This study used text network analysis and topic modeling to examine the knowledge structure of family-centered care in neonatal ICU nurses. Text was extracted from abstracts of 110 peer-reviewed articles published between 1995 and 2023 and analyzed by identifying keywords, topics, and changes in research topics over time. Analysis of keywords revealed significant terms including "infant," "family," "experience," "interventions," and "parent participation," highlighting family's central roles in family-centered care in neonatal ICU discourse. The research topics identified included "family-centered partnerships," "barriers to implementing family-centered care," "infant-mother attachment intervention," "family participation intervention," and "parenthood." Over time, research on family-centered care in neonatal ICUs nurses has steadily increased, with notable increases in "family-centered partnerships" and "barriers to implementing family-centered care." The findings underscore the evolving landscape of family-centered care in neonatal ICUs, emphasizing the critical role of collaborative care models in enhancing neonatal and familial outcomes. These insights provide a foundation for developing family-centered care programs that empower both nurses and families, supporting the holistic care of vulnerable infants. This study's results offer comprehensive insights into understanding family-centered care in the neonatal ICUs and could serve as a foundation for future studies to develop family-centered care programs for neonatal ICU nurses and families. Based on this study, it is recommended that nursing education programs integrate family-centered care training into their curricula, with an emphasis on communication, cultural competence, and family partnerships.

This study analyzed the gaps in clinical guidelines for the Institute for Clinical Systems Improvement by using the Omaha System. Clinicians use various Non-Opioid approaches for pain management, leading to diverse coding requirements when inputting data into EHRs. Consequently, the lack of standardized coding for Non-Opioid pain management data leads to inconsistencies, hindering effective information transfer and reuse between care settings, impacting continuity of care. By encoding guidelines within the Omaha System, this study aims to create a standardized framework that enhances data integration and promotes seamless communication across healthcare environments. To address this, pain management guidelines for Non-Opioid approaches were mapped using the Omaha System, with a focus on content feasibility, linguistic validity, and term granularity. The analysis revealed three problems, three categories, and 11 targets in the coding of Non-Opioid approaches for pain management. By integrating guidelines encoded within EHRs, the development of improved guidelines is facilitated, enhancing their efficient utilization and thereby improving nursing records and information delivery systems. In conclusion, this approach addresses the need for standardized coding, advancing both guideline development and continuity of care through improved information systems.