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OBJECTIVE: The study aimed to develop natural language processing (NLP) algorithms to automate extracting patient-centred breast cancer treatment outcomes from clinical notes in electronic health records (EHRs), particularly for women from under-represented populations. METHODS: The study used clinical notes from 2010 to 2021 from a tertiary hospital in the USA. The notes were processed through various NLP techniques, including vectorisation methods (term frequency-inverse document frequency (TF-IDF), Word2Vec, Doc2Vec) and classification models (support vector classification, K-nearest neighbours (KNN), random forest (RF)). Feature selection and optimisation through random search and fivefold cross-validation were also conducted. RESULTS: The study annotated 100 out of 1000 clinical notes, using 970 notes to build the text corpus. TF-IDF and Doc2Vec combined with RF showed the highest performance, while Word2Vec was less effective. RF classifier demonstrated the best performance, although with lower recall rates, suggesting more false negatives. KNN showed lower recall due to its sensitivity to data noise. DISCUSSION: The study highlights the significance of using NLP in analysing clinical notes to understand breast cancer treatment outcomes in under-represented populations. The TF-IDF and Doc2Vec models were more effective in capturing relevant information than Word2Vec. The study observed lower recall rates in RF models, attributed to the datasets imbalanced nature and the complexity of clinical notes. CONCLUSION: The study developed high-performing NLP pipeline to capture treatment outcomes for breast cancer in under-represented populations, demonstrating the importance of document-level vectorisation and ensemble methods in clinical notes analysis. The findings provide insights for more equitable healthcare strategies and show the potential for broader NLP applications in clinical settings.

The document outlines the Advanced Pharmacy Australia Clinical Pharmacy Standards, emphasizing person-centered care, training, and workforce development for clinical pharmacy services. It highlights the importance of safe medication management, patient prioritization, and collaboration in optimizing health outcomes. Guidelines for conducting patient/carer medication history interviews are provided, stressing the need for accuracy, privacy, and collaboration among healthcare professionals. The text also encourages ongoing evaluation, research, and innovation in pharmacy practice to enhance patient care outcomes and support evidence-based practice. [Extracted from the article]

Background Methods Results Conclusions Clinical Relevance The healthcare industry increasingly values high‐quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real‐time artificial intelligence (AI)‐based CDS tool.We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note–derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians.Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing–driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions.This study discusses the creation of a time‐series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF.This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day‐to‐day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations. [ABSTRACT FROM AUTHOR]

Objectives To explore home healthcare (HHC) clinicians' needs for Clinical Decision Support Systems (CDSS) information delivery for early risk warning within HHC workflows. Methods Guided by the CDS "Five-Rights" framework, we conducted semi-structured interviews with multidisciplinary HHC clinicians from April 2023 to August 2023. We used deductive and inductive content analysis to investigate informants' responses regarding CDSS information delivery. Results Interviews with thirteen HHC clinicians yielded 16 codes mapping to the CDS "Five-Rights" framework (right information, right person, right format, right channel, right time) and 11 codes for unintended consequences and training needs. Clinicians favored risk levels displayed in color-coded horizontal bars, concrete risk indicators in bullet points, and actionable instructions in the existing EHR system. They preferred non-intrusive risk alerts requiring mandatory confirmation. Clinicians anticipated risk information updates aligned with patient's condition severity and their visit pace. Additionally, they requested training to understand the CDSS's underlying logic, and raised concerns about information accuracy and data privacy. Discussion While recognizing CDSS's value in enhancing early risk warning, clinicians highlighted concerns about increased workload, alert fatigue, and CDSS misuse. The top risk factors identified by machine learning algorithms, especially text features, can be ambiguous due to a lack of context. Future research should ensure that CDSS outputs align with clinical evidence and are explainable. Conclusion This study identified HHC clinicians' expectations, preferences, adaptations, and unintended uses of CDSS for early risk warning. Our findings endorse operationalizing the CDS "Five-Rights" framework to optimize CDSS information delivery and integration into HHC workflows. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Design Methods Data Sources Results Conclusion Implications for the Profession Impact Reporting Method Patient or Public Contribution To assess the top 1000 cited nursing articles in terms of their impact, conceptual and social characteristics.Bibliometric literature review design.A bibliometric analysis on the 1000 most cited nursing articles in English, focusing on assessing their impact and prevalent terms, keywords, co‐occurrence networks and topic trends. Non‐parametric statistical tests were used.Web of Science Core Collection (accessed 14 February 2024).The 1000 most cited articles were exported from 201,310 eligible articles.The most cited articles received a total of 319,643 citations. The Journal of Advanced Nursing and the International Journal of Nursing Studies were the most cited journals. Literature reviews accounted for 21% of the most cited articles, compared to only 7% of all eligible articles. Most first authors were female, 63%. The data showed an increase in female first authorship among the most cited articles over time. This may reflect a shift towards greater gender equity in nursing research. Shorter article titles and fewer article pages were associated with more citations.Methodological and conceptual articles received the most citations, likely due to their broad applicability (e.g., across disciplines) and enduring relevance. There was a statistically significant correlation between article brevity and citation count, but the relationship should be viewed with caution given the small effect size.Bibliometrics is important for evidence‐based practice because it helps nurses evaluate journals, articles and research topics. Since citation counts do not always indicate research quality, nurses and nursing students would benefit from training in bibliometrics to enhance their critical thinking in this area.Top‐cited nursing articles indicate influential research topics and methods. They also influence authors' academic career opportunities, allowing assessment of research equity in terms of dominant countries and author gender representation.The Preferred Reporting Items for Bibliometric Analysis (PRIBA) guidelines.No Patient or Public Contribution. [ABSTRACT FROM AUTHOR]

Background: The biomedical and health informatics (BMHI) fields have been advancing rapidly, a trend particularly emphasised during the recent COVID-19 pandemic, introducing innovations in BMHI. Over nearly 50 years since its establishment as a scientific discipline, BMHI has encountered several challenges, such as mishaps, delays, failures, and moments of enthusiastic expectations and notable successes. This paper focuses on reviewing the progress made in the BMHI discipline, evaluating key milestones, and discussing future challenges. Methods: To, Structured, step-by-step qualitative methodology was developed and applied, centred on gathering expert opinions and analysing trends from the literature to provide a comprehensive assessment. Experts and pioneers in the BMHI field were assigned thematic tasks based on the research question, providing critical inputs for the thematic analysis. This led to the identification of five key dimensions used to present the findings in the paper: informatics in biomedicine and healthcare, health data in Informatics, nurses in informatics, education and accreditation in health informatics, and ethical, legal, social, and security issues. Results: Each dimension is examined through recently emerging innovations, linking them directly to the future of healthcare, like the role of artificial intelligence, innovative digital health tools, the expansion of telemedicine, and the use of mobile health apps and wearable devices. The new approach of BMHI covers newly introduced clinical needs and approaches like patient-centric, remote monitoring, and precision medicine clinical approaches. Conclusions: These insights offer clear recommendations for improving education and developing experts to advance future innovations. Notably, this narrative review presents a body of knowledge essential for a deep understanding of the BMHI field from a human-centric perspective and, as such, could serve as a reference point for prospective analysis and innovation development. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Design Methods Results Conclusion Implications Impact Reporting Method Patient or Public Contribution To utilise natural language processing (NLP) to analyse interviews about the impact of COVID‐19 in underserved communities and to compare it to traditional thematic analysis in a small subset of interviews.NLP and thematic analysis were used together to comprehensively examine the interview data.Fifty transcribed interviews with purposively sampled adults living in underserved communities in the United States, conducted from June 2021 to May 2022, were analysed to explore the impact of the COVID‐19 pandemic on social activities, mental and emotional stress and physical and spiritual well‐being. NLP includes several stages: data extraction, preprocessing, processing using word embeddings and topic modelling and visualisation. This was compared to thematic analysis in a random sample of 10 interviews.Six themes emerged from thematic analysis: The New Normal, Juxtaposition of Emotions, Ripple Effects on Health, Brutal yet Elusive Reality, Evolving Connections and Journey of Spirituality and Self‐Realisation. With NLP, four clusters of similar context words for each approach were analysed visually and numerically. The frequency‐based word embedding approach was most interpretable and well aligned with the thematic analysis.The NLP results complemented the thematic analysis and offered new insights regarding the passage of time, the interconnectedness of impacts and the semantic connections among words. This research highlights the interdependence of pandemic impacts, simultaneously positive and negative effects and deeply individual COVID‐19 experiences in underserved communities.The iterative integration of NLP and thematic analysis was efficient and effective, facilitating the analysis of many transcripts and expanding nursing research methodology.While thematic analysis provided richer, more detailed themes, NLP captured new elements and combinations of words, making it a promising tool in qualitative analysis.Not applicable.No patient or public contribution. [ABSTRACT FROM AUTHOR]

A rapid expansion of the computer technology industry, particularly in the field of artificial intelligence, has ignited a global concern that warrants our immediate action. As nurses, our professional values frameworks compel us to protect public health and address national and global health issues. When industry activities adversely affect the social wellbeing of civil society and social institutions, it is important to evaluate them against their industry's 'social license to operate,' which is a measure of public trust, credibility, and the legitimacy of their industrial and corporate citizenship status. The central question is, do computer technology companies continue to have a social license to operate in civil society? Nurses are encouraged to evaluate the computer technology industry's recent 'generative artificial intelligence' chatbot activities against its tacit undertaking to be good corporate citizens in return for social acceptance of their operations and behaviour. An evidence-based overview of chatbot impacts on societies, environmental sustainability and human rights provide a basis for evaluation. Basic computer technology terminology and relevant concepts are explained. This article is a direct call to action for clinical nurses and those involved in research, education, management, and policy. We have a duty to critically assess the claims made by chatbot technology vendors in both practice and social contexts. If these vendors integrate chatbot technologies with existing machine learning used in nursing and healthcare technologies it could result in detrimental effects beyond user control. By influencing decisions on technology adoption, we can ensure the implementation of safeguards, protect patient safety and social well-being, and uphold the integrity of nursing values. A closing discussion of impacts of computer industry trust deficits on healthcare and research reflects the author's concerns and conclusions about the central question. Readers may draw other conclusions and perhaps use the issues and evidence presented here to stimulate further investigations. [ABSTRACT FROM AUTHOR]

Objective: This study aims to examine the impact of nurses' nursing information competence on their creative self-efficacy and innovation behavior, and to investigate its role as a mediating factor between these two elements. Methods: A survey was conducted from July to September 2023 involving 1,200 nurses from two tertiary-level oncology specialty hospitals in Beijing, selected through convenience sampling. Instruments used included the Creative Self-Efficacy Scale, Nursing Information Competence Assessment Scale, and Nurses' Innovative Behavior Scale. Data analysis was conducted using SPSS 25.0 and R 4.1.2; AMOS26 was used to construct structural equation models and Bootstrap method was used to test the mediating hypotheses. Results: Out of the distributed questionnaires, 1,166 were valid, yielding an effective response rate of 97.16%. Pearson correlation analysis revealed significant correlations between innovation self-efficacy, nursing information competence, and nurses' innovative behaviors (P < 0.001). The Bootstrap method indicated that nursing information competence serves as a mediating factor in the relationship between creative self-efficacy and innovative behaviors, contributing to 24.5% of the observed effect. Additionally, regression analysis suggested that nursing information competence moderates the relationship between creative self-efficacy and innovation behavior. Conclusion: The findings suggest that nursing information competence not only mediates but also moderates the relationship between creative self-efficacy and innovative behavior. Enhancing nurses' information competence could therefore foster creative self-efficacy, leading to an increase in innovative behavior and, subsequently, improvements in the quality of oncology nursing care. [ABSTRACT FROM AUTHOR]

Artificial intelligence revolutionizes nursing informatics and healthcare by enhancing patient outcomes and healthcare access while streamlining nursing workflow. These advancements, while promising, have sparked debates on traditional nursing ethics like patient data handling and implicit bias. The key to unlocking the next frontier in holistic nursing care lies in nurses navigating the delicate balance between artificial intelligence and the core values of empathy and compassion. Mindful utilization of artificial intelligence coupled with an unwavering ethical commitment by nurses may transform the very essence of nursing. [ABSTRACT FROM AUTHOR]

With the increasing use of technology in nursing, how nurses perform practice care has changed, inevitably leading to ethical concerns that differ from original ethical norms in nursing. Studies have focused on ethical issues in health informatics from clinicians' or patients' perspectives, while nurses' perspective is needed. This paper conducts a theoretical study on ethical predicaments that arise in nursing informatics from nurses' perspectives. Why and how these predicaments emerge are elaborated. Also, this paper offers countermeasures in realistic contexts from technique, education, and leadership aspects. Collaborations between governments, administrators, educators, technicians, and nurses are needed to step out of these predicaments. [ABSTRACT FROM AUTHOR]

With artificial intelligence (AI) rapidly advancing, advanced practice nurses must understand and use it responsibly. Here, we describe an assignment in which Doctor of Nursing Practice (DNP) students learned to use generative text AI. Using our program and course outcomes, developed from the 2021 American Association of Colleges of Nursing (AACN) Essentials competency for DNP students to learn and use AI, we reviewed the literature seeking examples using ChatGPT for the DNP informatics course. No published examples existed to guide us toward infusing a ChatGPT assignment into the course. We developed a novel assignment that included a guide for students on how to use ChatGPT. Students were given time before the assignment to learn the AI/chatbot technology. They were then given the assignment and grading rubric. The assignment was to develop a tool for their current or future practice using ChatGPT. During the course faculty debrief, we learned that few students had questions and the assignment was clear. We also learned that students who sought to develop straightforward, uncomplicated patient tools succeeded with the technology. Those who sought to create something for complex patients had more challenges. Nursing education and practice will be influenced by the increasing prevalence of AI. This manuscript outlines an AI-based assignment for graduate nursing education intended for the students to become familiar with current AI and best practices for patient care. The assignment was well received by students. We plan to use it again in the next course offering. [ABSTRACT FROM AUTHOR]

Background: Technology in health care is pervasive and growing exponentially. Simulation in academic settings also continues to expand with the use of advancing technologies. Problem: Technology appropriate usage and implementation can become problematic without experts with the right skills in nursing simulation labs. Gaps in technology utilization, simulation best practices, and data analytics now exist. Approach: A school of nursing employed a nurse informaticist in its simulation laboratory to address the complexities of technology usage and aid in data analytics. Outcomes: The nurse informaticist was effective at promoting simulation use, increasing faculty and learner usage of the simulation space. The initiation of data capturing was also achieved. Conclusions: Highly trained nurse informaticists are ready to address the unique complexities of advanced simulation environments. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Objective This study aims to examine the impact of nurses’ nursing information competence on their creative self-efficacy and innovation behavior, and to investigate its role as a mediating factor between these two elements. Methods A survey was conducted from July to September 2023 involving 1,200 nurses from two tertiary-level oncology specialty hospitals in Beijing, selected through convenience sampling. Instruments used included the Creative Self-Efficacy Scale, Nursing Information Competence Assessment Scale, and Nurses’ Innovative Behavior Scale. Data analysis was conducted using SPSS 25.0 and R 4.1.2; AMOS26 was used to construct structural equation models and Bootstrap method was used to test the mediating hypotheses. Results Out of the distributed questionnaires, 1,166 were valid, yielding an effective response rate of 97.16%. Pearson correlation analysis revealed significant correlations between innovation self-efficacy, nursing information competence, and nurses’ innovative behaviors (P

Aim: This study explored the knowledge and confidence levels of nursing academics in teaching both the theories and practical skills of digital health in undergraduate nursing programs. Design: A cross‐sectional study. Methods: A structured online survey was distributed among nursing academics across Australian universities. The survey included two sections: (1) the participants' demographics and their nursing and digital health teaching experience; (2) likert scales asking the participants to rate their knowledge and confidence to teach the theories and practical skills of four main themes; digital health technologies, information exchange, quality and digital professionalism. Results: One hundred and nineteen nursing academics completed part one, and 97 individuals completed part two of the survey. Only 6% (n = 5) of the participants reported having formal training in digital health. Digital health was mainly taught as a module (n = 57, 45.9%), and assessments of theory or practical application of digital health in the nursing curriculum were uncommon, with 79 (69.9%) responding that there was no digital health assessment in their entry to practice nursing programs. Among the four core digital health themes, the participants rated high on knowledge of digital professionalism (22.4% significant knowledge vs. 5.9% no knowledge) but low on information exchange (30% significant knowledge vs. 28.3% no knowledge). Statistically significant (p <.001) associations were found between different themes of digital health knowledge and the level of confidence in teaching its application. Nursing academics with more than 15 years of teaching experience had a significantly higher level of knowledge and confidence in teaching digital health content compared with those with fewer years of teaching experience. Conclusion: There is a significant gap in nursing academics' knowledge and confidence to teach digital health theory and its application in nursing. Nursing academics need to upskill in digital health to prepare the future workforce to be capable in digitally enabled health care settings. Implications for the Profession: Nursing academics have a limited level of digital knowledge and confidence in preparing future nurses to work in increasingly technology‐driven health care environments. Addressing this competency gap and providing sufficient support for nursing academics in this regard is essential. Impact: What problem did the study address? Level of knowledge and confidence among nursing academics to teach digital health in nursing practice.What were the main findings? There is a significant gap in nursing academics' knowledge and confidence to teach digital health theory and its application in nursing.Where and on whom will the research have an impact? Professional nursing education globally. Reporting Method: The STROBE guideline was used to guide the reporting of the study. Patient or Public Contribution: The call for participation from nursing academics across Australia provided an introductory statement about the project, its aim and scope, and the contact information of the principal researcher. A participant information sheet was shared with the call providing a detailed explanation of participation. Nursing academics across Australia participated in the survey through the link embedded in the participation invite. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this study was to analyze proposed Korean nursing legislation as depicted in newspaper articles, to highlight issues related to the legislative process for this potential law, and to better understand social awareness regarding this matter. Methods: The study focused on articles from 11 leading newspapers in Korea, published between February 2020 and August 2023, that pertained to nursing legislation. The articles were retrieved from the BigKinds database. Following text preprocessing, analytical methods including term frequency-inverse document frequency were employed, along with latent Dirichlet allocation (LDA), for word and topic modeling analysis. Additionally, LDA was applied across time periods to examine temporal changes in topics. Results: Following preprocessing, a total of 7,967 words were extracted from the 991 articles selected for analysis. The primary themes identified in newspaper articles concerning the nursing legislation were organized into three main topics: 1) the necessity and impact of enactment of the nursing law, 2) the political context surrounding enactment of the law, and 3) the conflicts between and actions of healthcare organizations related to enactment of the law. Conclusions: The findings confirmed that media coverage regarding the proposed nursing legislation primarily concentrated on the political and social conflicts associated with the law's passage, rather than its necessity and substance. More compelling evidence must be presented concerning the influence of the nursing workforce and the work environment of nurses on patient safety and health outcomes. Additionally, strategies should be devised to improve public comprehension of the nursing law's provisions. [ABSTRACT FROM AUTHOR]

As a significant technological innovation in the fields of medicine and geriatric care, smart care wheelchairs offer a novel approach to providing high-quality care services and improving the quality of care. The aim of this review article is to examine the development, applications and prospects of smart nursing wheelchairs, with particular emphasis on their assistive nursing functions, multiple-sensor fusion technology, and human–machine interaction interfaces. First, we describe the assistive functions of nursing wheelchairs, including position changing, transferring, bathing, and toileting, which significantly reduce the workload of nursing staff and improve the quality of care. Second, we summarized the existing multiple-sensor fusion technology for smart nursing wheelchairs, including LiDAR, RGB-D, ultrasonic sensors, etc. These technologies give wheelchairs autonomy and safety, better meeting patients' needs. We also discussed the human–machine interaction interfaces of intelligent care wheelchairs, such as voice recognition, touch screens, and remote controls. These interfaces allow users to operate and control the wheelchair more easily, improving usability and maneuverability. Finally, we emphasized the importance of multifunctional-integrated care wheelchairs that integrate assistive care, navigation, and human–machine interaction functions into a comprehensive care solution for users. We are looking forward to the future and assume that smart nursing wheelchairs will play an increasingly important role in medicine and geriatric care. By integrating advanced technologies such as enhanced artificial intelligence, intelligent sensors, and remote monitoring, we expect to further improve patients' quality of care and quality of life. [ABSTRACT FROM AUTHOR]

AbstractPurposeMaterials and methodsResultsConclusionsThe purpose of this study is to explore student perceptions of generative AI use and cheating in health professions education. The authors sought to understand how students believe generative AI is acceptable to use in coursework.Five faculty members surveyed students across health professions graduate programs using an updated, validated survey instrument. Students anonymously completed the survey online, which took 10–20 min. Data were then tabulated and reported in aggregate form.Nearly 400 students from twelve academic programs including health and rehabilitation science, occupational therapy, physical therapy, physician assistant studies, speech-language pathology, health administration and health informatics, undergraduate healthcare studies, nurse anesthesiology, and cardiovascular perfusion. The majority of students identify the threat of generative AI to graded assignments such as tests and papers, but many believe it is acceptable to use these tools to learn and study outside of graded assignments.Generative AI tools provide new options for students to study and learn. Graduate students in the health professions are currently using generative AI applications but are not universally aware or in agreement of how its use threatens academic integrity. Faculty should provide specific guidance on how generative AI applications may be used. [ABSTRACT FROM AUTHOR]

Background: Despite the growing adoption of digital health tools as a means to support mental health, many individuals remain unaware of the variety of mental health resources available to them through this format. To address this knowledge gap, this study advanced the design, development, and implementation of a text-based service called SaskWell to raise awareness of evidence based mental health resources and create more immediate connections to these tools. The two primary objectives of the study were to assess and evaluate the adoption of SaskWell by focusing on user acceptance, satisfaction, and perceived benefit, and to identify factors which contributed to user engagement with the SaskWell text-based service. Both quantitative and qualitative data contributed to the final study results. Results: This study utilized a co-designed text-messaging service to provide residents of Saskatchewan an important connection to digital mental health and wellness resources during the height of the COVID-19 pandemic. Using the RE-AIM framework as an implementation guide, four distinct cycles of SaskWell were delivered with modifications to the service in each subsequent cycle based on user engagement, feedback, and the direction of a community advisory group. Quantitative data was collected through user engagement text message response data, along with enrollment and exit surveys, while semi-structured interviews served as the primary means of qualitative data collection. In addition to the quantitative user data, these user interviews resulted in themes exploring motivation to sign-up for the service, perceptions of texting as a mechanism to deliver mental health resources, the impact of SaskWell on mental health and well-being, and beliefs on the future potential of text-based mental health supports. Conclusions: Both the user engagement survey and the qualitative data supported the worth of ongoing efforts to refine and extend the use of text messaging as a means to engage citizens around the awareness and use of digital mental health and wellness resources. As the pandemic has receded into the background in many peoples' daily lives, for healthcare providers, and others who continue to be impacted more heavily by the persistent challenges of this global event, this type of service may continue to be timely. [ABSTRACT FROM AUTHOR]

Aim: This study examines the intricate language and communication patterns of nurse‐to‐nurse handoffs across three units with varying patient acuity levels and nurse–patient ratios, seeking to identify linguistic factors that may affect the quality of information transfer and patient outcomes. Design: A mixed‐methods cross‐sectional design. Methods: This study used the Nurse‐to‐Nurse Transition of Care Communication Model to explore the content and meaning of language in nursing handoffs within a large academic medical centre. Data were collected on three units through digital audio recordings of 20 handoffs between June and September 2022, which were transcribed and analysed using the Linguistic Inquiry Word Count programme. Trustworthiness was established by adhering to COREQ and STROBE guidelines for qualitative and quantitative research, respectively. Results: Analysis revealed a preference for casual, narrative language across all units, with ICU nurses demonstrating a higher confidence and leadership in communication. Cognitive processes such as insight and causation were found to be underrepresented, indicating a potential area for miscommunication. Communication motives driven by affiliation were more pronounced in ICU settings, suggesting a strong collaborative nature. No significant differences were observed among the units post multiple testing adjustments. Speech dysfluencies were most pronounced in ICU handoffs, reflecting possible stress and cognitive overload. Conclusion: The study highlights the need for improved communication strategies such as interventions to enhance language clarity and incorporating technological tools into handoff processes to mitigate potential miscommunications and errors. The findings advance nursing science by highlighting the critical role of nuanced language in varied‐acuity hospital settings and the necessity for structured nurse education in handoff communication and standardized handoff procedures. Implications for the profession and patient care: This study underscores the critical role of language in nurse‐to‐nurse handoffs. It calls for enhanced communication strategies, technology integration and training to reduce medical errors, improving patient outcomes in high‐acuity hospital settings. Patient or Public Contribution: Nurses only. [ABSTRACT FROM AUTHOR]

This study aimed to analyze students’ and graduates’ perceptions regarding the use of Problem-Based Learning (PBL) in nurse education. This is a qualitative study that employs the comprehensive and interpretative approach proposed by Dialectical Hermeneutics. Four focus groups were conducted with the participation of 17 students and 16 graduates from a higher education institution that implements PBL in nurse education. The analysis of results allowed for the identification of five thematic categories: difficulty in adapting to the method; attainment of autonomy in one’s own learning; encouragement of clinical reasoning development; enhancement of communication and interpersonal relationships; and integration between theory and practice. It is evident that the use of PBL promotes alignment with the propositions of curriculum guidelines for nurse education by fostering the development of skills and competencies such as autonomy, communication, interpersonal relationships, and clinical reasoning through comprehensive and contextualized practices. However, students encounter challenges with the changes observed when introduced to PBL, which are overcome during the implementation process. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Digital health plays a vital role in healthcare services. Governments in many countries, including China, are increasingly advocating for the appropriate use of digital technologies to address significant health system challenges. It is crucial to incorporate digital health education into the curriculum for future nurses to adapt to the changes in the digital medical system. This study aimed to evaluate the impact of an online Digital Health and Informatics Course in China on the knowledge and comprehension of key digital health and informatics topics, self-assessment of nursing informatics competencies, and satisfaction among undergraduate nursing students. The findings of this study provide recommendations for the design and implementation of future digital health education. Methods: This study employed a one-group, quasi-experimental mixed-methods design with pre- and post-assessments. The participants received digital health and informatics education through six three-hour online sessions in six interactive days, with online self-learning materials in between. An online quiz and focus group discussions pre- and post the course were designed to evaluate the knowledge and comprehension of key digital health and informatics topics. Also, a validated Chinese version of the Self-assessment of Nursing Informatics Competencies Scale was conducted pre- and post-course to assess self-assessment of nursing informatics competencies. Additionally, all students were invited to participate in an online survey with a performance-focused course evaluation form as well as focus group discussions to gather their feedback on the learning experience and their evaluations of the course. Results: A total of 24 undergraduate nursing students were enrolled in the course. All students completed all sessions of this course, resulting in an attendance rate of 100%. Additionally, all students completed both pre- and post-assessments. In terms of the knowledge and comprehension of key digital health and informatics topics, scores of the quiz on knowledge assessment improved from the pre-test [mean pretest score: 78.33 (SD 6.005)] to the post-test [mean post-test score: 83.17 (SD 4.86)] upon completion of the course (P < 0.001). Also, students acknowledged that the course enhanced their knowledge and comprehension of informatics and digital health, the benefits of (nursing) informatics in clinical practice, and the role of health care professionals in informatics and digital health. In terms of self-assessment of nursing informatics competencies, scores on nursing informatics attitudes demonstrated significant improvement (P < 0.001). Furthermore, students reported high satisfaction with various aspects of this course, including the opportunity to explore broad horizons in informatics for future careers, engaging in group discussions, and analyzing case studies on the use of informatics and digital health in clinical practice. Conclusions: This Online Digital Health and Informatics education effectively improved undergraduate nursing students' knowledge and comprehension of the key digital health and informatics topics, nursing informatics attitudes in the self-assessment of nursing informatics competency with high levels of satisfaction. In order to ensure that future education in digital health and informatics for nursing students is in line with the technological advancements in clinical settings, it is necessary to foster collaboration between medical school training and clinical practice. This collaboration should involve the use of clinical examples to illustrate advanced digital health applications and the inclusion of practical exercises on the use of digital health technology in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Nurses and researchers emphasize the importance of adding educational content of palliative care to nursing curricula in Iran as a means to improve the quality of care at the end of life and self-efficacy is considered as an important determinant in palliative care nursing. However, undergraduate nursing students are not sufficiently trained to achieve the qualifications required in palliative care. The aim of this study was to determine the effect of combined training (theoretical-practical) of palliative care on the perceived self-efficacy of nursing students. Methods: This is a semi-experimental study with a pretest-posttest design. Sampling was nonrandomized with convenience method and included 23 seventh-semester students. The intervention consisted of palliative care training for ten theoretical sessions and three practical sessions. Data were collected using demographic and the perceived self-efficacy questionnaires completed before and after the intervention. Data were then analyzed in the statistical SPSS 23 software using descriptive and analytical statistics. Results: The mean age of the samples was 22.78 (SD1.17). Most of the participants were male (56.5%) and single(91.3%). The findings showed that, perceived self-efficacy, psycho-social support and symptom management improved significantly after the intervention (p<0.05). Conclusion: Palliative care training can increase the nursing students perceived self-efficacy. Since nursing students are the future nurses of the care system, therefore, managers and planners can take a step towards improving the quality of nursing care by using palliative care training programs. Since nursing students will be future nurses in health care system, therefore, managers and planners can take steps to improve the quality of nursing care by using palliative care education programs. [ABSTRACT FROM AUTHOR]

Introduction: New technologies play an important role in the health industry, providing solutions in the fields of Telehealth and Telenursing. The use of digital technology in healthcare has been further enhanced by the extraordinary circumstances of COVID-19 pandemic. Methodology: A systematic literature review was conducted in the PubMed database using specific keywords: "Telehealth AND Nursing" and "Telenursing" and a time limit of two years. From the initial search, 918 studies were found, of which 13 were finally evaluated. Results: Telehealth and Telenursing interventions are associated with improved patient compliance with medication and increased satisfaction with the use of digital technology, while the complementary use of new remote technologies along with the provision of standard care is recommended for optimal effectiveness. In addition, there is a reduction in readmissions, an improvement in quality of life and a reduction in patients' anxiety and clinical symptoms. Also, the medical and nursing staff seem to comply satisfactorily with the use of new technologies, while a further training is deemed necessary to improve efficiency and acquire the necessary digital skills. Conclusions: The Telehealth and Telenursing services can supplement and support effectively the in-life health services, especially in cases when geographical limitations are observed. [ABSTRACT FROM AUTHOR]

Introduction: The World Health Organization (WHO) called for the expansion of all nursing roles, including advanced practice nurses (APNs), nurse practitioners (NPs) and clinical nurse specialists (CNSs). A clearer understanding of the impact of these roles will inform global priorities for advanced practice nursing education, research, and policy. Objective: To identify gaps in advanced practice nursing research globally. Materials and methods: A review of systematic reviews was conducted. We searched CINAHL, Embase, Global Health, Healthstar, PubMed, Medline, Cochrane Library, DARE, Joanna Briggs Institute EBP, and Web of Science from January 2011 onwards, with no restrictions on jurisdiction or language. Grey literature and hand searches of reference lists were undertaken. Review quality was assessed using the Critical Appraisal Skills Program (CASP). Study selection, data extraction and CASP assessments were done independently by two reviewers. We extracted study characteristics, country and outcome data. Data were summarized using narrative synthesis. Results: We screened 5840 articles and retained 117 systematic reviews, representing 38 countries. Most CASP criteria were met. However, study selection by two reviewers was done inconsistently and language and geographical restrictions were applied. We found highly consistent evidence that APN, NP and CNS care was equal or superior to the comparator (e.g., physicians) for 29 indicator categories across a wide range of clinical settings, patient populations and acuity levels. Mixed findings were noted for quality of life, consultations, costs, emergency room visits, and health care service delivery where some studies favoured the control groups. No indicator consistently favoured the control group. There is emerging research related to Artificial Intelligence (AI). Conclusion: There is a large body of advanced practice nursing research globally, but several WHO regions are underrepresented. Identified research gaps include AI, interprofessional team functioning, workload, and patients and families as partners in healthcare. PROSPERO registration number: CRD42021278532. [ABSTRACT FROM AUTHOR]

Purpose Methods Findings Conclusions and implications for nursing This integrative review was conducted to provide a comprehensive picture of the use of standardized nursing languages (SNLs) in long‐term care (LTC) systems.A comprehensive search was performed with terminological variants of “standardized terminology” and “long‐term care” in eight electronic databases up to December 2021. Eligible studies were further identified by screening the reference lists of publications that met the inclusion criteria. The quality of the included studies was appraised using the Joanna Briggs Institute checklists. The study findings were organized into themes, which represent the focus of the study.Eighty‐one publications that studied 12 SNLs in 17 countries are presented in this review. The Omaha System, NANDA‐I, NIC, and NOC were the most common SNLs. Study foci were classified into five themes: evaluating the applicability of 10 SNLs (n = 22), characterizing nursing care using six SNLs (n = 16), developing core sets and tools based on seven SNLs (n = 15), documenting nursing care by using four SNLs (n = 14), and implementing intervention programs based on six SNLs (n = 14).SNLs can be used for various purposes, and the available evidence supports the expansion of their utilization. Further studies should continue to identify gaps in the existing versions of SNLs to reflect the LTC nursing process in multiple societies. Additionally, the successful use of SNLs requires background knowledge of nursing informatics; therefore, preparation should be started in the nursing curriculum and continued in healthcare facilities, including LTC settings. These research findings will assist healthcare managers, researchers, and policymakers in the LTC field in effectively utilizing SNLs. [ABSTRACT FROM AUTHOR]

Educational technology has advanced tremendously in recent years, with several major developments becoming available in healthcare professionals' education, including nursing. Furthermore, the COVID-19 pandemic resulted in obligatory physical distancing, which forced an accelerated digital transformation of teaching tools. This review aimed to summarize all the available digital tools for nursing undergraduate education developed from 2019 to 2023. A robust search algorithm was implemented in the Scopus database, resulting in 1592 publications. Overall, 266 relevant studies were identified enrolling more than 22,500 undergraduate nursing students. Upon excluding multiple publications on the same digital tool, studies were categorized into three broad groups: serious games (28.0%), gamified applications (34.5%), and VR simulations and other non-gamified digital interventions (37.5%). Digital tools' learning activity type (categories = 8), geographical distribution (countries = 34), educational subjects (themes = 12), and inclusion within a curriculum course (n = 108), were also explored. Findings indicate that digital educational tools are an emerging field identified as a potential pedagogical strategy aiming to transform nursing education. This review highlights the latest advances in the field, providing useful insights that could inspire countries and universities which have not yet incorporated digital educational tools in their nursing curriculum, to invest in their implementation. [ABSTRACT FROM AUTHOR]

Currently, there is a need to improve the education system and develop interdisciplinary research at all levels of education, from school to postgraduate education. The introduction of interdisciplinary connections contributes to the formation of a holistic understanding of natural phenomena and the connections between them. Thus, this knowledge becomes more meaningful and applicable in practice. This article proposes a conceptual model of the content of education in the form of a thesaurus and ontology. The use of these models will allow you to adaptively select and systematize educational information. The article also discusses the possibilities and experience of using ontological modeling and engineering for the conceptual description of school and higher education. In addition, the article discusses the development of an ontological model of the process of expanding teachers' competencies with the integration of science, technology, engineering and mathematics (STEM) education. The use of ontological engineering methods will improve the quality of teacher education through the semantic description of knowledge in the subject area and the use of interdisciplinary and STEM approaches in the educational process. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to comprehensively assess the field of health informatics and its subdomains, addressing a gap in the literature. The primary objective is to provide insights into the integration of expertise from various disciplines and explore the impact of emerging technologies, such as artificial intelligence, machine learning, robotic process automation, and virtual reality on healthcare processes. The research question queries the current status of health informatics and how the latest technological developments affect health informatics and its subfields. Method: Conducted through an extensive literature review, this research explores medical informatics, nursing informatics, pharmacy informatics, dentistry informatics, biomedical informatics, bioinformatics, public health informatics, clinical informatics, and primary care informatics. Results: Findings highlight a comprehensive understanding of health informatics and its subdomains, emphasizing the interdisciplinary integration of expertise. The study also reveals the significant impact of new and hype technologies on various health informatics domains. Conclusions: Filling a literature gap, this study provides valuable insights into the current state of health informatics. It underscores the interdisciplinary nature of the field and emphasizes the profound influence of emerging technologies on the evolving landscape of health informatics. The study thoroughly examines nine specific informatics fields within health informatics, revealing that recent years have seen a collective influence of artificial intelligence, deep learning, and machine learning across these domainsThe findings strongly suggest that courses on these emerging current technologies be integrated into undergraduate curricula within health informatics education. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables synthetic data generation from real patient records in a privacy preserving and compliant fashion, is interpretable and allows for expert intervention. Methods: Our approach ties together two established tools in medical informatics, namely OMOP as a data standard for electronic health records and Synthea as a data synthetization method. For this study, data pipelines were built which extract data from OMOP, convert them into time series format, learn temporal rules by 2 statistical algorithms (Markov chain, TARM) and 3 algorithms of causal discovery (DYNOTEARS, J-PCMCI+, LiNGAM) and map the outputs into Synthea graphs. The graphs are evaluated quantitatively by their individual and relative complexity and qualitatively by medical experts. Results: The algorithms were found to learn qualitatively and quantitatively different graph representations. Whereas the Markov chain results in extremely large graphs, TARM, DYNOTEARS, and J-PCMCI+ were found to reduce the data dimension during learning. The MultiGroupDirect LiNGAM algorithm was found to not be applicable to the problem statement at hand. Conclusion: Only TARM and DYNOTEARS are practical algorithms for real-world data in this use case. As causal discovery is a method to debias purely statistical relationships, the gradient-based causal discovery algorithm DYNOTEARS was found to be most suitable. [ABSTRACT FROM AUTHOR]

Background: Reducing the risk of infection transmission by getting emergency care for pediatric patients is a challenging task. Aim: The study aim was to assess emergency nurses' readiness to provide care for pediatric patients with infectious diseases. Method: Two hundred Jordanian emergency department nurses were surveyed using a descriptive design. Results: The study revealed that insufficient safety and infection control procedures were put into place, starting with family support to allow nurses to work 145 (78%), family care plans intended to assist caregivers 139 (74.7%), the availability of respiratory protection and a backup plan for standard precautions, training requirements, and equipment 131 (70.4%), create a unit pandemic safety strategy 124 (66.7%), have a plan for emergencies for at-risk staff 116 (62.4%), have a hospital pandemic safety plan 113 (60.8%), manage inventory 102 (54.8%), use reuse guidelines if there will be severe shortages 99 (53.2%), create a strategy for nurses' access to healthcare for themselves and their families 96 (51.6%), and end with any required system updates for new policies 88 (47.3%). Staff nurses made up a large proportion of participants (145; 78%; 115; 62.8%) who said they lacked experience with care for pediatric patients with infectious illnesses who were critically sick. A 62.8% of nurses reported they did not have training in infectious disease emergency prevention and control for pediatric patients. What nurses prioritize it was determined that the concept of crisis standards of care (34.9%) was the most important educational topic for training emergency room nurses to care for pediatric patients who are critically ill with infectious infections, while the clarity of communication pathways was ranked lowest. Conclusion: More training and support are needed for emergency room nurses to properly care for children's patients with infectious illnesses. [ABSTRACT FROM AUTHOR]

Nursing informatics merges nursing science with information and analytical sciences to identify, describe, manage, and disseminate nursing data, information, knowledge, and wisdom. Identifying nurses' informatics competency will help improve information technology utilisation in clinical practice. The aim of this study was to assess basic competency in nursing informatics and related factors influencing nurses working in a university teaching hospital. Thus, a cross-sectional study was conducted. A stratified random sampling of the total population of 1,136 nurses with sample size of 316 nurses participated in this study. The data was collected using a self-reported questionnaire utilising the Nursing Informatics Competency Assessment Tool (NICAT) reaching targeted sample by convenient approach. The results of this study showed that 85% (n = 269) nurses were competent in nursing informatics competency. There was a significant relationship between basic nursing informatics competency and sociodemographic of age (t = 4.194, p = 0.000), gender (t = -2.558, p = 0.011), educational level (F [2,313] = 5.094, p = 0.007) and working discipline (F [6,309] = 8.309, p = 0.000). There was also a significant relationship between basic nursing informatics competency and working experience (p = -0.231, n = 316, p = 0.000). However, the study is based on self-reporting and does not measure the actual performance of nursing informatics competency. Overall, the findings indicated the need for improvement in nursing informatics by exposure or awareness for potential age group and particular clinical setting for training and educational of nursing informatics. [ABSTRACT FROM AUTHOR]

Objective: The in-service training aims to maintain nurses' individual and professional development, update their existing knowledge and skills, ensure their adaptation to new tasks, develop their professional identity, develop their creativity, increase the quality/quality of the care they provide, improve individual and institutional productivity, and prevent work accidents and errors. The research aimed to discover nurses' views about in-service distance training. Methods: The study used a qualitative research design. The research was conducted with 45 nurses who volunteered to participate. The data were collected using the information form and semi-structured individual interview form. In the analysis of qualitative data, "content analysis technique" was used. Results: The results of the research were collected under six main themes: In-service distance training's contributions to professional development, in-service distance training's strengths, in-service distance training's weaknesses, in-service distance training's problems, solutions to these problems, and preferred in-service training environment. Nurses indicated that they preferred blended training the most. Conclusion: Determining nurses' views about distance education may provide clues about the structuring of distance in-service training and the effective use of resources. Therefore, it can also improve the quality of nursing care. [ABSTRACT FROM AUTHOR]

• Exercise programs are effective in reducing low back pain for both nursing staff: nurses and nursing assistants. • Focusing on back and trunk exercises provide evidence based for low back pain relief for nurses and nursing assistants. • Exercise program for nurses and nursing assistants are more successful in those under 40 years old engaging in shorter exercise (20 sessions). Introduction : Nurses have a high prevalence of low back pain due to ergonomic hazards in healthcare workplaces. While exercise programs have been suggested as an intervention strategy, the effectiveness of low back pain programs has been inconsistent in the research literature. The purpose of study is to determine the effect of exercise programs to reduce low back pain among nursing staff. Methods : A systematic review and meta-analysis was conducted with five databases and systematically searched. Following the PRISMA guidelines, included studies evaluated low back pain relief among nurses or nursing assistants and described the exercise program. Two reviewers independently appraised, extracted, and synthesized all available studies. The study protocol was registered in PROSPERO (CRD42022359511). Results : A total of 296 articles with 1,355 nursing staff from nine countries were obtained. Nine randomized controlled trials with a moderate to low risk of bias quality were included. Exercise programs had a small but significant effect on low back pain of nursing staff (SMD = -0.48; 95% CI = -0.76 to −0.19; p = 0.03, I2 = 62%, p = 0.001). A subgroup analysis of nurses and nursing assistants showed moderate and small effects, respectively (I2 = 0% p < 0.0001, SMD −0.73 CI 95% [-0.97 to –0.48], p = 0.76, and I2 = 0% p = 0.002, SMD −0.23 CI 95% [-0.38 to −0.08], p < 0.88). Exercise for back and trunk exhibited a moderate effect on low back pain (SMD −0.56 CI 95% [-0.86 to −0.25], p = 0.01, I2 = 66%, p < 0.0004). A subgroup analysis comparing age, under 40 years old revealed a moderate effect size (SMD = -0.59; 95% CI = -0.83to −0.35; p = 0.06; I2 = 64%, p < 0.0001). Conclusions : Exercise programs are an effective treatment to reduce low back pain in nurses and nursing assistants, especially among younger staff. Practical application : Back and trunk exercise programs should be recommended for nursing staff with low back pain. [ABSTRACT FROM AUTHOR]

This paper presents a five-stage framework for AI learning based on classroom observations. It defines the stages and explores how teachers and students develop confidence in utilizing various AI tools, acknowledging both their constructive advantages and potential risks. The study emphasizes the transformative influence of integrating AI into the dynamics of learning and teacher-student relationships, fostering a more interactive educational environment. Through case studies conducted in South Korean classrooms, this research offers practical steps and considerations for educators and administrators to successfully integrate AI technologies, with the aim of enhancing digital and AI competencies in education. The findings highlight the significance of adopting a comprehensive approach to AI-integrated instruction, taking into account factors such as educational level, subject, and students' preparedness. This framework is designed to provide guidance for the effective utilization of AI in educational settings, supporting the objective of promoting AI literacy and closing educational gaps. [ABSTRACT FROM AUTHOR]

Nursing information systems are becoming increasingly prevalent in our medical institutions. However, changes in the social environment and imbalances between the demands of caregivers and care recipients mean that current nursing information systems are inadequate in terms of quality and operational needs. This article was written to provide insights into opportunities to leverage technology to further promote care quality by applying a "data, information, knowledge, and wisdom" system development structure to develop intelligent technology products that equitably meet the needs of patients, caregivers, and nursing processes. Applied in clinical settings, these products should help satisfy patient needs and facilitate nursing work. [ABSTRACT FROM AUTHOR]

The emergence of virtual reality (VR) simulation has brought about a significant shift in the healthcare industry, as it integrates modern technologies with human talents to foster patient-centered care, clinical efficiency, and a compassionate healthcare digital ecosystem. The use of clinical simulation in nursing education has become essential in the current day, revolutionizing the training of future medical professionals. This paper explored the realm of simulation-based learning, illuminating its importance, obstacles, and endless potential in the field of nursing education. Given the ever-changing healthcare landscape, nurses need to possess a broad range of skills and a thorough comprehension of real-world situations. But conventional didactic methods frequently fail to adequately prepare student-nurses for the intricacies of clinical practice. VR is one of the most crucial elements of immersive learning that increases constructive pedagogic engagements due to generative imagination it offers. By using VR headgear or goggles, student-nurses can fully submerge themselves in a customized digital world as if they were truly there, interacting with their surroundings and learn in an interactive and pedagogic informative digital ecosystem. In order to help student-nurses practice problem-solving techniques without really placing themselves in risk, VR can also be used to construct very realistic simulations. In this study, the authors offered the transformative potential of VR, with significances to improve nursing education by offering engaging and interactive learning environments. The paper presented a novel approaches in addressing nursing education through technology familiarization, proposing a cutting-edge simulation platform using actor network (ANT) model for the resource distribution. [ABSTRACT FROM AUTHOR]

Background: Nursing Informatics (NI) and the development and growth of Health Information Technology (HIT) are becoming a necessary part of all aspects of the nursing practice, especially in critical care settings. In addition, researchers agree on using standardized and electronic documentation to support the nursing process and promote nursing documentation quality. Purpose: To examine the relationship between Intensive Care Unit Nurses' Informatics Competency and Quality of Patients' Electronic Health Record Documentation. Method: A descriptive, correlational, retrospective, cross-sectional design was used. Three hospitals that implemented the Electronic Health Records (EHRs) system were included in this study, using non-probability convenience sampling technique to recruit a total of 176 nurses. The nursing informatics competency was measured by the Self-Assessment of Nursing Informatics Competencies Scale (SANICS). The Quality of Electronic Health Record Documentation was assessed by the Audit instrument for nursing care plans in the patient record (Cat-ch-Ing). Descriptive and Inferential statistics were utilized to answer research questions. Results: The overall mean informatics competency score among nurses was 2.49 (SD = .73), with most of the nurses (81.79%) reporting a low competency score of less than three. The highest percentage of participants 29.4% (n = 52) have moderate quality of EHR documentation. Also, personal and clinical related characteristics accounts for 93.7% of the variance in quality of patients’ electronic health record documentation (R² = .937, F = 8.707, p = .004). Once nursing informatics competency were entered into the model R² still the same, making a total explained variance 93.7% (R² = .937, F = 6.907, p = .013). Conclusion: The present study revealed low levels of nursing informatics competency among nurses, and the highest percentage of participants have moderate quality of EHR documentation. In addition, personal and clinical related characteristics accounts for 93.7% of the variance in quality of patients’ electronic health record documentation Implication to Nursing: This study provides evidence to guide nursing leaders, supervisors and policymakers in their planned actions and policies to support nursing capacity, nursing education, and nursing practice in the area of nursing informatics and electronic nursing documentation. [ABSTRACT FROM AUTHOR]

With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI) can assist researchers in swiftly extracting valuable patterns, trends, and associations from subjective information. Tribological behaviors are characterized by dependence on systems, evolution with time, and multidisciplinary coupling. The friction process involves a variety of phenomena, including mechanics, thermology, electricity, optics, magnetics, and so on. Hence, tribological information possesses the distinct characteristics of being multidisciplinary, multilevel, and multiscale, so that the application of AI in tribology is highly extensive. To delineate the scope, classification, and recent trends of AI implementation in tribology, this review embarks on exploration of the tribology research domain. It comprehensively outlines the utilization of AI in basic theory of tribology, intelligent tribology, component tribology, extreme tribology, bio-tribology, green tribology, and other fields. Finally, considering the emergence of "tribo-informatics" as a novel interdisciplinary field, which combines tribology with informatics, this review elucidates the future directions and research framework of "AI for tribology". In this paper, tribo-system information is divided into 5 categories: input information (I), system intrinsic information (S), output information (O), tribological state information (Ts), and derived state information (Ds). Then, a fusion method among 5 types of tribo-system information and different AI technologies (regression, classification, clustering, and dimension reduction) has been proposed, which enables tribo-informatics methods to solve common problems such as tribological behavior state monitoring, behavior prediction, and system optimization. The purpose of this review is to offer a systematic comprehension of tribo-informatics and to inspire new research ideas of tribo-informatics. Ultimately, it aspires to enhance the efficiency of problem-solving in tribology. [ABSTRACT FROM AUTHOR]

The distribution and verification of quantum nonlocality across a network of users is essential for future quantum information science and technology applications. However, beyond simple point-to-point protocols, existing methods struggle with increasingly complex state preparation for a growing number of parties. Here, we experimentally demonstrate multiparty detection-loophole-free quantum steering, where one party simultaneously steers multiple spatially separate parties, using a multi-qubit state produced from a set of qubits of which only one pair is entangled. We derive loss-tolerant steering inequalities, enabling our experiment to close the detection loophole, and enabling us to show the scalability of this approach to rigorously verify quantum nonlocality across arbitrarily many parties. This provides practical tools for developing the future quantum internet. [ABSTRACT FROM AUTHOR]

Objective: to analyze the use profile and content of the messages posted in the Community of Practice for Nursing in the Region of the Americas of the Pan American Health Organization as a tool intended to share experiences, knowledge and opportunities for nurses. Method: a descriptive and qualitative study aimed at analyzing the messages posted in the Community of Practice forums. The data were analyzed by content analysis. Results: the Community of Practice has allowed the participation of 1,765 professionals from 20 countries, with a total of 4,001 posts. The topics analyzed (education, employment, leadership and service delivery) were addressed from the perspective of professionals from different countries, presenting the challenges they face and their reflections regarding the situation of nursing in the region. Conclusion: the platform allowed professionals from different countries and performance scopes to interact and discuss relevant topics for nursing education and practice in the Region of the Americas. Through the Community of Practice, the expectation is to enhance commitment, cooperation and solidarity for collective learning and skills development, thus maximizing nurses’ contributions to health systems and services.

Objective: to develop an information model on pain management in hospitalized aged people. Method: a Big Data retrospective and observational study guided by the Applied Healthcare Data Science Roadmap. The sample included all Electronic Health Records related to pain management in older adults aged at least 75 years old considered vulnerable in the institution and admitted to clinical and surgical units. Data science packages were used in Python ® for data analysis. Results: a total of 9,635 hospitalizations were found for 4,753 patients, with a mean age of 81 years old and 54% belonging to the female gender. The main reasons for hospitalization were diseases of the circulatory system (n=1,593; 28.6%), neoplasms (n=893; 16%) and diseases of the genitourinary system (n=508; 9.1%). A total of 60 attributes related to pain were identified and organized into groups: current pain, assessment instruments and characteristics, Nursing diagnosis, etiology of the Nursing diagnosis, interventions for relief, consultations to specialties and pain reassessment. The groups were classified into four large panels that constituted the information model. Conclusion: the information model developed presented an overview of the healthcare reality of pain management in vulnerable aged people, supporting decision-making for pain management in this population segment.

The article discusses the successful partnership between the European Society of Gastroenterology and Endoscopy Nurses and Associates (ESGENA) and the European Society of Gastrointestinal Endoscopy (ESGE). ESGENA was established in 1995 with the support of Professor Jean Francois Rey, and it now has over 7,000 members from 29 European countries. The organization focuses on expanding and harmonizing continuing education for nurses in endoscopy and gastroenterology, and it has been involved in the development of guidelines, curricula, and position statements. The collaboration between ESGENA and ESGE has led to the establishment of annual conferences and workshops, as well as the promotion of teamwork and improved patient care in GI endoscopy. [Extracted from the article]