Hasil untuk "Nursing"

Pam. Moule, H. Aveyard, M. Goodman

Nursing Research covers key issues, including health promotion, human responses to illness, acute care nursing research, symptom management, cost-effectiveness, vulnerable populations, health services, and community-based nursing studies. Each issue highlights the latest research techniques, quantitative and qualitative studies, and new state-of-the-art methodological strategies, including information not yet found in textbooks. Expert commentaries and briefs are also included. In addition to 6 issues per year, Nursing Research from time to time publishes supplemental content not found anywhere else.

F. Nightingale

S. Decker

Richard A. Smiley, P. Lauer, C. Bienemy et al.

Background Every two years, the National Council of State Boards of Nursing (NCSBN) and the National Forum of State Nursing Workforce Centers (Forum) conduct the only national-level survey focused on the entire U.S. nursing workforce. The survey generates data on the supply of registered nurses (RNs) and licensed practical nurses/licensed vocational nurses (LPNs/LVNs). These data are especially crucial in providing information on emerging nursing issues which in 2020 was the significant burden placed on nurses and the healthcare system by the coronavirus (COVID-19) pandemic. Purpose To provide data critical to planning for enough adequately prepared nurses and ensuring a safe, diverse, and effective healthcare system. Methods This study used a national, randomized sample survey of 157,459 licensed RNs and 172,045 LPNs/LVNs. Data from 42,021 RN respondents and 39,765 LPN/LVN respondents were collected between February 19, 2020, and June 30, 2020. Data included nurse demographics, educational attainment, employment, practice characteristics, and trends. Results The total number of active RN and LPN/LVN licenses in the United States were 4,198,031 and 944,813, respectively. The median age of RNs was 52 years and 53 years for LPNs/LVNs. The nursing workforce has become more diverse than in any other study year as nurses between 19 and 49 years of age have introduced greater racial diversity. Findings suggest the nursing workforce is becoming increasingly more educated and experienced. An average of 83% of all nurses who maintain licensure are employed in nursing with roughly two-thirds working full-time. Hospitals and nursing/extended care facilities continue to be the primary practice setting for RNs and LPNs, respectively. More than one-fifth of all nurses reported they plan to retire from nursing over the next 5 years. Nursing incomes have remained essentially flat over time. Conclusion Employment setting, age, diversity, and education have all changed over the last 2 years. Challenges will continue in the nursing workforce such as matching workforce diversity to the population, compensation, and opportunities; preparing for the large numbers of nurses retiring; exploring the role of nurses in new practice settings; and changes in healthcare delivery modalities such as telehealth.

C. Waltz, O. Strickland, E. Lenz

H. J. Streubert, D. R. Carpenter

B. H. Thomas, D. Ciliska, M. Dobbins et al.

Mika Fukada

Nursing competency includes core abilities that are required for fulfilling one's role as a nurse. Therefore, it is important to clearly define nursing competency to establish a foundation for nursing education curriculum. However, while the concepts surrounding nursing competency are important for improving nursing quality, they are still not yet completely developed. Thus, challenges remain in establishing definitions and structures for nursing competency, competency levels necessary for nursing professionals, training methods and so on. In the present study, we reviewed the research on definitions and attributes of nursing competency in Japan as well as competency structure, its elements and evaluation. Furthermore, we investigated training methods to teach nursing competency.

P. Griffiths, A. Recio-Saucedo, C. Dall'ora et al.

Abstract Aims To identify nursing care most frequently missed in acute adult inpatient wards and to determine evidence for the association of missed care with nurse staffing. Background Research has established associations between nurse staffing levels and adverse patient outcomes including in‐hospital mortality. However, the causal nature of this relationship is uncertain and omissions of nursing care (referred as missed care, care left undone or rationed care) have been proposed as a factor which may provide a more direct indicator of nurse staffing adequacy. Design Systematic review. Data Sources We searched the Cochrane Library, CINAHL, Embase and Medline for quantitative studies of associations between staffing and missed care. We searched key journals, personal libraries and reference lists of articles. Review Methods Two reviewers independently selected studies. Quality appraisal was based on the National Institute for Health and Care Excellence quality appraisal checklist for studies reporting correlations and associations. Data were abstracted on study design, missed care prevalence and measures of association. Synthesis was narrative. Results Eighteen studies gave subjective reports of missed care. Seventy‐five per cent or more nurses reported omitting some care. Fourteen studies found low nurse staffing levels were significantly associated with higher reports of missed care. There was little evidence that adding support workers to the team reduced missed care. Conclusions Low Registered Nurse staffing is associated with reports of missed nursing care in hospitals. Missed care is a promising indicator of nurse staffing adequacy. The extent to which the relationships observed represent actual failures, is yet to be investigated.

A. Karaca, Z. Durna

To evaluate patients’ satisfaction with the quality of nursing care and examine associated factors.

C. Ronquillo, Laura-Maria Peltonen, Lisiane Pruinelli et al.

Abstract Aim To develop a consensus paper on the central points of an international invitational think‐tank on nursing and artificial intelligence (AI). Methods We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3‐day invitational think tank in autumn 2019. Activities included a pre‐event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities. Implications for nursing Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice. Conclusion There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems. Impact We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.

C. Buchanan, Lyndsay Howitt, R. Wilson et al.

Background It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature. Objective A scoping review was conducted to summarize the current and predicted influences of AIHTs on nursing education over the next 10 years and beyond. Methods This scoping review followed a previously published protocol from April 2020. Using an established scoping review methodology, the databases of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest were searched. In addition to the use of these electronic databases, a targeted website search was performed to access relevant grey literature. Abstracts and full-text studies were independently screened by two reviewers using prespecified inclusion and exclusion criteria. Included literature focused on nursing education and digital health technologies that incorporate AI. Data were charted using a structured form and narratively summarized into categories. Results A total of 27 articles were identified (20 expository papers, six studies with quantitative or prototyping methods, and one qualitative study). The population included nurses, nurse educators, and nursing students at the entry-to-practice, undergraduate, graduate, and doctoral levels. A variety of AIHTs were discussed, including virtual avatar apps, smart homes, predictive analytics, virtual or augmented reality, and robots. The two key categories derived from the literature were (1) influences of AI on nursing education in academic institutions and (2) influences of AI on nursing education in clinical practice. Conclusions Curricular reform is urgently needed within nursing education programs in academic institutions and clinical practice settings to prepare nurses and nursing students to practice safely and efficiently in the age of AI. Additionally, nurse educators need to adopt new and evolving pedagogies that incorporate AI to better support students at all levels of education. Finally, nursing students and practicing nurses must be equipped with the requisite knowledge and skills to effectively assess AIHTs and safely integrate those deemed appropriate to support person-centered compassionate nursing care in practice settings. International Registered Report Identifier (IRRID) RR2-10.2196/17490

Hanna von Gerich, Hans Moen, L. Block et al.

BACKGROUND Research on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. OBJECTIVES To synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. DESIGN Scoping review METHODS: PubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. RESULTS A total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n = 55, 59.1%) and formation (testing) (n = 28, 30.1%) phases, followed by implementation (n = 9, 9.7%) and operational (n = 1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3%) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. CONCLUSIONS Contemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.

Yeunhee Kwak, Jung-Won Ahn, Y. Seo

Background Artificial intelligence (AI) technology has recently seen rapid advancement, with an expanding role and scope in nursing education and healthcare. This study identifies the influence of AI ethics awareness, attitude toward AI, anxiety, and self-efficacy on nursing students’ behavioral intentions to use AI-based healthcare technology. Methods The participants included 189 nursing students in Gyeonggi-do, with data collected from November to December 2021 using self-reported questionnaires. We analyzed the data using the SPSS/WIN 26.0 program, including a t-test, Pearson’s correlation coefficient, and hierarchical multiple linear regression. Results The results revealed that AI ethical awareness (t = − 4.32, p  < .001), positive attitude toward AI (t = − 2.60, p  = .010), and self-efficacy (t = − 2.65, p  = .009) scores of the third and fourth-year nursing students were higher, while their anxiety scores were lower (t = 2.30, p  = .022) compared to the scores of the first and second-year nursing students. The factors influencing behavioral intention included a positive attitude toward AI (β = 0.58) and self-efficacy (β = 0.22). The adjusted R 2 was 0.42. Conclusion It is necessary to inculcate a positive attitude toward AI and self-efficacy by providing educational programs on AI-based technology in healthcare settings.

G. Cummings, Sarah Lee, Kaitlyn Tate et al.

BACKGROUND Nursing leadership plays a vital role in shaping outcomes for healthcare organizations, personnel and patients. With much of the leadership workforce set to retire in the near future, identifying factors that positively contribute to the development of leadership in nurses is of utmost importance. OBJECTIVES To identify determining factors of nursing leadership, and the effectiveness of interventions to enhance leadership in nurses. DESIGN We conducted a systematic review, including a total of nine electronic databases. DATA SOURCES Databases included: Medline, Academic Search Premier, Embase, PsychInfo, Sociological Abstracts, ABI, CINAHL, ERIC, and Cochrane. REVIEW METHODS Studies were included if they quantitatively examined factors contributing to nursing leadership or educational interventions implemented with the intention of developing leadership practices in nurses. Two research team members independently reviewed each article to determine inclusion. All included studies underwent quality assessment, data extraction and content analysis. RESULTS 49,502 titles/abstracts were screened resulting in 100 included manuscripts reporting on 93 studies (n=44 correlational studies and n=49 intervention studies). One hundred and five factors examined in correlational studies were categorized into 5 groups experience and education, individuals' traits and characteristics, relationship with work, role in the practice setting, and organizational context. Correlational studies revealed mixed results with some studies finding positive correlations and other non-significant relationships with leadership. Participation in leadership interventions had a positive impact on the development of a variety of leadership styles in 44 of 49 intervention studies, with relational leadership styles being the most common target of interventions. CONCLUSIONS The findings of this review make it clear that targeted educational interventions are an effective method of leadership development in nurses. However, due to equivocal results reported in many included studies and heterogeneity of leadership measurement tools, few conclusions can be drawn regarding which specific nurse characteristics and organizational factors most effectively contribute to the development of nursing leadership. Contextual and confounding factors that may mediate the relationships between nursing characteristics, development of leadership and enhancement of leadership development programs also require further examination. Targeted development of nursing leadership will help ensure that nurses of the future are well equipped to tackle the challenges of a burdened health-care system.

C. Agu, J. Stewart, Nadine McFarlane-Stewart et al.

Background COVID‐19 pandemic has impacted the way things are done in walks of life including nursing education in both developing and developed countries. Nursing schools all over the world as well as in developing countries responded to the pandemic following the guidelines of the World Health Organisation and different countries specific guidelines regarding the pandemic. Aim This reflective piece aims to describe the effect of COVID‐19 on nursing education in developing countries. Result Face‐to‐face teaching and learning were converted to virtual remote learning and clinical experiences suspended to protect the students from the pandemic. Specific but broader responses to the pandemic in the Caribbean and other developing countries have been shaped by financial, political and other contextual factors, especially the level of information technology infrastructure development, and the attendant inequities in access to such technology between the rural and urban areas. Internet accessibility, affordability and reliability in certain areas seem to negatively affect the delivery of nursing education during the COVID‐19 lockdown. Conclusion and Implications for Nursing and/or Health Policy The impact of COVID‐19 on nursing education in the Caribbean and other parts of the world has shown that if adequate measures are put in place by the way of disaster preparedness and preplanned mitigation strategies, future crises like COVID‐19 will have less impact on nursing education. Therefore, health policymakers and nursing regulatory bodies in the developing countries should put policies in place that will help in responding, coping and recovering quickly from future occurrences.

Katja Pursio, P. Kankkunen, E. Sanner-Stiehr et al.

AIM To summarize knowledge of professional autonomy in nursing. BACKGROUND Professional autonomy is associated with experienced meaningfulness of the work. This refers to participation in decision-making and the ability to influence working practices. EVALUATION In an integrative review, relevant studies were retrieved from four databases. Quality was systematically evaluated using critical appraisal tools. PRISMA guidelines were followed. Inductive content analysis was used to analyse current knowledge of the focal subject. KEY ISSUES The search identified 27 relevant studies published between 2000 and 2019. Elements describing nurses' professional autonomy were independence in decision-making and ability to utilize one's own competence. Themes relating to nurses' professional autonomy were shared leadership, professional skills, inter- and intra-professional collaboration and healthy work environment. CONCLUSION Understanding the multidimensional nature of professional autonomy is essential to create attractive work environments. It is important to enable nurses to participate in decision-making and develop nursing through shared leadership to enhance the recruitment and retention of a skilled workforce. IMPLICATIONS FOR NURSING MANAGEMENT The findings have anticipated utility for supporting nursing practice and nurse leaders' understanding of approaches to foster nurses' professional autonomy.

Huili Cao, Yejun Song, Yan-Yun Wu et al.

Background Nursing professionalism plays an important role in clinical nursing. However, a clear conceptual understanding of nursing professionalism is lacking. Method Walker and Avant’s strategy was used to analyse the concept of nursing professionalism. We searched electronic databases, including PubMed, Scopus, and CINAHL, for studies published from 1965 to 2021. Quantitative or qualitative studies published in English that focused on nursing professionalism were included in the study. Results The three attributes of nursing professionalism are multidimensional, dynamic, and culture oriented. Based on the analysis, nursing professionalism is defined as providing individuals care based on the principles of professionalism, caring, and altruism. Conclusions This study offers a theoretical definition and conceptual model of nursing professionalism that may be applied to develop standardized assessment tools or nursing professionalism training programs.

F. Maghsoud, M. Rezaei, F. Asgarian et al.

Background Nursing workload and its effects on the quality of nursing care is a major concern for nurse managers. Factors which mediate the relationship between workload and the quality of nursing care have not been extensively studied. This study aimed to investigate the mediating role of implicit rationing of nursing care, job satisfaction and emotional exhaustion in the relationship between workload and quality of nursing care. Methods In this cross-sectional study, 311 nurses from four different hospitals in center of Iran were selected by convenience sampling method. Six self-reported questionnaires were completed by the nurses. The data were analyzed by SPSS version 16. Structural equation modeling was used to determine the relationships between the components using Stata 14 software. Results Except direct and mutual relationship between workload and quality of nursing care ( P  ≥ 0.05), the relationship between other variables was statistically significant ( P   0.9 and RMSEA < 0.08 and χ 2 /df < 3). Conclusion Workload affects the quality of the provided nursing care by affecting implicit rationing of nursing care, job satisfaction and emotional exhaustion. Nurse managers need to acknowledge the importance of quality of nursing care and its related factors. Regular supervision of these factors and provision of best related strategies, will ultimately lead to improve the quality of nursing care.