JMIR nursing最新文献

Background: Leadership development programs in health care often fail due to their lack of adaptability to the schedules of busy clinicians. This study addressed the need for scalable, flexible programs tailored to nurse leaders.

Objective: This study evaluated the acceptability, appropriateness, and feasibility of the Relational Playbook, an evidence-based leadership development program developed in the Veterans Health Administration delivered through the Whistle Systems employee recognition web application and mobile app.

Methods: A 1-year, single-team pilot was deployed using descriptive survey data and qualitative interview analysis. The Relational Playbook's educational content and interventions were hosted on the Whistle platform, which integrates behavioral science and gamification strategies. Content was delivered weekly via app-based nudge notifications and email. Engagement metrics included activity completion rates. User experience data were collected through weekly reflection surveys (with Likert-scale responses and open-text options); monthly check-ins; and a postimplementation acceptability, appropriateness, and feasibility survey and interview. Descriptive statistics summarized engagement levels and trends, and qualitative data were analyzed using content analysis to identify recurring concepts. Quantitative and qualitative data were analyzed sequentially for comprehensive insights.

Results: The section chief and 4 practicing cardiology nurse practitioners from a large academic medical center participated. The nurse practitioner section chief deemed the Whistle platform an acceptable, appropriate, and feasible technology for delivering the Relational Playbook content. They valued the weekly nudges, microlearning content, and flexibility of the web application and mobile app. The Relational Playbook content supported their personal growth and fostered positive shifts in attitudes toward work.

Conclusions: Delivering leadership development content through the Whistle platform is an acceptable approach to support the growth and well-being of busy nurse leaders. The small sample and absence of a comparison group limit generalizability.

Background: Digital health refers to the field of knowledge and practice associated with the development and use of digital technologies to improve clinical practice and health outcomes. Knowledge of digital health technology is becoming essential for all nurses and health providers.

Objective: This study aims to present the results of the systematic reviews that were used to inform the recommendations in a best practice guideline (BPG) following the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. Reviews focused on digital health education for nurses and health providers, peer champion models, and the use of predictive analytics in digital health environments.

Methods: The BPG team, in collaboration with a panel of 17 experts, conducted 5 systematic reviews to address 5 recommendation questions. Systematic searches looked for relevant studies published in English from January 2017 to July 2022 from 10 databases. The GRADE approach was used to synthesize and evaluate the quality of evidence, ensuring the guideline aligned with international reporting standards.

Results: A total of 18 articles across 4 systematic reviews met the inclusion criteria. From these reviews, 4 corresponding recommendations were drafted for nurses and health providers. The strength of the recommendations was determined through discussion and consensus by the expert panel using the GRADE approach. Among all, 1 systematic review resulted in no recommendation due to insufficient evidence.

Conclusions: The BPG on digital health provides 4 evidence-based recommendations for nurses and health providers on how to incorporate digital health technologies into clinical practice. This BPG is intended to be used across all health care settings.

Background: Evidence-based practice is essential for delivering safe, high-quality nursing care; however, its implementation remains challenging due to barriers such as limited knowledge, a lack of supportive organizational culture, and insufficient access to relevant knowledge at the point of care. Knowledge management systems (KMSs) have the potential to bridge this gap by integrating evidence into the nursing process through technological support. Despite growing interest, the integration of KMS into daily nursing practice is still underexplored, especially from the perspective of frontline nurses.

Objective: The aim of this study was to explore nurses' perspectives on the requirements for a KMS that supports evidence-based practice at the point of care, with a focus on usability, process integration into the electronic nursing care plan and patient chart, and implementation challenges and benefits.

Methods: A qualitative study was conducted in a Swiss hospital using observations, focus groups, and individual interviews with 6 registered nurses, 9 advanced practice nurses, 2 nursing managers, and 1 head physician. Data were analyzed using thematic analysis.

Results: The analysis revealed four main categories and ten subcategories: (1) content of the KMS, (2) personal and structural factors of knowledge management, (3) technical conditions of the KMS, and (4) implementation of a KMS. Participants emphasized the need for an intuitively structured, process-integrated system that links evidence-based information directly to nursing interventions in the electronic nursing care plan and patient chart. Organizational support, interprofessional collaboration, and clear responsibilities were identified as critical for successful implementation.

Conclusions: There is a clear need for a KMS that is user-friendly, seamlessly integrated into clinical workflows, and supports quick, reliable access to evidence-based knowledge. A KMS could enhance nurses' access to reliable knowledge, promote evidence-based decision-making, and strengthen professional confidence at the point of care. By embedding evidence directly into the electronic nursing care plan and patient chart, such systems can streamline workflows, reduce time spent searching for information, and support more consistent application of best practices. These capabilities may improve information retrieval and contribute to a safer, more consistent nursing practice.

Background: Assessing the current landscape of nurses' knowledge and attitudes is a critical first step in facilitating a smooth and effective transition toward artificial intelligence (AI)-enhanced critical care.

Objective: This study aimed to assess the levels of and factors affecting the knowledge of and general attitudes toward AI in critical care among nurses.

Methods: A cross-sectional correlational design was used with 203 critical care nurses in Hail, Saudi Arabia, using the Nurses' AI Knowledge Questionnaire and the 20-item General Attitudes Toward Artificial Intelligence Scale from May 2025 to July 2025. Data were analyzed using 2-tailed t tests, ANOVA, Pearson correlation, and multivariable linear regression. Statistical significance was set at P<.05.

Results: Critical care nurses demonstrated moderate knowledge of (mean score 4.93, SD 1.78) and positive attitudes toward AI (mean score 64.39, SD 8.26). A moderate positive correlation was found between knowledge of and attitudes toward AI (r=0.45; P<.001). In multivariable analyses, older age was associated with lower knowledge (≥40 years: β=-1.29, 95% CI -2.12 to -0.45; P=.003) and less positive attitudes (β=-8.97, 95% CI -12.49 to -5.44; P<.001). Female nurses reported lower knowledge (β=-0.69, 95% CI -1.20 to -0.19; P=.007) and less positive attitudes (β=-2.65, 95% CI -4.78 to -0.52; P=.02) than male nurses. Greater experience (>5 years) was positively associated with knowledge (β=1.20, 95% CI 0.65-1.75; P<.001) and attitudes (β=8.08, 95% CI 5.76-10.41; P<.001).

Conclusions: Critical care nurses in Hail demonstrated moderate knowledge of and positive attitudes toward AI, which varied based on their demographic and professional characteristics. These findings highlight the need to strengthen AI literacy and provide targeted support to groups with lower scores, which may enhance readiness for AI integration in critical care settings.

Background: Digital technologies are increasingly being introduced into the health care system and in settings such as hospitals and geriatric long-term care (LTC) facilities, offering potential benefits such as improved care quality, reduced workload, or enhanced documentation processes. However, the success of these technologies also depends on the acceptance by the primary users, that is, the nursing staff.

Objective: This review synthesizes empirical studies that have explored the acceptance of digital technologies by nursing staff in geriatric LTC settings, building upon the foundational work by Yu et al (2009). The goal is to identify influencing factors, assess the extent of existing evidence, and highlight research gaps in this care setting.

Methods: A systematic literature review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. The SPIDER (sample, phenomenon of interest, design, evaluation, research type) framework was used for eligibility criteria. Databases searched included PubMed, ACM Digital Library, Web of Science, and the Health Administration Database ProQuest. Studies were included if they empirically examined the acceptance of digital technologies by nursing staff in geriatric LTC settings. Two reviewers independently screened the studies, extracted data, and assessed methodological quality using the CASP (Critical Appraisal Skills Programme) checklist.

Results: A total of 3 studies met the criteria, highlighting a gap in research on this topic. The studies applied cross-sectional quantitative designs and highlighted critical determinants of technology acceptance, including perceived usefulness, ease of use, digital competence, and organizational support. The studies involved a total of 1019 participants from Germany, Australia, and the Netherlands. Barriers included lack of user involvement, lack of training, poor system design, and demographic differences in digital affinity.

Conclusions: This review shows that the acceptance of digital technologies by nursing staff in geriatric LTC settings is shaped by a constellation of individual factors, such as digital competence and perceived relevance of technology, as well as organizational factors such as access to training and involvement of staff in the implementation process. Despite these insights, the limited number of empirical studies highlights a research gap in this care setting. To ensure sustainable digital transformation in geriatric LTC, future research should prioritize rigorous and participatory approaches, using longitudinal, intervention-based, or multilevel study designs.

Background: Hospital-acquired pressure injuries (HAPIs) remain a largely preventable cause of patient injury and are often utilized as nursing-sensitive quality metrics. At a tertiary military hospital in XXXXXX, rising HAPI rates necessitated implementing a comprehensive quality improvement program in accordance with the National Database of Nursing Quality Indicators (NDNQI) guidelines. On the basis of Donabedian's Structure-Process-Outcome model, we hypothesized that the implementation of a standardized, evidence-based pressure injury prevention bundle, accompanied by structured staff education (structure), will enhance adherence to prevention practices (process) and markedly decrease HAPI incidence and prevalence (outcomes) among hospitalized adult inpatients.

Objective: To assess the effect of introducing a standardized, evidence-based pressure injury prevention bundle and corresponding staff education on HAPI incidence and prevalence.

Methods: We implemented a comprehensive hospital-wide quality improvement project utilizing a pre-post methodology underpinned by Plan-Do-Study-Act (PDSA) cycles, statistical process control monitoring, and the FOCUS-PDSA framework. The strategy established a standardized preventive package for high-risk patients; it included routine risk and skin assessments, scheduled repositioning, pressure redistribution support surfaces, nutrition optimization with dietitian input, and moisture control. The primary outcomes were monthly HAPI incidence (per 1,000 patient-days), measured using wound care census and unit reporting, and quarterly HAPI prevalence, evaluated using NDNQI surveys by trained NDNQI link nurses, with >90% interrater reliability for staging.

Results: In the initial deployment phase (July-December 2023), the HAPI incidence rate was 2.32 per 1,000 patient-days (267 cases/115,314 patient-days). The incidence declined to 1.44 per 1,000 patient-days (330 cases/229,647 patient-days) in 2024 (38% reduction from the baseline) and to 0.88 per 1,000 patient-days (98 cases/111,589 patient-days) by June 2025, (62% reduction from the baseline). The prevalence decreased from 5.12% in Q3 2023 to 1.38% in Q3 2024 and remained low at 1.43% in Q2 2025.

Conclusions: Implementation of a standardized prevention bundle, supported by systematic staff education, interdisciplinary collaboration, and periodic incidence and prevalence surveillance was associated with sustained reductions in HAPI incidence and prevalence over 2 years. These findings support a bundle-based approach to prevention, combined with real-time feedback and competency-driven teaching, as a scalable means of enhancing patient safety.

Clinicaltrial: none.