JMIR nursing最新文献_第2页

Acceptance of Digital Technology Among Nursing Staff in Geriatric Long-Term Care: Systematic Review. 老年人长期护理中护理人员对数字技术的接受：系统回顾。

IF 4

JMIR nursing

Pub Date : 2026-01-15 DOI: 10.2196/82223

Jeton Iseni, Walter Swoboda, Daniel Houben, Roman Hilla

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.

背景：数字技术正越来越多地被引入卫生保健系统以及医院和老年长期护理（LTC）设施等环境，提供诸如提高护理质量、减少工作量或增强文件编制流程等潜在益处。然而，这些技术的成功还取决于主要用户，即护理人员的接受程度。目的：本综述在Yu等人（2009）的基础工作基础上，综合了探索老年LTC环境中护理人员对数字技术接受程度的实证研究。目的是确定影响因素，评估现有证据的程度，并强调在这种护理环境中的研究差距。方法：根据PRISMA（首选报告项目用于系统评价和荟萃分析）2020指南进行系统文献综述。使用SPIDER（样本、感兴趣的现象、设计、评估、研究类型）框架作为合格标准。检索的数据库包括PubMed、ACM数字图书馆、Web of Science和健康管理数据库ProQuest。如果研究经验性地检查了老年LTC环境中护理人员对数字技术的接受程度，则将其纳入研究。两位审稿人独立筛选研究，提取数据，并使用CASP（关键评估技能计划）检查表评估方法学质量。结果：共有3项研究符合标准，突出了该主题研究的空白。这些研究应用了横断面定量设计，并强调了技术接受的关键决定因素，包括感知有用性、易用性、数字能力和组织支持。这些研究共涉及来自德国、澳大利亚和荷兰的1019名参与者。障碍包括缺乏用户参与、缺乏培训、糟糕的系统设计以及数字亲和力的人口统计学差异。结论：本综述表明，老年LTC护理人员对数字技术的接受程度受到一系列个人因素的影响，如数字能力和感知到的技术相关性，以及组织因素，如获得培训和员工参与实施过程。尽管有这些见解，有限数量的实证研究突出了这一护理环境的研究差距。为了确保老年LTC的可持续数字化转型，未来的研究应优先考虑严谨和参与性的方法，采用纵向、基于干预或多层次的研究设计。

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引用次数: 0

Reducing Hospital-Acquired Pressure Injuries via a Quality Improvement Initiative: Results and Insights Gained. 通过质量改进倡议减少医院获得性压力伤害：结果和见解。

IF 4

JMIR nursing

Pub Date : 2026-01-03 DOI: 10.2196/90714

Mousa Asiri, Homoud Alanazi, Homoud Alanazi, Sahar Abdulkarim Al-Ghareeb, Bander Mohammed Alanazi, Badr Ayed Alenazy

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.

背景：医院获得性压力损伤（HAPIs）仍然是一个很大程度上可预防的患者伤害原因，经常被用作护理敏感的质量指标。在XXXXXX年的一家三级军队医院，由于幸福指数不断上升，有必要根据国家护理质量指标数据库（NDNQI）准则实施全面的质量改进方案。在Donabedian的结构-过程-结果模型的基础上，我们假设实施标准化的、基于证据的压力伤害预防捆绑，伴随着结构化的员工教育（结构），将提高对预防实践（过程）的依从性，并显着降低住院成人住院患者HAPI的发病率和患病率（结果）。目的：评价标准化、循证压伤预防工作包的引入及相应的医护人员教育对医院压伤发生率和患病率的影响。方法：采用以计划-执行-研究-行动（PDSA）循环、统计过程控制监测和FOCUS-PDSA框架为基础的前后方法学，在全院范围内实施了一项全面的质量改进项目。该战略为高危患者制定了标准化的一揽子预防措施；它包括常规风险和皮肤评估、定期重新定位、压力重新分配支持面、营养学家输入的营养优化和水分控制。主要结果是每月HAPI发生率（每1000患者日），使用伤口护理普查和单位报告测量，以及季度HAPI患病率，由训练有素的NDNQI联系护士使用NDNQI调查评估，分期的间信度为90%。结果：在初始部署阶段（2023年7 - 12月），HAPI发病率为2.32 / 1000患者-天（267例/115,314患者-天）。2024年发病率降至每1000患者日1.44例（330例/229,647患者日）（比基线减少38%），到2025年6月降至每1000患者日0.88例（98例/111,589患者日）（比基线减少62%）。患病率从2023年第三季度的5.12%下降到2024年第三季度的1.38%，并在2025年第二季度保持在1.43%的低位。结论：在系统的工作人员教育、跨学科合作和定期发病率和流行率监测的支持下，标准化预防方案的实施与HAPI发病率和流行率在2年内持续下降有关。这些发现支持基于捆绑的预防方法，结合实时反馈和能力驱动的教学，作为一种可扩展的增强患者安全的手段。临床试验:没有。

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引用次数: 0

Acceptance of Digital Technology among Nursing Staff in Geriatric Long-Term Care: A Systematic Review. 老年人长期护理中护理人员对数字技术的接受：一项系统综述。

IF 4

JMIR nursing

Pub Date : 2025-12-28 DOI: 10.2196/82223

Jeton Iseni, Walter Swoboda, Daniel Houben, Roman Hilla

Background: Digital technologies are increasingly being introduced into the healthcare system and in settings like 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 depends also on the acceptance by the primary users, 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 2020 guidelines. The SPIDER 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 three studies met the criteria, highlighting a gap in research on this topic. The studies applied cross-sectional quantitative designs, highlighted critical determinants of technology acceptance, including perceived usefulness, ease of use, digital competence and organizational support. The studies involved a total of n=1,019 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 like 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.

Clinicaltrial:

背景：数字技术越来越多地被引入医疗保健系统以及医院和老年长期护理（LTC）设施等环境，提供了诸如提高护理质量、减少工作量或增强文件处理等潜在好处。然而，这些技术的成功还取决于主要使用者——护理人员的接受程度。目的：在Yu等人（2009）的基础工作基础上，本综述综合了探索老年LTC环境中护理人员对数字技术接受程度的实证研究。目的是确定影响因素，评估现有证据的程度，并强调在这种护理环境中的研究差距。方法：根据PRISMA 2020指南进行系统文献综述。使用SPIDER框架作为资格标准。检索的数据库包括PubMed、ACM数字图书馆、Web of Science和健康管理数据库ProQuest。如果研究经验性地检查了老年LTC环境中护理人员对数字技术的接受程度，则将其纳入研究。两名审稿人独立筛选研究，提取数据并使用CASP（关键评估技能计划）检查表评估方法学质量。结果：共有3项研究符合标准，突出了该主题研究的空白。这些研究应用了横断面定量设计，强调了技术接受度的关键决定因素，包括感知有用性、易用性、数字能力和组织支持。这些研究共涉及来自德国、澳大利亚和荷兰的1019名参与者。障碍包括缺乏用户参与、缺乏培训、糟糕的系统设计和数字亲和力的人口统计学差异。结论：本综述表明，老年LTC环境中护理人员对数字技术的接受程度受到一系列个人因素的影响，如数字能力和感知到的技术相关性，以及组织因素，如获得培训和员工参与实施过程。尽管有这些见解，有限数量的实证研究突出了这一护理环境的研究差距。为了确保老年LTC的可持续数字化转型，未来的研究应优先考虑严谨和参与性的方法，采用纵向、基于干预或多层次的研究设计。临床试验:

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引用次数: 0

Impact of COVID-19 Pandemic-Induced Changes in Clinical Practicums on the Mental Health of Newly Graduated Nurses: Longitudinal Study. 新冠肺炎大流行导致的临床实习变化对新毕业护士心理健康影响的纵向研究

IF 4

JMIR nursing

Pub Date : 2025-12-23 DOI: 10.2196/79556

Takashi Ohue, Yuka Ohue

Background: The COVID-19 pandemic disrupted nursing education worldwide, particularly clinical practicums, reducing opportunities for hands-on learning. Newly graduated nurses have reported increased stress, reduced confidence, and a higher risk of burnout. However, few studies have examined the long-term mental health effects of these disruptions.

Objective: This study aimed to longitudinally examine how changes in clinical practicums during the COVID-19 pandemic affected the mental health of nurses who graduated in the academic year 2021-2022.

Methods: A quantitative longitudinal study was conducted at 3 time points: June 2022, September 2022, and December 2022. This study assessed the nurses' demographic data and the perceived impact on the students of disruptions in domain-specific and integration practicums, practicum formats, and clinical difficulty. Instruments used included the Nursing Job Stressor Scale, the Maslach Burnout Inventory, and adapted items for measuring intention to leave the profession. Participants were categorized into high- and low-impact groups. A 2-way ANOVA was used to examine mental health indicators over time.

Results: Participants who perceived a greater impact of practicum disruptions reported substantially higher levels of clinical difficulty and stressors. In the September 2022 survey, those perceiving less impact from the integration practicum reported a stronger intention to continue nursing. In the December 2022 survey, emotional exhaustion, a core component of burnout, was significantly higher in the high-impact group.

Conclusions: The perceived quality and extent of clinical practicum experiences significantly influenced the psychological burden and career intentions of newly graduated nurses. Disruptions caused by the COVID-19 pandemic may have lasting effects on nurses' mental health. These findings underscore the need for continuous workplace support and targeted mental health interventions for early-career nurses to ensure safe and sustainable nursing practice.

背景：2019冠状病毒病大流行扰乱了全球护理教育，特别是临床实习，减少了实践学习的机会。据报道，刚毕业的护士压力增加，信心下降，倦怠的风险更高。然而，很少有研究调查这些干扰对心理健康的长期影响。目的：本研究旨在纵向考察2019冠状病毒病大流行期间临床实习的变化对2021-2022学年毕业护士心理健康的影响。方法：在2022年6月、2022年9月和2022年12月三个时间点进行定量纵向研究。本研究评估了护士的人口统计数据，以及在特定领域和整合实习、实习形式和临床难度方面中断对学生的感知影响。使用的工具包括护理工作压力源量表、马斯拉克职业倦怠量表和用于测量离职意向的适应性项目。参与者被分为高影响力组和低影响力组。采用双因素方差分析来检查心理健康指标随时间的变化。结果：认为实习中断影响更大的参与者报告了更高水平的临床困难和压力源。在2022年9月的调查中，那些认为整合实习影响较小的人表示更愿意继续护理。在2022年12月的调查中，情绪耗竭（倦怠的核心组成部分）在高影响力组中明显更高。结论：临床实习体验的感知质量和程度对新毕业护士的心理负担和职业意向有显著影响。COVID-19大流行造成的破坏可能会对护士的心理健康产生持久影响。这些发现强调需要持续的工作场所支持和有针对性的心理健康干预，以确保早期职业护士安全和可持续的护理实践。

{"title":"Impact of COVID-19 Pandemic-Induced Changes in Clinical Practicums on the Mental Health of Newly Graduated Nurses: Longitudinal Study.","authors":"Takashi Ohue, Yuka Ohue","doi":"10.2196/79556","DOIUrl":"10.2196/79556","url":null,"abstract":"Background: The COVID-19 pandemic disrupted nursing education worldwide, particularly clinical practicums, reducing opportunities for hands-on learning. Newly graduated nurses have reported increased stress, reduced confidence, and a higher risk of burnout. However, few studies have examined the long-term mental health effects of these disruptions.Objective: This study aimed to longitudinally examine how changes in clinical practicums during the COVID-19 pandemic affected the mental health of nurses who graduated in the academic year 2021-2022.Methods: A quantitative longitudinal study was conducted at 3 time points: June 2022, September 2022, and December 2022. This study assessed the nurses' demographic data and the perceived impact on the students of disruptions in domain-specific and integration practicums, practicum formats, and clinical difficulty. Instruments used included the Nursing Job Stressor Scale, the Maslach Burnout Inventory, and adapted items for measuring intention to leave the profession. Participants were categorized into high- and low-impact groups. A 2-way ANOVA was used to examine mental health indicators over time.Results: Participants who perceived a greater impact of practicum disruptions reported substantially higher levels of clinical difficulty and stressors. In the September 2022 survey, those perceiving less impact from the integration practicum reported a stronger intention to continue nursing. In the December 2022 survey, emotional exhaustion, a core component of burnout, was significantly higher in the high-impact group.Conclusions: The perceived quality and extent of clinical practicum experiences significantly influenced the psychological burden and career intentions of newly graduated nurses. Disruptions caused by the COVID-19 pandemic may have lasting effects on nurses' mental health. These findings underscore the need for continuous workplace support and targeted mental health interventions for early-career nurses to ensure safe and sustainable nursing practice.","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e79556"},"PeriodicalIF":4.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12724397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of AI Literacy on Well-Being Among Nursing Students-Mediating Roles of Empowerment and Anxiety: Cross-Sectional Study. 人工智能素养对护生幸福感的影响——授权和焦虑的中介作用：横断面研究

IF 4

JMIR nursing

Pub Date : 2025-12-22 DOI: 10.2196/79789

Amira Alshowkan, Emad Shdaifat

Background: The integration of artificial intelligence (AI) in health care is changing nursing practice, and it calls for the acquisition of AI literacy by students, which includes knowledge, skills, and attitudes. An understanding of the effect of AI literacy on the well-being and empowerment of students is crucial in guiding effective educational strategies.

Objective: This study aims to investigate the impact of AI literacy on well-being, with psychological empowerment and anxiety serving as mediating variables. Using partial least squares structural equation modeling (PLS-SEM), this study examines gender differences within these relationships.

Methods: A cross-sectional design was used, and data were gathered from 497 nursing students from Imam Abdulrahman Bin Faisal University, Saudi Arabia, via a structured online questionnaire assessing AI literacy, psychological empowerment, anxiety, and well-being. PLS-SEM was used to evaluate both the measurement and structural models, encompassing mediation and multigroup analyses based on gender.

Results: The constructs demonstrated substantial reliability and validity, and the model's fit was deemed satisfactory. Well-being was moderately accounted for (R²=0.41), whereas empowerment and anxiety exhibited lower levels of explained variance. All hypotheses were supported, indicating that AI literacy positively influenced empowerment and negatively affected both anxiety and well-being. Furthermore, empowerment was found to negatively impact both anxiety and well-being. The mediation effects were significant, and no gender differences were observed.

Conclusions: The study demonstrates that AI literacy significantly influences psychological empowerment, anxiety, and overall well-being through both direct and indirect pathways. The findings elucidate the intricate relationships among these variables and provide evidence for the applicability of the model across genders. This underscores the critical importance of promoting AI literacy and empowerment as a means to improve well-being outcomes.

背景：人工智能（AI）在医疗保健中的整合正在改变护理实践，这需要学生获得人工智能素养，包括知识、技能和态度。了解人工智能素养对学生福祉和赋权的影响，对于指导有效的教育战略至关重要。目的：本研究旨在探讨人工智能素养对幸福感的影响，并以心理赋权和焦虑为中介变量。利用偏最小二乘结构方程模型（PLS-SEM），本研究考察了这些关系中的性别差异。方法：采用横断面设计，通过结构化的在线问卷评估人工智能素养、心理赋权、焦虑和幸福感，从沙特阿拉伯伊玛目·阿卜杜勒拉赫曼·本·费萨尔大学的497名护理专业学生中收集数据。PLS-SEM用于评估测量和结构模型，包括基于性别的中介和多组分析。结果：本构念具有相当的信度和效度，模型的拟合令人满意。幸福感被适度解释（R²=0.41），而授权和焦虑表现出较低水平的解释方差。所有假设都得到支持，表明人工智能素养对赋权产生积极影响，对焦虑和幸福感产生负面影响。此外，赋权被发现对焦虑和幸福感都有负面影响。中介效应显著，且无性别差异。结论：该研究表明，人工智能素养通过直接和间接途径显著影响心理赋权、焦虑和整体幸福感。研究结果阐明了这些变量之间错综复杂的关系，并为该模型的跨性别适用性提供了证据。这强调了促进人工智能素养和赋权作为改善福祉结果的手段的至关重要性。

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引用次数: 0

Sociotechnical Needs of Registered Nurses in the Heart Failure Hospitalizations of African American Patients: Cross-Sectional Study. 非裔美国人心力衰竭住院患者注册护士的社会技术需求：横断面研究。

IF 4

JMIR nursing

Pub Date : 2025-12-12 DOI: 10.2196/75080

Tremaine Brueon Williams, Milan Bimali, Maryam Y Garza, Pearman Parker, Chase Paladino-Vaden, Emel Seker, Alisha Crump, Randy Rice, Latrina Prince, Taren Massey-Swindle, Kevin Wayne Sexton

Background: The African American population is disproportionately impacted by congestive heart failure (CHF). The impact includes a hospitalization rate that is 2.5 times higher and a hospital stay that is, on average, a quarter of a day longer compared with Caucasians. Notably, nursing care has been associated with nearly a 30% decrease in hospitalizations and readmissions. Previous studies have demonstrated that registered nurses (RNs), working in conjunction with electronic health record systems to conduct care tasks, may optimize length of stay in African Americans with CHF.

Objective: This study aimed to identify the needs of RNs who performed sociotechnical tasks, the perceived importance of these sociotechnical tasks, and the perceived performance of these tasks by RNs, in relation to the length of stay of their African American patients with CHF.

Methods: The study used an observational, cross-sectional survey design in RNs who were randomly selected from a total population of 3498 RNs who provided care to 22,703 African American patients with CHF within 113,543 heart failure hospitalizations between January 1, 2015, and January 1, 2024. The RNs were retrospectively stratified into 2 groups based on EHR data: those whose African American patients had a mean length of stay of 10 days or less (Group A) and those whose mean length of stay was greater than 10 days (Group B). Descriptive statistics, Cohen d, and a 2-sided unpaired t test were used to analyze the data.

Results: The total sample of 200 RNs responded to the survey (100% survey completion rate). Group A (100 RNs) reported the least important task as drawing conclusions about how to use the EHR to care for African American patients (mean 4.66, SD 1.82). The least important task in Group B (100 RNs) was reading published research on African American patients (mean 4.88, SD 1.70). Group A reported performing best in caring for African American patients (mean 5.61, SD 1.44). Group B reported performing best at caring for all patients (mean 5.86, SD 1.04). A total of 17 significant sociotechnical needs were identified among groups. In total, 2 sociotechnical needs were unique to group B: caring for patients (ie, the full scope of social and technological processes in nursing care; Cohen d=0.32, 95% CI 0.04-0.59; P=.04) and working with information related to a patient's CHF in the EHR (eg, laboratory results, discharge summaries, or radiographic images) to care for the patient (Cohen d=0.33, 95% CI 0.05-0.61; P=.03).

Conclusions: Lengths of patient stay may be reduced by identifying and addressing sociotechnical needs through targeted training, nursing care interventions, and RN-led risk stratification guidelines for working with EHRs to reduce lengths of stay in those who are disproportionately impacted by CHF.

背景：非洲裔美国人受充血性心力衰竭（CHF）的影响不成比例。其影响包括住院率是白人的2.5倍，住院时间平均比白人长四分之一天。值得注意的是，护理与住院和再入院率降低近30%有关。先前的研究表明，注册护士（RNs）与电子健康记录系统一起工作来执行护理任务，可以优化非裔美国人CHF的住院时间。目的：本研究旨在确定执行社会技术任务的注册护士的需求，这些社会技术任务的感知重要性，以及注册护士对这些任务的感知表现，与他们的非裔美国CHF患者的住院时间有关。方法：该研究采用观察性横断面调查设计，随机选择从2015年1月1日至2024年1月1日期间113,543例心力衰竭住院患者中为22,703名非裔美国人瑞士法郎患者提供护理的3498名注册护士。根据电子病历资料将注册护士回顾性地分为两组：平均住院时间不超过10天的非裔美国患者（a组）和平均住院时间大于10天的注册护士（B组）。采用描述性统计、Cohen d和双侧非配对t检验对数据进行分析。结果：共有200名注册护士参与调查，调查完成率100%。A组（100名注册护士）报告的最不重要的任务是得出关于如何使用电子病历照顾非裔美国患者的结论（平均4.66，标准差1.82）。B组（100名注册护士）最不重要的任务是阅读关于非裔美国患者的已发表研究（平均4.88，标准差1.70）。据报道，A组在照顾非裔美国患者方面表现最好（平均5.61，标准差1.44）。B组在护理所有患者方面表现最好（平均5.86，标准差1.04）。共有17个重要的社会技术需求在群体中被确定。总的来说，B组有2个社会技术需求是独特的：照顾病人（即护理中社会和技术过程的全部范围；Cohen d=0.32, 95% CI 0.04-0.59； P= 0.04）和处理电子病历中与病人CHF相关的信息（例如，实验室结果、出院总结或放射图像）来照顾病人（Cohen d=0.33, 95% CI 0.05-0.61； P= 0.03）。结论：通过有针对性的培训、护理干预和rn主导的风险分层指南来识别和解决社会技术需求，可以缩短患者的住院时间，这些指南与电子病历一起工作，以减少那些受到CHF不成比例影响的患者的住院时间。

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引用次数: 0

An Expert Knowledge Algorithm and Model Predicting Wound Healing Trends for a Decision Support System for Pressure Injury Management in Home Care Nursing: Development and Validation Study. 一个专家知识算法和模型预测伤口愈合趋势的决策支持系统在家庭护理压力损伤管理：开发和验证研究。

IF 4

JMIR nursing

Pub Date : 2025-12-09 DOI: 10.2196/65716

Aya Kitamura, Aruto Ando, Gojiro Nakagami, Hiromi Sanada

Background: Home-visiting nurses have difficulty selecting appropriate pressure injury (PI) management despite using clinical practice guidelines in various home-visiting settings. Clinical decision support systems can help home-visiting nurses' decision-making.Objective: This study aimed to develop a care algorithm reflecting the expertise of a wound expert nurse and a predictive model for the change of PI severity to inform home-visiting nurses to receive actual consultation.Methods: First, an existing algorithm was modified by semistructured interviews with a certified wound expert nurse. Case information was input into both base and high-expertise algorithms, which provided care recommendations across 9 fields: (1) pressure relief; (2) nutritional management; (3) shear relief; (4) moisture management; (5) wound dressing use; (6) care for physical factors including bone prominence, obesity, joint contractures, and periwound edema; (7) care for systemic disorder; (8) selection of wound dressings, ointments, and negative pressure wound therapy; and (9) wound cleansing. An expert interviewee assessed the high-expertise algorithm's recommendations on a 5-point scale, comparing them to the base algorithm and their own clinical judgment. To measure the algorithm's applicability, agreement proportions were calculated as the number of vignettes where the care recommendation was considered appropriate or total number of vignettes. To measure the algorithm's alignment, improvement proportions were calculated as the number of vignettes where the care recommendation improved or total number of vignettes excluding vignettes when the existing and high-expertise algorithm both showed an appropriate recommendation. Expected healing levels were evaluated by a 4-point scale where 4 indicates the high-expertise algorithm can "much improve" the case. Second, predictive distributions of changes in DESIGN-R 2020 score, PI severity score, were estimated with a hierarchical Bayesian model. The best model determined using training data (n=42) calculated coverage probabilities of 90% prediction interval in test data (n=34). The coverage probability of a 90% prediction interval was defined as follows: the number of times when actual scores were within the 90% prediction interval or the number of assessments when the prediction was conducted.Results: The agreement proportions were 0.92 (33/36), 0.75 (27/36), and 0.89 (32/36) for each round. The improvement proportions were 0.73 (8/11), 0.25 (3/12), and 0.76 (13/17), respectively. The expected healing level was 2.67, 3.00, and 3.25, respectively. Coverage probabilities of 90% prediction interval in the test data were 0.67 (4/6), 0.83 (5/6), 0.86 (6/7), and 0.80 (8/10), respectively.Conclusions: This study developed an algorithm reflecting the expertise and a model to estimate predictive distributions of chan

背景：尽管在各种家访设置中使用临床实践指南，家访护士仍难以选择适当的压力损伤（PI）管理。临床决策支持系统可以帮助家访护士进行决策。目的：本研究旨在开发一种反映伤口专家护士专业知识的护理算法和PI严重程度变化的预测模型，以告知家访护士接受实际会诊。方法：首先，通过对一名注册伤口专家护士进行半结构化访谈，对现有算法进行改进。将病例信息输入到基础算法和高专业度算法中，该算法提供了9个领域的护理建议：(1)减压；(2)营养管理；(3)剪切救济；(4)水分管理；(5)伤口敷料的使用；(6)照顾生理因素，包括骨突出、肥胖、关节挛缩、创面周围水肿等；(7)全身性疾病的护理；(8)创面敷料、药膏的选择，负压创面治疗；(9)伤口清洗。一位专家受访者以5分制对高专业度算法的建议进行评估，并将其与基本算法和他们自己的临床判断进行比较。为了衡量算法的适用性，一致性比例被计算为护理建议被认为合适的小片段的数量或小片段的总数。为了衡量算法的一致性，改进比例被计算为护理建议得到改善的小片段的数量或排除现有和高专业度算法都显示适当推荐的小片段的总数量。预期愈合水平通过4分制进行评估，其中4表示高专业知识算法可以“大大改善”病例。其次，采用层次贝叶斯模型估计DESIGN-R 2020评分（PI严重程度评分）变化的预测分布。使用训练数据（n=42）确定的最佳模型计算了90%预测区间在测试数据（n=34）中的覆盖概率。90%预测区间的覆盖概率定义为：实际得分在90%预测区间内的次数或预测时的评估次数。结果：每轮的一致性比例分别为0.92（33/36）、0.75（27/36）和0.89（32/36）。改善比例分别为0.73（8/11）、0.25（3/12）和0.76（13/17）。预期愈合水平分别为2.67、3.00和3.25。测试数据中90%预测区间的覆盖概率分别为0.67（4/6）、0.83（5/6）、0.86（6/7）和0.80（8/10）。结论：本研究开发了一种反映专业知识的算法和一个模型来估计DESIGN-R 2020评分变化的预测分布，用于开发临床适用的临床决策支持系统，为家访护士提供适当的PI管理。

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引用次数: 0

Exploring Health Professionals' Knowledge and Perceptions of Telehealth Implementation in Multisite Public Hospitals of East Wollega Zone, Oromia, West Ethiopia: Cross-Sectional Study. 探索卫生专业人员的知识和远程医疗实施的看法在多地点公立医院东沃勒加区，奥罗米亚，西埃塞俄比亚：横断面研究。

IF 4

JMIR nursing

Pub Date : 2025-12-04 DOI: 10.2196/71870

Adugna Oluma, Tesfaye Abera Gudeta, Misganu Diriba Olana, Aliyi Benti Daba, Demiso Geneti Dinagde, Ashenafi Tesfaye Yadesa, Lammi Atomsa, Takele Mitiku Tesema

Background: A significant gap exists among health professionals regarding telehealth due to limited knowledge and varying perceptions. This disparity is particularly pronounced in low-income regions, where numerous barriers hinder its implementation.

Objective: This study aimed to assess the knowledge and perception of telehealth among health professionals in public hospitals in East Wollega, Oromia Region, Ethiopia.

Methods: A study was conducted with 397 health professionals in public health facilities in East Wollega Zone, selected through systematic random sampling. Data were collected via self-administered questionnaires from March 2024 to June 2024 and entered into EpiData (version 3.1; EpiData Association) and analyzed using SPSS (version 24; IBM Corp). Descriptive statistics, including percentages and frequency distributions, were used. The Hosmer and Lemeshow test assessed variable homogeneity. Significant variables (P<.05) in bivariable logistic regression analysis were included in multivariable logistic analysis and reported as adjusted odds ratios (AOR) with 95% CI.

Results: Findings indicated high levels of knowledge and perception among participants. Factors significantly associated with knowledge included educational status (AOR 4.22, 95% CI 3.45-13.12; P=.001), income between Ethiopian Birr 7001-9000 (a currency exchange rate of Ethiopian Birr 52=US $1 during the study period; AOR 3.255, 95% CI 1.790-8.878; P=.001), access to computers (AOR 2.414, 95% CI 1.046-14.764; P=.001), consultation sessions (AOR 2.389, 95% CI 1.961-10.158; P=.001), and smartphone use (AOR 3.027, 95% CI 2.797-14.729; P=.001). For perception, significant associations included income over 9000 Birr (AOR 2.675, 95% CI 2.271-19.277; P=.001), improving quality of life (AOR 1.786, 95% CI 1.575-22.587; P=.009), increased accessibility (AOR 1.244, 95% CI 1.061-11.333; P=.04), consultation sessions (AOR 4.777, 95% CI 2.318-15.062; P=.001), and smartphone use (AOR 3.836, 95% CI 2.900-13.573; P=.001).

Conclusions: Approximately two-thirds of participants demonstrated good knowledge and perception of telehealth. It is highly recommended to create awareness through educational programs for individuals with lower educational backgrounds and to improve access to technological devices.

背景：由于知识有限和观念不一，卫生专业人员在远程医疗方面存在很大差距。这种差距在低收入地区尤其明显，那里有许多障碍阻碍其实施。目的：本研究旨在评估埃塞俄比亚奥罗米亚地区东沃勒加公立医院卫生专业人员对远程医疗的知识和认知。方法：采用系统随机抽样的方法，对东沃勒加区公共卫生机构的397名卫生专业人员进行调查。数据采集时间为2024年3月至2024年6月，采用自填问卷收集，录入EpiData (version 3.1; EpiData Association)，使用SPSS （version 24; IBM Corp）进行分析。使用描述性统计，包括百分比和频率分布。Hosmer和Lemeshow检验评估变量同质性。显著变量(结果：研究结果表明，参与者的知识和感知水平较高。与知识显著相关的因素包括教育状况（AOR 4.22, 95% CI 3.45-13.12， P=.001）、埃塞俄比亚比尔7001-9000之间的收入（研究期间埃塞俄比亚比尔52= 1美元的货币汇率；AOR 3.255, 95% CI 1.790-8.878， P=.001）、使用电脑（AOR 2.414, 95% CI 1.046-14.764， P=.001）、咨询会议（AOR 2.389, 95% CI 1.961-10.158， P=.001）和智能手机使用（AOR 3.027, 95% CI 2.797-14.729， P=.001）。感知方面，显著相关包括收入超过9000 Birr （AOR 2.675, 95% CI 2.271-19.277； P= 0.001）、生活质量改善（AOR 1.786, 95% CI 1.575-22.587； P= 0.009）、可及性增加（AOR 1.244, 95% CI 1.061-11.333； P= 0.04）、咨询时间（AOR 4.777, 95% CI 2.318-15.062； P= 0.001）和智能手机使用（AOR 3.836, 95% CI 2.900-13.573； P= 0.001）。结论：大约三分之二的参与者表现出良好的远程保健知识和认知。强烈建议通过教育项目来提高教育背景较低的个人的意识，并改善技术设备的使用。

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引用次数: 0

Shift-to-Shift Information Transfer: Phenomenological Study of Nurses' Experiences. 轮班到轮班信息传递：护士经验的现象学研究。

IF 4

JMIR nursing

Pub Date : 2025-11-28 DOI: 10.2196/81703

María-Josefa Montoya-Garrido, Claudio-Alberto Rodríguez-Suárez, Noa Mateos-López, Yeray-Tomás Santiago-Díaz, Héctor González-de la Torre

Background: Handovers represent a critical moment for patient safety, where the effective transfer of information between nurses is essential. In this context, digital documentation systems such as identification, diagnosis, evolution, activities, support (IDEAS) have been implemented to standardize and enhance the quality of clinical handovers.Objective: This study aims to explore nurses' perceptions in the hospital setting regarding information transfer during shift changes. Specific objectives included identifying the perceived strengths and weaknesses of the handover process, as well as the difficulties and improvement proposals reported by nurses.Methods: A qualitative study with a phenomenological approach was conducted. Semistructured interviews were carried out with nurses from the Hospital Universitario Insular de Gran Canaria who had experience using the IDEAS system, between June 2023 and September 2024, until data saturation was reached. After transcribing the interviews, an inductive thematic analysis was performed to identify emerging themes using both descriptive and interpretative approaches. Axial coding through co-occurrence analysis, analytical triangulation, and reflexivity strategies was incorporated to strengthen the credibility and consistency of the findings. Atlas.ti software (version 25.0.1; Scientific Software Development GmbH) was used for the analysis. The study was approved by the local ethics committee (code: 2023-244-1).Results: From the interviews (n=15), 6 subthemes were identified and grouped into three main themes: (1) nurses (difficulties and improvement proposals in information transfer, strengths and weaknesses in the handover process), (2) patients (electronic health records: Benefit for patients, transfer of patient information), and (3) records (Comments on the form, information management). Participants valued the structured access to clinical information provided by the IDEAS system. However, they reported limitations such as poor data prioritization, editing difficulties, outdated information, and a lack of integration between nursing and medical records. In addition, training deficiencies and variability in system use, particularly among less experienced professionals, were noted. Suggestions for improvement included redesigning the handover form, automating updates, incorporating brief clinical summaries, and providing ongoing training.Conclusions: While the IDEAS system represents an improvement over previous handover methods, its effectiveness remains constrained by technical, organizational, and cultural barriers. Optimizing the system requires clinically oriented redesigns, alongside training strategies and an institutional culture that promotes shared responsibility for documentation quality. These elements are essential for establishing a safer, more standardized, and patient-cent

背景：交接是患者安全的关键时刻，护士之间有效的信息传递是必不可少的。在这种情况下，已经实施了诸如识别、诊断、演变、活动、支持（IDEAS）等数字文件系统，以标准化和提高临床移交的质量。目的：本研究旨在探讨医院护士对换班期间信息传递的认知。具体目标包括确定交接过程的优势和劣势，以及护士报告的困难和改进建议。方法：采用现象学方法进行定性研究。在2023年6月至2024年9月期间，对来自大加那利岛大学医院（Hospital Universitario Insular de Gran Canaria）有使用IDEAS系统经验的护士进行了半结构化访谈，直到达到数据饱和。在记录访谈后，进行归纳主题分析，以确定使用描述性和解释性方法的新兴主题。通过共现分析、分析三角测量和反身性策略进行轴向编码，以加强研究结果的可信度和一致性。阿特拉斯。采用ti软件（version 25.0.1; Scientific software Development GmbH）进行分析。本研究已获得当地伦理委员会批准（代码：2023-244-1）。结果：从访谈（n=15）中，确定了6个子主题，并将其分为三个主题：(1)护士（信息传递的困难和改进建议、移交过程中的优势和劣势）、(2)患者（电子病历：患者受益、患者信息传递）和(3)病历（表格评论、信息管理）。参与者非常重视IDEAS系统提供的临床信息的结构化访问。然而，他们报告了诸如数据优先级差、编辑困难、过时信息以及护理和医疗记录之间缺乏整合等局限性。此外，还注意到系统使用方面的培训不足和变化，特别是经验不足的专业人员。改进建议包括重新设计交接表、自动更新、合并简短的临床总结以及提供持续的培训。结论：虽然IDEAS系统比以前的移交方法有所改进，但其有效性仍然受到技术、组织和文化障碍的限制。优化系统需要以临床为导向的重新设计，以及培训策略和促进文件质量共享责任的机构文化。这些要素对于建立一个更安全、更标准化和以患者为中心的临床交接模式至关重要。

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引用次数: 0

Interpretation of Health-Smart Home Data and Implications for Clinical Decision-Making: Inductive Content Analysis. 解读健康智能家居数据及其对临床决策的影响：归纳内容分析。

IF 4

JMIR nursing

Pub Date : 2025-11-21 DOI: 10.2196/75234

Gordana Dermody, Diane J Cook, Roschelle L Fritz

Background: Health-smart home technologies offer real-time sensor-based monitoring of older adult activities of daily living, allowing for early detection of changes in health. The way clinicians interpret and use this data, particularly in visualized formats, such as bar, line, and pie graphs, remains underexplored.

Objective: A qualitative descriptive study design with a quantitative component was used to explore how nurses interpret sensor-derived health data from health-smart homes in 3 cases.

Methods: Using an inductive content analysis approach, we analyzed nurses' qualitative interpretations of existing sensor-derived health data from health-smart homes from 3 older adults living with ambient whole-home sensing. Nurses provided structured written feedback on visualized trends in sensor-derived health data, including activity, sleep, and mobility patterns.

Results: The findings highlight both opportunities and challenges of using sensor-derived health data in older adults' care. Nurses identified key patterns in sleep, mobility, and home engagement, but interpretation difficulties, such as unclear sleep metrics and lack of clinical context, hindered decision-making. Nurses preferred bar and line graphs over pie charts for interpreting these data. Survey results show a statistically significant difference in how nurses rated different graph types (χ²2=17.1, P<.001), with pie charts rated significantly lower than both bar and line graphs (P<.001 and P=.008, respectively). These findings underscore the need for improved data visualization and integration to enhance the clinical utility of sensor-derived health data from health-smart homes.

Conclusions: Findings indicate that nurses were able to provide accurate interpretations of the sensor-derived health data from health-smart homes. However, there is a need for improved visualization techniques and clinician training to optimize health-smart home data for early intervention. Standardized approaches to data representation could enhance nurses' ability to detect and act on subtle yet important information about older adults' health changes occurring in home settings.

背景：健康智能家居技术提供基于传感器的老年人日常生活活动实时监测，允许早期发现健康变化。临床医生解释和使用这些数据的方式，特别是可视化格式，如条形图、线形图和饼状图，仍未得到充分探索。目的：采用定量成分的定性描述性研究设计，探讨护士如何解释来自健康智能家居的传感器衍生健康数据。方法：采用归纳内容分析方法，分析护士对健康智能家居中现有传感器衍生健康数据的定性解释，这些数据来自3名生活在环境全家居传感中的老年人。护士对传感器衍生的健康数据的可视化趋势提供结构化的书面反馈，包括活动、睡眠和移动模式。结果：研究结果强调了在老年人护理中使用传感器衍生健康数据的机遇和挑战。护士确定了睡眠、活动和家庭参与的关键模式，但解释困难，如不清楚的睡眠指标和缺乏临床背景，阻碍了决策。在解释这些数据时，护士更喜欢柱状图和线形图，而不是饼状图。调查结果显示，护士对不同图表类型的评分差异有统计学意义（χ 2=17.1, p）。结论：研究结果表明，护士能够对健康智能家居的传感器健康数据提供准确的解释。然而，需要改进可视化技术和临床医生培训，以优化健康智能家居数据，以便进行早期干预。数据表示的标准化方法可以提高护士发现老年人在家庭环境中发生的健康变化的细微但重要的信息并采取行动的能力。

{"title":"Interpretation of Health-Smart Home Data and Implications for Clinical Decision-Making: Inductive Content Analysis.","authors":"Gordana Dermody, Diane J Cook, Roschelle L Fritz","doi":"10.2196/75234","DOIUrl":"10.2196/75234","url":null,"abstract":"Background: Health-smart home technologies offer real-time sensor-based monitoring of older adult activities of daily living, allowing for early detection of changes in health. The way clinicians interpret and use this data, particularly in visualized formats, such as bar, line, and pie graphs, remains underexplored.Objective: A qualitative descriptive study design with a quantitative component was used to explore how nurses interpret sensor-derived health data from health-smart homes in 3 cases.Methods: Using an inductive content analysis approach, we analyzed nurses' qualitative interpretations of existing sensor-derived health data from health-smart homes from 3 older adults living with ambient whole-home sensing. Nurses provided structured written feedback on visualized trends in sensor-derived health data, including activity, sleep, and mobility patterns.Results: The findings highlight both opportunities and challenges of using sensor-derived health data in older adults' care. Nurses identified key patterns in sleep, mobility, and home engagement, but interpretation difficulties, such as unclear sleep metrics and lack of clinical context, hindered decision-making. Nurses preferred bar and line graphs over pie charts for interpreting these data. Survey results show a statistically significant difference in how nurses rated different graph types (χ²2=17.1, P<.001), with pie charts rated significantly lower than both bar and line graphs (P<.001 and P=.008, respectively). These findings underscore the need for improved data visualization and integration to enhance the clinical utility of sensor-derived health data from health-smart homes.Conclusions: Findings indicate that nurses were able to provide accurate interpretations of the sensor-derived health data from health-smart homes. However, there is a need for improved visualization techniques and clinician training to optimize health-smart home data for early intervention. Standardized approaches to data representation could enhance nurses' ability to detect and act on subtle yet important information about older adults' health changes occurring in home settings.","PeriodicalId":73556,"journal":{"name":"JMIR nursing","volume":"8 ","pages":"e75234"},"PeriodicalIF":4.0,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12638034/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145575027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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