JMIR Nursing
Virtualizing care from hospital to community: Mobile health, telehealth, and digital patient care.
Editor-in-Chief:
Elizabeth Borycki, RN, PhD, FIAHIS, FACMI, FCAHS, Social Dimensions of Health Program Director, Health and Society Program Director, Office of Interdisciplinary Studies; Professor, School of Health Information Science, University of Victoria, Canada
CiteScore 5.2
Recent Articles
![A Scalable and Extensible Logical Data Model of Electronic Health Record Audit Logs for Temporal Data Mining (RNteract): Model Conceptualization and Formulation Article Thumbnail](https://asset.jmir.pub/assets/aa83317bc5d340a5ee8a34b731cf18b7.png 480w,https://asset.jmir.pub/assets/aa83317bc5d340a5ee8a34b731cf18b7.png 960w,https://asset.jmir.pub/assets/aa83317bc5d340a5ee8a34b731cf18b7.png 1920w,https://asset.jmir.pub/assets/aa83317bc5d340a5ee8a34b731cf18b7.png 2500w)
Increased workload, including workload related to electronic health record (EHR) documentation, is reported as a main contributor to nurse burnout and adversely affects patient safety and nurse satisfaction. Traditional methods for workload analysis are either administrative measures (such as the nurse-patient ratio) that do not represent actual nursing care or are subjective and limited to snapshots of care (eg, time-motion studies). Observing care and testing workflow changes in real time can be obstructive to clinical care. An examination of EHR interactions using EHR audit logs could provide a scalable, unobtrusive way to quantify the nursing workload, at least to the extent that nursing work is represented in EHR documentation. EHR audit logs are extremely complex; however, simple analytical methods cannot discover complex temporal patterns, requiring use of state-of-the-art temporal data-mining approaches. To effectively use these approaches, it is necessary to structure the raw audit logs into a consistent and scalable logical data model that can be consumed by machine learning (ML) algorithms.
![Navigating the Pedagogical Landscape: Exploring the Implications of AI and Chatbots in Nursing Education Article Thumbnail](https://asset.jmir.pub/assets/fcc90f897e20afaafcc16c7c76b80609.png 480w,https://asset.jmir.pub/assets/fcc90f897e20afaafcc16c7c76b80609.png 960w,https://asset.jmir.pub/assets/fcc90f897e20afaafcc16c7c76b80609.png 1920w,https://asset.jmir.pub/assets/fcc90f897e20afaafcc16c7c76b80609.png 2500w)
This viewpoint paper explores the pedagogical implications of artificial intelligence (AI) and AI-based chatbots such as ChatGPT in nursing education, examining their potential uses, benefits, challenges, and ethical considerations. AI and chatbots offer transformative opportunities for nursing education, such as personalized learning, simulation and practice, accessible learning, and improved efficiency. They have the potential to increase student engagement and motivation, enhance learning outcomes, and augment teacher support. However, the integration of these technologies also raises ethical considerations, such as privacy, confidentiality, and bias. The viewpoint paper provides a comprehensive overview of the current state of AI and chatbots in nursing education, offering insights into best practices and guidelines for their integration. By examining the impact of AI and ChatGPT on student learning, engagement, and teacher effectiveness and efficiency, this review aims to contribute to the ongoing discussion on the use of AI and chatbots in nursing education and provide recommendations for future research and development in the field.
![Evaluation of Autonomic Nervous System Function During Sleep by Mindful Breathing Using a Tablet Device: Randomized Controlled Trial Article Thumbnail](https://asset.jmir.pub/assets/26c83493d7e6599b9e9afffb9321c9b7.png 480w,https://asset.jmir.pub/assets/26c83493d7e6599b9e9afffb9321c9b7.png 960w,https://asset.jmir.pub/assets/26c83493d7e6599b9e9afffb9321c9b7.png 1920w,https://asset.jmir.pub/assets/26c83493d7e6599b9e9afffb9321c9b7.png 2500w)
One issue to be considered in universities is the need for interventions to improve sleep quality and educational systems for university students. However, sleep problems remain unresolved. As a clinical practice technique, a mindfulness-based stress reduction method can help students develop mindfulness skills to cope with stress, self-healing skills, and sleep.
![Nurses’ Use of mHealth Apps for Chronic Conditions: Cross-Sectional Survey Article Thumbnail](https://asset.jmir.pub/assets/b6f7375aee6829a1c6506eb2749403c7.png 480w,https://asset.jmir.pub/assets/b6f7375aee6829a1c6506eb2749403c7.png 960w,https://asset.jmir.pub/assets/b6f7375aee6829a1c6506eb2749403c7.png 1920w,https://asset.jmir.pub/assets/b6f7375aee6829a1c6506eb2749403c7.png 2500w)
Mobile health (mHealth) is increasingly used to support public health practice, as it has positive benefits such as enhancing self-efficacy and facilitating chronic disease management. Yet, relatively few studies have explored the use of mHealth apps among nurses, despite their important role in caring for patients with and at risk of chronic conditions.
![Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review Article Thumbnail](https://asset.jmir.pub/assets/908be094b633d2fd286dce52eb505280.png 480w,https://asset.jmir.pub/assets/908be094b633d2fd286dce52eb505280.png 960w,https://asset.jmir.pub/assets/908be094b633d2fd286dce52eb505280.png 1920w,https://asset.jmir.pub/assets/908be094b633d2fd286dce52eb505280.png 2500w)
The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence–based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early.
![The Cooperation Between Nurses and a New Digital Colleague “AI-Driven Lifestyle Monitoring” in Long-Term Care for Older Adults: Viewpoint Article Thumbnail](https://asset.jmir.pub/assets/e4e326dae073f5ffbefc8fea7d8597f8.png 480w,https://asset.jmir.pub/assets/e4e326dae073f5ffbefc8fea7d8597f8.png 960w,https://asset.jmir.pub/assets/e4e326dae073f5ffbefc8fea7d8597f8.png 1920w,https://asset.jmir.pub/assets/e4e326dae073f5ffbefc8fea7d8597f8.png 2500w)
Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult’s home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague.
![Health Care Workers’ Expectations of the Mercury Advance SMARTcare Solution to Prevent Pressure Injuries: Individual and Focus Group Interview Study Article Thumbnail](https://asset.jmir.pub/assets/fcc271a7c3c11b947fb484072d744a76.png 480w,https://asset.jmir.pub/assets/fcc271a7c3c11b947fb484072d744a76.png 960w,https://asset.jmir.pub/assets/fcc271a7c3c11b947fb484072d744a76.png 1920w,https://asset.jmir.pub/assets/fcc271a7c3c11b947fb484072d744a76.png 2500w)
The transformation in global demography and the shortage of health care workers require innovation and efficiency in the field of health care. Digital technology can help improve the efficiency of health care. The Mercury Advance SMARTcare solution is an example of digital technology. The system is connected to a hybrid mattress and is able to detect patient movement, based on which the air pump either starts automatically or sends a notification to the app. Barriers to the adoption of the system are unknown, and it is unclear if the solution will be able to support health care workers in their work.
![In-Home Respite Care Services Available to Families With Palliative Care Needs in Quebec: Novel Digital Environmental Scan Article Thumbnail](https://asset.jmir.pub/assets/ecb625c911c836643e464f4e4a2f9ac2.png 480w,https://asset.jmir.pub/assets/ecb625c911c836643e464f4e4a2f9ac2.png 960w,https://asset.jmir.pub/assets/ecb625c911c836643e464f4e4a2f9ac2.png 1920w,https://asset.jmir.pub/assets/ecb625c911c836643e464f4e4a2f9ac2.png 2500w)
Caregiving dyads in palliative care are confronted with complex care needs. Respite care services can be highly beneficial in alleviating the caregiving burden, supporting survivorship and dying at home. Yet, respite care services are difficult to locate and access in the province of Quebec, Canada, particularly when navigating ubiquitous sources of online health information of varying quality.
![Sentiment Analysis of Patient- and Family-Related Sepsis Events: Exploratory Study Article Thumbnail](https://asset.jmir.pub/assets/6a5846c58be4f59e40c384d7121d6c4e.png 480w,https://asset.jmir.pub/assets/6a5846c58be4f59e40c384d7121d6c4e.png 960w,https://asset.jmir.pub/assets/6a5846c58be4f59e40c384d7121d6c4e.png 1920w,https://asset.jmir.pub/assets/6a5846c58be4f59e40c384d7121d6c4e.png 2500w)
Despite the life-threatening nature of sepsis, little is known about the emotional experiences of patients and their families during sepsis events. We conducted a sentiment analysis pertaining to sepsis incidents involving patients and families, leveraging textual data retrieved from a publicly available blog post disseminated by the Centers for Disease Control and Prevention (CDC).
![Technology-Supported Guidance Models to Stimulate Nursing Students’ Self-Efficacy in Clinical Practice: Scoping Review Article Thumbnail](https://asset.jmir.pub/assets/04c0da2e1f2fdac17bfa7c9d3feb5953.png 480w,https://asset.jmir.pub/assets/04c0da2e1f2fdac17bfa7c9d3feb5953.png 960w,https://asset.jmir.pub/assets/04c0da2e1f2fdac17bfa7c9d3feb5953.png 1920w,https://asset.jmir.pub/assets/04c0da2e1f2fdac17bfa7c9d3feb5953.png 2500w)
In nursing education, bridging the gap between theoretical knowledge and practical skills is crucial for developing competence in clinical practice. Nursing students encounter challenges in acquiring these essential skills, making self-efficacy a critical component in their professional development. Self-efficacy pertains to individual’s belief in their ability to perform tasks and overcome challenges, with significant implications for clinical skills acquisition and academic success. Previous research has underscored the strong link between nursing students’ self-efficacy and their clinical competence. Technology has emerged as a promising tool to enhance self-efficacy by enabling personalized learning experiences and in-depth discussions. However, there is a need for a comprehensive literature review to assess the existing body of knowledge and identify research gaps.
![mHealth Gratitude Exercise Mindfulness App for Resiliency Among Neonatal Intensive Care Unit Staff: Three-Arm Pretest-Posttest Interventional Study Article Thumbnail](https://asset.jmir.pub/assets/342cc74a67378248ff56d0a3e7219f76.png 480w,https://asset.jmir.pub/assets/342cc74a67378248ff56d0a3e7219f76.png 960w,https://asset.jmir.pub/assets/342cc74a67378248ff56d0a3e7219f76.png 1920w,https://asset.jmir.pub/assets/342cc74a67378248ff56d0a3e7219f76.png 2500w)
Health care is highly complex and can be both emotionally and physically challenging. This can lead health care workers to develop compassion fatigue and burnout (BO), which can negatively affect their well-being and patient care. Higher levels of resilience can potentially prevent compassion fatigue and BO. Strategies that enhance resilience include gratitude, exercise, and mindfulness.
Preprints Open for Peer-Review
Open Peer Review Period:
-