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

JMIR Nursing (JN, Editor-in-Chief: Elizabeth Borycki, RN PhD, FIAHIS, FACMI, FCAHS) is a peer-reviewed journal for nursing in the 21st century. The focus of this journal is original research related to the paradigm change in nursing due to information technology and the shift towards preventative, predictive, personal medicine:

"In the 21st century the whole foundations of health care are being shaken. Technology is taking service to new heights of portability: less invasive, short-term, and with greater impact on both the length and quality of life. (...)

Time-based nursing care with the activities of bathing, treating, changing, feeding, intervening, drugging, and discharging are quickly becoming historic references to an age of practice that no longer exists. Now the challenge for nursing practice skills relates more to taking on the activities of accessing, informing, guiding, teaching, counseling, typing, and linking. "

(Tim Porter-O'Brady, Nurs Outlook 2001;49:182-6)

All papers are rigorously peer-reviewed, copyedited, and XML-typeset. 

JMIR Nursing (JN, ISSN 2562-7600) is indexed in National Library of Medicine (NLM)/MEDLINE, PubMed, PubMed Central, DOAJ, Scopus, Sherpa Romeo, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the International Academy of Nursing Editors (INANE) directory of nursing journals. With a CiteScore of 5.2, JMIR Nursing ranks in the 88th percentile (#17 of 139) as a Q1 journal in the field of General Nursing.

Recent Articles

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Nursing Education and Training

Nursing students’ learning during clinical practice is largely influenced by the quality of the guidance they receive from their nurse preceptors. Students that have attended placement in nursing home settings have called for more time with nurse preceptors and an opportunity for more help from the nurses for reflection and developing critical thinking skills. To strengthen students’ guidance and assessment and enhance students’ learning in the practice setting, it has also been recommended to improve the collaboration between faculties and nurse preceptors.

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Nursing Education and Training

Caring profession students require skills and competencies to proficiently use information technologies for providing high-quality and effective care. However, there is a gap in exploring the perceptions and experiences of students in developing virtual care skills within online environments.

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Theme Issue (2023): Artificial Intelligence (AI) in Nursing

Although the use of artificial intelligence (AI)–based technologies, such as AI-based decision support systems (AI-DSSs), can help sustain and improve the quality and efficiency of care, their deployment creates ethical and social challenges. In recent years, a growing prevalence of high-level guidelines and frameworks for responsible AI innovation has been observed. However, few studies have specified the responsible embedding of AI-based technologies, such as AI-DSSs, in specific contexts, such as the nursing process in long-term care (LTC) for older adults.

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Theme Issue (2023): Artificial Intelligence (AI) in Nursing

Depression is one of the most common mental disorders that affects >300 million people worldwide. There is a shortage of providers trained in the provision of mental health care, and the nursing workforce is essential in filling this gap. The diagnosis of depression relies heavily on self-reported symptoms and clinical interviews, which are subject to implicit biases. The omics methods, including genomics, transcriptomics, epigenomics, and microbiomics, are novel methods for identifying the biological underpinnings of depression. Machine learning is used to analyze genomic data that includes large, heterogeneous, and multidimensional data sets.

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Viewpoints

eHealth interventions are becoming a part of standard care, with software solutions increasingly created for patients and health care providers. Testing of eHealth software is important to ensure that the software realizes its goals. Software testing, which is comprised of alpha and beta testing, is critical to establish the effectiveness and usability of the software. In this viewpoint, we explore existing practices for testing software in health care settings. We scanned the literature using search terms related to eHealth software testing (eg, “health alpha testing,” “eHealth testing,” and “health app usability”) to identify practices for testing eHealth software. We could not identify a single standard framework for software testing in health care settings; some articles reported frameworks, while others reported none. In addition, some authors misidentified alpha testing as beta testing and vice versa. There were several different objectives (ie, testing for safety, reliability, or usability) and methods of testing (eg, questionnaires, interviews) reported. Implementation of an iterative strategy in testing can introduce flexible and rapid changes when developing eHealth software. Further investigation into the best approach for software testing in health care settings would aid the development of effective and useful eHealth software, particularly for novice eHealth software developers.

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Relationship and Communication between Patients and Nurses

Multimedia interventions may play an important role in improving patient care and reducing the time constraints of patient-clinician encounters. The “MyStay Cardiac” multimedia resource is an innovative program designed to be accessed by adult patients undergoing cardiac surgery.

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Nursing Education and Training

As technology will continue to play a pivotal role in modern-day health care and given the potential impact on the nursing profession, it is vitally important to examine the types and features of digital health education in nursing so that graduates are better equipped with the necessary knowledge and skills needed to provide safe and quality nursing care and to keep abreast of the rapidly evolving technological revolution.

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Theme Issue (2023): Artificial Intelligence (AI) in Nursing

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.

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Theme Issue (2023): Artificial Intelligence (AI) in Nursing

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.

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Nursing and Public Health

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.

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Mobile Apps for Nurses

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.

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Theme Issue (2023): Artificial Intelligence (AI) in Nursing

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.

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