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To review the current evidence on mixed reality (MR) applications in nursing practice, focusing on efficiency, ergonomics, satisfaction, competency, and team effectiveness.
Mixed methods systematic review of empirical studies evaluating MR interventions in nursing practice.
The systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered with PROSPERO. Studies were included if they assessed nursing outcomes related to MR interventions. Exclusion criteria encompassed reviews, studies focusing solely on virtual reality, and those involving only nursing students. The Cochrane ROBINS-I, RoB 2, and CASP tools assessed the risk of bias and methodological quality.
A comprehensive search of 12 databases (MEDLINE, Embase, CINAHL, Cochrane Library, Web of Science, and others) covered literature published between January 2013 and January 2023.
Eight studies met inclusion criteria, exploring diverse MR implementations, including smart glasses and mobile applications, across various nursing specialisations. MR demonstrated potential benefits in efficiency, such as faster task completion and improved accuracy. Satisfaction outcomes were limited but indicated promise. Ergonomic challenges were identified, including discomfort and technical issues. Studies on competency showed mixed results, with some evidence of improved skill acquisition. Team effectiveness and health equity outcomes were underexplored.
While MR shows potential in enhancing nursing practice, evidence is heterogeneous and clinical relevance remains unclear. Further rigorous comparative studies are necessary to establish its utility and address barriers to adoption.
MR technology may enhance nursing efficiency, competency and satisfaction. Addressing ergonomic and technical challenges could optimise adoption and benefit patient care.
This review adheres to PRISMA guidelines.
No Patient or Public Contribution.
PROSPERO registration: #CRD42022324066
As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System provides public health surveillance of US violent deaths; however, understanding the National Violent Death Reporting System's research utility is limited. The purpose of our rapid review of the 2019-2023 literature was to understand to what extent artificial intelligence methods are being used with the National Violent Death Reporting System. We identified 16 National Violent Death Reporting System artificial intelligence studies, with more than half published after 2020. The text-rich content of National Violent Death Reporting System enabled researchers to center their artificial intelligence approaches mostly on natural language processing (50%) or natural language processing and machine learning (37%). Significant heterogeneity in approaches, techniques, and processes was noted across the studies, with critical methods information often lacking. The aims and focus of National Violent Death Reporting System studies were homogeneous and mostly examined suicide among nurses and older adults. Our findings suggested that artificial intelligence is a promising approach to the National Violent Death Reporting System data with significant untapped potential in its use. Artificial intelligence may prove to be a powerful tool enabling nursing scholars and practitioners to reduce the number of preventable, violent deaths. To determine the frequency, timing, and duration of post-acute sequelae of SARS-CoV-2 infection (PASC) and their impact on health and function.
Post-acute sequelae of SARS-CoV-2 infection is an emerging major public health problem that is poorly understood and has no current treatment or cure. PASC is a new syndrome that has yet to be fully clinically characterised.
Descriptive cross-sectional survey (n = 5163) was conducted from online COVID-19 survivor support groups who reported symptoms for more than 21 days following SARS-CoV-2 infection.
Participants reported background demographics and the date and method of their covid diagnosis, as well as all symptoms experienced since onset of covid in terms of the symptom start date, duration, and Likert scales measuring three symptom-specific health impacts: pain and discomfort, work impairment, and social impairment. Descriptive statistics and measures of central tendencies were computed for participant demographics and symptom data.
Participants reported experiencing a mean of 21 symptoms (range 1–93); fatigue (79.0%), headache (55.3%), shortness of breath (55.3%) and difficulty concentrating (53.6%) were the most common. Symptoms often remitted and relapsed for extended periods of time (duration M = 112 days), longest lasting symptoms included the inability to exercise (M = 106.5 days), fatigue (M = 101.7 days) and difficulty concentrating, associated with memory impairment (M = 101.1 days). Participants reported extreme pressure at the base of the head, syncope, sharp or sudden chest pain, and “brain pressure” among the most distressing and impacting daily life.
Post-acute sequelae of SARS-CoV-2 infection can be characterised by a wide range of symptoms, many of which cause moderate-to-severe distress and can hinder survivors' overall well-being.
This study advances our understanding of the symptoms of PASC and their health impacts.
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