Background: Quality-of-care improvement and prevention of practice errors is dependent on nurses' adherence to the principles of patient safety. Aims: This paper aims to provide a systematic review of the international literature, to synthesise knowledge and explore factors that influence nurses' adherence to patient-safety principles. Methods: Electronic databases in English, Norwegian, and Finnish languages were searched, using appropriate keywords to retrieve empirical articles published from 2010-2019. Using the theoretical domains of the Vincent's framework for analysing risk and safety in clinical practice, we synthesized our findings according to 'patient', 'healthcare provider', 'task', 'work environment', and 'organisation and management'. Findings: Six articles were found that focused on adherence to patient-safety principles during clinical nursing interventions. They focused on the management of peripheral venous catheters, surgical hand rubbing instructions, double-checking policies of medicines management, nursing handover between wards, cardiac monitoring and surveillance, and care-associated infection precautions. Patients' participation, healthcare providers' knowledge and attitudes, collaboration by nurses, appropriate equipment and electronic systems, education and regular feedback, and standardization of the care process influenced nurses' adherence to patient-safety principles. Conclusions: The revelation of individual and systemic factors has implications for nursing care practice, as both influence adherence to patient-safety principles. More studies using qualitative and quantitative methods are required to enhance our knowledge of measures needed to improve nurse' adherence to patient-safety principles and their effects on patient-safety outcomes.
Purpose The purpose of this paper is to expand current knowledge about the recent trend of wearable technology to assess both its potential in the work environment and the challenges concerning the utilisation of wearables in the workplace. Design/methodology/approach After establishing exclusion and inclusion criteria, an independent systematic search of the ACM Digital Library, IEEE Xplore, ScienceDirect and Web of Science databases for relevant studies was performed. Out of a total of 359 articles, 34 met the selection criteria. Findings This review identifies 23 categories of wearable devices. Further categorisation of the devices based on their utilisation shows they can be used in the work environment for activities including monitoring, augmenting, assisting, delivering and tracking. The review reveals that wearable technology has the potential to increase work efficiency among employees, improve workers’ physical well-being and reduce work-related injuries. However, the review also reveals that technological, social, policy and economic challenges related to the use of wearable devices remain. Research limitations/implications Many studies have investigated the benefits of wearable devices for personal use, but information about the use of wearables in the work environment is limited. Further research is required in the fields of technology, social challenges, organisation strategies, policies and economics to enhance the adoption rate of wearable devices in work environments. Originality/value Previous studies indicate that occupational stress and injuries are detrimental to employees’ health; this paper analyses the use of wearable devices as an intervention method to monitor or prevent these problems. Introducing a categorisation framework during implementation may help identify which types of device categories are suitable and could be beneficial for specific utilisation purposes, facilitating the adoption of wearable devices in the workplace.
Since the 1950s, artificial intelligence (AI) has been a recurring topic in research. However, this field has only recently gained significant momentum because of the advances in technology and algorithms, along with new AI techniques such as machine learning methods for structured data, modern deep learning, and natural language processing for unstructured data. Although companies are eager to join the fray of this new AI trend and take advantage of its potential benefits, it is unclear what implications AI will have on society now and in the long term. Using the five dimensions of sustainability to structure the analysis, we explore the impacts of AI on several domains. We find that there is a significant impact on all five dimensions, with positive and negative impacts, and that value, collaboration, sharing responsibilities; ethics will play a vital role in any future sustainable development of AI in society. Our exploration provides a foundation for in-depth discussions and future research collaborations.
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