Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/28540
Title: Artificial intelligence and mindfulness: systematic literature review based on prisma method
Authors: Weerakkody, Shalini
Rajapaksha, Sisitha
Keywords: Artificial Intelligence, AI, Future Research Directions, Mindfulness, Systematic Literature Review
Issue Date: 2023
Publisher: The Library, University of Kelaniya, Sri Lanka
Citation: Weerakkody, Shalini; Rajapaksha, Sisitha (2023), Artificial intelligence and mindfulness: systematic literature review based on prisma method, The Journal of Desk Research Review and Analysis (2023) Volume 1, Issue 2, The Library, University of Kelaniya, Sri Lanka
Abstract: Isolating oneself from the constant barrage of new technologies and machines in today's fast-paced world can be challenging. Throughout history, people have used the practice of mindfulness to better themselves and find inner calm by focusing on the here and now rather than on the past or the future. However, in recent years, Artificial Intelligence has emerged from the technological revolution, radically altering the landscape of mental health and mindfulness. This conceptual review aims to revisit the prevailing literature on artificial intelligence and mindfulness and explore future research opportunities. A systematic literature review (SLR) with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used to conduct the review. VOSviewer software has been used to perform keyword co-occurrence analysis to reveal the areas that need the attention of researchers. Articles have been downloaded from the Scopus database to ensure the quality of the input of this conceptual paper. Future research directions have been provided with respect to the research gaps identified in this effort. Some knowledge gaps, empirical gaps, contextual gaps and methodological gaps have been identified in this research.
URI: http://repository.kln.ac.lk/handle/123456789/28540
Appears in Collections:JDRRA Volume 1 Issue 2

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