ArticleFrontiers in psychology2019
Principles, Approaches and Challenges of Applying Big Data in Safety Psychology Research.
Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Improving Likert scale big data analysis in psychometric health economics: reliability of the new compositional data approach.Brain informatics · 2024Article
- Evaluating the Impact of Information System Quality on Continuance Intention Toward Cloud Financial Information System.Frontiers in psychology · 2021Article
- Commentary: Principles, Approaches and Challenges of Applying Big Data in Safety Psychology Research.Frontiers in psychology · 2019Article
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3 authors.
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Abstract
Big data is now widely used in many fields and is also widely applied to the integration of disciplines. Traditional methods of safety psychology are not well suited for analyzing psychological states, especially in the management of human factors in industrial production. Also, big data now becomes a new way to excavate related insight by analyzing a large amount of psychological data. So, this paper is to propose the concept of big data of safety psychology (BDSP) and to illustrate the challenges of applying big data in safety psychology. First, this paper puts forward the concept of BDSP and analyzes the difference between BDSP and traditional sample data. Subsequently, this paper summarizes the classification standard and basic characteristic of BDSP, explores the framework of BDSP and then constructs a three-dimensional structure of BDSP. Lastly, this paper discusses the challenges of using BDSP. This study is of great help to safety practitioners to solve psychological issues in the safety domain, and points out one of the research trends of human factor in industrial safety.
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