Abstract
Many construction accidents are caused by workers’ unsafe behavior, and evidence suggests that individuals who are not sensitive to risks are accident-prone. Therefore, identifying workers with certain personal characteristics related to habitual insensitive response to safety risks potentially can help construction managers develop individualized safety training and interventions. Although the methods by which construction managers could identify those workers with specific personal characteristics have been limited, wearable sensors provide an opportunity for construction managers to monitor individual workers’ behavior without any interruptions. This study investigated whether and how sensing data about workers’ behavior around hazards can reveal their personality traits related to risk-taking behavior. In particular, this research focused on a personality trait well known to be related to risk-taking behavior, locus of control (LOC). An experiment was designed to collect workers’ behavioral response to various hazards in terms of gait patterns; LOC was measured using standard instruments. The analysis showed that the degree of gait change around hazards is significantly correlated with LOC score. Additionally, those with internal LOC had more consistent gait patterns over a number of repetitive exposures to the same hazard (i.e., sustained sensitivity to safety risks) than those with an external LOC. These results demonstrate the potential of using wearable sensors to identify workers with personality traits associated with unsafe behavior.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
Acknowledgments
The authors acknowledge Dr. Terry Stentz, Associate Professor, Durham School of Architectural Engineering and Construction, University of Nebraska at Lincoln; Dr. Hyunsoo Kim, Assistant Professor, Department of Architectural Engineering at Gyeongnam National University of Science and Technology; and Dr. Kanghyeok Yang, postdoctoral researcher at the Texas A&M University for their contributions to experimental design and data collection. This study was financially supported by the National Science Foundation (CMMI #1538029). Any opinions, findings, conclusions, or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Journal of Construction Engineering and Management
Volume 146 • Issue 7 • July 2020
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©2020 American Society of Civil Engineers.
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Received: Jan 27, 2019
Accepted: Jan 16, 2020
Published online: May 7, 2020
Published in print: Jul 1, 2020
Discussion open until: Oct 7, 2020
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