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Abstract
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INTRODUCTION: A growing body of applied research has identified certain psychological traits that are predictive of worker safety. However, most of these studies suffer from an overreliance on common method bias caused by self-report measures of both: (a) personal factors such as personality traits; and (b) outcomes such as safety behaviors and injuries.
METHOD: This study utilized archival data from 796 employees at a large U.S. automobile manufacturer. Data were gathered on a pre-employment assessment, SecureFit®, that measured key personality characteristics such as conscientiousness, locus of control, and risk taking. In addition, objective measures of workers' compensation claims and disciplinary actions were also gathered.
RESULTS: The results indicated that disciplinary actions and workers' compensation claims were strongly correlated. It also demonstrated that the pre-employment assessment was able to predict both disciplinary actions and workers' compensation claims up to 12months in the future. Screening out just 8% of the applicant sample using the assessment would have resulted in a 35% reduction in disciplinary actions and 46% in workers' compensation claims, respectively.
CONCLUSIONS: The study found a very strong relationship between counterproductive work behaviors (CWBs), such as not following rules, and workers' compensation claims. It also found a strong relationship between a combination of personality traits that have been shown to be associated with both variables, although the current study was able to demonstrate that relationship with objective measure of both variables. PRACTICAL APPLICATIONS: Individuals who receive disciplinary actions for things such as not following rules, not coming to work on time, etc. are significantly more likely to also be involved in serious safety incidents, and vice versa. Identifying those individuals early on in the hiring process and screening them out can significantly reduce the number of CWBs as well as workers' compensation claims.
Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.
Language: en |