Recently, numerous high-profile instances of police misconduct and corruption have been thrust into the national spotlight. Hiring police officers who will act with integrity and not betray public trust remains essential. The present research experimentally examines this phenomenon by evaluating pre-employment assessment results against applicant performance on a simulated cheating task (i.e., The Dots Task) in order to derive information to improve contemporary pre-employment screening and selection models. Four case examples are presented which depict malicious actors who possessed privileged access, assumed no one would ever scrutinize their activities, and attempted to leverage a lack of oversight for their personal benefit. A literature review of previous research findings is presented, and results from the current study are discussed. Spearman correlation analyses consistently indicated that participants who cheated were predisposed to moral disengagement via advantageous comparison. Participants who left all or part of their monetary award were less prone to general moral disengagement, particularly displacement of responsibility, while the opposite effect was observed for participants who took more than their earned award. Impression management was positively associated with stealing extra money, and cheating was more common among participants with elevated distorted thought patterns, including obsessional thinking, paranoid ideation, and alienation/perceptual distortion. Stepwise linear multiple regression analyses further substantiated the relationship between cheating and both distorted thought patterns and impression management, as well as provided evidence that (1) internalizing morality as part of one's self-identity and (2) warmth act as protective factors against cheating behavior. Positive relationships between cheating and distortion of consequences were also present within multiple regression analyses. Behavioral models produced from stepwise linear multiple regression analyses offer the potential to predict the likelihood and severity of cheating behavior that an individual may be predisposed to commit based upon their pre-employment assessment data, thereby enhancing pre-employment screening and selection decisions.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-7256 |
| Date | 01 January 2018 |
| Creators | Montaquila, Julian |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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