Predicting Future Risk of Liability in Police Officer Candidates Using M-PULSE Inventory(TM)

Description

<p> The Matrix Predictive Uniform Law Enforcement Inventory (M-PULSE &trade;) is a self-report, actuarial instrument used to predict job performance and liability risk, as well as assist law enforcement agencies in selecting qualified candidates. This study examined whether there is a statistically significant difference between two clusters of candidates' Empirical Scales scores as they relate to applicants' mean scale score differences on the M-Pulse&trade; liability scales. This study was conducted in an effort to confirm predictive and ecological validity and used archived data from a proprietary database retained by MHS, Inc. This data consisted of 1,000 randomly selected individuals from a normalized database of 5,000 individuals who had previously completed the M-PULSE &trade; and were subsequently hired by a law enforcement agency. A series of independent-samples t-tests were conducted to compare each of the M-Pulse &trade; liability scales scores of law enforcement applicants in each cluster. Post hoc Bonferroni correction resulted in &agr; &le; .003. Statistically significant differences were found in Potential for Resignation when comparing scores for Cluster 1 (<i>M</i> = 49.49, <i> SD</i> = 9.85) and Cluster 2 (<i>M</i> = 51.85, <i>SD </i> = 10.97); <i>t</i>(998) = -3.545, <i>p</i> &lt; .003; <i>d</i> = .226 and in Potential for Termination: Cluster 1 (<i>M</i> = 49.05, <i>SD</i> = 9.48) and Cluster 2 (<i> M</i> = 52.14, <i>SD</i> = 10.57); t(998) = -4.833, <i> p</i> &lt; .003; <i>d</i> = .308. This study suggests the M-PULSE &trade; can tease out candidates who show a propensity to prematurely resign or be terminated. Predicting foreseeable liability risks helps law enforcement agencies manage ecological issues that affect officers.</p>

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Identifer	oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3612238
Date	03 April 2014
Creators	Foreman, Mark E.
Publisher	Alliant International University
Source Sets	ProQuest.com
Language	English
Detected Language	English
Type	thesis