Prediction of Police Officer Performance Among New Mexico State Police as Assessed by the Personality Assessment Inventory View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-11

AUTHORS

David W. Richardson, Susan B. Cave, Linda La Grange

ABSTRACT

Little research has been conducted regarding the use of the Personality Assessment Inventory (PAI) in law enforcement screening and selection. The limited body of research that does exist appears to support its utility in the selection process. The purpose of the present study was to investigate the validity and reliability of the Psychological Rating Risk Factor Statement (PRRFS) developed by Roberts, Thompson, and Johnson (2004) in predicting and discriminating problem from non-problem New Mexico State Police (NMSP) applicants. PAI profiles for each officer were obtained and transferred into the PAI Law Enforcement, Corrections, and Public Safety Selection software program, which generated probability estimates (PRRFS) to predict the likelihood that participants were not well-suited for a career in law enforcement. Subsequent logistic regression and receiver operating characteristic (ROC) statistical analyses revealed that the PRRFS was ineffective in predicting and discriminating between problem and non-problem officers. Potential explanations for this finding are discussed. More... »

PAGES

84-90

References to SciGraph publications

  • 1993-03. The MMPI goodCop/bad cop profile in identifying dysfunctional law enforcement personnel in JOURNAL OF POLICE AND CRIMINAL PSYCHOLOGY
  • 2004-06. The personality assessment inventory as a selection device for law enforcement personnel in JOURNAL OF POLICE AND CRIMINAL PSYCHOLOGY
  • 1999-06. Using the good cop/bad cop profile with the MMPI-2 in JOURNAL OF POLICE AND CRIMINAL PSYCHOLOGY
  • 2004-06. Law enforcement officer seniority and PAI variables in psychological fitness for duty examinations in JOURNAL OF POLICE AND CRIMINAL PSYCHOLOGY
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    http://scigraph.springernature.com/pub.10.1007/s11896-007-9010-7

    DOI

    http://dx.doi.org/10.1007/s11896-007-9010-7

    DIMENSIONS

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