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- W4385808570 abstract "The Personality-Job Fit Theory suggests that the better an employee’s personality fits with an organization’s culture and demands of the job the more likely that employee will be successful at the job. Researchers have repeatedly shown how various personality traits correlate with and predict job performance ratings for police and correctional officers. Similar research, however, is sparse for probation and parole officers (PPO), despite PPOs being identified in many states as peace officers. Therefore, the purpose of this study was to explore the degree to which personality traits, as measured by the Critical Hire-Personality Assessment (CH-PA), a pre-employment integrity, honesty and personality assessment, correlated with and predicted supervisor ratings of PPO job performance. The methods used to study this relationship consisted of supervisors within three community-based corrections agencies rating the job performance of 53 PPOs for purposes of this study. Job performance ratings were then analyzed against the PPO’s scale and subscale scores on the CH-PA the PPO took as part of their application and hiring process. Results revealed that multiple CH-PA personality scales and subscales significantly correlated with top performer ratings. Calibration, discrimination, and accuracy metrics also revealed that, when using a cut score of one standard deviation from the mean, multiple CH-PA scales adequately predicted PPO job performance ratings. Results from this study can provide PPO hiring agencies with information on what personality traits are empirically associated with top performer ratings and provide practical utility for agencies using the CH-PA." @default.
- W4385808570 created "2023-08-15" @default.
- W4385808570 creator A5047587694 @default.
- W4385808570 date "2023-08-09" @default.
- W4385808570 modified "2023-10-16" @default.
- W4385808570 title "Identifying High-Performing Probation and Parole Officers with the Critical Hire-Personality Assessment" @default.
- W4385808570 doi "https://doi.org/10.11648/j.jhrm.20231103.13" @default.
- W4385808570 hasPublicationYear "2023" @default.
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