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Could Time Detect a Faking-Good Attitude? A Study With the MMPI-2-RF
Paolo Roma1, Maria C Verrocchio2, Cristina Mazza1
1Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy.
Abstract:
Background and Purpose: Research on the relationship between response latency (RL) and faking in self-administered testing scenarios have generated contradictory findings. We explored this relationship further, aiming to add further insight into the reliability of self-report measures. We compared RLs and T-scores on the MMPI-2-RF (validity and restructured clinical [RC] scales) in four experimental groups. Our hypotheses were that: the Fake-Good Speeded group would obtain a different completion time; show higher RLs than the Honesty Speeded Group in the validity scales; show higher T-Scores in the L-r and K-r scales and lower T-scores in the F-r and RC scales; and show higher levels of tension and fatigue. Finally, the impact of the speeded condition in malingering was assessed. Materials and Methods: The sample was comprised of 135 subjects (M = 26.64; SD = 1.88 years old), all of whom were graduates (having completed at least 17 years of instruction), male, and Caucasian. Subjects were randomly assigned to four groups: Honesty Speeded, Fake-Good Speeded, Honesty Un-Speeded, and Fake-Good Un-Speeded. A software version of the MMPI-2-RF and Visual Analog Scale (VAS) were administered. To test the hypotheses, MANOVAs and binomial logistic regressions were run. Results: Significant differences were found between the four groups, and particularly between the Honest and Fake-Good groups in terms of test completion time and the L-r and K-r scales. The speeded condition increased T-scores in the L-r and K-r scales but decreased T-scores in some of the RC scales. The Fake groups also scored higher on the VAS Tension subscale. Completion times for the first and second parts of the MMPI-2-RF and T-scores for the K-r scale seemed to predict malingering. Conclusion: The speeded condition seemed to bring out the malingerers. Limitations include the sample size and gender bias.
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