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The detection of fake-bad and fake-good responding on the Millon Clinical Multiaxial Inventory III
1Department of Education and Human Services, Lehigh University, USA. sdaubert@wellspan.org
Abstract:
The purpose of this study was to examine the effectiveness of the 3 Modifying Indices of the Millon Clinical Multiaxial Inventory III (MCMI-III) in the detection of fake-bad and fake-good responding. The sample consisted of 160 psychiatric outpatients. Paired t tests were performed to examine the effects of instructional set (faking vs. standard instructions). As hypothesized, instructional set produced significant differences on Scale X, Scale Y, and Scale Z in both fake-bad and fake-good analyses. Single-scale cutoff scores were as effective as multiple-scale cutoffs. The overall rates of successful classification indicated moderate effectiveness and utility of the MCMI-III Modifying Indices in the detection of dissimulated responding. When base rates were varied to more closely approximate a general clinical population, overall classification accuracy increased, but identification of faking (positive predictive power) gradually eroded with declining base-rate estimates. At lower base rates of faking, MCMI-III standard cutoff points yielded a high number of false positives.
Insights
The Millon Clinical Multiaxial Inventory III (MCMI-III) modifying indices moderately detect fake-good and fake-bad responses. However, accuracy decreases with lower base rates of faking in clinical populations.
Area of Science:
- Psychological Assessment
- Clinical Psychology
- Psychometrics
Background:
- Accurate assessment of response bias is crucial in clinical psychology.
- The Millon Clinical Multiaxial Inventory III (MCMI-III) is a widely used personality assessment tool.
- Understanding the effectiveness of MCMI-III's modifying indices in detecting dissimulation is important for valid interpretations.
Purpose of the Study:
- To evaluate the efficacy of the three modifying indices of the MCMI-III.
- To determine the ability of these indices to detect fake-bad and fake-good response sets.
- To compare the effectiveness of single-scale versus multiple-scale cutoffs for detecting response bias.
Main Methods:
- A sample of 160 psychiatric outpatients participated in the study.
- Paired t-tests were used to analyze the impact of instructional sets (faking vs. standard).
- The study examined MCMI-III Scales X, Y, and Z under different response conditions.
Main Results:
- Instructional set significantly influenced scores on MCMI-III Scales X, Y, and Z for both fake-bad and fake-good conditions.
- Single-scale cutoff scores demonstrated comparable effectiveness to multiple-scale cutoffs in identifying dissimulated responding.
- Overall classification accuracy was moderate, indicating utility of the MCMI-III modifying indices.
Conclusions:
- The MCMI-III modifying indices offer moderate effectiveness in detecting fake-good and fake-bad responding.
- Classification accuracy increased with adjusted base rates but positive predictive power for faking decreased.
- Lower base rates of faking led to a higher rate of false positives with standard MCMI-III cutoff points.