Recently, PAR added several new features to the PAI Plus reports on PARiConnect. As a result, we have received a few questions about how to use the Negative Impression Management (NIM) and Positive Impression Management (PIM) predicted profile overlays as well as the NIM- and PIM-specific profiles. We went directly to author Leslie C. Morey, PhD, to get his answers on how you can use these features to enhance your understanding.
LM: NIM and PIM predicted profile overlays are regression-based predictions of the profile based on information from the validity scales. These profiles represent one strategy for understanding the influence of the response styles represented by the validity scales, NIM and PIM. In this approach, PAI scale scores are predicted solely by either NIM or PIM, using a regression model based on the correlations observed in the standardization samples. Thus, these profiles are not based on data from the profile of the individual being assessed, with the exception of their NIM or PIM scores. The resulting profile constitutes what would be expected given the observed score on NIM or PIM. The contrast between observed (i.e., the respondent’s actual PAI profile) and predicted profiles indicates the extent to which scale scores are expected to have been influenced by response set distortion. If the observed and expected scores are comparable (e.g., within one standard error of measurement), then the scores can be largely attributed to the effects of whatever led to the observed response set, such as potential exaggeration or cognitive distortions.
LM: The NIM- and PIM-specific profiles represent another strategy for understanding the influence of any observed response styles on the PAI profile. However, instead of predicting every score on the rest of the profiles, it compares the observed profile to a group of profiles from the standardization samples that displayed a similarly elevated score on PIM or NIM. This strategy then calculates standard scores for the individual’s observed scores based on the means and standard deviations of similarly distorted profiles. Thus, elevations indicate psychopathology above and beyond response sets. Unlike the predicted scores, which tend to yield greater variability in predictions for negative impression management than for positive impression management, the specific score strategy is equally useful in understanding the influences of both types of response sets.
Two groups are used for comparison purposes on the NIM- and PIM-specific scores, as defined by two ranges on these scales. The first group, the lower range, is based on cutoff scores determined to have maximal efficiency in distinguishing impression management from genuine groups. For NIM, this range is 84T to 91T; for PIM, it is 57T to 67T. The second group, the higher range, is equivalent to scores that equal or exceed two standard deviations above the mean in a clinical population: 92T for NIM and 68T for PIM. No specific scores are generated if NIM is less than 84T and PIM is less than 57T.
Read more about how the NIM scale can be used to assess malingering.
The PAI Plus takes the existing PAI items and gives users an updated way to interpret the data. Using the original PAI items, the new report offers:
DSM-5® update: Diagnostic possibilities align with the most up-to-date criteria.
Alternative Model for Personality Disorders Profile: An optional new profile scores the PAI in accordance with the model.
Additional supplemental indices: 15 new supplemental indices plus supplemental clinical indicators provide additional profile information.
Context-specific norm groups: Profile overlays for new normative groups can be compared to the examinee’s profile.
Related post: Now on the Training Portal: PAI Plus webinar!
The PAI-SP offers exclusive features
The PAI Plus Interpretive Explorer, only available on the PAI-SP, enables you to interact with PAI reports to access definitions, review supplemental indexes, and compare client data with normative and clinical samples to offer additional insights into your client.
Further additions allow users to compare client scores to context-specific norm groups via z scores.
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The Personality Assessment Inventory™ (PAI®) has earned its reputation as one of the most important innovations in personality assessment. Its 22 nonoverlapping scales cover the constructs most relevant to a broad-based assessment of mental disorders. Now with the introduction of the PAI Plus, there are even more ways to interpret PAI data.
A recorded webinar from presenters Kevin Lauer, PhD, and Sierra Iwanicki, PhD, is now available on the PAR Training Portal. It covers topics such as:
Visit partrainingportal.com to view it today!
We’ve heard the requests. And we listened! The PAI Plus is coming this fall!
The PAI Plus takes the existing PAI items and gives users an updated way to interpret the data. Using the PAI, an objective inventory of adult personality, the new PARiConnect report offers: • DSM-5® update: Updated diagnostic possibilities align with the DSM criteria. • Alternative Model Profile: An optional new profile scores in accordance with the Alternative Model for Personality Disorders. • Additional supplemental indices: Based on years of academic research, 15 new supplemental indices provide additional profile information related to negative and positive distortion and random responding. Supplemental clinical indicators provide profile information related to suicidality, aggression, level of care, presence of ADHD, and more. • Context-specific norm groups: Including profile overlays for bariatric surgery candidates, child custody evaluations, chronic pain patients, college students, deployed military, egg donors/gestational carriers, motor vehicle accident claimants, police applicants, and potential kidney donors. This profile is overlayed onto the examinee’s profile to allow for comparison. • Updated report: An updated look and feel create a streamlined and modern-looking report.
A manual supplement details the research, theory, and development behind this update.
To determine the right kit for your needs or to preorder, call Customer Support at 1.800.331.8378.