Personality Assessment Inventory among patients with psychogenic seizures and those with epilepsy

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1 BRIEF COMMUNICATION Personality Assessment Inventory among patients with psychogenic seizures and those with epilepsy *ys. Marc Testa, zronald P. Lesser, zgregory L. Krauss, and yzjason Brandt *Baltimore VA Medical Center, Baltimore, Maryland, U.S.A.; ydepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, U.S.A.; and zdepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, U.S.A. SUMMARY The Personality Assessment Inventory (PAI) is a widely used self-report questionnaire designed to detect and quantify dimensions of adult psychopathology. Previous studies that examined the ability of the PAI to differentiate between patients with psychogenic nonepileptic seizures (PNES) and those with epilepsy (EPIL) have yielded inconsistent results. We compared the full PAI profiles of 62 patients with PNES, 55 with EPIL, and 45 normal control (NC) participants to determine the diagnostic accuracy of the PAI. We also sought to highlight psychopathologic symptoms that may inform psychological treatment of patients with PNES or epilepsy. PNES and EPIL patients reported more somatic concerns and symptoms of anxiety and depression than did NC persons. PNES patients reported more unusual somatic symptoms, as well as greater physical symptoms of anxiety and depression than did patients with EPIL. Classification accuracy of the NES Indicator was not much better than chance, whereas the Conversion subscale alone had reasonable sensitivity (74%) and specificity (67%). Overall, the PAI demonstrated only moderate classification accuracy in an epilepsy monitoring unit sample. However, the inventory appears to identify specific psychopathological symptoms that may be targets of psychological/psychiatric intervention. KEY WORDS: Psychogenic seizures, Diagnosis, Somatoform disorders, Personality Assessment Inventory, Psychological testing. The Personality Assessment Inventory (PAI) (Morey, 1991) is a popular instrument for the assessment of adult psychopathology and has several psychometric advantages (Rogers, 2003) over similar instruments [e.g., Minnesota Multiphasic Personality Inventory (MMPI/MMPI-2) (Hathaway & McKinley, 1951]. Only two studies have examined the diagnostic utility of the PAI in epilepsy (EPIL) and psychogenic nonepileptic seizures (PNES). Wagner et al. (2005) developed an NES [nonepileptic seizure] Indicator consisting of the difference between two Somatic Complaints subscales (Conversion minus Health Concerns). It classified correctly 84% of PNES (N = 26) and 73% of epilepsy (N = 15) patients. In an attempted replication with a much larger sample, Thompson et al. (2010) achieved high specificity (84%), but near-chance sensitivity for PNES (59%). Neither Thompson et al. (2010) nor Wagner et al. (2005) report data on all the PAI scales and subscales. Accepted May 4, 2011; Early View publication July 8, Address correspondence to S. Marc Testa, PhD, Baltimore VA Medical Center (BT/116/MH), 10 N. Greene Street, Baltimore, MD 21201, U.S.A. smtesta@gmail.com Wiley Periodicals, Inc. ª 2011 International League Against Epilepsy There is little overlap in the scales that they do report, and neither included a neurologically normal comparison sample. Therefore, the first objective of the current study is to describe the modal PAI profiles of PNES patients and EPIL patients. The second objective is to determine whether PAI scales can correctly discriminate patients with PNES, those with EPIL, and normal control (NC) participants. Methods Participants Fifty-five adults with EPIL and 62 with PNES evaluated at the Johns Hopkins Hospital (JHH) Epilepsy Monitoring Unit (EMU) were included in this study. All consecutive inpatients meeting criteria for the study were approached for participation. All patients were subsequently given definitive diagnoses by a faculty epileptologist based on video electroencephalography (VEEG) recording and other supporting evidence (e.g., neuroimaging). Only patients who had one or more seizure events recorded during their EMU hospitalization were included in the study. Forty-five adults who reported no history of neurologic or psychiatric disorder or chronic medical condition served as e84

2 e85 PAI Assessment and Seizure Disorders a normal control (NC) group (N = 45). They were recruited from the JHH community by advertisement. All participants were at least 18 years old and had IQ estimates of at least 70 based on the Wonderlic Personnel Test (Dodrill & Warner, 1988). Potential control participants were excluded if they had been diagnosed previously with a neurologic disease or a severe psychiatric illness or had current drug or alcohol abuse. Demographic information and medical history were collected through review of the medical chart and interview with the participant. The research protocol was reviewed and approved by the Johns Hopkins Medicine Institutional Review Board. All participants gave informed consent after the goals and methods of the study, and the risks and benefits of participating, were explained fully. Procedure Participants completed the PAI (Morey, 1991) early on in their EMU hospitalization, prior to their first seizure or typical event (or, for control participants, during an office visit). The PAI consists of 344 items to which participants respond on a 4-point scale (False, Slightly True, Mainly True, and Very True). The PAI yields validity scales to assess the consistency of item responses, overendorsement of unusual items, and the tendency to present oneself in an overly positive or negative manner. There are 11 clinical scales, 9 of which contain subscales derived from factor analysis and 2 that assess alcohol and drug use. In addition, there are five treatment implication scales (Aggression, Suicidality, Stress, Nonsupport, and Treatment Rejection), and two interpersonal scales (Dominance and Warmth). The PAI has excellent psychometric properties (Morey, 1991; Rogers et al., 1998; Siefert et al., 2009). Data analyses Group comparisons Two three-group multivariate analyses of variance (MANOVAs) were performed to determine whether there are reliable between-group differences in PAI profiles for the major scales and separately, for the subscales. Separate three-group analyses of variance (ANOVAs) were then conducted on all the main scales of the PAI. Post hoc comparisons were performed only for variables that were significant at p < Separate ANOVAs and post hoc comparisons were carried out for the subscales of the clinical scales that had effect size values (g 2 p ) >0.10. An a level at 0.01 was used for the post hoc analyses to offset the increased type 1 error rate due to multiple comparisons. Group classification Univariate logistic regressions were modeled to assess the ability of the ``NES Indicator to predict group membership. The ``NES Indicator is derived from subtracting the T-scores of the Health Concerns (SOM-H) subscale of the Somatic Complaints scales from the Conversion subscale (SOM-C). Therefore, positive scores reflect diminished health concerns relative to the number of reported symptoms. Finally, using stepwise multivariate logistic regression, the PAI scales and subscales with the largest between-group differences (i.e., Cohen s d 0.40) were used to predict group membership among PNES and EPIL patients. Results The groups differed on several demographic characteristics (see Table 1). When the variables that differ between groups were included as covariates the magnitude or Table 1. Characteristics of three groups of participants NC (N = 45) EPIL (N = 55) PNES (N = 62) Variable M SD M SD M SD p-value Age a Education a,b <0.01 Estimated IQ a <0.001 % Male c <0.01 % Caucasian c <0.05 Age at onset a <0.001 Duration of illness a <0.001 AEDs a,b <0.001 Frequency of seizures c % Daily <0.01 % Weekly % Monthly % Yearly NC, normal control; EPIL, epilepsy; PNES, psychogenic nonepileptic seizures; AED, antiepileptic drug; SD, standard deviation. a One-way ANOVAs. b Highest grade completed. c Chi-square.

3 e86 S.M. Testa et al. significance of group differences in PAI scales or subscales were not altered. Therefore, for the sake of simplicity and clarity, the unadjusted results are presented. PAI Scale group comparisons The mean PAI profiles of the three groups are shown in Fig. 1 (Top). The overall difference between groups was significant (Hotelling s T 44, 274 = 5.03, g 2 p = 0.45, p < 0.001). Univariate ANOVAs revealed group differences on several PAI scales (see supporting Tables S1 and S2 for F-tests and post hoc statistics). Patients with PNES scored higher than EPIL on Somatic Complaints and Stress. Patients with PNES scored higher than NC on Negative Impression Figure 1. Mean PAI scale (Top) and subscale (Bottom) profiles of PNES patients, EPIL patients, and NC participants. Note: Error bars represent standard error of the mean (SEM). Only some PAI scales have subscales. INC, Inconsistency; INF, Infrequency; NIM, Negative Impression; PIM, Positive Impression; SOM, Somatic Complaints; ANX, Anxiety; ARD, Anxiety-Related Disorders; DEP, Depression; MAN, Mania; PAR, Paranoia; SCZ, Schizophrenia; BOR, Borderline Features; ANT, Antisocial Features; ALC, Alcohol Problems; DRG, Drug Problems; SUI, Suicidal Ideation; STR, Stress; NON, Nonsupport; RXR, Treatment Rejection; AGG, Aggression; DOM, Dominance; SOM-C, Conversion; SOM-S, Somatization; SOM-H, Health Concerns; ANX-C, Cognitive; ANX-A, Affective; ANX-P, Physiological; ARD-O, Obsessive-Compulsive; ARD-P, Phobias; ARD-T, Traumatic Stress; DEP-C, Cognitive; DEP-A, Affective; DEP-P, Physiological; MAN-A, Activity Level; MAN-G, Grandiosity; MAN-I, Irritability; PAR-H, Hypervigilance; PAR-P, Persecution; PAR-R, Resentment; SCZ-P, Psychotic Experiences; SCZ-S, Social Detachment; SCZ-T, Thought Disorder; BOR-I, Identity Problems; BOR-N, Negative Relationships; BOR-S, Self-Harm; ANT-A, Antisocial Behaviors; ANT-E, Egocentricity; ANT-S, Stimulus-Seeking; AGG-A, Aggressive Attitude; AGG-V, Verbal Aggression; AGG-P, Physical Aggression. Epilepsia ILAE

4 e87 PAI Assessment and Seizure Disorders Management, Somatic Complaints, Anxiety, Anxiety Related Disorders, Depression, Schizophrenia, Borderline Features, and Suicidal Ideation. The EPIL participants scored higher than NC participants on Negative Impression Management, Somatic Complaints, Anxiety, Depression, and Schizophrenia. PAI subscale group comparisons The mean PAI subscale profiles of the three groups are shown in Fig. 1 (Bottom). The multivariate effect of group was significant (Hotelling s T 62, 256 = 4.22, g 2 p = 0.51, p < 0.001). Subscale level comparisons were made for the three scales (Somatic Complaints, Anxiety, and Depression) with effect sizes (g 2 p ) >0.10. Patients with PNES scored higher than EPIL, and patients with EPIL scored higher than NC (p < 0.001) on the Somatic Complaints subscales of Conversion (SOM-C) and Somatization (SOM-S). The Health Concerns scale did not differ between PNES and EPIL; but both groups scored higher than NC. The Physiological Anxiety subscale was higher in PNES than in EPIL and NC, and higher in EPIL than NC. PNES and EPIL were equivalent on the Cognitive and Affective subscales of Anxiety. Both PNES and EPIL were higher than NC for the Cognitive and Affective Anxiety subscales. A very similar pattern emerged on the Depression scales (see supporting Tables S3 and S4 for F-tests and post hoc statistics). Group classification The mean nonepileptic seizure (NES) Indicator score is significantly different among the three groups (F 2, 162 = 11.22, g 2 p = 0.12, p < 0.001). The NES Indicator scores for NC (M = )1.31, SD = 9.15) and EPIL (M = )4.34, SD = 11.24) are equivalent, and lower than for PNES (M = 5.74, SD = 13.87). Despite these differences, applying the NES Indicator resulted in limited classification accuracy. A univariate logistic regression using the NES Indicator to differentiate PNES from EPIL (with an optimal cutting score of 1.5) yielded poor overall classification (61.5%), with low sensitivity to detect PNES (66.1%) and at-chance specificity (56.4%). Although the NES Indicator had high sensitivity for distinguishing patients with EPIL or PNES from normal controls (80.0% and 77.4%, respectively), specificity was low (15.6% and 28.9%, respectively). In contrast, classification rates in differentiating PNES from a combined NC and EPIL group revealed low sensitivity (40.3%), high specificity (90.0%), and reasonable positive (71.4%) and negative (70.9%) predictive values. To develop our own discriminative algorithm, the PAI subscales with the largest between-group differences (i.e., Cohen s d 0.40) were used as independent variables in a multivariate logistic regression to predict group membership among PNES and EPIL patients. The subscales included were Conversion, Somatization, Physiological Anxiety, and Physiological Depression. Only the Conversion subscale was retained in the final model, which classified correctly 67% of EPIL and 74% of PNES patients. These classification rates were at a cutting T-score of 67, and yielded a 71.9% positive and a 69.8% negative predictive value. Discussion Psychological tests can help identify and characterize psychopathology in patients with PNES. This can help guide therapy and potentially be combined with VEEG to distinguish patients with PNES from patients with epilepsy. Our study showed that the PAI profiles of the PNES and EPIL groups were clinically elevated on Somatic Complaints, Anxiety, Depression, Schizophrenia, and Borderline Features scales. Therefore, the profiles of both groups reflect significant mood dysregulation, affective instability and uncertainty about major life issues, disorganized thought processes, as well as excessive concerns about health status and physical functioning. However, the patient groups differed on several subscales, suggesting that such symptoms may be experienced differently. For instance, in addition to higher scores on the Stress and Suicidal Ideation scales, the PNES group endorsed more physical complaints of anxiety (e.g., shakiness and heart racing) and depression (e.g., poor sleep, diminished appetite) than the EPIL group, despite endorsing an equal number of affective and cognitive symptoms of depression and anxiety. Although both the PNES and EPIL patients report substantial concern about their health status and physical functioning, the PNES group endorsed more Conversion and Somatization subscale items than EPIL. This could indicate that PNES patients experience more frequent and peculiar somatic symptoms (i.e., higher Conversion scores) that they perceive as disabling. In reality, such symptoms may be manifestations of a mood disorder. Overall, the PAI appears to have some utility in describing the psychopathological symptoms and potential treatment targets of individual patients seen at epilepsy treatment centers. The PAI profiles of the EPIL group are generally consistent with those reported previously (Wagner et al., 2005; Pizzi et al., 2009; Thompson et al., 2010). Pizzi et al. (2009) compared the PAI profiles of epilepsy patients to the PAI normative sample and found clinically meaningful elevations on the Depression and Somatic Complaints scales. Neither Wagner et al. (2005) nor Thompson et al. (2010) performed normative statistical comparisons, but both also reported elevated Somatic Complaints and Depression for their epilepsy groups. Our EPIL group had slightly higher (though within normal range) elevations than the NC group on the Anxiety and Schizophrenia scales. One clinical interpretation of these elevations is that patients with epilepsy

5 e88 S.M. Testa et al. may experience slightly greater worry and difficulties concentrating and controlling their thoughts than neurologically healthy individuals. PAI scores demonstrated variable accuracy in the differential diagnosis of PNES and EPIL. The NES Indicator (Wagner et al., 2005) was not much better than chance in distinguishing between patient groups. Our findings are consistent with those of Thompson et al. (2010). However, we found that the Conversion subscale alone could correctly classify 7 of 10 patients. Our classification rates and those of Thompson et al. (2010) are fairly consistent with the overall classification accuracy of the MMPI in differentiating between PNES and EPIL (Cragar et al., 2002). The PNES population is heterogeneous and differences across studies may reflect this heterogeneity. Higher classification rates might be attained if symptom groupings or PNES subtypes (Gumnit & Gates, 1986) are considered. Substantially larger samples would be needed for such analyses. The results reported here should be interpreted in the context of several limitations. First, the groups differed on several demographic variables. However, the PAI scales are not meaningfully associated with demographic variables (Morey, 1991). Moreover, the results of our analyses did not change when these variables were included as covariates. Results were also not impacted by seizure frequency or number of antiepileptic medications prescribed. However, we did not investigate whether specific antiepileptic agents influenced PAI elevations. This may be important to consider in future studies as certain agents might increase suicidal thinking and depressive symptoms (Hesdorffer & Kanner, 2009). We did not record seizure type systematically, so we could not examine any potential relationships between seizure or event semiology (convulsive vs. nonconvulsive) and psychopathology. Although we made multiple statistical comparisons, we were conservative in our analytic approach, and many of the effect sizes we report are moderately large. As in most studies of PNES, our sample was not necessarily representative of the epilepsy monitoring unit population (due to our exclusion factors). Acknowledgments This study was made possible by the Gertrude A. Sergievsky Research Endowment supported by the Epilepsy Foundation Behavioral Sciences Postdoctoral Fellowship (S.M.T.). The authors would also like to thank the faculty and staff of the Johns Hopkins University Epilepsy Center for their support, and research assistants Jung Geum Im, Sarini Ettigi, Shaina Fieldstone, and Molly Sprung. References Cragar DE, Berry DTR, Fakhoury TA, Cibula JE, Schmitt FA. (2002) A review of diagnostic techniques in the differential diagnosis of epileptic and nonepileptic seizures. Neuropsychol Rev 12: Dodrill CB, Warner MH. (1988) Further studies of the Wonderlic Personnel Test as a brief measure of intelligence. J Consult Clin Psychol 56: Gumnit RJ, Gates JR. (1986) Psychogenic seizures. Epilepsia 27(Suppl. 2): Hathaway SR, McKinley JC. (1951) The minnesota multiphasic personality inventory manual, Revised edition. Psychological Corporation, New York. Hesdorffer DC, Kanner AM. (2009) The FDA alert on suicidality and antiepileptic drugs: fire or false alarm? Epilepsia 50: Morey LC. (1991) The Personality Assessment Inventory professional manual. Psychological Assessment Resources, Odessa, FL. Pizzi AM, Chapin JS, Tesar GE, Busch RM. (2009) Comparison of personality traits in patients with frontal and temporal lobe epilepsies. Epilepsy Behav 15: Rogers R, Ustad KL, Salekin RT. (1998) Convergent validity of the personality assessment inventory: A study of emergency referrals in a correctional setting. Assessment 5:3 12. Rogers R. (2003) Forensic use and abuse of psychological tests: multiscale inventories. J Psychiatr Pract 9: Siefert CJ, Sinclair SJ, Kehl-fie KA, Blais MA. (2009) An item-level psychometric analysis of the personality assessment inventory: clinical scales in a psychiatric inpatient unit. Assessment 16: Thompson AW, Hantke N, Phatak V, Chaytor N. (2010) The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures. Epilepsia 51: Wagner MT, Wymer JH, Topping KB, Pritchard PB. (2005) Use of the Personality Assessment Inventory as an efficacious and cost-effective diagnostic tool for nonepileptic seizures. Epilepsy Behav 7: Supporting Information Additional supporting information may be found in the online version of this article: Data S1. Brief Summary. Table S1. Personality Assessment Inventory univariate and post hoc comparisons and effect sizes. Table S2. Post hoc t statistics for Personality Assessment Inventory scales. Table S3. Group comparisons of select Personality Assessment Inventory subscales. Table S4. Select Personality Assessment Inventory subscale t statistics. Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article. Disclosures None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.