Use of the Personality Assessment Inventory as an efficacious and cost-effective diagnostic tool for nonepileptic seizures

Functional seizures are not less important than epilepsy

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People with functional seizures often suffer from psychiatric comorbidities.

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People with FS report detrimental effects on social aspects of their lives.

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FS are associated with a considerable direct and indirect economic burden.

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FS have increased rates of mortality compared to healthy controls.

Functional seizures (FS) are frequently encountered in neurology clinics, often affect young adults, and have significant negative impacts on many aspects of a person’s life. In the current narrative review, we searched the literature regarding some of the consequences of FS (i.e., psychiatric comorbidities, social consequences, costs that are associated with the condition, cognitive impairment in patients with FS, the quality of life of the people with FS, and the increased risk of mortality that is associated with FS). Evidence shows that FS have significant negative consequences, comparable in their magnitude to those affecting patients with epilepsy. The clinical and scientific communities should take steps to address these consequences through clinical care and research that prioritizes, facilitates, and expedites evidence-based diagnosis and treatment for FS.

Differentiating epilepsy from psychogenic nonepileptic seizures using neuropsychological test data

OBJECTIVE

Differentiating epileptic seizures (ES) from psychogenic nonepileptic seizures (PNES) represents a challenging differential diagnosis with important treatment implications. This study was designed to explore the utility of neuropsychological test scores in differentiating ES from PNES.

METHOD

Psychometric data from 72 patients with ES and 33 patients with PNES were compared on various tests of cognitive ability and performance validity. Individual measures that best discriminated the diagnoses were then entered as predictors in a logistic regression equation with group membership (ES vs. PNES) as the criterion.

RESULTS

On most tests of cognitive ability, the PNES sample outperformed the ES sample (medium-large effect) and was less likely to fail the Reliable Digit Span. However, patients with PNES failed two embedded validity indicators at significantly higher rates (risk ratios (RR): 2.45-4.16). There were no group differences on the Test of Memory Malingering (TOMM). A logistic regression equation based on seven neuropsychological tests correctly classified 85.1% of patients. The cutoff with perfect specificity was associated with 0.47 sensitivity.

CONCLUSIONS

Consistent with previous research, the utility of psychometric methods of differential diagnosis is limited by the complex neurocognitive profiles associated with ES and PNES. Although individual measures might help differentiate ES from PNES, multivariate assessment models have superior discriminant power. The strongest psychometric evidence for PNES appears to be a consistent lack of impairment on tests sensitive to diffuse neurocognitive deficits such as processing speed, working memory, and verbal fluency. While video-electroencephalogram (EEG) monitoring is the gold standard of differential diagnosis, psychometric testing has the potential to enhance clinical decision-making, particularly in complex or unclear cases such as patients with nondiagnostic video-EEGs. Adopting a standardized, fixed neuropsychological battery at epilepsy centers would advance research on the differential diagnostic power of psychometric testing.

A simple clinical score for prediction of nonepileptic seizures

Psychogenic nonepileptic seizures (PNES), often mistaken for epilepsy in community practice, require inpatient video-EEG (VEEG) monitoring for diagnostic confirmation. We developed a simple score designed for use in an outpatient setting to predict the subsequent VEEG diagnosis of PNES. We retrospectively compared fifty-five consecutive patients with VEEG-proven PNES (N₁=55) with a group of randomly selected patients with VEEG-proven epilepsy (N₂=55). Patients were divided into two groups: I) a 'truly retrospective' group of 27 patients with PNES and 27 patients with epilepsy whose data served to develop the score, and II) a 'pseudoprospective' group of 28 patients each with PNES and epilepsy to whom the score was applied. Six features in the history of the Group I cohort appeared more prominent in patients with PNES than patients with epilepsy and were assigned escalating numerical values as follows: number of declared drug allergies (0, 0.5, 1), number of declared comorbidities (0, 0.5, 1), number of previous invasive medical interventions of any type (0, 0.5, 1), and a history of significant psychological or physical trauma (0 or 1). In addition, a score was assigned to verbal description of the seizures themselves as being consistent (=0), atypical (=1), or indeterminate (=0.5) for epilepsy. The values were added to yield an omnibus score ranging from 0 to 6. Scoring of Group II subjects in a blinded fashion revealed that in general patients with PNES had higher scores, and the majority obtained a score >2; most patients with epilepsy scored <1.5. Group difference in the mean between the PNES and epilepsy cohort was highly significant (p<0.0001, Wilcoxon rank-sum test). Our score is a simple clinical instrument based on the patient history that may find use in the triage of patients awaiting hospitalization for VEEG and in pre-VEEG counseling.

The relationship between the Neuro-Quality of Life Depression and Anxiety Measures and the Personality Assessment Inventory in persons with epilepsy

BACKGROUND

To investigate the associations between the Neuro-Quality of Life (NQOL) Depression and Anxiety measures with an objective emotional inventory (Personality Assessment Inventory; PAI), and demonstrate the clinical utility of the NQOL as screening measures for depression and anxiety in persons with epilepsy (PWE).

METHODS

PWE (N=72) were concurrently administered the NQOL Depression and Anxiety measures and the PAI. Pearson product moment correlations were used to determine the relationships between the NQOL measures and the respective PAI scales (i.e., depression, anxiety). One-way ANOVAs were conducted comparing NQOL scores between patients with elevated levels of depression and anxiety (T-score≥65 on the PAI) to profiles that were within normal limits. Using sensitivity and specificity analyses, optimal cut-scores on the NQOL measures were determined.

RESULTS

Participants were primarily Caucasian (89%), female (60%), and ~35 years old. The NQOL Depression measure was significantly correlated with the PAI Depression total score (r=.747; p<0.001) and its subscales (p's<0.001). Similarly, the NQOL Anxiety measure was significantly correlated with the PAI Anxiety total score (r=.750; p<0.001) and its subscales (p's<0.001). Compared to profiles that were within normal limits, individuals with elevated depressive symptoms on the PAI had significantly higher NQOL Depression scores (F(1,71)=48.2, p<0.001, d=1.6). Similarly, those who endorsed elevated anxiety on the PAI had significantly higher NQOL Anxiety scores (F(1,71)=32.2, p<0.001, d=1.5). Cut-off scores of 19 on the NQOL Depression and 24 on the NQOL Anxiety measures adequately detected depression (sensitivity=0.67; specificity=0.93; PPV=0.91; NPV=0.74) and anxiety symptoms (sensitivity=0.77; specificity=0.82; PPV=0.81; NPV=0.78) in PWE.

CONCLUSIONS

The NQOL Depression and Anxiety measures evidenced strong associations with the PAI Depression and Anxiety scales and may be effective in detecting depressive and anxiety symptoms in PWE using the provided cut-scores.

Psychological and psychiatric aspects of psychogenic non-epileptic seizures (PNES): A systematic review

Psychogenic non-epileptic seizures (PNES) are common in neurological settings and often associated with considerable distress and disability. The psychological mechanisms underlying PNES are poorly understood and there is a lack of well-established, evidence-based treatments. This paper advances our understanding of PNES by providing a comprehensive systematic review of the evidence pertaining to the main theoretical models of this phenomenon. Methodological quality appraisal and effect size calculation were conducted on one hundred forty empirical studies on the following aspects of PNES: life adversity, dissociation, anxiety, suggestibility, attentional dysfunction, family/relationship problems, insecure attachment, defence mechanisms, somatization/conversion, coping, emotion regulation, alexithymia, emotional processing, symptom modelling, learning and expectancy. Although most of the studies were only of low to moderate quality, some findings are sufficiently consistent to warrant tentative conclusions: (i) physical symptom reporting is elevated in patients with PNES; (ii) trait dissociation and exposure to traumatic events are common but not inevitable correlates of PNES; (iii) there is a mismatch between subjective reports of anxiety and physical arousal during PNES; and (iv) inconsistent findings in this area are likely to be attributable to the heterogeneity of patients with PNES. Empirical, theoretical and clinical implications are discussed.

Psychogenic nonepileptic seizures in children - Psychological presentation, treatment, and short-term outcomes

PURPOSE

The purpose of this study was to better understand the etiologies, features, and care outcomes of psychogenic nonepileptic seizures (PNESs) in a pediatric setting.

METHOD

We performed a retrospective analysis of 32 sequentially referred children for suspected PNESs to a neurology psychology service over a 6-year period. After excluding non-PNES paroxysmal events (related to anxiety or migraine), 29 patients were identified with final diagnosis of PNESs. Charts were examined for presenting symptom data, demographics, comorbidities, neurological diagnoses and investigations, as well as psychological assessment, management, and outcome. Treatment consisted of education around diagnosis and of individual psychological treatment, which, in most cases, was cognitive behavioral therapy up to 14 sessions. Additional mental health services including psychiatric medication, family therapy, and admission to day or inpatient treatment were also utilized in a smaller number of cases. Total treatment periods ranged from 4 weeks to 12 months.

RESULTS

The majority of patients identified were adolescent (90%), Caucasian (72%), and female (76%). Preceding psychology referral, point of entry into medical care for PNESs was primarily through the emergency department (66%) or outpatient neurology clinic referral (31%). Whereas 39% of parents described significant internalizing symptoms in their child (BASC-2), patients themselves tended to underreport anxiety or depression as demonstrated by only 16% endorsement on the BYI-II. By contrast, MACI personality assessment response patterns for adolescents demonstrated high levels of psychic tension/anxiety (65%), depressive affect (55%), and maladaptive personality traits including inhibition (45%), submissiveness (35%), and introversion (30%). Appropriate psychological treatment was associated with high rates of full remission (no new events, n=17, 59%) and partial remission (50% or greater reduction in events, n=6, 21%) as self-reported at discharge. Accurate diagnosis and referral to psychology also led to a sevenfold reduction in PNES-related emergency department visits one year after initial psychology visit compared with the preceding year.

CONCLUSIONS

This study suggests that appropriate care for PNESs reduces inappropriate medical investigation and therapy, expedites rates of remission, and decreases health-care utilization in a pediatric setting.

Personalities of patients with nonepileptic psychogenic status

The purposes of this study were to determine whether personalities of patients with nonepileptic psychogenic status (NEPS) are different from those of patients with typical intermittent psychogenic nonepileptic seizures (iPNES) using the Personality Assessment Inventory (PAI) and to compare their PAI profiles with the population norms. We hypothesized that patients with NEPS have more psychopathology compared with patients with iPNES and that, as a group, patients with PNES (iPNES+NEPS) would have more psychopathology compared with healthy individuals. We first compared the PAI profiles of patients with iPNES and NEPS and then the profiles of patients with NEPS, iPNES, and PNES with population norms in order to assess which PAI specific scales differed between groups in order to better characterize the psychopathology of PNES. All patients admitted for diagnostic evaluation to the epilepsy monitoring unit (EMU) were prospectively approached for participation. All patient/family interviews were conducted by an epileptologist, and the diagnosis of iPNES or NEPS was confirmed in all cases through video/EEG and/or family interview. The population norms for PAI were obtained from the manual. Of the 224 approached patients, 130 completed the PAI, and included 43 iPNES and 11 with NEPS. There were no significant differences between the two groups in regard to demographic or PAI profiles. Comparison with population norms revealed the presence of abnormal personality profiles on all scales in patients with iPNES, NEPS, or PNES. We conclude that while the occurrence of NEPS is relatively common in patients with PNES, the demographic characteristics and personality profiles of patients with NEPS are not different from those of patients with iPNES. We also confirmed the presence of significant psychopathology in the group with PNES when compared with population norms.

Quality of life in psychogenic nonepileptic seizures and epilepsy: the role of somatization and alexithymia

It is clear that many individuals with psychogenic nonepileptic seizures (PNESs) often present with poorer quality of life compared with those with epileptic seizures (ESs). However, the mechanisms linking seizure diagnosis to quality-of-life outcomes are much less clear. Alexithymia and somatization are emotional markers of psychological functioning that may explain these differences in quality of life. In the current study, patients from an epilepsy monitoring unit with vEEG-confirmed diagnosis of PNESs or ESs were compared on measures of alexithymia, somatization, quality of life, and a variety of demographic and medical variables. Two models using alexithymia and somatization individually as mediators of the relations between diagnosis and quality of life were tested. Results indicated that patients with PNESs had significantly poorer quality of life compared with those with ESs. Alexithymia was associated with poor quality of life in both groups but did not differentiate between diagnostic groups. Further, alexithymia did not mediate the relationship between diagnosis and quality of life. Somatization was associated with poor quality of life, and patients with PNESs reported greater somatization compared with patients with ESs. Somatization also significantly mediated the relationship between diagnosis and quality of life. In conclusion, somatization may be one mechanism affecting poor quality of life among patients with PNESs compared with ESs and should be a target of comprehensive treatments for PNESs. Alexithymia proved to be an important factor impacting quality of life in both groups and should also be targeted in treatment for patients with PNESs and patients with ESs.

Cognitive impairment and evaluation in psychogenic nonepileptic seizures: an integrated cognitive-emotional approach

Neuropsychological studies comparing patients with psychogenic nonepileptic seizures (PNES) to those with epilepsy have been largely equivocal. The variability in the neuropsychological literature highlights the heterogeneity of the PNES population across a number of psychiatric and neurologic factors. Phenotypic presentations in PNES arise from complex interactions between vulnerable cognitive and emotional systems. We propose that variability in neuropsychological findings in PNES emerge in the context of diverse psychiatric, neurologic, and clinical factors. Traditional assessments that fail to integrate cognitive and emotional/behavioral profiles sufficiently would fall short in characterizing the complexity of brain-behavior relationships in this population. To advance the neuropsychology of PNES, we propose a systematic approach to measure a number of factors that influence cognitive impairment in this population. We begin by reviewing the current neuropsychological literature in PNES and discussing a number of factors that influence cognitive deficits. We then present a comprehensive neuropsychological battery designed to capture elements (cognitive dysfunction, psychopathology, emotion processing deficits) underlying the proposed vulnerable cognitive-emotional system in PNES. It is our hope that the proposed battery will facilitate the aggregation of data across neuropsychological investigations, to allow more advanced statistical analyses, and ultimately enhance our understanding of PNES and the development of effective management and treatment options.

The diagnostic and therapeutic challenge of nonepileptic seizures: An interdisciplinary approach

Nonepileptic seizures were recognized in antiquity, but their diagnosis continues to be challenging in the present day. The diagnosis of seizures as nonepileptic has been based on associated physical conditions, social factors, laboratory findings, or psychological test findings. Pitfalls remain in the use of electroencephalography. We present several case studies of representative etiologies that demonstrate the value and the need for an interdisciplinary approach focusing on the individual, in the present, in all current dimensions, with careful consideration of seizure phenomena, physical explanations for symptoms, and psychodynamic profile in order to make the diagnosis and formulate successful treatment. This interdisciplinary approach provides a more comprehensive understanding of nonepileptic seizures and, more often, leads to successful outcome.

The influence of impression management scales on the Personality Assessment Inventory in the epilepsy monitoring unit

The Somatic Complaints scale (SOM) and Conversion subscale (SOM-C) of the Personality Assessment Inventory perform best in classifying psychogenic non-epileptic seizures (PNES) from epileptic seizures (ES); however, the impact of positive impression management (PIM) and negative impression management (NIM) scales on SOM and SOM-C classification has not been examined. We studied 187 patients from an epilepsy monitoring unit with confirmed PNES or ES. On SOM, the best cut score was 72.5 T when PIM was elevated and 69.5 T when there was no bias. On SOM-C, when PIM was elevated, the best cut score was 67.5 T and 76.5 T when there was no bias. Negative impression management elevations (n=9) were too infrequent to analyze separately. Despite similarities in classification accuracy, there were differences in sensitivity and specificity with and without PIM, impacting positive and negative predictive values. The presence of PIM bias generally increases positive predictive power of SOM and SOM-C but decreases negative predictive power.

Concurrent administration of the MMPI-2 and PAI in a sample of patients with epileptic or non-epileptic seizures: implications for an inpatient epilepsy monitoring unit

The Minnesota Multiphasic Personality Inventory-second edition (MMPI-2) and the Personality Assessment Inventory (PAI) are commonly used in the epilepsy monitoring unit (EMU) to evaluate personality characteristics and mood-related symptoms in those individuals being evaluated for epileptic seizures (ES) or psychogenic non-epileptic seizures (PNES). A direct comparison of these measures through concurrent administration to the same group has not been carried out. Both measures were administered to 40 patients (17 ES and 23 PNES). Logistic regression suggested the optimal predictive model for EMU discharge diagnosis included subscales from each measure, which outperformed either measure separately. Combining the conversion (SOM-C) and health concerns (SOM-H) subscales from the PAI and the hysteria subscale (Hy) from the MMPI-2 resulted in 85% overall classification accuracy, 86.7% sensitivity, and 82.4% specificity. Variability in the literature regarding the predictive utility of these measures may stem from the possibility that they measure different aspects of PNES.

Confirming psychogenic nonepileptic seizures with video-EEG: sex matters

The influence of gender on psychogenic nonepileptic seizures (PNES) diagnosis was examined retrospectively in 439 subjects undergoing video-EEG (vEEG) for spell classification, of whom 142 women and 42 men had confirmed PNES. The epileptologist's predicted diagnosis was correct in 72% overall. Confirmed epilepsy was correctly predicted in 94% men and 88% women. In contrast, confirmed PNES was accurately predicted in 86% women versus 61% men (p=0.003). Sex-based differences in likelihood of an indeterminate admission were not observed for predicted epilepsy or physiologic events, but were for predicted PNES (39% men, 12% women, p=0.0002). More frequent failure to record spells in men than women with predicted PNES was not explained by spell frequency, duration of monitoring, age, medication use, or personality profile. PNES are not only less common in men, but also more challenging to recognize in the clinic, and even when suspected more difficult to confirm with vEEG.

Predicting psychogenic nonepileptic seizures with the Personality Assessment Inventory and seizure variables

Early identification of likely cases of psychogenic nonepileptic seizures may prompt earlier and more appropriate diagnosis and treatment. This study investigated the validity of multiple independent self-report variables in predicting psychogenic nonepileptic versus epileptic seizures. One hundred forty-three patients with psychogenic nonepileptic seizures and 129 patients with epileptic seizures were compared with the Personality Assessment Inventory, age at seizure onset, years since first seizure, and length of seizures. Diagnostic prediction was made by analyses of variance and logistic regressions. Cut scores were developed for the multivariate predictors with maximal sensitivity and specificity. The Personality Assessment Inventory conversion subscale (SOM-C), years since first seizure, and length of seizures provided 84% correct classification. Ninety-six percent of patients meeting cut scores of SOM-C ≥70, years since first seizure ≤8, and length of seizures ≥3 minutes were diagnosed with psychogenic nonepileptic seizures. Results demonstrated good ability to identify likely cases of psychogenic nonepileptic seizurs by multiple predictors that are easily and cost-effectively obtainable.

Randomized comparison of the Personality Assessment Inventory and the Minnesota Multiphasic Personality Inventory-2 in the epilepsy monitoring unit

The two most common personality measures used in evaluation of patients on epilepsy monitoring units (EMUs) are the Personality Assessment Inventory (PAI) and the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Both have been evaluated separately for their ability to distinguish patients with epilepsy from patients with psychogenic events, but they have never been compared directly. The primary aim of this study was to provide comparison data in an EMU population between the PAI, MMPI-2, and the MMPI-2-RF (MMPI-2 Restructured Form). Results show that the PAI Somatic Complaints (SOM) scale and the Conversion subscale (SOM-C), with classification rates of 79%, outperform other indicators from the PAI and indicators from the MMPI-2 and the MMPI-2-RF. Given its other strengths combined with better diagnostic validity performance, the PAI may be the better personality assessment measure for use in distinguishing patients with epilepsy from those with psychogenic seizures in the EMU.

Do patients with psychogenic nonepileptic seizures have positive covert attitudes toward sickness?

Some individuals with psychogenic nonepileptic seizures (PNES) are seen as having adopted a "sick role" that relinquishes them of responsibility for meeting stressful life demands. Thus, patients with PNES may have positive, albeit unrecognized, attitudes toward seizures, or perhaps illness in general. Because such covert attitudes may not be amendable to self-report, the current study used the Implicit Association Test (IAT), a methodology by which attitudes toward illness and disability can be inferred from performance on an ostensibly neutral task. Individuals with PNES did not have a reduced interference effect when responding to sickness-related and pleasant words on the same response key. Exploratory analyses revealed that a pronounced somatic focus and higher extraversion were associated with more neutral attitudes toward illness among patients with PNES. This IAT methodology found little support for the notion that patients with PNES harbor positive attitudes toward illness. Limitations of the IAT methodology are reviewed and recommendations are provided.

The Minnesota Multiphasic Personality Inventory-2-Restructured Form in the epilepsy monitoring unit

The Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) is a restructuring of the MMPI-2 that has improved the psychometric characteristics of the test. The primary aim of this study was to provide diagnostic utility data on the MMPI-2-RF in an epilepsy monitoring unit population (N=429). Mean comparisons revealed group differences on Validity Scales Fs and FBS-r; Restructured Clinical Scales RC1 and RC3; and Somatic Scales MLS, GIC, HPC, and NUC. Diagnostic utility data are provided for those scales with the largest effect sizes: RC1, FBS-r, and NUC. On RC1, sensitivity was 76% and specificity was 60%, similar to values found when applying published decision rules to the MMPI-2. RC1 explains unique variance in diagnosis beyond that explained by demographic or medical history risk factors. We provide likelihood ratios for scores on RC1, FBS-r, and NUC that can be used by the clinician to calculate posttest odds and probability of nonepileptic seizures using the base rate of nonepileptic seizures in his/her population.

The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures

Using 184 subjects with valid personality assessment interview (PAI) profiles and video-electroencephalography (VEEG)-confirmed diagnoses of epileptic seizures (ES; n = 109) or psychogenic nonepileptic seizures (PNES; n = 75), we present the diagnostic test performance of the PAI PNES Indicator and other PAI scales when used to differentiate PNES from ES. Subjects with PNES reported significantly higher somatic, conversion, depressed, anxious, and suicidal symptoms. As a diagnostic tool, the PNES Indicator does not add additional accuracy beyond the conversion subscale (SOM-C). The somatization (SOM-S) and physiological depression (DEP-P) subscales perform as well as the SOM-C subscale. The SOM-C scale (cut point > or =70) was 58.7% sensitive and 83.5% specific at diagnosing PNES. Assuming a 30% prevalence of PNES, the SOM-C scale has a positive predictive value (PPV) of 60.4% and negative predictive value (NPV) of 82.5%. Overall, the PAI SOM-C subscale does not appear more accurate than other psychometric tests used to differentiate PNES from ES.

Using the Minnesota Multiphasic Inventory 2, EEGs, and clinical data to predict nonepileptic events

Minnesota Multiphasic Inventory 2 (MMPI-2) scale 3, duration of illness, and routine EEGs have been used to predict nonepileptic events (NEEs) with a high degree of accuracy in patients referred for video/EEG (vEEG) monitoring. This study tested the Storzbach logistic regression equation in our patients with definitive epileptic seizures (n=57) or NEEs without evidence of epileptiform activity (n=51) during vEEG monitoring, yielding an overall classification accuracy of 81%, sensitivity of 80%, and specificity of 81%. This study also replicated previous findings of significant group differences in duration (years) of spells, number of elevations on the MMPI-2, MMPI-2 elevations on scales 1, 2, 3, and 8, and incidence of the conversion valley on the MMPI-2. Our findings indicated that combined use of the MMPI-2 and clinical variables was most predictive of patients with NEEs.

Somatoform disorders in neurological practice

PURPOSE OF REVIEW

Patients with medically unexplained symptoms continue to intrigue, fascinate and frustrate clinicians. They are common in general medicine and often present with apparent neurological disorder. This review aims to provide insight into the recent literature that has sought to clarify epidemiology, diagnostic issues, aetiologic understanding and treatment of patients with psychogenic disorders who usually first present to neurologists.

RECENT FINDINGS

Somatoform disorders are common in neurological practice. A number of papers have addressed issues of epidemiology and identified that medically unexplained symptoms in neurological populations are higher than originally thought. A number of recent review papers have served to summarize areas of considerable information (e.g. treatments) and areas of rapid growth in knowledge (e.g. neuroimaging). Studies investigating the role of psychological factors are well represented and clarify our psychopathological understanding of somatoform disorders in patients presenting to neurologists. Treatment studies are few and continue to be limited by population sizes and study designs.

SUMMARY

Somatoform disorders are common in neurological populations. Comorbidity related to somatoform disorders with known organic neurological conditions requires further study. On account of the limitations of treatment studies, evidence-based clinical management of these patients is awaited.