Personality Disorders: Theory, Research, and Treatment 2015, Vol. 6, No. 2, 129 –140

© 2015 American Psychological Association 1949-2715/15/$12.00 http://dx.doi.org/10.1037/per0000119

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The Facets of Identity: Personality Pathology Assessment Through the Inventory of Personality Organization Emanuele Preti and Antonio Prunas

Chiara De Panfilis and Carlo Marchesi

University of Milano-Bicocca

University of Parma

Fabio Madeddu

John F. Clarkin

University of Milano-Bicocca

Weill Cornell Medical College

This work aims to further validate the object-relations– based model of personality pathology assessment, evaluating the psychometric properties of the Italian version of the Inventory of Personality Organization (IPO), a self-report instrument for the assessment of personality organization according to O. Kernberg’s model of personality pathology. Six hundred ninety-six nonclinical volunteers and 121 psychiatric patients completed a set of questionnaires including the IPO, the Severity Indices of Personality Problems, the Borderline Personality Disorder Checklist, the Response Evaluation Measure 71, and the Symptom Checklist 90 –Revised. Confirmatory factor-analyses on the IPO items supported the 1-, 2-, 3-, and 4-factor solutions. The last (Instability of sense of self/others, Instability of goals, Instability of behaviors, Psychosis) resulted in relatively better fit indexes. Invariance across samples (nonclinical, clinical) and gender was confirmed. The 4 IPO subscales showed good levels of internal coherence and, in the nonclinical sample, good test–retest reliability. Associations with the convergent measures were in line with theoretical expectations and supported the benefit of adopting a 4-factor solution. The 4 factors showed the expected criterion relations: All the dimensions discriminated between clinical and nonclinical subjects, whereas only Instability of self/others and Instability of goals discriminated patients with borderline personality disorder from patients with other diagnoses. Our results suggest that the Italian version of the IPO is a reliable and valid tool for the assessment of personality organization according to Kernberg’s model. Results are discussed in the context of the current directions in the evaluation of personality disorders proposed by the Diagnostic and Statistical Manual of Mental Disorders, 5th edition. Keywords: assessment, borderline personality disorder, DSM–5, personality structure

berg & Caligor, 2005) appears particularly in keeping with the DSM–5 conceptualization of personality functioning. This model identifies three levels of personality organization along a continuum of severity of personality pathology, from the lower psychotic level, through the borderline level, to the higher neurotic level. Three main dimensions—Identity, Defense mechanisms, and Reality-testing—represent the foundation of personality organization. Identity integration corresponds to a stable, flexible, and realistic inner experience of self and others; Identity diffusion, on the other hand, refers to superficial and polarized representations of self and others. Defense mechanisms mediate internal conflicts between competing impulses and feelings; the array of individual defenses can vary from mature and flexible mechanisms that allow dealing with everyday life demands, to an immature and rigid defense style interfering with adaptive functioning. Lastly, reality-testing can be defined as the process of relating one’s self to the external world and distinguishing between inner and outer reality. Individuals functioning at the neurotic level show intact realitytesting, identity integration, and a generally mature defense style. Borderline personality organization is characterized by a generally intact reality-testing, in the context of a fragmented and inconsistent sense of self and others. Identity diffusion is the trademark of borderline personality organization and is sustained by the use of

After the publication of Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5; American Psychiatric Association, 2013), the topic of personality disorders diagnosis has attracted a new wave of attention. Dimensional models, that seemed to represent the future of personality disorders, ended up leaving the scene of formal diagnosis but nevertheless gained a primary position within Emerging measures and models (for a recent report of the current debate see Widiger & Krueger, 2013). Studies on dimensional models of personality pathology have thus increased in recent years, and the empirical test of different psychopathological models has become a leading research theme. Among dimensional approaches, Otto Kernberg’s objectrelations model of personality pathology (Kernberg, 1984; Kern-

Emanuele Preti and Antonio Prunas, Department of Psychology, University of Milano-Bicocca; Chiara De Panfilis and Carlo Marchesi, Department of Neuroscience, Unit of Psychiatry, University of Parma; Fabio Madeddu, Department of Psychology, University of Milano-Bicocca; John F. Clarkin, Department of Psychiatry, Weill Cornell Medical College. Correspondence concerning this article should be addressed to Emanuele Preti, Department of Psychology, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, Milano, 20126 Italy. E-mail: emanuele.preti@ unimib.it 129

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primitive defense mechanisms—above all, splitting. This tendency to view the world and other people in a polarized manner results in severe interpersonal problems. Finally, the psychotic level of personality organization is mainly characterized by severe distortions of reality-testing. Personality organization assessment has undergone several refinements through the years. The first assessment model—the structural interview (Kernberg, 1981)—aimed at evaluating the three structural criteria. In recent years, a structured version of this interview has been developed: the Structured Interview of Personality Organization (STIPO; Clarkin, Caligor, Stern, & Kernberg, 2002; Stern et al., 2010). Finally, starting from the same pool of items composing the interview (Oldham et al., 1985), a self-report questionnaire for the assessment of personality organization was developed. The Inventory of Personality Organization (IPO; Lenzenweger, Clarkin, Kernberg, & Foelsch, 2001) comprises 57 items assessing the level of personality functioning across the three core dimensions of Kernberg’s model. The IPO has been translated in different languages: Japanese (Igarashi et al., 2009), French (Normandin et al., 2002), Dutch (Berghuis, Kamphuis, Boedijn, & Verheul, 2009; Smits, Vermote, Claes, & Vertommen, 2009), and German (Zimmermann et al., 2013). Several studies have investigated the factor structure and psychometric properties of the different versions of the questionnaire, both in clinical and community samples. In particular, the exploration of factor structure supported the theoretical 3-dimensions solution (Lenzenweger et al., 2001; Igarashi et al., 2009; Verreault, Sabourin, Lussier, Normandin, & Clarkin, 2013), encompassing the original dimensions of Identity diffusion (sample item: “I see myself in totally different ways at different times”), Primitive defenses (sample item: “I need to admire people in order to feel secure”), and Reality-testing (sample item: “I can’t tell whether certain physical sensations I’m having are real, or whether I am imagining them”). Other results (Lenzenweger et al., 2001; Berghuis et al., 2009) support a 2-factor solution, in which identity and primitive defenses merge in a unique factor (sample items are “I feel I’m a different person at home as compared to how I am at work or at school” and “I tend to feel things in a somewhat extreme way, experiencing either great joy or intense despair”), underlining the close link between a primitive defensive array and the identity diffusion syndrome. More recently, a 4-factor solution has been proposed (Ellison & Levy, 2012). This last dimensional model proposed a first factor, Instability of self/others, composed by items originally belonging to the Identity domain (sample item: “I feel that my tastes and opinions are not really my own, but have been borrowed from other people”), the Primitive defenses domain (sample item: “It is hard for me to trust people because they so often turn against me or betray me”), and items from the original Reality-testing domain related to difficulties in correctly reading social cues (sample item: “Somehow, I never know quite how to conduct myself with people”); as the proposed examples show, items composing this first factor are related to instability both of the sense of self and of interpersonal relationships. The second factor, Instability of goals (sample item: “My life goals change frequently from year to year”) refers to difficulties in maintaining long-term goals and investments. The third factor, Instability of behaviors (sample item originally pertaining to Identity diffusion “I do things on impulse that I think are socially unacceptable,” to Primitive defenses “People tell me I behave in contradictory ways,” and to Reality-testing

“People see me as being rude or inconsiderate and I don’t know why”) captures aspects of behavioral impulsivity and instability. Finally, the Psychosis factor is composed by those items originally belonging to the Reality-testing domain more strictly connected to psychotic features (sample item: “I can see things or hear things that nobody else can see or hear”). Moreover, different studies reported good internal consistency values and good levels of test–retest reliability (Lenzenweger et al., 2001; Berghuis et al., 2009; Normandin et al., 2002). Finally, convergent validity of the instrument has been established through concurrent measures of negative affects, irritability, aggression, schizotypy, depression, and anxiety (Lenzenweger et al., 2001; Igarashi et al., 2009; Berghuis et al., 2009). A number of studies used the IPO to examine the interactions between personality structure and other personality and psychopathological features and to differentiate borderline personality disorder (BPD) and depressed patients (Walter et al., 2009), and BPDs and non-BPDs (Kraus, Dammann, Rothgordt, & Berner, 2004). Specifically, Vermote and colleagues (2009) reported relations between the IPO dimensions and self-harm, anxiety, depression, and anger. Hoermann, Clarkin, Hull, and Levy (2005) found that identity diffusion and primitive defenses were related with low effortful control in a sample of BPD patients. More recently, Lenzenweger, McClough, Clarkin, and Kernberg (2012) reported relations between the personality dimensions of Alienation, Aggression, Absorption and Stress reaction, and the Identity and Primitive defenses dimensions of the IPO. Yun, Stern, Lenzenweger, and Tiersky (2013) used the IPO as external validity measure for a PD taxonomy based on paranoid, aggressive, and antisocial features. Other IPO applications include the evaluation of couple dynamics (Verreault et al., 2013; Naud et al., 2013), intimate partner violence (Maneta, Cohen, Schulz, & Waldinger, 2013), and associations between mothers’ personality structure and children’s attachment and externalizing behaviors (Goodman, Bartlett, & Stroh, 2013). Finally, the IPO has been used as outcome measure in randomized controlled trials (RCTs) of personality disorders treatment (Arntz & Bernstein, 2006; Giesen-Bloo et al., 2006). Particularly, Lenzenweger, Clarkin, Levy, Yeomans, and Kernberg (2012) found that baseline Identity diffusion as measured by the IPO predicted the rate of change in the domain of social adjustment/self acceptance following one year of Transference-Focused Psychotherapy (Clarkin, Levy, Lenzenweger, & Kernberg, 2007). Thus, the IPO can be considered a reliable indicator of the level of personality functioning. Indeed, the abovementioned studies demonstrate that the instrument can detect not only the severity of personality functioning but also features connected to personality functioning as intended by DSM–5. In line with these considerations, as shown by Lowyck, Luyten, Verhaest, Vandeneede, and Vermote (2013) in a recent study, the IPO is to date one of the few available instruments allowing for a DSM–5-oriented assessment of personality pathology. Given these promising results, the present study aims to further validate the object-relations– based model of personality pathology assessment, evaluating the psychometric properties of the IPO in an Italian large community sample and in a clinical sample. Indeed, extending prior evidence focusing on the factor structure and the psychometric properties of the IPO we will also focus on convergence with external measures of personality functioning,

FACETS OF IDENTITY

and we will test the specificity of this assessment instrument as regards clinical status in general; finally, given the theoretic foundation of the instrument, we will test the specificity of Identity diffusion and Primitive defense mechanisms in identifying subjects with BPD.

Method

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Participants Community sample. Participants were 696 nonclinical volunteers, recruited through fliers posted in meeting places in the community and through word of mouth. The mean age was 36.51 years (range: 18 –74, SD ⫽ ⫾ 14.08 years); 240 participants were male (37%) and 408 were female (63%; data on gender were missing for 48 participants). One hundred ninety-six participants (30.3%) were students, 365 (56.5%) were workers, whereas 34 (5.3%) were unemployed and 51 (7.9%) were retired. Eighty-eight participants (13.6%) reported a low level of education (⬍high school), whereas 86.4% (557) reported a higher level of education (high school or above). Clinical sample. One hundred twenty-one clinical participants were recruited from a residential treatment facility, from a public mental health center, and at private practitioners’ offices. Inclusion criteria were (a) age between 18 and 75 years, (b) absence of cognitive impairment, and (c) no current manic episode or psychotic disorder. The mean age was 37.22 years (range 18 – 66, SD ⫽ ⫾ 10.54 years). Fifty-three participants were male (43.8%) and 68 were female (56.2%); 12.6% (14) of participants were students and 50.5% (56) were workers, whereas 33.3% (37) were unemployed and 3.6% (4) were retired. Thirty-nine participants (33.3%) reported a low level of education (⬍high school), whereas 79 (66%) reported a higher level of education (higher school or above). Data on clinical and personality disorders were gathered from clinical records. Diagnoses were attributed to patients admitted to the treatment facilities or to the private practitioners treatment through unstructured DSM-oriented clinical assessment conducted by a psychiatrist. One hundred four participants (88.1%) reported one or more psychiatric diagnoses: Substance related disorders (n ⫽ 42, 34.7%), mood disorders (n ⫽ 38, 31.4%), eating disorders (n ⫽ 13, 10.7%), anxiety disorders (n ⫽ 10, 8.3%), and other (n ⫽ 10, 8.3%). One hundred three participants (87.3%) had at least one PD. Thirty-two patients (26.4%) had more than one personality disorder. Prevalence rates are reported in Table 1.

Measures All participants completed the following self-report questionnaires. Inventory of Personality Organization. The Inventory of Personality Organization (IPO; Lenzenweger et al., 2001) is a 57-item (Likert scale, 1–5) measure of personality organization. The original version of the instrument is composed of three scales: Identity diffusion, Primitive defenses, and Reality-testing. The score of each dimension is calculated as the mean score of the items of the dimension. The Italian version of the IPO was translated by the authors. The adequacy of the translation to its respective English version was assessed through a back-translation by an

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Table 1 Prevalence of Personality Disorders in the Clinical Sample Disorder

n

%

Paranoid Schizoid Schizotypal Any cluster A Antisocial Borderline Narcissistic Histrionic Any cluster B Avoidant Dependent Obsessive/Compulsive Any cluster C Passive/Aggressive Depressive NOS

7 1 3 11 12 30 15 12 69 9 10 9 28 9 5 34

5.8 .8 2.5 9.1 9.9 24.8 12.4 9.9 57.0 7.4 8.3 7.4 23.1 7.4 4.1 28.1

English native speaker, and the authors of the original English IPO checked the back-translation. A subgroup of participants from the community sample (n ⫽ 53) completed the questionnaire again after one month. Severity Indices of Personality Problems. The Severity Indices of Personality Problems (SIPP-118; Verheul et al., 2008), comprising 118 items (Likert scale, 1– 4), assess the core components of maladaptive personality functioning. Five higher order factors (self-control, identity integration, relational capacities, social concordance, and responsibility) are measured. Self-control comprises the facets of Emotion regulation (7 items) and Effortful control (7 items); Identity integration comprises the facets of Self respect (8 items), Stable self-image (7 items), Self-reflexive functioning (7 items), Enjoyment (7 items), and Purposefulness (7 items); Responsibility comprises the facets of Responsible industry (7 items) and Trustworthiness (8 items); Relational capacities comprises the facets of Intimacy (7 items), Enduring relationships (7 items), and Feeling recognized (8 items); Social concordance comprises the facets of Aggression regulation (8 items), Frustration tolerance (8 items), Cooperation (7 items), and Respect (8 items). Higher scores suggest better personality functioning. Previous studies in Italian samples (Prunas, Mognetti, Hartmann, & Bini, 2013) reported good reliability results. In our study ␣ values varied between .69 and .89 (AIC between .52 and .72) in the Community sample and between .63 and .90 (AIC between .57 and .78) in the Clinical sample. Response Evaluation Measure 71. The Response Evaluation Measure 71 (REM-71; Steiner, Araujo, & Koopman, 2001) comprises 71 items evaluating 21 defenses. Two factors are used to divide these defenses into two styles (mature and immature). A study on the Italian version of the instrument (Prunas et al., 2009) confirmed the 2-factor structure and reported good reliability results. In this study only the immature defenses factor (41 items; Community sample: ␣ ⫽ .87, AIC ⫽ .15; Clinical sample: ␣ ⫽ .90, AIC ⫽ .18) was considered. Borderline Personality Disorder Checklist. The Borderline Personality Disorder Checklist (BPDCL; Arntz, van den Hoorn, Cornelis, Verheul, van den Bosch, & de Bie, 2003) comprises 47 items that assess the patient’s burden of complaints about border-

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132 Table 2 Fit Indexes of the 4 CFA Models in the Different Subgroups (Clinical, Community; Males, Females) Model

Group

␹2

df

n

CFI

TLI

RMSEA

1 factor

Clinical Community Males Females Clinical Community Males Females Clinical Community Males Females Clinical Community Males Females

2084.843 3980.932 2482.171 3464.742 2052.994 3812.456 2436.164 3287.062 2050.260 3782.478 2427.078 3270.097 1781.134 3035.325 2088.518 2646.309

1539 1539 1539 1539 1538 1538 1538 1538 1536 1536 1536 1536 1371 1371 1371 1371

103 680 278 504 103 680 278 504 103 680 278 504 103 680 278 504

.870 .894 .915 .892 .878 .902 .919 .902 .878 .903 .920 .903 .901 .924 .933 .927

.865 .890 .912 .888 .873 .898 .916 .898 .873 .899 .917 .899 .897 .921 .930 .924

.054 .048 .046 .049 .053 .046 .045 .047 .053 .046 .044 .046 .050 .042 .042 .042

2 factors

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3 factors

4 factors

line personality disorder symptoms in the previous month according to Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision (DSM–IV–TR) criteria. Results on the psychometric properties of the Italian version of the instrument (Prunas, Sarno, Capizzi, & Madeddu, 2006) report good reliability values. In our study ␣ values of .97 (AIC ⫽ .46) and .91 (AIC ⫽ .28) were obtained, respectively in the Community sample and in the Clinical sample. Symptom Checklist 90-R. The Symptom Checklist 90-R (SCL 90-R; Derogatis, 1977) comprises 90 items that assess psychological symptoms within nine primary dimensions as well as a Global Severity Index (GSI). The Italian version of the instrument (Prunas, Sarno, Preti, Madeddu, & Perugini, 2012) reported good reliability values. In our study ␣ values of .97 (AIC ⫽ .27) and .98 (AIC ⫽ .36) for the GSI were obtained, respectively in the Community sample and in the Clinical sample.

Data Analyses Different factor-structure solutions were examined through a series of multigroup Confirmatory Factor Analyses (CFA) using Mplus software (Muthén & Muthén, 1998 –2010). Multigroup invariance was considered across the Community sample and the Clinical sample and across gender (considering the Community sample and the Clinical sample together). Because the IPO assesses pathological personality functioning, skewed distributions may be expected and item responses may not be considered as continuous (Lenzenweger et al., 2001; Ellison & Levy,

2012). In such cases, weighted least squares means and variance adjusted (WLSMV) estimation may be preferred over standard maximum likelihood estimation (Beauducel & Herzberg, 2006; Brown, 2006; Flora & Curran, 2004; Dolan, 1994; Muthén & Kaplan, 1992). For these reasons, data were considered as ordinal and factor analyses were implemented through the polychoric correlation matrix (Olsson, 1979), using WLSMV estimates available in Mplus. Because ␹2 test is dependent on sample size, fit indexes that correct for sample size were also used: the Comparative Fit Index (CFI; Bentler, 1990), the Tucker-Lewis fit Index (TLI; Bentler & Bonett, 1980), and the Root Mean Square Error of Approximation (RMSEA; Steiger, 1990). As for interpretation guidelines (Hu & Bentler, 1999), CFI and TLI values between .90 and .95 indicate adequate model fit, whereas values of .95 and above suggest excellent fit; RMSEA values between .05 and .08 indicate adequate fit and values between .00 and .05 excellent fit. The comparisons between the 1-factor, 2-factor, and 3-factor nested models were performed examining the ␹2 differences (⌬) between the nested models through the difftest command of Mplus (Asparouhov & Muthén, 2006). This test determines whether a significant decrement in fit occurs between the unconstrained and the constrained models. Nevertheless, as indicated by Cheung and Rensvold (2002), particular caution should be applied in using ⌬␹2 tests in nested models. In this case, the authors recommended to consider CFI differences ⱕ .01 as indicators of factor invariance. Because the 3-factor and the 4-factor competing models were non-nested, decisions related to differences in the goodness of fit were taken in a descriptive way (no formal tests of incremental fit were used; Muthén & Muthén, 1998 – 2010). Internal consistency was assessed through Cronbach’s alpha, whereas test–retest reliability was evaluated through intraclass correlation coefficients (ICC), Pearson’s r, and paired t tests, using SPSS software package (version 22). To evaluate the unique contribution of each of the 4 IPO dimensions in predicting concurrent measures, two-step hierarchical multiple regressions were conducted using SPSS software package (version 22). In the first step we inserted the clinical status (Community sample vs. Clinical sample), whereas the second step assessed the independent contribution of the IPO dimensions. A second three-step hierarchical multiple regression was conducted, in order to control for the degree of general psychopathology. Analyses of covariance (ANCOVA), controlling for gender and age, were performed to evaluate significant differences in the IPO scores between the Community sample and the Clinical sample, and between BPD and non-BPD participants.

Table 3 Fit Indexes of the CFAs of Nested Multigroup Models (1-, 2-, and 3-Factor Solutions) and of the 4-Factor Multigroup Model Considering Clinical Sample and Community Sample Model 4 3 2 1

factors factors factors factor

␹2

df

n

CFI

TLI

RMSEA

⌬␹2

⌬df

p

4484.506 5318.856 5342.716 5506.798

2900 3240 3245 3248

817 817 817 817

.925 .904 .903 .896

.926 .906 .905 .898

.037 .040 .040 .041

— — 49.530 173.827

— — 5 3

— — ⬍.001 ⬍.001

FACETS OF IDENTITY

133

Table 4 Fit Indexes of the CFAs of Nested Multigroup Models (1-, 2-, and 3-Factor Solutions) and of the 4-Factor Multigroup Model Considering Gender Model 4 3 2 1

factors factors factors factor

␹2

df

n

CFI

TLI

RMSEA

⌬␹2

⌬df

p

4762.822 5682.372 5707.982 5919.492

2900 3240 3245 3248

769 769 769 769

.931 .912 .912 .904

.932 .914 .913 .906

.041 .044 .044 .046

— — 45.150 188.217

— — 5 3

— — ⬍.001 ⬍.001

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Results Factor Structure The goodness of fit of four models was tested in the different subgroups (Clinical vs. Non clinical; Males vs. Females). The first (baseline) is the unidimensional model, in which all items load on a single factor. We thus tested the bidimensional model (items from “Primitive defenses” and “Identity diffusion” are collapsed in a single dimension). The original 3-factor solution was then evaluated. Finally, the 4-factor model was tested (see Table 2 for all fit indexes in the different subgroups). The 4-factor model reported relatively better fit indexes compared with the other three models. Considering the nested nature of the 1-, 2-, and 3-factor solutions, multigroup comparisons were conducted among these models, both considering gender and clinical status. Fit indexes indicate a good fit of the configural invariance model (Tables 3 and 4). Considering the 3 nested models, the difftest was significant but differences in terms of CFI suggested factor invariance (CFIdiff ⬍ .01). The 1-, 2-, and 3-factor models thus provide equal fit to the data. The 4-factor model provided the best fit indexes among the set of different models tested. Nevertheless, no comparison with the other models could be provided through statistical tests, given the non-nested nature of such model. We decided to further explore the psychometric characteristics of the 4-factor model for three main reasons: (a) Fit indexes were consistently better in all subgroups (Table 2) and in the multigroup CFAs (although no statistical comparison was possible between the competing indexes and differences were of limited magnitude; see Tables 3 and 4); (b) Considering the two multigroup models (clinical status and gender) of the 4-factor solution, the intercorrelations between factors were high but (also considering standard errors) acceptable (see Table 5); (c) The different associations with the concurrent measures and the specificity of differences between clinical and non clinical participants and between BPD and non BPD participants (see below) support the 4-factor solution. We thus tested factorial invariance of the 4-factor model through a multigroup CFA considering clinical and community participants, estimating a series of gradually more restrictive nested models (Muthén & Muthén, 1998 –2010). The first step was to assess configural invariance (i.e., the same observed variable must be an indicator of the same latent variable in each group; Horn & McArdle, 1992). Fit indexes indicate a good fit of the invariance model (see Table 6). The second step tested metric invariance (i.e., the factor loadings of the observed variables need to be equivalent across groups). Fit indexes (Table 6) were acceptable. The difftest was significant but differences in terms of CFI

resulted minimal (CFIdiff ⫽ .003). The last two steps tested respectively the invariance of the covariances between latent factors and the invariance of the variances of the latent factors. These two models were confirmed (Table 6). The same procedure was then applied considering gender. The total of 817 participants had a mean age of 36.63 years (range 18 –74, SD ⫽ ⫾ 13.58 years). Males (n ⫽ 293) were 38.1%, females (n ⫽ 476) 61.9%. Fit indexes confirm factor invariance also across gender (see Table 7).1

Internal Consistency As shown in Table 8, ␣ values for the 4 IPO factors ranged between .72 and .91 (mean ␣ ⫽ .81) in the Community sample (AIC between .25 and .57) and from .80 to .93 (mean ␣ ⫽ .85) in the Clinical sample (AIC between .29 and .68). Considering the Community sample, all corrected item-total correlations except one were above .30. Item 5 (Psychosis factor) had a correlation below .30; the increase in internal consistency after removing the item was, nevertheless, minimal (from ␣ ⫽ .794 to ␣ ⫽ .798). Considering the Clinical sample, almost all corrected item-total correlations were above .30. Three items reported a correlation below .30 (6, 41: Instability of self/others; 35: Psychosis). The increase in internal consistency after removing these items was, nevertheless, minimal (from ␣ ⫽ .929 to ␣ ⫽ .930 for the first two items; from ␣ ⫽ .843 to ␣ ⫽ .855 for the third item).

Test–Retest Reliability Fifty-three participants from the Community sample completed the IPO again after one month. Males (n ⫽ 5) were 9.4% of the subsample, females (n ⫽ 48) were 90.6%. Mean age was 23.60 years (range 21– 49, SD ⫽ ⫾ 5.10 years). Table 9 shows descriptive statistics of the 4 factors at T1 and T2. Intraclass correlation coefficients (ICC) are all high and significant. Also, correlations between the dimensions at T1 and T2 are all high and significant. Paired t tests revealed significant changes for the Instability of self/other and Psychosis dimensions.

Convergent Validity To evaluate the unique contribution of each of the 4 IPO dimensions in predicting personality functioning measured through SIPP-118, specific BPD symptom severity measured through BPDCL, and immature defenses measured through REM1 All models of invariance (clinical status and gender) were confirmed also for the 1-, 2-, and 3-factor solutions.

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134

Table 5 Intercorrelations (and Standard Errors) Between Factors in the Two Multigroup 4-Factor Models Clinical versus nonclinical

Criterion Validity

Male versus female

Factor

2

3

4

2

3

4

1 2 3

.64 (.03) — —

.76 (.02) .56 (.04) —

.81 (.02) .61 (.03) .77 (.03)

.63 (.04) — —

.78 (.03) .61 (.05) —

.86 (.02) .67 (.05) .83 (.03)

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Note. 1 ⫽ Instability of self/other; 2 ⫽ Instability of goals; 3 ⫽ Psychosis; 4 ⫽ Instability of behavior.

A first ANCOVA revealed significantly higher scores on the four IPO dimensions for clinical versus nonclinical participants (see Table 12). A second ANCOVA compared BPDs and non-BPDs (Clinical sample). Instability of self/others and Instability of goals are significantly higher among BPDs (see Table 13). Controlling for general psychopathology measured through the GSI of SCL-90, results still show a marginally significant effect for Instability of self/others, F(1,109) ⫽ 3.327, p ⫽ .07, and a significant effect for Instability of goals, F(1,105) ⫽ 4.486, p ⬍ .05.

Discussion 71, two-step hierarchical multiple regressions were conducted (see Table 10). In the first step we inserted clinical status, while the second step assessed the independent contribution of the four IPO dimensions. Considering the five higher order SIPP-118 factors, we found significant increments in variance explained by the 4 IPO dimensions over and above clinical status, ranging from 33% to 40% (p ⬍ .001). The IPO dimension Instability of self/others uniquely contributes significant portions of variance explained for all the 5 SIPP-118 domains. The IPO dimension Instability of goals uniquely contributes significant portions of variance explained for SIPP-118 Responsibility, with an additional marginal contribution for SIPP-118 Identity integration. The IPO dimension Instability of behavior uniquely contributes significant portions of variance explained for SIPP-118 Responsibility, Social concordance, and Self control, whereas the IPO dimension Psychosis showed only marginal contributions to the prediction of SIPP-118 Responsibility and Identity integration. As for borderline symptomatology (BPDCL), the IPO resulted in a significant increment in variance explained (18%, p ⬍ .001), with a unique contribution of Instability of self/others and a marginal increment due to Instability of behavior. Finally, considering Immature defenses (REM-71), there was a significant increment due to the IPO (32%, p ⬍ .001), with the unique contribution of Instability of self/others, Psychosis, and a marginal increment due to Instability of behavior. We thus conducted three-step hierarchical multiple regressions, inserting the general level of psychopathological distress measured through the GSI of SCL 90-R as a second step (see Table 11). Results were comparable with those obtained through the two-step hierarchical multiple regressions, with the exception of borderline symptomatology (BPDCL). In this last measure no unique contributions of the IPO dimensions were detected, after controlling for general psychopathological distress.

The study aimed at providing further evidence of the structural model of personality pathology by evaluating the psychometric properties of the Italian version of the Inventory of Personality Organization in both a community and a clinical sample. We first tested the different hypotheses about IPO dimensions that had emerged in the literature. The 4-factors model proposed by Ellison and Levy (2012) showed a relatively best fit to our data both in a clinical sample and in a community sample. Furthermore, we showed that the four dimensions are invariant across clinical status and gender. This last result is in line with Kernberg’s object-relations model of personality pathology, according to which personality structure shows no gender differences (Kernberg, 1984). Our data showed that also the three competing models (1-, 2-, and 3-factor solutions) yielded acceptable results in terms of fit indexes. Nevertheless, our results regarding the associations with external measures support the usefulness of a 4-factor solution. Thus, in a large community sample and in a clinical sample the IPO can be applied to measure Instability of self and others, Instability of goals, Instability of behaviors, and Psychosis. Cronbach’s alpha values also confirmed the reliability of these four dimensions (Nunnally & Bernstein, 1994). Results related to a subgroup of participants from the community sample also provided partial support to the stability of the IPO scores over time: One-month test–retest reliability for the 4 IPO dimensions was confirmed by excellent levels of ICCs. A separate examination of rank-order consistency and mean-level stability revealed mixed results. While rank-order stability was supported by the correlations between the dimensions at T1 and T2, the Instability of self-other and the Psychosis dimensions revealed significant changes over time. Overall, these results are comparable with data reported in previous psychometric studies of the IPO (Lenzenweger et al., 2001; Normandin et al., 2002; Berghuis et al., 2009). Furthermore, these results are consistent with theoretical

Table 6 Fit Indexes of the CFAs of Nested Multigroup Models Considering Clinical and Community Samples Invariance model

␹2

df

n

CFI

TLI

RMSEA

⌬␹2

⌬df

p

Configural Metric Covariances Variances

4484.506 4457.736 4570.176 4592.707

2900 2950 2956 2960

783 783 783 783

.925 .928 .923 .922

.926 .930 .926 .925

.037 .035 .037 .037

— 86.460 48.973 27.262

— 50 6 4

— .001 ⬍.001 ⬍.001

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Table 7 Fit Indexes of the CFAs of Nested Multigroup Models Considering Gender Invariance model

␹2

df

n

CFI

TLI

RMSEA

⌬␹2

⌬df

p

Configural Metric Covariances Variances

4762.822 4680.548 4625.979 4612.948

2900 2950 2956 2960

734 734 734 734

.931 .936 .938 .939

.932 .938 .940 .941

.041 .039 .038 .038

— 76.250 6.148 10.544

— 50 6 4

— .01 ⬍.001 ⬍.05

expectations that structural personality features are stable, pervasive, and enduring over time. Nonetheless, our results related to a certain degree of change at a mean-level for some of the IPO dimensions underline the need for data on the stability of the personality dimensions measured through the IPO in larger samples and in clinical participants. One of our main aims was to extend previous findings regarding factor structure and psychometric properties of the IPO, testing convergent relations with external measures of personality functioning. In this regard, considering the two samples together and controlling for clinical status, a coherent pattern of convergent relations emerged. Particularly, the IPO dimension Instability of self/other was inversely associated with SIPP-118 measures of personality functioning, and especially with the Identity integration, Relational capacities, Self-control, and Social concordance domains. Instability of goals was inversely associated with Responsibility. Instability of behavior showed negative associations with Responsibility, Social concordance, and Self-control. The additional unique associations that emerged between Instability of goals, Instability of behaviors, and the SIPP-118 domains support the idea that these IPO factors can be considered as further facets of identity assessment. Our results show that, while the IPO factor Instability of self/others shows the stronger associations with Identity integration measured by the SIPP-118, these two additional facets measure connected features (as shown by the intercorrelations between IPO domains), but present different patterns of associations with external measures, less related to internal representations and more connected to behavioral outcomes of identity diffusion. Measuring these features can thus lead to a more comprehensive profile of identity integration, encompassing also behavioral components and aspects of self-definition connected with long-term objectives. Consistently, the Psychosis dimension of the IPO was not associated with any personality features measured by the SIPP-118 (with the exception of marginal contributions to variance prediction). It could be argued that psychotic features

should be related to impairments in intimacy and capacity to form enduring relationships (SIPP-118 domain); in our clinical sample, nevertheless, participants with psychotic disorders were excluded, so it is possible to hypothesize that the psychotic features measured by the IPO factor did not reach a level of severity that could impair relational capacities. The marginal positive associations between the SIPP-118 dimensions and the Psychosis dimension of the IPO could be attributable to suppressor effect (Horst, 1941; Cohen & Cohen, 1975). Concerning convergent relations with descriptive psychopathological measures, the Instability of self/others dimension of the IPO was related to a specific measure of BPD symptoms (BPDCL). The association between the core feature of identity diffusion measured by the IPO and psychopathological distress has already been found in previous studies (Lenzenweger et al., 2001; Berghuis et al., 2009). According to Kernberg’s model of personality pathology (Kernberg & Caligor, 2005) and also considering other research results (Depue & Lenzenweger, 2001), personality disorders— especially those pertaining to Borderline Personality Organization—are characterized by high levels of anxiety, depression, and related psychological symptoms. The associations with BPD symptoms further demonstrate the specificity of the connections between identity integration and the DSM borderline pathology model. Surprisingly, we found only weak marginal associations between BPD symptoms and the Instability of behaviors factor of the IPO. A closer look at regressions considering the 9 BPDCL subscales, however, revealed that, coherently, stronger associations emerged with symptom dimensions related to BPD features that can cause behavioral problems: Impulsivity (⌬R2 ⫽ .05, p ⬍ .001; Semipartial correlation ⫽ .11, p ⬍ .001) and anger (⌬R2 ⫽ .12, p ⬍ .001; Semipartial correlation ⫽ .16, p ⬍ .001). We also found that, controlling for general psychopathology (i.e., the GSI index of SCL 90-R), on the one hand the associations between the IPO dimensions and descriptive symptoms of BPD no longer provide additional unique contributions, whereas on the

Table 8 Cronbach’s ␣ and Corrected Item-Total Correlations of the 4 IPO Dimensions in the Community Sample and in the Clinical Sample Corrected item–total correlation ␣

Community

Clinical

Factor (n items)

Community

Clinical

M

Range

M

Range

Instability of self/others (32) Instability of goals (2) Psychosis (12) Instability of behavior (8)

.91 .72 .79 .81

.93 .81 .84 .80

.48 .57 .45 .52

.30–.63 .57–.57 .27–.54 .37–.65

.52 .68 .52 .51

.24–.72 .68–.68 .18–.71 .40–.63

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Table 9 Descriptive Statistics of the 4 IPO Dimensions at T1 and T2, Paired t Tests, Correlations, and ICC for a Subsample of 53 Participants

Factor Instability of self/others Instability of goals Psychosis Instability of behavior

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ⴱ

p ⬍ .05.

ⴱⴱⴱ

T1

T2

M

M

2.35 (.58) 2.23 (.85) 1.71 (.56) 1.71 (.64)

t(52)

r

ⴱ

2.28 (.61) 2.08 (.76) 1.53 (.48) 1.66 (.62)

ICC

ⴱⴱⴱ

.92 .68ⴱⴱⴱ .79ⴱⴱⴱ .83ⴱⴱⴱ

2.220 1.577 3.851ⴱⴱⴱ 1.006

.96ⴱⴱⴱ .80ⴱⴱⴱ .88ⴱⴱⴱ .90ⴱⴱⴱ

p ⬍ .001.

other hand, the IPO dimensions still significantly contribute to the increments in variance explained related to personality functioning measures. Finally, an external measure of primitive defensive functioning (REM-71) was associated with Instability of self/other and with Psychosis. Such results can be explained considering that the more intrapsychic/representational facet of identity, related to the lack of a stable, flexible, and realistic inner experience of self and others, is coherently associated with the adoption of a primitive defensive style. Again, considering the absence of actual psychotic features in our samples, the association between primitive defenses measured by the REM-71 and the Psychosis factor of the IPO could be explained by the effects of a primitive defensive style in terms of mild reality distortions. Another main goal of our work was to test the IPO as an assessment instrument that can be helpful in specific psychopathological domains, particularly as regards the realm of BPD. Results on criterion validity showed that the 4 factors of the IPO can be used to assess the presence of general personality pathology. More specifically, only Instability of self/others and Instability of goals discriminate between BPD and non-BPD patients. These results demonstrate that the core pathological feature of the structural model of personality pathology—that is, identity diffusion—is tightly tied to DSM BPD diagnosis. Taken together, our results therefore, although at a factor analytic level confirming also the goodness of fit of the original theoretical tri-dimensional structure of the IPO, underline the clinical usefulness of considering different facets of identity. As stated by Ellison and Levy (2012), the 4-factor dimensionality

supported by our results is nevertheless in line with essential features of the structural model of personality. We thus propose that 3 IPO factors (i.e., Instability of self/other, Instability of goals, and Instability of behaviors) can be considered as measures of different facets of identity. Each of these three facets is coherent both with Kernberg’s model of personality structure and with the DSM–5 proposed dimensional model of personality pathology. Instability of self/other and Instability of goals can be considered as indicators of identity diffusion. In Kernberg’s model identity diffusion arises both in the difficulty in holding a stable and integrated image of self and significant others and in the difficulty in investing in stable, strong and long term goals (in terms of work or study). Further evidence for the centrality of these two factors in personality structure pathology derives from the convergent associations described above. In addition, these are the sole two factors that proved to discriminate between BPD and non-BPD individuals. The third facet, Instability of behavior, does not have direct correspondences with the original theoretical model. We propose that this dimension measures the impulsive and instable/incoherent behavioral outcomes that stem from the defensive and identity configuration of patients with Borderline Personality Organization. Caution should be taken in considering this factor as a separate facet, because of the high intercorrelations with the other IPO domains (see Table 5). Nevertheless, results related to the associations with the external indexes support the idea that measuring this third identity facet can add a descriptive dimension to the personality structure profile.

Table 10 Multiple Hierarchic Regressions (Controlling for Clinical Status) Step 1

Step 2

External measures

R2 (clinical status)

⌬R2 (IPO)

Semipartial correlations

BPDCL REM SIPP-118 Self control Social concordance Identity integration Relational capacities Responsibility

.16ⴱⴱⴱ .08ⴱⴱⴱ

.18ⴱⴱⴱ .32ⴱⴱⴱ

.19ⴱⴱⴱ .20ⴱⴱⴱ

.25ⴱⴱⴱ .06ⴱⴱⴱ .25ⴱⴱⴱ .10ⴱⴱⴱ .29ⴱⴱⴱ

.40ⴱⴱⴱ .34ⴱⴱⴱ .40ⴱⴱⴱ .30ⴱⴱⴱ .33ⴱⴱⴱ

⫺.29ⴱⴱⴱ ⫺.23ⴱⴱⴱ ⫺.39ⴱⴱⴱ ⫺.31ⴱⴱⴱ ⫺.13ⴱⴱⴱ

1

2 .03 .02 ⫺.05 ⫺.02 ⫺.09ⴱⴱ .01 ⫺.16ⴱⴱⴱ

3 .02 .18ⴱⴱⴱ ⫺.05 ⫺.01 .06ⴱ ⫺.01 .08ⴱⴱ

4 .09ⴱ .07ⴱ ⫺.16ⴱⴱⴱ ⫺.18ⴱⴱⴱ ⫺.02 ⫺.07 ⫺.24ⴱⴱⴱ

Note. 1 ⫽ Instability of self/other; 2 ⫽ Instability of goals; 3 ⫽ Psychosis; 4 ⫽ Instability of behavior; GSI ⫽ Global Severity Index of SCL-90-R; REM ⫽ Immature defenses factor of REM-71; BPDCL ⫽ Borderline Personality Disorder Checklist total score. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

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Table 11 Multiple Hierarchic Regressions (Controlling for Clinical Status and General Psychopathology) Step 1

Step 2

Step 3

External measures

R2 (clinical status)

⌬R2 (GSI)

⌬R2 (IPO)

1

Semipartial correlations 2

BPDCL REM SIPP-118 Self control Social concordance Identity integration Relational capacities Responsibility

.16ⴱⴱⴱ .08ⴱⴱⴱ

.25ⴱⴱⴱ .31ⴱⴱⴱ

.03ⴱⴱⴱ .09ⴱⴱⴱ

.09 .11ⴱⴱ

.02 .00

.25ⴱⴱⴱ .06ⴱⴱⴱ .25ⴱⴱⴱ .10ⴱⴱⴱ .29ⴱⴱⴱ

.20ⴱⴱⴱ .16ⴱⴱⴱ .30ⴱⴱⴱ .19ⴱⴱⴱ .12ⴱⴱⴱ

.21ⴱⴱⴱ .18ⴱⴱⴱ .15ⴱⴱⴱ .13ⴱⴱⴱ .21ⴱⴱⴱ

⫺.37ⴱⴱⴱ ⫺.23ⴱⴱⴱ ⫺.46ⴱⴱⴱ ⫺.30ⴱⴱⴱ ⫺.17ⴱⴱⴱ

⫺.08 ⫺.02 ⫺.14ⴱⴱ .02 ⫺.25ⴱⴱⴱ

3 .00 .23ⴱⴱⴱ .09ⴱ ⫺.00 .13ⴱ ⫺.01 .13ⴱ

4 .08 .06 ⫺.25ⴱⴱⴱ ⫺.22ⴱⴱⴱ ⫺.01 ⫺.08 ⫺.23ⴱⴱⴱ

Note. 1 ⫽ Instability of self/other; 2 ⫽ Instability of goals; 3 ⫽ Psychosis; 4 ⫽ Instability of behavior; GSI ⫽ Global Severity Index of SCL-90-R; REM ⫽ Immature defenses factor of REM-71; BPDCL ⫽ Borderline Personality Disorder Checklist total score. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

This multifacets conceptualization of identity assessment is also coherent with DSM–5 Levels of personality functioning evaluation. In fact, in assessing the level of functioning in relation to Self the DSM–5 proposes to evaluate both the level of impairment in the sense of continuity of and uniqueness of self and in the capacity to set reasonable goals based on a realistic assessment of one’s own capacities. On the other hand, DSM–5 encourages the assessment of interpersonal personality functioning. In line with this indication, the first factor of the IPO measures the stability and coherence of the idea that the individual has of other people. In line with Morey and colleagues (2011), the Instability of self/others factor (the core of identity diffusion) seem to capture a global dimension of personality pathology that considers dysfunctions in self and interpersonal relatedness as a core dimension of severity of personality pathology. As stated by Ellison and Levy (2012), the Psychosis dimension shows the closest similarity to one of the original IPO subscales, Reality-testing. This dimension contains the most severe psychotic symptoms. Other reality-testing impairments more connected with Borderline Personality Organization—such as “social reality-testing”—load on the Instability of self/other dimension. Realitytesting has thus two faces. On the one hand psychotic-like symptoms mark the border of Psychotic Personality Organization. On the other hand, the misinterpretation of social cues impairs the individual’s capacity to hold a realistic consideration of self and others. Consistent with these result, the authors of the STIPO (Clarkin et al., 2002; Stern et al., 2010) have developed the

Identity section also considering—together with the capacity to invest coherently and constantly in study and work and to form a coherent and stable self and other image—the capacity to accurately perceive and interpret social events. The 4-factor model of the IPO does not encompass the presence of a separate assessment of primitive defensive functioning. Our results suggest, as recognized by Ellison and Levy (2012) and by Lenzenweger, Clarkin, et al. (2012), that identity functioning is—in all its facets—intertwined with the individual defensive array. This is also reflected in the high intercorrelations found between these two different facets both in our study and in previous reports (Lenzenweger et al., 2001; Stern et al., 2010; Ellison & Levy, 2012). In this sense defensive operations that reflect a lack of integration of one’s and others image are measured by the Instability of self/others domain, whereas the behavioral outcomes of defenses that lead to impulsivity or erratic behavior are captured by the Instability of behavior dimension. The study presented has some methodological limitations. A large number of participants in the clinical sample (34.7%) had a comorbid substance-related disorder. Caution should thus be taken in generalizing our results to patients with personality disorders without comorbid substance-related conditions. This limitation, nevertheless, makes our sample more ecologically sound, because comorbidity between personality disorders and substance-related disorders seems to represent the rule more than the exception (Trull, Jahng, Tomko, Wood, & Sher, 2010). Convergent validity

Table 12 Differences in IPO Mean Scores Between the Community Sample and the Clinical Sample, Controlling for Gender and Age Gender and age correction

Factor

S1 n ⫽ 696 M ⫾ SD

S2 n ⫽ 121 M ⫾ SD

F1,816

Instability of self/other Instability of goals Psychosis Instability of behavior

2.07 ⫾ .50 2.03 ⫾ .83 1.52 ⫾ .42 1.51 ⫾ .49

2.54 ⫾ .71 2.45 ⫾ 1.06 1.71 ⫾ .65 2.15 ⫾ .76

76.643 24.149 17.627 144.792

a

For all Fs, p ⬍ .001.

a

S1 n ⫽ 696 M; SE

S2 n ⫽ 121 M; SE

F1,767a

2.08; .02 2.03; .03 1.52; .02 1.52; .02

2.55; .05 2.45; .08 1.71; .04 2.16; .05

79.553 22.810 16.892 142.000

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Table 13 Differences in IPO Mean Scores Between Clinical Sample Participants With and Without BPD, Controlling for Gender and Age Gender and age correction

Factor

BPD n ⫽ 30 M ⫾ SD

No BPD n ⫽ 88 M ⫾ SD

Instability of self/other Instability of goals Psychosis Instability of behavior

2.91 ⫾ .56 2.97 ⫾ 1.09 1.89 ⫾ .64 2.41 ⫾ .54

2.42 ⫾ .72 2.28 ⫾ 1.00 1.64 ⫾ .63 2.07 ⫾ .81

ⴱ

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a

p ⬍ .05. ⴱⴱ p ⬍ .01. For all Fs, p ⬍ .001.

ⴱⴱⴱ

F1,816a

BPD n ⫽ 30 M; SE

No BPD n ⫽ 88 M; SE

F1,767a

11.548ⴱⴱⴱ 9.604ⴱⴱ 3.490 4.497ⴱ

2.87; .13 2.99; .19 1.88; .12 2.38; .14

2.45; .07 2.28; .11 1.65; .07 2.09; .08

8.464ⴱⴱ 9.784ⴱⴱ 2.609 (NS) 3.058 (NS)

p ⬍ .001.

has been assessed only through self-report instruments. These could have caused social desirability problems. More specifically, previous research acknowledged methodological challenges in studying automatic, unconscious processes by self-report instruments (Prunas et al., 2009; Cramer, 1998). Also, mean interitem correlations (AIC) of some of the self-report measures (i.e., REM 71 and SCL 90-R) indicate a degree of heterogeneity in the measures. Finally, as reported by Ellison and Levy (2012), problems may arise by the fact that the Instability of goals factor is measured by only 2 items. Future research should try to add new items to this dimension. Also, the high intercorrelations between the Instability of behavior and Instability of self/others factors should be addressed adding/modifying items to better differentiate the two factors. In conclusion, our results support the idea that identity can be considered as a multifaceted construct. The facets measured by the IPO are all consistent with Kernberg’s personality structure model. Furthermore, identity assessment conducted through the IPO is in line with the current directions for dimensional assessment of personality functioning suggested by the DSM–5. In terms of clinical usefulness, personality pathology assessment through the IPO can provide significant information related to different facets of the patient’s functioning. Identity diffusion assessment (Instability of sense of self/others; Instability of goals) is a crucial aspect of an object relations-oriented approach to personality pathology, and the recognition of this core component of Borderline Personality Organization—together with the evaluation of a relatively preserved reality-testing (Psychosis) can lead the clinician to a tailored treatment indication (i.e., Transference-Focused Psychotherapy, Clarkin, Yeomans, & Kernberg, 2006). Furthermore, the same core components of identity diffusion can provide useful clinical information related to the DSM–5 Levels of Personality Functioning. Finally, the additional facet related to Instability of behavior can provide relevant information related to the impact of identity diffusion in the patient’s functioning.

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