Facets of Identity: Personality Pathology Assessment Through theInventory of Personality Organization

Emanuele Preti and Antonio PrunasUniversity of Milano-Bicocca

Chiara De Panfilis and Carlo MarchesiUniversity of Parma

Fabio MadedduUniversity of Milano-Bicocca

John F. ClarkinWeill 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’smodel of personality pathology. Six hundred ninety-six nonclinical volunteers and 121 psychiatricpatients completed a set of questionnaires including the IPO, the Severity Indices of PersonalityProblems, the Borderline Personality Disorder Checklist, the Response Evaluation Measure 71, and theSymptom 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 ofbehaviors, 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 inline with theoretical expectations and supported the benefit of adopting a 4-factor solution. The 4 factorsshowed the expected criterion relations: All the dimensions discriminated between clinical and nonclini-cal subjects, whereas only Instability of self/others and Instability of goals discriminated patients withborderline personality disorder from patients with other diagnoses. Our results suggest that the Italianversion of the IPO is a reliable and valid tool for the assessment of personality organization accordingto Kernberg’s model. Results are discussed in the context of the current directions in the evaluation ofpersonality disorders proposed by the Diagnostic and Statistical Manual of Mental Disorders, 5thedition.

Keywords: assessment, borderline personality disorder, DSM–5, personality structure

After the publication of Diagnostic and Statistical Manual ofMental Disorders (5th ed.; DSM–5; American Psychiatric Associ-ation, 2013), the topic of personality disorders diagnosis has at-tracted a new wave of attention. Dimensional models, that seemedto represent the future of personality disorders, ended up leavingthe scene of formal diagnosis but nevertheless gained a primaryposition within Emerging measures and models (for a recent reportof the current debate see Widiger & Krueger, 2013). Studies ondimensional models of personality pathology have thus increasedin recent years, and the empirical test of different psychopatho-logical models has become a leading research theme.

Among dimensional approaches, Otto Kernberg’s object-relations model of personality pathology (Kernberg, 1984; Kern-berg & Caligor, 2005) appears particularly in keeping with theDSM–5 conceptualization of personality functioning. This modelidentifies three levels of personality organization along a contin-uum of severity of personality pathology, from the lower psychoticlevel, through the borderline level, to the higher neurotic level.Three main dimensions—Identity, Defense mechanisms, and Re-ality-testing—represent the foundation of personality organization.Identity integration corresponds to a stable, flexible, and realisticinner experience of self and others; Identity diffusion, on the otherhand, refers to superficial and polarized representations of self andothers. Defense mechanisms mediate internal conflicts betweencompeting impulses and feelings; the array of individual defensescan vary from mature and flexible mechanisms that allow dealingwith everyday life demands, to an immature and rigid defense styleinterfering with adaptive functioning. Lastly, reality-testing can bedefined as the process of relating one’s self to the external worldand distinguishing between inner and outer reality.Individuals functioning at the neurotic level show intact reality-

testing, identity integration, and a generally mature defense style.Borderline personality organization is characterized by a generallyintact reality-testing, in the context of a fragmented and inconsis-

Emanuele Preti and Antonio Prunas, Department of Psychology, Uni-versity of Milano-Bicocca; Chiara De Panfilis and Carlo Marchesi, De-partment of Neuroscience, Unit of Psychiatry, University of Parma; FabioMadeddu, Department of Psychology, University of Milano-Bicocca; JohnF. 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, Piazzadell’Ateneo Nuovo 1, Milano, 20126 Italy. E-mail: emanuele.preti@unimib.it

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tent sense of self and others. Identity diffusion is the trademark ofborderline personality organization and is sustained by the use ofprimitive defense mechanisms—above all, splitting. This tendencyto view the world and other people in a polarized manner results insevere interpersonal problems. Finally, the psychotic level of per-sonality organization is mainly characterized by severe distortionsof reality-testing.Personality organization assessment has undergone several re-

finements through the years. The first assessment model—thestructural interview (Kernberg, 1981)—aimed at evaluating thethree structural criteria. In recent years, a structured version of thisinterview has been developed: the Structured Interview of Person-ality Organization (STIPO; Clarkin, Caligor, Stern, & Kernberg,2002; Stern et al., 2010). Finally, starting from the same pool ofitems composing the interview (Oldham et al., 1985), a self-reportquestionnaire for the assessment of personality organization wasdeveloped. The Inventory of Personality Organization (IPO; Len-zenweger, Clarkin, Kernberg, & Foelsch, 2001) comprises 57items assessing the level of personality functioning across the threecore dimensions of Kernberg’s model. The IPO has been translatedin different languages: Japanese (Igarashi et al., 2009), French(Normandin et al., 2002), Dutch (Berghuis, Kamphuis, Boedijn, &Verheul, 2009; Smits, Vermote, Claes, & Vertommen, 2009), andGerman (Zimmermann et al., 2013). Several studies have investi-gated the factor structure and psychometric properties of the dif-ferent versions of the questionnaire, both in clinical and commu-nity samples. In particular, the exploration of factor structuresupported the theoretical 3-dimensions solution (Lenzenweger etal., 2001; Igarashi et al., 2009; Verreault, Sabourin, Lussier, Nor-mandin, & Clarkin, 2013), encompassing the original dimensionsof Identity diffusion (sample item: “I see myself in totally differentways at different times”), Primitive defenses (sample item: “I needto admire people in order to feel secure”), and Reality-testing(sample item: “I can’t tell whether certain physical sensations I’mhaving are real, or whether I am imagining them”). Other results(Lenzenweger et al., 2001; Berghuis et al., 2009) support a 2-factorsolution, in which identity and primitive defenses merge in aunique factor (sample items are “I feel I’m a different person athome as compared to how I am at work or at school” and “I tendto feel things in a somewhat extreme way, experiencing eithergreat joy or intense despair”), underlining the close link between aprimitive 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 belongingto the Identity domain (sample item: “I feel that my tastes andopinions are not really my own, but have been borrowed fromother people”), the Primitive defenses domain (sample item: “It ishard for me to trust people because they so often turn against meor betray me”), and items from the original Reality-testing domainrelated to difficulties in correctly reading social cues (sample item:“Somehow, I never know quite how to conduct myself withpeople”); as the proposed examples show, items composing thisfirst factor are related to instability both of the sense of self and ofinterpersonal 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 invest-ments. The third factor, Instability of behaviors (sample itemoriginally pertaining to Identity diffusion “I do things on impulse

that I think are socially unacceptable,” to Primitive defenses “Peo-ple tell me I behave in contradictory ways,” and to Reality-testing“People see me as being rude or inconsiderate and I don’t knowwhy”) captures aspects of behavioral impulsivity and instability.Finally, the Psychosis factor is composed by those items originallybelonging to the Reality-testing domain more strictly connected topsychotic features (sample item: “I can see things or hear thingsthat nobody else can see or hear”). Moreover, different studiesreported good internal consistency values and good levels oftest–retest reliability (Lenzenweger et al., 2001; Berghuis et al.,2009; Normandin et al., 2002). Finally, convergent validity of theinstrument has been established through concurrent measures ofnegative 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 psycho-pathological features and to differentiate borderline personalitydisorder (BPD) and depressed patients (Walter et al., 2009), andBPDs and non-BPDs (Kraus, Dammann, Rothgordt, & Berner,2004). Specifically, Vermote and colleagues (2009) reported rela-tions between the IPO dimensions and self-harm, anxiety, depres-sion, and anger. Hoermann, Clarkin, Hull, and Levy (2005) foundthat identity diffusion and primitive defenses were related with loweffortful control in a sample of BPD patients. More recently,Lenzenweger, McClough, Clarkin, and Kernberg (2012) reportedrelations between the personality dimensions of Alienation, Ag-gression, Absorption and Stress reaction, and the Identity andPrimitive defenses dimensions of the IPO. Yun, Stern, Lenzen-weger, and Tiersky (2013) used the IPO as external validitymeasure for a PD taxonomy based on paranoid, aggressive, andantisocial features. Other IPO applications include the evaluationof couple dynamics (Verreault et al., 2013; Naud et al., 2013),intimate partner violence (Maneta, Cohen, Schulz, & Waldinger,2013), and associations between mothers’ personality structure andchildren’s attachment and externalizing behaviors (Goodman, Bar-tlett, & Stroh, 2013).Finally, the IPO has been used as outcome measure in random-

ized 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 IPOpredicted the rate of change in the domain of social adjustment/selfacceptance following one year of Transference-Focused Psycho-therapy (Clarkin, Levy, Lenzenweger, & Kernberg, 2007).Thus, the IPO can be considered a reliable indicator of the level

of personality functioning. Indeed, the abovementioned studiesdemonstrate that the instrument can detect not only the severity ofpersonality functioning but also features connected to personalityfunctioning as intended by DSM–5. In line with these consider-ations, as shown by Lowyck, Luyten, Verhaest, Vandeneede, andVermote (2013) in a recent study, the IPO is to date one of the fewavailable instruments allowing for a DSM–5-oriented assessmentof personality pathology.Given these promising results, the present study aims to further

validate the object-relations–based model of personality pathologyassessment, evaluating the psychometric properties of the IPO inan Italian large community sample and in a clinical sample. In-deed, extending prior evidence focusing on the factor structure and

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the psychometric properties of the IPO we will also focus onconvergence with external measures of personality functioning,and we will test the specificity of this assessment instrument asregards clinical status in general; finally, given the theoretic foun-dation of the instrument, we will test the specificity of Identitydiffusion and Primitive defense mechanisms in identifying sub-jects with BPD.

Method

Participants

Community sample. Participants were 696 nonclinical vol-unteers, recruited through fliers posted in meeting places in thecommunity and through word of mouth. The mean age was 36.51years (range: 18–74, SD 5 6 14.08 years); 240 participants weremale (37%) and 408 were female (63%; data on gender weremissing 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-eightparticipants (13.6%) reported a low level of education (,highschool), whereas 86.4% (557) reported a higher level of education(high school or above).Clinical sample. One hundred twenty-one clinical partici-

pants were recruited from a residential treatment facility, from apublic 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 episodeor psychotic disorder.The mean age was 37.22 years (range 18–66, SD 5 6 10.54

years). Fifty-three participants were male (43.8%) and 68 werefemale (56.2%); 12.6% (14) of participants were students and50.5% (56) were workers, whereas 33.3% (37) were unemployedand 3.6% (4) were retired. Thirty-nine participants (33.3%) re-ported 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 tothe treatment facilities or to the private practitioners treatmentthrough unstructured DSM-oriented clinical assessment conductedby a psychiatrist. One hundred four participants (88.1%) reportedone or more psychiatric diagnoses: Substance related disorders(n 5 42, 34.7%), mood disorders (n 5 38, 31.4%), eating disorders(n 5 13, 10.7%), anxiety disorders (n 5 10, 8.3%), and other (n 5

10, 8.3%). One hundred three participants (87.3%) had at least onePD. Thirty-two patients (26.4%) had more than one personalitydisorder. Prevalence rates are reported in Table 1.

Measures

All participants completed the following self-report question-naires.Inventory of Personality Organization. The Inventory of

Personality Organization (IPO; Lenzenweger et al., 2001) is a57-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. Thescore of each dimension is calculated as the mean score of theitems of the dimension. The Italian version of the IPO was trans-

lated by the authors. The adequacy of the translation to its respec-tive English version was assessed through a back-translation by anEnglish native speaker, and the authors of the original English IPOchecked the back-translation. A subgroup of participants from thecommunity sample (n 5 53) completed the questionnaire againafter one month.Severity Indices of Personality Problems. The Severity In-

dices of Personality Problems (SIPP-118; Verheul et al., 2008),comprising 118 items (Likert scale, 1–4), assess the core compo-nents of maladaptive personality functioning. Five higher orderfactors (self-control, identity integration, relational capacities, so-cial concordance, and responsibility) are measured. Self-controlcomprises the facets of Emotion regulation (7 items) and Effortfulcontrol (7 items); Identity integration comprises the facets of Selfrespect (8 items), Stable self-image (7 items), Self-reflexive func-tioning (7 items), Enjoyment (7 items), and Purposefulness (7items); Responsibility comprises the facets of Responsible indus-try (7 items) and Trustworthiness (8 items); Relational capacitiescomprises the facets of Intimacy (7 items), Enduring relationships(7 items), and Feeling recognized (8 items); Social concordancecomprises the facets of Aggression regulation (8 items), Frustra-tion tolerance (8 items), Cooperation (7 items), and Respect (8items). Higher scores suggest better personality functioning. Pre-vious studies in Italian samples (Prunas, Mognetti, Hartmann, &Bini, 2013) reported good reliability results. In our study a valuesvaried between .69 and .89 (AIC between .52 and .72) in theCommunity 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) com-prises 71 items evaluating 21 defenses. Two factors are used todivide these defenses into two styles (mature and immature). Astudy on the Italian version of the instrument (Prunas et al., 2009)confirmed the 2-factor structure and reported good reliability re-sults. In this study only the immature defenses factor (41 items;Community sample: a 5 .87, AIC 5 .15; Clinical sample: a 5 .90,AIC 5 .18) was considered.Borderline Personality Disorder Checklist. The Borderline

Personality Disorder Checklist (BPDCL; Arntz, van den Hoorn,

Table 1Prevalence of Personality Disorders in the Clinical SampleDisorder n %

Paranoid 7 5.8Schizoid 1 .8Schizotypal 3 2.5

Any cluster A 11 9.1Antisocial 12 9.9Borderline 30 24.8Narcissistic 15 12.4Histrionic 12 9.9

Any cluster B 69 57.0Avoidant 9 7.4Dependent 10 8.3Obsessive/Compulsive 9 7.4

Any cluster C 28 23.1Passive/Aggressive 9 7.4Depressive 5 4.1NOS 34 28.1

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Cornelis, Verheul, van den Bosch, & de Bie, 2003) comprises 47items that assess the patient’s burden of complaints about border-line personality disorder symptoms in the previous month accord-ing to Diagnostic and Statistical Manual of Mental Disorders,fourth edition, text revision (DSM–IV–TR) criteria. Results onthe psychometric properties of the Italian version of the instru-ment (Prunas, Sarno, Capizzi, & Madeddu, 2006) report goodreliability values. In our study a values of .97 (AIC 5 .46) and.91 (AIC 5 .28) were obtained, respectively in the Communitysample and in the Clinical sample.Symptom Checklist 90-R. The Symptom Checklist 90-R

(SCL 90-R; Derogatis, 1977) comprises 90 items that assess psy-chological symptoms within nine primary dimensions as well as aGlobal Severity Index (GSI). The Italian version of the instrument(Prunas, Sarno, Preti, Madeddu, & Perugini, 2012) reported goodreliability values. In our study a values of .97 (AIC 5 .27) and .98(AIC 5 .36) for the GSI were obtained, respectively in the Com-munity sample and in the Clinical sample.

Data Analyses

Different factor-structure solutions were examined through aseries of multigroup Confirmatory Factor Analyses (CFA) usingMplus software (Muthén & Muthén, 1998–2010). Multigroupinvariance was considered across the Community sample and theClinical sample and across gender (considering the Communitysample and the Clinical sample together). Because the IPOassesses pathological personality functioning, skewed distribu-

tions may be expected and item responses may not be consid-ered as continuous (Lenzenweger et al., 2001; Ellison & Levy,2012). In such cases, weighted least squares means and varianceadjusted (WLSMV) estimation may be preferred over standardmaximum likelihood estimation (Beauducel & Herzberg, 2006;Brown, 2006; Flora & Curran, 2004; Dolan, 1994; Muthén &Kaplan, 1992). For these reasons, data were considered asordinal and factor analyses were implemented through the poly-choric correlation matrix (Olsson, 1979), using WLSMV esti-mates available in Mplus. Because x2 test is dependent onsample size, fit indexes that correct for sample size were alsoused: the Comparative Fit Index (CFI; Bentler, 1990), theTucker-Lewis fit Index (TLI; Bentler & Bonett, 1980), and theRoot Mean Square Error of Approximation (RMSEA; Steiger,1990). As for interpretation guidelines (Hu & Bentler, 1999),CFI and TLI values between .90 and .95 indicate adequatemodel fit, whereas values of .95 and above suggest excellent fit;RMSEA values between .05 and .08 indicate adequate fit andvalues between .00 and .05 excellent fit. The comparisonsbetween the 1-factor, 2-factor, and 3-factor nested models wereperformed examining the x2 differences (D) between the nestedmodels through the difftest command of Mplus (Asparouhov &Muthén, 2006). This test determines whether a significant dec-rement in fit occurs between the unconstrained and the con-strained models. Nevertheless, as indicated by Cheung andRensvold (2002), particular caution should be applied in usingDx2 tests in nested models. In this case, the authors recom-mended to consider CFI differences # .01 as indicators offactor invariance. Because the 3-factor and the 4-factor com-peting models were non-nested, decisions related to differencesin the goodness of fit were taken in a descriptive way (no formaltests of incremental fit were used; Muthén & Muthén, 1998–2010).Internal consistency was assessed through Cronbach’s alpha,

whereas test–retest reliability was evaluated through intraclasscorrelation coefficients (ICC), Pearson’s r, and paired t tests, usingSPSS software package (version 22).To evaluate the unique contribution of each of the 4 IPO

dimensions in predicting concurrent measures, two-step hierarchi-cal multiple regressions were conducted using SPSS softwarepackage (version 22). In the first step we inserted the clinical status(Community sample vs. Clinical sample), whereas the second stepassessed the independent contribution of the IPO dimensions. Asecond 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

Table 2Fit Indexes of the 4 CFA Models in the Different Subgroups(Clinical, Community; Males, Females)Model Group x2 df n CFI TLI RMSEA

1 factor Clinical 2084.843 1539 103 .870 .865 .054Community 3980.932 1539 680 .894 .890 .048Males 2482.171 1539 278 .915 .912 .046Females 3464.742 1539 504 .892 .888 .049

2 factors Clinical 2052.994 1538 103 .878 .873 .053Community 3812.456 1538 680 .902 .898 .046Males 2436.164 1538 278 .919 .916 .045Females 3287.062 1538 504 .902 .898 .047

3 factors Clinical 2050.260 1536 103 .878 .873 .053Community 3782.478 1536 680 .903 .899 .046Males 2427.078 1536 278 .920 .917 .044Females 3270.097 1536 504 .903 .899 .046

4 factors Clinical 1781.134 1371 103 .901 .897 .050Community 3035.325 1371 680 .924 .921 .042Males 2088.518 1371 278 .933 .930 .042Females 2646.309 1371 504 .927 .924 .042

Table 3Fit Indexes of the CFAs of Nested Multigroup Models (1-, 2-, and 3-Factor Solutions) and of the 4-Factor Multigroup ModelConsidering Clinical Sample and Community SampleModel x2 df n CFI TLI RMSEA Dx2 Ddf p4 factors 4484.506 2900 817 .925 .926 .037 — — —3 factors 5318.856 3240 817 .904 .906 .040 — — —2 factors 5342.716 3245 817 .903 .905 .040 49.530 5 ,.0011 factor 5506.798 3248 817 .896 .898 .041 173.827 3 ,.001

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scores between the Community sample and the Clinical sample,and between BPD and non-BPD participants.

Results

Factor Structure

The goodness of fit of four models was tested in the differentsubgroups (Clinical vs. Non clinical; Males vs. Females). The first(baseline) is the unidimensional model, in which all items load ona single factor. We thus tested the bidimensional model (itemsfrom “Primitive defenses” and “Identity diffusion” are collapsed ina single dimension). The original 3-factor solution was then eval-uated. Finally, the 4-factor model was tested (see Table 2 for all fitindexes in the different subgroups).The 4-factor model reported relatively better fit indexes com-

pared with the other three models. Considering the nested nature ofthe 1-, 2-, and 3-factor solutions, multigroup comparisons wereconducted among these models, both considering gender and clin-ical status. Fit indexes indicate a good fit of the configural invari-ance 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 thedata. The 4-factor model provided the best fit indexes among theset of different models tested. Nevertheless, no comparison withthe other models could be provided through statistical tests, giventhe non-nested nature of such model. We decided to further ex-plore the psychometric characteristics of the 4-factor model forthree main reasons: (a) Fit indexes were consistently better in allsubgroups (Table 2) and in the multigroup CFAs (although nostatistical comparison was possible between the competing indexesand differences were of limited magnitude; see Tables 3 and 4); (b)Considering the two multigroup models (clinical status and gen-der) of the 4-factor solution, the intercorrelations between factorswere high but (also considering standard errors) acceptable (seeTable 5); (c) The different associations with the concurrent mea-sures and the specificity of differences between clinical and nonclinical 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 communityparticipants, estimating a series of gradually more restrictivenested models (Muthén & Muthén, 1998–2010). The first step wasto assess configural invariance (i.e., the same observed variablemust be an indicator of the same latent variable in each group;Horn & McArdle, 1992). Fit indexes indicate a good fit of theinvariance model (see Table 6). The second step tested metric

invariance (i.e., the factor loadings of the observed variables needto be equivalent across groups). Fit indexes (Table 6) were accept-able. The difftest was significant but differences in terms of CFIresulted minimal (CFIdiff 5 .003). The last two steps tested re-spectively the invariance of the covariances between latent factorsand the invariance of the variances of the latent factors. These twomodels 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 (range18–74, SD 5 6 13.58 years). Males (n 5 293) were 38.1%,females (n 5 476) 61.9%. Fit indexes confirm factor invariancealso across gender (see Table 7).1

Internal Consistency

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

Test–Retest Reliability

Fifty-three participants from the Community sample completedthe IPO again after one month. Males (n 5 5) were 9.4% of thesubsample, females (n 5 48) were 90.6%. Mean age was 23.60years (range 21–49, SD 5 6 5.10 years). Table 9 shows descrip-tive statistics of the 4 factors at T1 and T2. Intraclass correlationcoefficients (ICC) are all high and significant. Also, correlationsbetween the dimensions at T1 and T2 are all high and significant.Paired t tests revealed significant changes for the Instability ofself/other and Psychosis dimensions.

Convergent Validity

To evaluate the unique contribution of each of the 4 IPOdimensions in predicting personality functioning measured

1 All models of invariance (clinical status and gender) were confirmedalso for the 1-, 2-, and 3-factor solutions.

Table 4Fit Indexes of the CFAs of Nested Multigroup Models (1-, 2-, and 3-Factor Solutions) and of the4-Factor Multigroup Model Considering GenderModel x2 df n CFI TLI RMSEA Dx2 Ddf p4 factors 4762.822 2900 769 .931 .932 .041 — — —3 factors 5682.372 3240 769 .912 .914 .044 — — —2 factors 5707.982 3245 769 .912 .913 .044 45.150 5 ,.0011 factor 5919.492 3248 769 .904 .906 .046 188.217 3 ,.001

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through SIPP-118, specific BPD symptom severity measuredthrough BPDCL, and immature defenses measured through REM-71, two-step hierarchical multiple regressions were conducted (seeTable 10). In the first step we inserted clinical status, while thesecond step assessed the independent contribution of the four IPOdimensions.Considering the five higher order SIPP-118 factors, we found

significant increments in variance explained by the 4 IPO dimen-sions over and above clinical status, ranging from 33% to 40%(p , .001). The IPO dimension Instability of self/others uniquelycontributes significant portions of variance explained for all the 5SIPP-118 domains. The IPO dimension Instability of goalsuniquely contributes significant portions of variance explained forSIPP-118 Responsibility, with an additional marginal contributionfor SIPP-118 Identity integration. The IPO dimension Instability ofbehavior uniquely contributes significant portions of variance ex-plained for SIPP-118 Responsibility, Social concordance, and Selfcontrol, whereas the IPO dimension Psychosis showed only mar-ginal contributions to the prediction of SIPP-118 Responsibilityand 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 amarginal increment due to Instability of behavior. Finally, consid-ering Immature defenses (REM-71), there was a significant incre-ment due to the IPO (32%, p , .001), with the unique contributionof Instability of self/others, Psychosis, and a marginal incrementdue to Instability of behavior.We thus conducted three-step hierarchical multiple regressions,

inserting the general level of psychopathological distress measuredthrough the GSI of SCL 90-R as a second step (see Table 11).Results were comparable with those obtained through the two-stephierarchical multiple regressions, with the exception of borderlinesymptomatology (BPDCL). In this last measure no unique contri-butions of the IPO dimensions were detected, after controlling forgeneral psychopathological distress.

Criterion Validity

A first ANCOVA revealed significantly higher scores on thefour 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 sig-nificantly higher among BPDs (see Table 13). Controlling forgeneral psychopathology measured through the GSI of SCL-90,results still show a marginally significant effect for Instability ofself/others, F(1,109) 5 3.327, p 5 .07, and a significant effect forInstability of goals, F(1,105) 5 4.486, p , .05.

Discussion

The study aimed at providing further evidence of the structuralmodel of personality pathology by evaluating the psychometricproperties of the Italian version of the Inventory of PersonalityOrganization 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 proposedby Ellison and Levy (2012) showed a relatively best fit to our databoth in a clinical sample and in a community sample. Furthermore,we showed that the four dimensions are invariant across clinicalstatus and gender. This last result is in line with Kernberg’sobject-relations model of personality pathology, according towhich personality structure shows no gender differences (Kern-berg, 1984). Our data showed that also the three competing models(1-, 2-, and 3-factor solutions) yielded acceptable results in termsof fit indexes. Nevertheless, our results regarding the associationswith external measures support the usefulness of a 4-factor solu-tion.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. Cron-bach’s alpha values also confirmed the reliability of these fourdimensions (Nunnally & Bernstein, 1994).Results related to a subgroup of participants from the commu-

nity sample also provided partial support to the stability of the IPOscores over time: One-month test–retest reliability for the 4 IPOdimensions was confirmed by excellent levels of ICCs. A separateexamination of rank-order consistency and mean-level stabilityrevealed mixed results. While rank-order stability was supportedby the correlations between the dimensions at T1 and T2, theInstability of self-other and the Psychosis dimensions revealedsignificant changes over time. Overall, these results are compara-ble 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 theoreticalexpectations that structural personality features are stable, perva-

Table 5Intercorrelations (and Standard Errors) Between Factors in theTwo Multigroup 4-Factor ModelsClinical versus nonclinical Male versus female

Factor 2 3 4 2 3 4

1 .64 (.03) .76 (.02) .81 (.02) .63 (.04) .78 (.03) .86 (.02)2 — .56 (.04) .61 (.03) — .61 (.05) .67 (.05)3 — — .77 (.03) — — .83 (.03)

Note. 1 5 Instability of self/other; 2 5 Instability of goals; 3 5 Psycho-sis; 4 5 Instability of behavior.

Table 6Fit Indexes of the CFAs of Nested Multigroup Models Considering Clinical and Community SamplesInvariance model x2 df n CFI TLI RMSEA Dx2 Ddf pConfigural 4484.506 2900 783 .925 .926 .037 — — —Metric 4457.736 2950 783 .928 .930 .035 86.460 50 .001Covariances 4570.176 2956 783 .923 .926 .037 48.973 6 ,.001Variances 4592.707 2960 783 .922 .925 .037 27.262 4 ,.001

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sive, and enduring over time. Nonetheless, our results related to acertain degree of change at a mean-level for some of the IPOdimensions underline the need for data on the stability of thepersonality dimensions measured through the IPO in larger sam-ples and in clinical participants.One of our main aims was to extend previous findings regarding

factor structure and psychometric properties of the IPO, testingconvergent relations with external measures of personality func-tioning. In this regard, considering the two samples together andcontrolling for clinical status, a coherent pattern of convergentrelations emerged. Particularly, the IPO dimension Instability ofself/other was inversely associated with SIPP-118 measures ofpersonality functioning, and especially with the Identity integra-tion, Relational capacities, Self-control, and Social concordancedomains. Instability of goals was inversely associated with Re-sponsibility. Instability of behavior showed negative associationswith Responsibility, Social concordance, and Self-control. Theadditional unique associations that emerged between Instability ofgoals, Instability of behaviors, and the SIPP-118 domains supportthe idea that these IPO factors can be considered as further facetsof identity assessment. Our results show that, while the IPO factorInstability of self/others shows the stronger associations with Iden-tity integration measured by the SIPP-118, these two additionalfacets measure connected features (as shown by the intercorrela-tions between IPO domains), but present different patterns ofassociations with external measures, less related to internal repre-sentations and more connected to behavioral outcomes of identitydiffusion. Measuring these features can thus lead to a more com-prehensive profile of identity integration, encompassing also be-havioral components and aspects of self-definition connected withlong-term objectives. Consistently, the Psychosis dimension of theIPO was not associated with any personality features measured bythe SIPP-118 (with the exception of marginal contributions tovariance prediction). It could be argued that psychotic featuresshould 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 mea-sured by the IPO factor did not reach a level of severity that couldimpair relational capacities. The marginal positive associationsbetween the SIPP-118 dimensions and the Psychosis dimension ofthe IPO could be attributable to suppressor effect (Horst, 1941;Cohen & Cohen, 1975).Concerning convergent relations with descriptive psychopatho-

logical measures, the Instability of self/others dimension of theIPO was related to a specific measure of BPD symptoms(BPDCL). The association between the core feature of identitydiffusion measured by the IPO and psychopathological distress hasalready been found in previous studies (Lenzenweger et al., 2001;Berghuis et al., 2009). According to Kernberg’s model of person-ality pathology (Kernberg & Caligor, 2005) and also consideringother research results (Depue & Lenzenweger, 2001), personalitydisorders—especially those pertaining to Borderline PersonalityOrganization—are characterized by high levels of anxiety, depres-sion, and related psychological symptoms. The associations withBPD symptoms further demonstrate the specificity of the connec-tions between identity integration and the DSM borderline pathol-ogy model. Surprisingly, we found only weak marginal associa-tions between BPD symptoms and the Instability of behaviorsfactor of the IPO. A closer look at regressions considering the 9BPDCL subscales, however, revealed that, coherently, strongerassociations emerged with symptom dimensions related to BPDfeatures that can cause behavioral problems: Impulsivity (DR2 5

.05, p , .001; Semipartial correlation 5 .11, p , .001) and anger(DR2 5 .12, p , .001; Semipartial correlation 5 .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 associationsbetween the IPO dimensions and descriptive symptoms of BPD nolonger provide additional unique contributions, whereas on theother hand, the IPO dimensions still significantly contribute to the

Table 7Fit Indexes of the CFAs of Nested Multigroup Models Considering GenderInvariance model x2 df n CFI TLI RMSEA Dx2 Ddf pConfigural 4762.822 2900 734 .931 .932 .041 — — —Metric 4680.548 2950 734 .936 .938 .039 76.250 50 .01Covariances 4625.979 2956 734 .938 .940 .038 6.148 6 ,.001Variances 4612.948 2960 734 .939 .941 .038 10.544 4 ,.05

Table 8Cronbach’s a and Corrected Item-Total Correlations of the 4 IPO Dimensions in theCommunity Sample and in the Clinical Sample

Factor (n items)Corrected item–total correlation

a Community Clinical

Community Clinical M Range M Range

Instability of self/others (32) .91 .93 .48 .30–.63 .52 .24–.72Instability of goals (2) .72 .81 .57 .57–.57 .68 .68–.68Psychosis (12) .79 .84 .45 .27–.54 .52 .18–.71Instability of behavior (8) .81 .80 .52 .37–.65 .51 .40–.63

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increments in variance explained related to personality functioningmeasures. Finally, an external measure of primitive defensivefunctioning (REM-71) was associated with Instability of self/otherand with Psychosis. Such results can be explained considering thatthe more intrapsychic/representational facet of identity, related tothe lack of a stable, flexible, and realistic inner experience of selfand others, is coherently associated with the adoption of a primi-tive defensive style. Again, considering the absence of actualpsychotic features in our samples, the association between primi-tive defenses measured by the REM-71 and the Psychosis factor ofthe IPO could be explained by the effects of a primitive defensivestyle 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 psychopatho-logical domains, particularly as regards the realm of BPD. Resultson criterion validity showed that the 4 factors of the IPO can beused to assess the presence of general personality pathology. Morespecifically, only Instability of self/others and Instability of goalsdiscriminate between BPD and non-BPD patients. These resultsdemonstrate that the core pathological feature of the structuralmodel of personality pathology—that is, identity diffusion—istightly tied to DSM BPD diagnosis.Taken together, our results therefore, although at a factor ana-

lytic level confirming also the goodness of fit of the originaltheoretical tri-dimensional structure of the IPO, underline theclinical usefulness of considering different facets of identity. Asstated by Ellison and Levy (2012), the 4-factor dimensionalitysupported by our results is nevertheless in line with essential

features of the structural model of personality. We thus proposethat 3 IPO factors (i.e., Instability of self/other, Instability of goals,and Instability of behaviors) can be considered as measures ofdifferent facets of identity. Each of these three facets is coherentboth with Kernberg’s model of personality structure and with theDSM–5 proposed dimensional model of personality pathology.Instability of self/other and Instability of goals can be consideredas indicators of identity diffusion. In Kernberg’s model identitydiffusion arises both in the difficulty in holding a stable andintegrated image of self and significant others and in the difficultyin investing in stable, strong and long term goals (in terms of workor study). Further evidence for the centrality of these two factorsin personality structure pathology derives from the convergentassociations described above. In addition, these are the sole twofactors that proved to discriminate between BPD and non-BPDindividuals.The third facet, Instability of behavior, does not have direct

correspondences with the original theoretical model. We proposethat this dimension measures the impulsive and instable/incoherentbehavioral outcomes that stem from the defensive and identityconfiguration of patients with Borderline Personality Organization.Caution should be taken in considering this factor as a separatefacet, because of the high intercorrelations with the other IPOdomains (see Table 5). Nevertheless, results related to the associ-ations with the external indexes support the idea that measuringthis third identity facet can add a descriptive dimension to thepersonality structure profile.

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

T1 T2

M M t(52) r ICC

Instability of self/others 2.35 (.58) 2.28 (.61) 2.220p .92ppp .96ppp

Instability of goals 2.23 (.85) 2.08 (.76) 1.577 .68ppp .80ppp

Psychosis 1.71 (.56) 1.53 (.48) 3.851ppp .79ppp .88ppp

Instability of behavior 1.71 (.64) 1.66 (.62) 1.006 .83ppp .90ppp

p p , .05. ppp p , .001.

Table 10Multiple Hierarchic Regressions (Controlling for Clinical Status)External measures

Step 1 Step 2 Semipartial correlations

R2 (clinical status) DR2 (IPO) 1 2 3 4

BPDCL .16ppp .18ppp .19ppp .03 .02 .09p

REM .08ppp .32ppp .20ppp .02 .18ppp .07p

SIPP-118Self control .25ppp .40ppp 2.29ppp 2.05 2.05 2.16ppp

Social concordance .06ppp .34ppp 2.23ppp 2.02 2.01 2.18ppp

Identity integration .25ppp .40ppp 2.39ppp 2.09pp .06p 2.02Relational capacities .10ppp .30ppp 2.31ppp .01 2.01 2.07Responsibility .29ppp .33ppp 2.13ppp 2.16ppp .08pp 2.24ppp

Note. 1 5 Instability of self/other; 2 5 Instability of goals; 3 5 Psychosis; 4 5 Instability of behavior; GSI 5Global Severity Index of SCL-90-R; REM 5 Immature defenses factor of REM-71; BPDCL 5 BorderlinePersonality Disorder Checklist total score.p p , .05. pp p , .01. ppp p , .001.

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This multifacets conceptualization of identity assessment is alsocoherent with DSM–5 Levels of personality functioning evaluation.In fact, in assessing the level of functioning in relation to Self theDSM–5 proposes to evaluate both the level of impairment in thesense of continuity of and uniqueness of self and in the capacity toset reasonable goals based on a realistic assessment of one’s owncapacities. On the other hand, DSM–5 encourages the assessmentof interpersonal personality functioning. In line with this indica-tion, the first factor of the IPO measures the stability and coher-ence of the idea that the individual has of other people. In line withMorey and colleagues (2011), the Instability of self/others factor(the core of identity diffusion) seem to capture a global dimensionof personality pathology that considers dysfunctions in self andinterpersonal relatedness as a core dimension of severity of per-sonality 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 psychoticsymptoms. Other reality-testing impairments more connected withBorderline Personality Organization—such as “social reality-test-ing”—load on the Instability of self/other dimension. Reality-testing has thus two faces. On the one hand psychotic-like symp-toms mark the border of Psychotic Personality Organization. Onthe other hand, the misinterpretation of social cues impairs theindividual’s capacity to hold a realistic consideration of self andothers. 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 toinvest coherently and constantly in study and work and to form acoherent and stable self and other image—the capacity to accu-rately perceive and interpret social events.The 4-factor model of the IPO does not encompass the

presence of a separate assessment of primitive defensive func-tioning. Our results suggest, as recognized by Ellison and Levy(2012) and by Lenzenweger, Clarkin, et al. (2012), that identityfunctioning is—in all its facets—intertwined with the individ-ual defensive array. This is also reflected in the high intercor-relations found between these two different facets both in ourstudy and in previous reports (Lenzenweger et al., 2001; Sternet al., 2010; Ellison & Levy, 2012). In this sense defensiveoperations that reflect a lack of integration of one’s and othersimage are measured by the Instability of self/others domain,whereas the behavioral outcomes of defenses that lead to im-pulsivity or erratic behavior are captured by the Instability ofbehavior dimension.The study presented has some methodological limitations. A

large number of participants in the clinical sample (34.7%) had acomorbid substance-related disorder. Caution should thus be takenin generalizing our results to patients with personality disorderswithout comorbid substance-related conditions. This limitation,nevertheless, makes our sample more ecologically sound, becausecomorbidity between personality disorders and substance-relateddisorders seems to represent the rule more than the exception(Trull, Jahng, Tomko, Wood, & Sher, 2010). Convergent validity

Table 11Multiple Hierarchic Regressions (Controlling for Clinical Status and General Psychopathology)External measures

Step 1 Step 2 Step 3 Semipartial correlations

R2 (clinical status) DR2 (GSI) DR2 (IPO) 1 2 3 4

BPDCL .16ppp .25ppp .03ppp .09 .02 .00 .08REM .08ppp .31ppp .09ppp .11pp .00 .23ppp .06SIPP-118Self control .25ppp .20ppp .21ppp 2.37ppp 2.08 .09p 2.25ppp

Social concordance .06ppp .16ppp .18ppp 2.23ppp 2.02 2.00 2.22ppp

Identity integration .25ppp .30ppp .15ppp 2.46ppp 2.14pp .13p 2.01Relational capacities .10ppp .19ppp .13ppp 2.30ppp .02 2.01 2.08Responsibility .29ppp .12ppp .21ppp 2.17ppp 2.25ppp .13p 2.23ppp

Note. 1 5 Instability of self/other; 2 5 Instability of goals; 3 5 Psychosis; 4 5 Instability of behavior; GSI 5 Global Severity Index of SCL-90-R;REM 5 Immature defenses factor of REM-71; BPDCL 5 Borderline Personality Disorder Checklist total score.p p , .05. pp p , .01. ppp p , .001.

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

Factor

S1n 5 696M 6 SDS2n 5 121M 6 SD F1,816a

Gender and age correction

S1n 5 696M; SES2n 5 121M; SE F1,767a

Instability of self/other 2.07 6 .50 2.546 .71 76.643 2.08; .02 2.55; .05 79.553Instability of goals 2.03 6 .83 2.456 1.06 24.149 2.03; .03 2.45; .08 22.810Psychosis 1.52 6 .42 1.716 .65 17.627 1.52; .02 1.71; .04 16.892Instability of behavior 1.51 6 .49 2.156 .76 144.792 1.52; .02 2.16; .05 142.000

a For all Fs, p , .001.

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has been assessed only through self-report instruments. Thesecould have caused social desirability problems. More specifically,previous research acknowledged methodological challenges instudying automatic, unconscious processes by self-report instru-ments (Prunas et al., 2009; Cramer, 1998). Also, mean interitemcorrelations (AIC) of some of the self-report measures (i.e., REM71 and SCL 90-R) indicate a degree of heterogeneity in themeasures. Finally, as reported by Ellison and Levy (2012), prob-lems may arise by the fact that the Instability of goals factor ismeasured by only 2 items. Future research should try to add newitems to this dimension. Also, the high intercorrelations betweenthe Instability of behavior and Instability of self/others factorsshould be addressed adding/modifying items to better differentiatethe two factors.In conclusion, our results support the idea that identity can be

considered as a multifaceted construct. The facets measured by theIPO are all consistent with Kernberg’s personality structure model.Furthermore, identity assessment conducted through the IPO is inline with the current directions for dimensional assessment ofpersonality functioning suggested by the DSM–5. In terms ofclinical usefulness, personality pathology assessment through theIPO can provide significant information related to different facetsof the patient’s functioning. Identity diffusion assessment (Insta-bility of sense of self/others; Instability of goals) is a crucial aspectof an object relations-oriented approach to personality pathology,and the recognition of this core component of Borderline Person-ality Organization—together with the evaluation of a relativelypreserved reality-testing (Psychosis) can lead the clinician to atailored treatment indication (i.e., Transference-Focused Psycho-therapy, Clarkin, Yeomans, & Kernberg, 2006). Furthermore, thesame core components of identity diffusion can provide usefulclinical information related to the DSM–5 Levels of PersonalityFunctioning. Finally, the additional facet related to Instability ofbehavior can provide relevant information related to the impact ofidentity diffusion in the patient’s functioning.

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

Factor

BPDn 5 30M 6 SDNo BPDn 5 88M 6 SD F1,816a

Gender and age correction

BPDn 5 30M; SENo BPDn 5 88M; SE F1,767a

Instability of self/other 2.916 .56 2.42 6 .72 11.548ppp 2.87; .13 2.45; .07 8.464pp

Instability of goals 2.976 1.09 2.28 6 1.00 9.604pp 2.99; .19 2.28; .11 9.784pp

Psychosis 1.896 .64 1.64 6 .63 3.490 1.88; .12 1.65; .07 2.609 (NS)Instability of behavior 2.416 .54 2.07 6 .81 4.497p 2.38; .14 2.09; .08 3.058 (NS)

p p , .05. pp p , .01. ppp p , .001.a For all Fs, p , .001.

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