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JOURNAL OF PERSONALITY ASSESSMENT, 89(1), 56–69Copyright C© 2007, Lawrence Erlbaum Associates, Inc.

Contributions to the Dimensional Assessment ofPersonality Disorders Using Millon’s Model and the

Millon Clinical Multiaxial Inventory (MCMI–III)

Stephen StrackU.S. Department of Veterans Affairs

Ambulatory Care Center, Los Angeles, California

Theodore MillonInstitute for Advanced Studies in Personology and Psychopathology

Coral Gables, Florida

For over 35 years, Mllion’s (1996) model of personality and the Millon Clinical MultiaxialInventory (Millon, 1977, 1987, 2006) have been useful resources for clinicians to understandand assess personality disorders (PDs) and clinical syndromes in psychiatric patients. In thisarticle, we highlight significant features of the model and test that have proved valuable topersonologists in their quest for a more satisfactory taxonomy of PDs based on continuouslydistributed traits. We also describe Millon’s (1996) prototypal domain approach to personalitythat combines dimensional and categorical elements for the description of PDs and their normalcounterparts.

Now in its third edition, the Millon Clinical MultiaxialInventory (MCMI–III; Millon, 1997a, 2006) was createdto assist clinicians in understanding the psychiatric prob-lems of greatest concern to their patients and to contex-tualize the patients’ presentation features within a person-ality framework. A guiding assumption of the inventoryis that everyone has a personality that influences the kindand severity of problems experienced, symptom expres-sion, and the types of treatments that are most likely to beeffective.

The test is a 175-item, true–false, self-report questionnairethat measures 14 personality disorders (PDs) and 10 clinicalsyndromes (CSs) via ordinal scales that quantify how muchand how well respondents match or fit the constructs beingassessed. With regard to the PD scales, items are dividedinto two groups: one representing core features of the per-sonality that are unique to that disorder and one representingfeatures more peripheral and likely to be shared with oneor more similar PDs. For scoring purposes, core items (alsocalled prototype items) are weighted 2, whereas peripheral,overlapping items are weighted 1. Therefore, the highest rawscores for each PD scale are obtained by respondents whoacknowledge more of the attitudes, thoughts, feelings, andbehaviors that are central to the definition of that personality.

In line with the Diagnostic and Statistical Manual ofMental Disorders (4th ed. [DSM-IV]; American PsychiatricAssociation, 1994; 4th ed., text revision; American Psychi-atric Association, 2000), MCMI–III Axis II PDs are assessedseparately from Axis I CSs. To assist in diagnosing patientsaccording to the DSM–IV, PD scale items cover majordiagnostic criteria, and normative data were obtained frompsychiatric patients with known DSM–IV diagnoses (Millon,1997a, 2006). By estimating the prevalence of each disorderwithin the test’s normative sample, scale scores weretransformed into base rate (BR) scores that help in catego-rizing patients according to DSM–IV criteria. For example,knowing that patients in the normative sample who werediagnosed as having a schizoid PD had raw scores on theMCMI–III Schizoid scale above a particular point allowedMillon (2006) to establish a BR cutoff score that would alertthe test user to a patient who was likely to meet DSM–IVcriteria for a schizoid PD.

The MCMI–III is one of a family of assessment in-struments (Millon, 1997b; Strack, 2002) that operational-ize Millon’s (e.g., 1969/1983b, 1990, 1996, 2005; Mil-lon & Grossman, 2006) evolutionary model of personalityand psychopathology. Developed over a period of nearly40 years, the model represents an attempt to create a

DIMENSIONAL ASSESSMENT OF PDS USING MILLON’S MODEL 57

mature clinical science of personology that embodies five keyelements:

1. Universal scientific principles—Science grounded in theubiquitous laws of nature.

2. Subject-oriented theories—Explanatory and heuristicconceptual schemas of nature’s expression in what wecall personology and psychopathology.

3. A taxonomy of personality patterns and clinicalsyndromes—A classification and nosology derived log-ically from a coordinated personality/psychopathologytheory.

4. Integrated clinical and personality assessmentinstruments—Tools that are empirically groundedand quantitatively sensitive.

5. Synergistic therapeutic interventions—Coordinatedstrategies and modalities of treatment.

According to Millon (2005; Millon & Grossman, 2006), itis the coordination of these elements so that they are recipro-cally enhancing and mutually reinforcing that constitutes theessence of a mature clinical science. Just as each person is anintrinsic unity, each component of a clinical science shouldnot remain a separate element of unconnected parts. Rather,each facet of clinical work—its principles, theories, taxon-omy, instrumentation, and therapy—should be integrated intoa gestalt, a coupled and synergistic unity in which the wholewill be coordinated and become more informative and usefulthan its individual parts.

Contained within the model are Millon’s (e.g., 1996, 2005,2006; Millon & Grossman, 2006) specifications for a per-sonality taxonomy (see Figure 1). Millon (1996) believedthat it is best for the DSM to employ diagnostic targetsthat represent complex personality prototypes (e.g., schizoid,avoidant, dependent) as opposed to dimensional traits such asdominance–submissiveness or sociability, which he viewedas subcomponents of the prototypes.1 Millon (1996) also be-lieved that the fundamental building blocks of the prototypesare continuously distributed domain traits (see following),and so personality prototypes can be assessed quantitativelyas well as categorically. For Millon, a personality prototypeis a superordinate category that subsumes and integrates psy-

1The word prototype is commonly used in the English language to meanthe model on which something is based or formed. Applied to personal-ity science, the term refers to the most common features or properties ofmembers of a category, in this case a personality type, style, or disorder. Apersonality prototype is a theoretical ideal or standard against which realpeople can be evaluated. All of the prototype’s properties are assumed tocharacterize at least some members of the category, but no one property isnecessary or sufficient for membership in the category. It is possible thatno actual person would match the theoretical prototype perfectly. Differentpeople approximate it to different degrees, and the closer a person comes tomatching all the definitional criteria, the more closely that person typifiesthe concept (Rosch, 1978). Millon’s (1996, 2006) taxonomy describes per-sonality in terms of prototypes, but for stylistic purposes, we use the termstype, style, disorder, and prototype interchangeably in this report.

TABLE 1Functional and Structural Domains of

Personality and Their Optimal Data Source

Domain and Date Sources

Functional Structural

BehavioralExpressive actsInterpersonal conduct

PhenomenologicalCognitive style Object representations

Self-imageIntrapsychic

Regulatory mechanisms Morphologic organizationBiophysical

Mood/temperament

Note. From Disorders of Personality: DSM–IV and Beyond (p. 138) by T.Millon (with R. D. Davis), 1996, New York: Wiley. Copyright 1996 by JohnWiley & Sons, Inc. Adapted with permission. Although the domains arebest measured using the data sources indicated in the table, they can beassessed with some accuracy using traditional questionnaire and interviewmethods.

chologically covariant traits that, in turn, represent a set ofcorrelated habits that, in their turn, stand for a response dis-played in a variety of situations (Millon & Grossman, 2006).In this way, categories and dimensions may be coordinatedand are not mutually exclusive.

Millon (1996) argued that personality prototypes can bedescribed and differentiated by a set of functional (expressivebehaviors, interpersonal conduct, cognitive style, intrapsy-chic regulatory mechanisms) and structural domain attributes(self-image, object representations, morphologic organiza-tion, mood temperament) that can be optimally assessed us-ing one of four data sources (behavioral, phenomenological,intrapsychic, biophysical). These components, which can bemeasured quantitatively, are more useful clinically than athe-oretically derived factor traits such as openness (see Figures 2and 3 and Table 1).

Functional domain attributes represent dynamic processesthat occur in the intrapsychic world between the self and psy-chosocial environment. They represent expressive modes ofregulatory action that manage, adjust, transform, coordinate,balance, and otherwise control the give and take of inner andouter life. By contrast, structural attributes represent deeplyembedded, relatively enduring templates of imprinted mem-ories, attitudes, needs, fears, and conflicts that guide experi-ence and transform the nature of people’s ongoing life events.Structural attributes may be conceived as substrates and ac-tion dispositions of a quasi-permanent nature that have anorienting and preemptive effect to alter the character of ac-tion and the impact of subsequent experiences in line withthe preformed inclinations and expectancies (Millon, 1996).The rationale for creating the domain traits was that theyhad to encompass a full range of clinically relevant char-acteristics (e.g., not just behaviors or cognitions), providetrue distinction among the various prototypes, parallel or

58 STRACK AND MILLON

FIGURE 1. Personality Circulargram I: Normal and abnormal personality patterns. Evolutionary foundations of the normal and abnormal extremesof each personality prototype of the 15 spectra. I: Existential orientation; II: Normal prototype; III: Abnormal prototype; IV: Adaptation style; V:MCMI–III scale number/letter. Copyright 2006 by Theodore Millon.

correspond to major therapeutic modalities (e.g., intrapsy-chic), and allow for coordination between and among thestructural and functional attributes and four levels of data(Millon, 1996).

Millon (1969/1983b, 1996) has also specified that thesame personality prototypes can be used to describe nor-mality and abnormality. Millon has suggested (1969/1983b,1996) normal and abnormal traits lie along a continuum withno sharp dividing line between the two. Normal and abnormalpersonality prototypes share similar domain traits, behaviors,and background characteristics. Thus, the normally shy per-sonality (see Figures 1 through 3) shares much in commonwith the pathological avoidant prototype. The major differ-ence is that the shy person maintains a relatively healthy,flexible adaptation to the environment, whereas the avoidantperson lacks the ability to adapt effectively due to rigid and

inflexible traits. As such, a diagnostic manual containingMillon’s (1996) prototypes could be used to assess normalas well as disordered personality.2

Furthermore, the model divides personality prototypesinto basic and severe categories according to whether a proto-type can be found in both normal and disordered form (basic)or only in disordered form (severe). Millon’s (1969/1983b,1996) group of basic personalities can be found in normaladults as healthy, adaptive styles or in patients as disor-ders. The severe personalities—schizotypal, borderline, andparanoid—are viewed as distortions or exaggerations of basic

2Should the American Psychiatric Association adopt a diagnostic systemthat included normal personality, the MCMI would have to be revised tomeasure a broader range of normal traits. Current MCMI–III PD scalesassess mostly abnormal features.


FIGURE 2. Personality Circulargram IIA: Functional personologic domains. I: Expressive behavior; II: Interpersonal conduct; III: Cognitivestyle/content; IV: Intrapsychic mechanisms; V: MCMI–III scale. Copyright 2006 by Theodore Millon.

personality types and do not have a normal counterpart. Thelogic for differentiating basic and severe personality typescomes from the idea that normal personality has evolvedover many years to help people survive and adapt, whereasabnormal personality arises from things that go wrong. Thereis no evolutionary basis for the survival of traits that causesevere dysfunction, so there is no evolutionary basis for thesevere personalities.

Finally, the personality prototypes can be usefully com-bined to describe subtypes (e.g., schizoid narcissistic,avoidant negativistic, compulsive dependent). Most peoplemanifest trait characteristics that typify different prototypesin varying degrees.3 By measuring the domains compris-

3The concept of personality subtypes does not negate the validity orimportance of personality prototypes any more than color blends negate thereality of the primary colors from which they are derived.

ing the several prototypes quantitatively, an overall person-ality profile can be generated for each person that showswhich trait characteristics are most dominant or salient. Inthis model, the basic personality prototypes (e.g., avoidant,histrionic) are believed to emanate from universal evolution-ary processes and are based on semistructured, relativelyunchanging characteristics; whereas the subtypes tend to beless fixed, more changeable, and subject to transient environ-mental influences (Davis & Patterson, 2005; Grossman & delRio, 2005; Millon, 1996; Millon & Grossman, 2006).

The MCMI–III PD scales operationalize the standard pro-totypes of the model directly and quantifiably. Scale scoresare continuous yet enable categorical diagnoses with the useof BRs anchored to the normative sample of DSM-assessedpatients. The use of patient norms limits the appropriatenessof the scales for assessing normal-range trait characteristics,but respondents can be differentiated as likely to be normal


FIGURE 3. Personality Circulargram IIB: Structural personologic domains. I: Self-image; II: Intrapsychic content; III: Intrapsychic structure; IV:Mood-affect; V: MCMI–III scale. Copyright 2006 by Theodore Millon.

or disordered based on PD scale elevations below and abovethe clinically significant cutoff of BR = 75. Importantly,a profile of each respondent can be generated to ascertainsubtype characteristics, allowing for a rich and complex per-sonality description that has a high probability of matchingclinical impressions, especially those based on interpersonaland expressive behaviors (Choca, 2004; Craig, 1999, 2002).

MCMI RESEARCH

Since the introduction of the MCMI in 1977, it has becomeone of the most frequently used assessment instruments forthe examination of PDs and CSs. Only the Rorschach (Exner,2003) and the Minnesota Multiphasic Personality Inventory–2 (MMPI–2; Butcher, Dahlstrom, Graham, Tellegen, &Kaemmer, 1989) have produced more research during thepast 15 years. There are now over 500 empirical studies based

on this measure as well as seven MCMI-related books (Craig,2002, 2005). A full examination of the literature is beyondour scope, but recent reviews are available to the reader (e.g.,Choca, 2004; Craig, 1999, 2005; Retzlaff & Dunn, 2003).For our purposes, it is useful to see whether the MCMI PDscales (a) have been shown to be reliable; (b) yield continuousdistributions in patient samples; (c) exhibit concurrent, con-vergent, and discriminant validity against other PD measuresand DSM criteria; (d) yield profile subgroups akin to thoseproposed by Millon (Davis & Patterson, 2005; Grossman &del Rio, 2005; Millon, 1996; Millon & Grossman, 2006); and(e) show evidence of continuity in normal populations.

Reliability

The internal consistency of test scales refers to how well theitems measure the same construct (Nunnally, 1978). High


internal consistency (e.g., coefficient α ≥ .80) is expected formeasures of stable personality characteristics to reflect thecohesiveness of the underlying traits. Lower levels of internalconsistency (e.g., coefficient α ≥ .70) are acceptable for re-search instruments and measures of less stable traits in abnor-mal populations. MCMI PD scales have historically exhibitedgood levels of internal consistency, although two MCMI–IIImeasures (Compulsive and Narcissistic) exhibited less thandesirable values (coefficient α = .66 and .67, respectively).As a group, estimates for the scales have ranged from .73 to.95 for the MCMI–I ( Mdn = .82; Millon, 1983a, p. 47); .86 to.93 for the MCMI–II (Millon, 1987, p. 129; Mdn = .90); and.66 to .89 for the MCMI–III (Mdn = .84; Millon, 2006, p. 58).The lowest internal consistency estimates for the MCMI–IIIcame from two scales that assess a number of normal, healthyattributes that are infrequently found in samples of psychi-atric patients (Choca, 2004). The low endorsement frequencyof items assessing normal, healthy characteristics in psychi-atric samples is not unexpected because most patients do notadvertise their positive features when seeking help.

Test–retest reliability indicates how stable test scores areover time (Nunnally, 1978). Personality scales are expected tobe reliable over long periods of time among adult respondentsowing to the pervasive and ingrained nature of the underlyingtraits, attitudes, and behaviors. A variety of studies that haveused different patient populations and test–retest intervalsranging from 5 days to 3 years have shown good stability forMCMI–II and MCMI–III PD scale scores. For the MCMI–I, most studies have reported a test–retest interval of about3 months and yielded a median reliability coefficient for allscales of r = .71, with a range of .19 (Passive–Aggressive) to.91 (Histrionic). For the MCMI–II, retest intervals between21 days and 4 months (average was 2–3 months) yielded amedian stability value of r = .73 for all scales, with a rangeof .62 (Borderline) to .78 (Compulsive). For the MCMI–III,retest intervals between 5 days and 4 months have provideda median value across PD scales of r = .78, with a range of.58 (Depressive) to .93 (Depressive, Antisocial, Borderline;Craig, 1999).

Scale Score Distributions

The continuous distribution of a test score is expected whenthe characteristic being measured is believed to be continu-ously distributed in the target population (Nunnally, 1978).According to Millon’s (e.g., 1996) model of personality, thetraits underlying PD prototypes and the prototypes them-selves should demonstrate continuity in psychiatric samples.The PD scales of all versions of the MCMI have been shownto have a continuous underlying distribution (Choca, 2004).Owing to the pathological nature of most MCMI test items,the score distributions are not normal; rather, they typicallyshow significant positive skew in which most respondentshave low rates of scale item endorsement with progressivelyfewer people showing high endorsement rates. Distributions

FIGURE 4. Distribution of MCMI–III weighted raw scores for theleast skewed (top) and most skewed (bottom) personality disorderscales in a sample of 2,366 psychiatric patients.

that approach normality are sometimes found in the MCMIscales measuring more normal characteristics (Histrionic,Narcissistic, Compulsive). For example, in a sample of 2,366psychiatric patients (see Haddy, Strack, & Choca, 2005, fordetails), skewness of the MCMI–III weighted raw score PDscales ranged from –.17 to .74, with a median of .25. TheHistrionic, Narcissistic, and Compulsive scales exhibited themost (nearly) normal distributions, with skewness coeffi-cients of –.15, .08, and –.17, respectively. Distributions forthe least skewed (Narcissistic) and most skewed (Schizoty-pal) PD scales are given in Figure 4.

Validity

MCMI PDs scales have fared well as a group in termsof concurrent, convergent, and discriminant validity when


measured against other self-report measures of PDs (Choca,2004; Craig, 1999; Retzlaff & Dunn, 2003; Rossi, Vanden Brande, An, Sloore, & Hauben, 2003). Rossi,Van denBrande, et al. (2003) noted consistent improvements in va-lidity with each new version of the test and found the bestconcurrent validity between MCMI–III PD scales and theMMPI–2 PD scales developed by Somwaru and Ben-Porath(1995). In Rossi,Van den Brande, et al.’s (2003) sample of477 patients and prisoners who completed a Dutch-languageversion of the MCMI–III, they found that the same PD scalesacross measures correlated between .56 (Narcissistic) and .75(Borderline), with the exception of the MCMI–III Compul-sive scale, which did not correlate positively with any of theSomwaru and Ben-Porath (1995) or Colligan, Morey, andOfford (1994) and Morey, Blashfield, Webb, and Jewell(1988) MMPI–2 PD scales. Rossi,Van den Brande, et al.’s(2003) survey of the literature pointed to a pattern of poorconcurrent, convergent, and discriminant validity for thisscale across all versions of the MCMI, which suggests thatMillon’s conceptualization of this disorder is different fromthat of other test developers (see also Choca, 2004, and Craig,1999).

The MCMI-I (Millon, 1977, 1983a) was the first mul-tidimensional measure to operationalize Meehl and Rosen’s(1955) idea of BRs to assist in clinical diagnosis. All versionsof the inventory provide transformations of raw scale scoresinto BR scores to reflect the distributions of various diagnosesin the normative samples. BR scores increase as a function ofthe probability that the respondent will meet DSM diagnosticcriteria for a particular disorder. A cutoff score of ≥75 is as-signed when scale score elevations reach a level where diag-nosis is probable, and a cutoff score of ≥85 is assigned whenthe disorder is likely to be the most prominent presentingproblem of the respondent. BR cutoff scores allow for cate-gorical diagnosis as well as the calculation of statistics to es-timate how accurate the scales are in identifying “true” cases.

All three versions of the MCMI have been shown to beuseful in making DSM diagnoses of PDs in clinical sam-ples, although results vary by scale (Choca, 2004; Millon,1997a, 2006). As a rule, no self-report measure—includingthe MCMI—should be used by itself for making clinical di-agnoses (Millon, 1996, 1997a, 2006; Rossi, Hauben, Van denBrande, & Sloore, 2003). Nevertheless, research has shownthat the MCMI is more diagnostically accurate than clinicalinterviews and more accurate than similar self-report mea-sures of personality (e.g., the MMPI–2; Retzlaff & Dunn,2003) but not more accurate than structured interviews con-ducted by experienced clinicians (Choca, 2004; Craig, 1999,2005).4

4Although the MCMI–III and other assessment instruments can be sum-marized as being accurate or inaccurate for making particular diagnoseswithin particular parameters, the research literature is still far from com-plete in terms of assaying all of the variables that affect clinical diagnosissuch as state–trait effects, comorbidity, and neurological factors. As such,

There are several widely used estimates of the diagnosticprecision of test scales (Gibertini, Brandenburg, & Retzlaff,1986; Hsu, 2002). Among them are the following. Sensi-tivity is defined as the percentage of patients identified byclinicians as having a particular diagnosis who were thenidentified by the scale as having the same disorder. Posi-tive predictive power is defined as the percentage of patientsidentified as having a particular disorder by the scale whowere also judged by clinicians as having the same disorder.Conversely, negative predictive power is defined as the per-centage of patients identified by a test scale as not havinga particular disorder who were judged by clinicians as alsonot having the disorder. Each of these estimates provide dif-ferent perspectives on a test scale’s accuracy in making (ornot making) a diagnosis. However, they do not fully accountfor the relationship between test accuracy and the prevalence(BR) rate of various disorders. When the prevalence of adisorder is high, say 50%, then a test scale would need to ac-curately diagnose that disorder significantly more than 50%of the time to be useful because without the test, a cliniciancould accurately make the same diagnosis 50% of the timejust based on chance. Alternatively, when the BR of a dis-order is quite low, say 5%, a test scale may make a usefulcontribution if it correctly diagnoses that disorder 25% ofthe time because this would signal an increased accuracy of20% above chance. Incremental validity of a positive test di-agnosis is an estimate of a scale’s accuracy beyond chanceand is calculated by subtracting the BR of a disorder fromthe scale’s positive predictive power (Hsu, 2002).5

Table 2 provides a summary of the diagnostic efficiencyof MCMI–III PD scales. Data were collected from a sample322 psychiatric patients and 67 experienced clinicians (fordetails, see Millon, 1997a, pp. 88–100). The clinicians wereasked to select patients from their case load whom they hadseen at least three times (mode = 7) and then to complete arating scale giving their estimate of the patient’s three mostprominent PD traits. Clinicians were asked to make their rat-ings blind with respect to the patient’s MCMI–III results, butthe data collection method did not strictly control for this. Asa result, some bias is likely to have accrued such that the accu-racy estimates are probably inflated (Hsu, 2002). In Table 2,the prevalence rate refers to the percentage of study patientsjudged as having the particular PD as their primary Axis II di-agnosis, whereas the various statistics were computed based

readers are cautioned not to overgeneralize the empirical findings presentedhere and elsewhere regarding the MCMI–III’s diagnostic accuracy.

5Specificity is also frequently used as an estimate of a measure’s diagnos-tic accuracy. This is defined as the number of patients who are determinedby clinicians as not having a particular disorder who are also shown not tohave the disorder by the measure. Research on the MCMI–I demonstratedthat the PD scales have high specificity (range = .85–.95; Gibertini et al.,1986), and this was confirmed for the MCMI–III (M for all scales = .97;Hsu, 2002). Specificity is similar to negative predictive power, which wepresent in Table 2.


TABLE 2Diagnostic Efficiency Estimates for MCMI–III

Personality Disorder Scales

IncrementalValidity of

Positive Negative a PositivePredictive Predictive Test

Scale/ Prevalence Sensitivity Power Power DiagnosisPersonality (%) (%) (%) (%) (%)

1. Schizoid 6 56 67 97 612A. Avoidant 11 65 73 96 622B. Depressive 12 57 49 94 37

3. Dependent 13 54 81 94 684. Histrionic 7 74 63 98 565. Narcissistic 7 59 72 97 65

6A. Antisocial 6 61 50 98 446B. Aggressive 2 71 71 99 69

7. Compulsive 9 73 79 97 708A. Passive–

Aggressive 5 44 39 97 348B. Self-Defeating 4 58 30 98 26S. Schizotypal 3 82 60 99 57C. Borderline 12 60 71 94 59P. Paranoid 4 92 79 100 75

Note. Patient N = 322; clinician N = 67. Prevalence, sensitivity, and posi-tive predictive power data are from Millon Clinical Multiaxial Inventory–III(MCMI–III) manual (3rd ed., pp. 97–99), By T. Millon, 2006, Minneapo-lis, MN: Pearson Assessments. Copyright 2006 by DICANDRIEN, Inc. Allrights reserved. Reprinted with permission. Estimates of negative predictivepower and incremental validity of a positive test diagnosis are data from“Diagnostic validity statistics and the MCMI–III,” by L. M. Hsu, 2002,Psychological Assessment, 14, p. 417. Copyright 2002 by American Psy-chological Association.

on the patients’ highest MCMI–III PD scale elevation. As canbe seen in the table, sensitivity ranged from 44% (Passive–Aggressive) to 92% (Paranoid), positive predictive powerranged from 30% (Self-Defeating) to 81% (Dependent), neg-ative predictive power was uniformly high at 94% to 100%,whereas the incremental validity of a positive test diagno-sis ranged from a low of 26% (Self-Defeating) to a high of75% (Paranoid), with a median of 60%. The scales with thelowest validity estimates (Depressive, Passive–Aggressive,and Self-Defeating) measure PDs that are not included in thecurrent diagnostic manual, which may have been a point ofconfusion for some raters; and although the Aggressive PDis likewise not included in DSM–IV (American PsychiatricAssociation, 1994, 2000), it exhibited good validity. It is pos-sible that the few patients in the sample who demonstratedthese personality features were especially salient and easilydifferentiated from antisocial persons who did not exhibitsadistic propensities.

Personality Profiles

Analysis of the profile of MCMI PD scale scores has alwaysbeen recommended because most people exhibit a blend oftraits from multiple prototype domains (Millon, 1983a, 1987,1997a, 2006). For example, it will be rare for a respondent

to obtain an elevation on only the Schizoid scale. Most re-spondents will show multiple scale elevations identifyingthe prototype domains that best fit their characteristic wayof thinking, feeling, and behaving. Frequently occurring 2-point and 3-point code types were identified by Millon andothers for the MCMI–I and MCMI–II (see Choca, 2004;Millon, 1983a, 1987), supporting this element of the model.Millon’s experience with these patient groups led him tomore formally propose 60 frequently occurring MCMI–IIIsubtypes (Davis & Patterson, 2005; Grossman & del Rio,2005; Millon, 1996; Millon & Grossman, 2006). The mostrecent addition to the test—Grossman (2004; Grossman &del Rio, 2005; Millon, 2006) facet subscales—measure sub-groups of PD scale items identified by factor analysis (FA)that reflect Millon’s (1996) structural and functional trait dis-tinctions.

Continuity Between Normal and Abnormal Traits

All versions of the MCMI were intended for use with pa-tient samples because their data were based on psychiatricpatient norms (Millon, 1983a, 1987, 2006). This effectivelyprohibits direct comparisons between patient and nonpatientsamples and limits the validity studies that can be conductedto evaluate how the test behaves with normal and abnormalpersons. Nevertheless, a few studies have been published inwhich the MCMI was given to normal participants, and theirresults supported Millon’s (1996) view that his basic person-ality prototypes exist in normal form as mild variants of thePDs (Choca, 2004; Retzlaff & Gibertini, 1987; Strack, 1991,2005a, 2005b). For example, the factor structure of MCMIPD scales is essentially the same in normal and patient sam-ples (Dyce, O’Connor, Parkins, & Janzen, 1997; Retzlaff& Gibertini, 1987; Strack, 1991), and both groups obtainedsimilar personality configurations on the MCMI and otherMillon measures that assess normal traits (Craig & Olson,2001; Strack, 2005a).

Summary

Overall, the empirical literature has been supportive of theMCMI PD scales as being reliable and valid measures ofcontinuously distributed prototype trait characteristics thatcan be useful for diagnosing patients according to DSMcriteria. MCMI PD test profiles are useful for identifyingsubtypes (i.e., personality prototype variants) that followMillon’s (e.g., 1996) theoretically and clinically derived for-mulations. Millon’s personality prototypes as measured bythe MCMI have also shown consistency across normal andabnormal populations, verifying the hypothesis that the basicPD prototypes are severe forms of the styles found in normalpersons.

However, substandard reliability and validity has beennoted for a few MCMI PD scales. Problems have croppedup most often when Millon’s (1996) (model and the MCMI


diverged from the DSM and from measures that used theDSM for their definitional base (e.g., structured diagnosticinterviews). Since DSM-III (3rd ed.; American PsychiatricAssociation, 1980), Millon’s ideas about PDs have stronglyshaped the taxonomy of Axis II, but Millon’s (1981, 1996)model and the DSM are not the same. As long as there aredivergences between the two, the MCMI will remain an im-perfect measure of DSM PDs.

FACTOR ANALYSIS

Over the years, a number of debates have arisen about thepsychometric properties of the MCMI, its factor structure,and its relationship to Millon’s (1996) model of personalityand psychopathology. Recent reviews of the MCMI literature(e.g., Choca, 2004; Craig, 1999, 2005) have summarizedthese debates very well, so we limit ourselves to a discussionof FA as a statistical method for understanding the propertiesof the instrument and its relationship to Millon’s model.

MCMI scales were created primarily to operationalizeMillon’s (1996) taxonomy of PDs, which is polythetic innature. Personality prototypes are viewed as the synthesis ofmany basic elements and systems that operate within an indi-vidual. The prototypes are derived from inherited predisposi-tions, sociocultural influences, and environmental character-istics. Although the prototypes with normal variants evolvedover thousands of years, their phenotypic expression varieswithin and across individuals over time and situations. Per-sonality prototypes are related to one another in a systematicmanner such that some prototypes share basic characteris-tics such as a passive or active orientation to shaping theirenvironment and a propensity to seek pleasure and/or avoidpain (Millon, 1996). MCMI PD scales were created withtwo groups of items, namely, nonoverlapping prototypicalitems and overlapping nonprototypical items. The formerare viewed as central features of the prototypes, whereas thelatter represent shared characteristics.

As mentioned in numerous publications, Millon (e.g.,1981, 1969/1983b, 1996) has not created his personal-ity model from the point of view of factorial dimen-sions. No underlying factor structure has been specifiedfor his taxonomy or the MCMI. The polythetic nature ofthe model and the use of overlapping items for scales re-sult in confounded factors, especially when Axis I andII scales are analyzed together (Choca, 2004; Haddy etal., 2005). Nevertheless, the MCMI PD scales can typi-cally be summarized by two or three underlying dimen-sions that are often labeled emotionality versus restraint,introversion versus extraversion, and dominance versus sub-missiveness (Craig & Bivens, 1998; Haddy et al., 2005;Millon, 1983a, 2006; Retzlaff & Gibertini, 1987; Strack,Choca, & Gurtman, 2001).

Recently, Grossman (2004; Grossman & del Rio, 2005;Millon, 2006) factor analyzed the items of the MCMI–III’s

individual PD scales using the test’s normative sample. Em-ploying an alpha factoring technique with oblique rotation,Grossman (2004) was able to recover two or three dimen-sional elements for each personality prototype that werelater refined into facet subscales using rational and empir-ical criteria. Importantly, the prototype subscales were foundto measure major structural and functional elements of thepersonalities as outlined by Millon (1996). A complete list-ing of the facet scales by prototype is given in Table 3. Thescales can now be calculated for all MCMI–III PD profiles(Millon, 2006).

Owing to Millon’s (1981, 1969/1983b, 1987, 1997a,2006) use of the terms dimension and axis to describe someof the underlying components of his personality prototypes(e.g., active–passive, pleasure–pain, self–other), confusionhas occurred as to whether these may be viewed as dimen-sions that can be recovered in factor analyses of the MCMI(Piersma, Ohnishi, Lee, & Metcalfe, 2002; Widiger, 1999).The simple answer is “no.” The MCMI is based on a theoret-ical model that uses bipolar axes and dimensions for descrip-tive and inferential purposes, but these are not to be confusedwith latent roots identified by factor analytic methods.

At the same time, although the taxonomy as a whole andmany of its elements cannot be recovered or adequately testedwith factor analysis, some components of the model can beexamined in experimental and nonexperimental designs us-ing FA and other statistical techniques that apply to traitcharacteristics measured on continuous scales. Grossman’s(2004; Grossman & del Rio, 2005) work on MCMI–III PDfacet scales is an example. Grossman (2004) used FA toidentify subgroups of PD scale items. Because most MCMI–III items address observable symptoms, feelings, attitudes,and behaviors, it was reasonable to assume that they wouldcluster together in ways that resemble the structural andfunctional characteristics proposed by Millon (1996), whichare also readily observable or easily inferred (see Table 3).Grossman’s work (2004; Grossman & del Rio, 2005) showedthat some of the trait domains could be recovered but notedthat there are not enough items on the MCMI–III to ade-quately represent all of the proposed structural and func-tional characteristics of each PD. Another example is Mil-lon’s (1996) hypothesis that a continuum exists between nor-mal and abnormal personality traits. Based on the hypothesis,it is reasonable to assume that whatever factor structure existsfor the MCMI PD scales, the same structure should obtainin normal and abnormal populations. The previous sectionon Continuity Between Normal and Abnormal Traits pro-vides references to a number of studies yielding evidence insupport of this particular proposition.6

6Whereas Millon (1996) hypothesized that many phenotypically ex-pressed personality characteristics will show continuous distributions inboth normal and abnormal samples (e.g., introversion–extraversion), otherfeatures important to personality classification (such as active–passive ori-entation) will not necessarily emerge in dimensional form. Because of this,


TABLE 3Grossman Facet Scales With Alpha

Coefficient Reliabilities

Prototype/Subscale Items Alpha

1 Schizoid1.1 Temperamentally Apathetic 8 .731.2 Interpersonally Unengaged 10 .791.3 Expressively Impassive 8 .602A Avoidant

2A.1 Interpersonally Aversive 9 .792A.2 Alienated Self-Image 10 .852A.3 Vexatious Representations 8 .78

2B Depressive2B.1 Temperamentally Woeful 7 .832B.2 Worthless Self-Image 9 .832B.3 Cognitively Fatalistic 8 .82

3 Dependent3.1 Inept Self-Image 8 843.2 Interpersonally Submissive 8 .643.3 Immature Representations 6 .71

4 Histrionic4.1 Gregarious Self-Image 7 .694.2 Interpersonally Attention-Seeking 8 .614.3 Expressively Dramatic 7 .55

5 Narcissistic5.1 Admirable Self-Image 10 .795.2 Cognitively Expansive 7 .505.3 Interpersonally Exploitive 10 .656A Antisocial

6A.1 Expressively Impulsive 9 .566A.2 Acting-Out Mechanism 10 .716A.3 Interpersonally Irresponsible 8 .61

6B Sadistic6B.1 Temperamentally Hostile 8 .656B.2 Eruptive Organization 8 .596B.3 Pernicious Representations 11 .71

7 Compulsive7.1 Cognitively Constricted 8 .517.2 Interpersonally Respectful 6 .487.3 Reliable Self-Image 7 .538A Negativistic

8A.1 Temperamentally Irritable 10 .778A.2 Expressively Resentful 7 .688A.3 Discontented Self-Image 7 .78

8B Masochistic8B.1 Discredited Representations 8 .758B.2 Cognitively Diffident 8 .788B.3 Undeserving Self-Image 10 .85

S SchizotypalS.1 Estranged Self-Image 11 .85S.2 Cognitively Autistic 10 .79S.3 Chaotic Representations 8 .78

C BorderlineC.1 Temperamentally Labile 10 .81C.2 Interpersonally Paradoxical 9 .77C.3 Uncertain Self-Image 9 .83P ParanoidP.1 Cognitively Mistrustful 8 .74P.2 Expressively Defensive 7 .64P.3 Projection Mechanism 9 .64

Note. Reliability coefficients were calculated from the MCMI–III nor-mative cross-validation sample, N = 398. Reprinted with permissionfromMillon Clinical Multiaxial Inventory–III (MCMI–III) manual (3rded., p. 114), By T. Millon, 2006, Minneapolis, MN: Pearson Assessments.Copyright 2006 by DICANDRIEN, Inc. All rights reserved.

Admittedly, some of the hypothesized biological compo-nents and their developmental influence on personality frominfancy to adulthood are extremely difficult to test at thistime because of the limitations of current scientific methods(Strack, 2006). An example is the active–passive polarity,which is hypothesized to underlie the expression of mostforms of personality. An individual’s orientation to an ac-tive or passive lifestyle is more than an algebraic functionof energy level (e.g., surgency), sociability, dominance, andintelligence. It refers to a complex coping and survival strat-egy where an individual actively shapes surrounding eventsor waits for circumstances to change to bring need gratifica-tion. An individual’s active or passive tendency is linked toinherited genetic dispositions that are, in turn, linked to struc-tural and biochemical elements in the brain that can changeduring childhood due to environmental factors such as theavailability of food and emotional sustenance, the reinforce-ments of one’s family and social groups, and exposure totraumas (Millon, 1990, 1996).7

Future validation research on the MCMI will be mosthelpful when investigators view the instrument in the contextof Millon’s (1996; Millon & Grossman, 2006) overarchingclinical science model and appreciate the limitations that ex-ist in the measure for validating the model and the DSM. Asnoted earlier, the MCMI–III (Millon, 1997a, 2006) measures14 PDs, not all of which are present in DSM–IV (AmericanPsychiatric Association, 1994, 2000). The MCMI–III is the-oretically derived from Millon’s model of personality, but itdoes not measure all of the components of the model. In ourview, it is a good measure of Millon’s PD prototypes, sub-types, and some of the functional and structural domain traitsthat the prototypes and subtypes are based on. Validation ofthe larger model, including its bipolar axes, will require lon-gitudinal research designs that use multiple measures anddata sources (Strack, 2006).

MAPPING THE FUTURE OF PERSONALITYASSESSMENT

This Special Series highlights the virtues and pitfalls of cat-egorical and dimensional assessment of PDs. The MCMI,and the theory from which it was derived, posits the exis-tence of continuous trait characteristics that form the basisof personality prototypes that can be assessed in categori-

Millon (1996) believed that factor analysis and dimensionalized traits alonecannot serve as an adequate foundation for a taxonomy of PDs—too manyelements would be lost.

7In this regard, it is unfortunate that the vast majority of publishedstudies on Millon’s (for example, 1996) body of work have focused on hisassessment measures rather than his model of personality and psychopathol-ogy. We strongly encourage research on his model that is independent of hismeasures because assessment instruments such as the MCMI are imperfectand limited in how they operationalize many theoretical variables.


cal form. In our view, the future of personality assessmentlies with the development of measures that are linked to acomprehensive clinical science, the features of which wereoutlined previously. We believe that the resolution of manyof the current dilemmas in personality diagnosis will comewith a more sophisticated, theory-driven approach, one thatgets beyond the simplicities of traditional categorical and di-mensional models. Here, we briefly present Millon’s (1996,2005; Millon & Grossman, 2006) views on the resolution ofcategorical versus dimensional models of personality.

The PDs found on Axis II of DSM–IV (American Psychi-atric Association, 1994, 2000) are diagnosed as categories.If a patient is judged to meet or exceed a minimum numberof diagnostic features, that patient may be said to have a par-ticular PD. If the patient falls short of the minimum numberof required features, no diagnosis is made. Most psycholo-gists dislike categorical diagnosis because it goes against abody of evidence showing that personality traits are, for themost part, distributed continuously in the human population(e.g., Strack, 2006). Medically trained psychiatrists have fa-vored categorical diagnosis for all types of disorders whetherphysical or mental (e.g., Livesley, 2001). This difference inconceptualizing personality reflects historical differences inthe way psychologists and psychiatrists have viewed theirsubject matter. Psychology’s substantive realms have beenapproached with considerable success by employing meth-ods of dimensional analysis and quantitative differentiation(e.g., intelligence measures, aptitude levels, and trait magni-tudes). By contrast, medicine has made its greatest progressby increasing its accuracy in identifying and categorizingdiscrete disease entities. The issue separating these two his-toric approaches as it relates to the subject domain of normaland abnormal personality may best be stated in the form of aquestion: Should personality be conceived and organized asa series of dimensional traits that combine to form a uniqueprofile for each individual, or should certain central charac-teristics be selected to exemplify and categorize personalitytypes found commonly in clinical populations?

The view that personality might best be conceived inthe form of dimensional traits has only recently begunto be taken as a serious alternative to the more clas-sic categorical approach by medical practitioners (Livesley,2001; Widiger & Simonsen, 2005). Certain trait dimensionshave been proposed in the past as relevant to these disorders(e.g., dominance–submission, introversion–extraversion),but these have not been translated into the full range of per-sonality pathology seen in clinical practice. Some attributeshave been formulated so that one extreme of a dimensionalpole differs significantly from the other end in terms of clin-ical implications. An example would be emotional stabilityversus emotional instability. Other traits are believed to beabnormal at both ends of the continuum while the middleground is normal. An example of this would be found in anactivity dimension such as listlessness versus restlessness.

Despite their seeming advantages, dimensional systemshave not taken strong root in the formal diagnosis of abnor-mal personality (Livesley, 2001). Numerous complicationsand limitations have been noted in the literature. First isthe fact that there is little agreement among dimensionaltheorists concerning the number of traits necessary to repre-sent personality. Historically, Menninger (1963) contendedthat a single dimension would suffice; Eysenck (1960) as-serted that three are needed, whereas Cattell (1965) claimedto have identified as many as 33. However, recent models,most notably the Five-factor model (Costa & McCrae, 1990;Goldberg, 1990; McCrae, 2006; Norman, 1963) have begunto achieve a modest level of consensus. And some suggestedthat the traits may mutually be understood in a hierarchi-cal fashion (Markon, Kreuger, & Watson, 2005). Neverthe-less, problems are still apparent in the literature in terms ofhow many and which dimensions are needed to cover nor-mal and abnormal functioning and how to create a workablehierarchy of higher order and lower order dimensions andfacets (Livesley, 2001; Markon et al., 2005; Panounen, 1998;Strack, 2006). Although the lexical tradition of using person-ality terms embedded in common language has been usefulin creating a taxonomy of trait dimensions among normalpersons, the same approach has not been as fruitful in identi-fying abnormal dimensional elements (Harkness & McNulty,1994).

Categorical models appear to have been the preferredschema for representing both CSs and PDs (Livesley, 2001).It should be noted, however, that most contemporary cat-egories neither imply nor are constructed to be all-or-none typologies. Although singling out and giving promi-nence to certain features of behavior, they do not overlookthe others but merely assign them lesser significance. It isthe process of assigning centrality or relative dominance toparticular characteristics that distinguishes a schema of cat-egories from one composed of trait dimensions. Conceivedin this manner, a type simply becomes a superordinate cate-gory that subsumes and integrates psychologically covarianttraits that, in turn, represent a set of correlated habits that,in their turn, stand for a response displayed in a variety ofsituations.

There are, of course, objections to the use of categoricaltypologies in personality. They contribute to the fallaciousbelief that syndromes of abnormality are discrete entities,even medical diseases, when in fact they are merely con-cepts that help focus and coordinate observations (Livesley,2001). Numerous classifications have been formulated in thepast century, and one may question whether any system isworth utilizing if there is so little consensus among cate-gorists themselves.

Is it possible to conclude from this review that categoricalor dimensional schemas are potentially the more useful forpersonality classification? An illuminating answer may havebeen provided by Cattell (1970), who wrote


The description by attributes [traits] and the description bytypes must be considered face and obverse of the same de-scriptive system. Any object whatever can be defined eitherby listing measurements for it on a set of [trait] attributes orby sequestering it to a particular named [type] category. (p.40)

In effect, Cattell (1970) concluded that the issue of choos-ing between dimensional traits and categorical types is mootbecause they are “two sides of the same coin.” The essentialdistinction to be made between these models is that of com-prehensiveness. Types are higher order syntheses of lowerorder traits; they encompass a wider scope of generality. Forcertain purposes, it may be useful to narrow attention to spe-cific traits; in other circumstances, a more inclusive level ofintegration may be appropriate (Grove & Tellegen, 1991).

An endeavor to resolve some of these issues has been de-scribed by Millon (1984, 1986, 1990) and summarized ear-lier. Termed prototypal trait domains, this approach mixescategorical and dimensional elements in a personologic clas-sification. As in the official schema, several criteria are spec-ified for each disorder, but these criteria encompass a largeset of clinical domains, for example, mood/temperament andcognitive style. The diagnostic criterion is conceived to beprototypal as is the personality as a whole. Each specificdomain is given a standard for each PD. For example, ifthe clinical attribute “interpersonal conduct” is deemed ofvalue in assessing personality, then a specific prototypal cri-terion would be identified to represent the characteristic ordistinctive manner in which each PD ostensibly conducts itsinterpersonal life (see Figure 2 for an example).

By composing a classification schema that includes allrelevant trait domains that are commonly used by clinicians(e.g., self-image, interpersonal conduct, cognitive style) andthat specifies a prototypal feature for each domain and PD,the proposed format would then be fully comprehensive inits scope, useful to experienced and sophisticated clinicalassessors, as well as possess directly comparable prototypalfeatures for its parallel categories. A schema of this naturewould not only be accepted by practitioners but would alsofurnish both detailed substance and symmetry to its assess-ment taxonomy. We described the 15 prototypes of Millon’smost recent personality model and its associated functionaland structural domains earlier (see Figures 1 through 3).

To enrich its qualitative categories (the several prototy-pal features comprising the trait range seen in each domain)with quantitative discriminations (numerical intensity rat-ings), personologists would not only identify which proto-typal features (e.g., woeful, hostile, labile) in a trait domain(e.g., mood/temperament) best characterizes a person butwould record a rating or number (e.g., from 1–10) to repre-sent the degree of prominence or pervasiveness of the chosenfeature(s). Personologists would be encouraged in such aprototypal schema to record and quantify more than one fea-ture per psychological domain (e.g., if suitable, to note both

“woeful” and “labile” moods should their observations leadthem to infer the presence of these two prototypal charac-teristics in that domain). Reference to the descriptive traitdomains of all but one personality may be found in Millon(1996). Information concerning the most recent personalityformat and details may be found in Millon (2006) and Millonand Grossman (2006).

The prototypal domain model illustrates that categorical(qualitative distinction) and dimensional (quantitative dis-tinction) approaches need not be framed in opposition, noless be considered mutually exclusive. Assessments can beformulated, first, to recognize qualitative (categorical) dis-tinctions in what prototypal features best characterize a per-son, permitting the multiple listing of several such features,and second, to differentiate these features quantitatively (di-mensionally) so as to represent their relative degrees of clin-ical prominence or pervasiveness. The prototypal domainapproach includes the specification and use of categorical at-tributes in the form of distinct prototypal characteristics yetallows for a result that permits the diversity and heterogeneityof a dimensional schema of clinically relevant domains.

ACKNOWLEDGMENTS

Participation of Stephen Strack was supported by the U.S.Department of Veterans Affairs. We thank Susan Stantonand Brandon Yakush for helpful comments on an early draftof the manuscript.

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Stephen StrackPsychology Service (116B)VA-LAACC351 East Temple StreetLos Angeles, CA 90012-3328Email: [email protected]

Received February 3, 2006Revised September 19, 2006

contributions to the dimensional assessment of iii schizoid scale above a particular point allowed...

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