Examining the Underlying Structure of Schizophrenic Phenomenology: Evidence for a Three-Process...

VOL. 17, NO. 3, 1991 Examining the UnderlyingStructure of SchizophrenicPhenomenology: Evidencefor a Three-Process Model

by Mark F. Lenzenweger,Robert H. Dworkin, and ElaineWethington

Abstract

The present report examined the la-tent structure of schizophrenic phe-nomenology. Schizophrenic patientcase histories (n = 192) were ratedfor positive symptoms, negativesymptoms, and premorbid social ad-justment and the observed covaria-tion among these clinical featureswas evaluated using a model-basedconfirmatory factor analyticapproach. Our results indicated thatschizophrenic phenomenology wasbest characterized by three distinctunderlying structures. These dataprovide empirical support for Strausset al.'s (1974) three-process model,which suggests that positive symp-toms, negative symptoms, and disor-dered premorbid personal-social rela-tionships are three distinct classes ofphenomenology possibly reflective ofthree relatively independent patho-logical processes in schizophrenia.The data are also consistent withCrow's (1980, 1985, 1987) model ofschizophrenic symptomatology, dif-ferentiating social impairment fromboth positive and negative symp-toms. The heuristic implications ofthese data for the development ofschizophrenia are discussed and theutility of a replication of the presentstudy is noted.

Strauss et al. (1974) hypothesizedthat three independent pathologicalprocesses might underlie theobserved occurrence of three generalclasses of schizophrenic signs andsymptoms, namely, positive symp-toms (hallucinations, delusions, for-mal thought disorder, and bizarrebehavior), negative symptoms(blunted affect, alogia, and apathy),and disordered personal-social rela-tionships. Although the precise etiol-ogies of the three putative disease

processes remained unspecified,Strauss et al. (1974) argued persua-sively that the patterning of pheno-typic manifestations in schizophreniamight reflect the actual pathologicalprocesses. Thus, Strauss et al. pro-posed a model of three functionalprocesses in schizophrenia that con-sisted of two distinct components: (1)At the descriptive level, three sepa-rate symptom dimensions (or clus-ters) were hypothesized to character-ize the phenotypic manifestations ofthe illness. (2) At the level of patho-genesis, the three symptom dimen-sions were hypothesized to be reflec-tive of three relatively distinctetiologies or pathophysiologies orboth.

Two of the three symptom classesemphasized by Strauss et al. (1974),positive and negative symptoms,have been the focus of recent theorydevelopment and research (Crow1980; Andreasen and Olsen 1982;Crow 1985). Currently available em-pirical data support the validity ofpositive and negative symptoms astwo relatively independent symptomdimensions (Lenzenweger et al. 1989)probably reflective of two pathologi-cal processes (Walker and Lewine1988). Deficits in premorbid socialfunctioning, however, are known tobe associated with negative symp-toms but not with positive symptoms(Walker and Lewine 1988); yet it isunclear whether such deficits shouldbe distinguished from negative phe-nomenology as suggested by Strausset al. (1974). An empirical examina-tion of the structures underlyingschizophrenic phenomenology mighthelp to further establish disordered

Reprint requests should be sent to Dr.M.F. Lenzenweger, PsychopathologyArea, Dept. of Human Development,Cornell University, G-65 Van RensselaerHall, Ithaca, NY 14853-4401.

by guest on July 2, 2015http://schizophreniabulletin.oxfordjournals.org/

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516 SCHIZOPHRENIA BULLETIN

social functioning as a third indepen-dent dimension underlying observedschizophrenic symptoms, one whichis relatively distinct from both posi-tive and negative symptoms. Suchdata would provide additional sup-port for Strauss et al.'s third patho-logical process.

An important conceptual issuearises in considering the nature ofdisordered personal-social relation-ships in relation to positive and neg-ative symptoms in schizophrenia.What is the nature of the relation-ship between a psychotic illness andsocial functioning across the lifespan?Strauss et al. (1974) hypothesizedthat the personal relationships di-mension has its own "longitudinalhistory and consistency as a psycho-logical process" (p. 68) independentof schizophrenic symptoms. How-ever, it is unclear to what extent thisprocess may be influenced by theemergence of schizophrenia as a dis-ease. Social and personal relationshipdeficits occurring after the onset ofschizophrenia could reflect (1) thecontinued expression of Strauss etal.'s third pathological process, es-sentially the post-psychotic reemer-gence of poor premorbid personalitytraits (Zubin 1985; Pogue-Geile andZubin 1988); (2) a genuine negativeschizophrenic symptom developing asa feature of the core disease (An-dreasen and Olsen 1982); or (3) a"secondary" negative symptom re-sulting from the impact of psychosisor antipsychotic medication or both(Crow 1985, 1987; Zubin 1985; Car-penter et al. 1988). It is also plausi-ble that impaired post-onset socialrelations may not be related to theschizophrenia disease process per sebut, rather, reflects a strategy usedby patients to withdraw from socialcontact for fear of undesired societalreactions to the diagnosis of schizo-phrenia (Strauss et al. 1974; Link et

al. 1989). Clearly, premorbid deficitsin social functioning must be distin-guished from social functioning im-pairments noted in patients after theonset of schizophrenia, and this dis-tinction should be accounted for inany evaluation of Strauss et al.'sthree-process model.

We undertook the present study toaddress two specific hypotheses, bothderived from the "descriptive" com-ponent of the Strauss et al. three-process model. First, we sought todetermine if three relatively distinctdimensions underlie schizophrenicphenomenology as Strauss et al. con-jectured. In particular, we sought toevaluate how well Strauss et al.'sthird process, reflected by disorderedpersonal relationships, could accountfor an identifiable domain of schizo-phrenic phenomenology independentof positive and negative symptoms.Second, we sought to specify the na-ture of the associations betweenpersonal-social adjustment and posi-tive and negative schizophrenicsymptoms in both the premorbid andthe morbid (i.e., post-onset) periods.

Methods

Subjects. As detailed in previouspublications (Dworkin and Lenzen-weger 1984; Lenzenweger et al.1989), the case histories of all mono-zygotic schizophrenic probands andtheir co-twins from the five majorEuropean twin studies of schizophre-nia that have been published in Eng-lish were assembled. These 302 casehistories of 151 monozygotic twinpairs were carefully edited to removeall identifying information that mightenable a rater to match a probandwith his or her co-twin. Zygosityand family history data were alsodeleted from the case histories beforethey were rated, and the case histo-

ries were then randomly ordered.Because of the intermixing of the his-tories of schizophrenic probands andtheir co-twins, the degree and typeof psychopathology described in thecase histories ranged from psychosisto absence of significant psycho-pathology. The histories typicallycovered psychosocial and psychiatricdevelopments across the lifespan foreach twin.

Measures. A manual was developedto assess positive and negativeschizophrenic symptoms in these casehistories. This manual consists ofdetailed descriptions of five catego-ries of negative symptoms (affectiveflattening, alogia, avolition-apathy,asociality-withdrawal, and attention-al impairment) and five categories ofpositive symptoms (hallucinations,delusions, positive formal thoughtdisorder, catatonic motor phenom-ena, and bizarre behavior). The neg-ative symptom portion of the manualis a modification of Andreasen's(1981) interview-based Scale for theAssessment of Negative Symptomsthat we adapted for use with casehistories. Most of these modificationswere minor, with one exception: weshifted anhedonia to the affectiveflattening symptom section and madeasociality-withdrawal a separatesymptom section (Andreasen's man-ual includes the category anhedonia-asociality). Doing so increased reli-ability by reducing some ambiguitythat the raters experienced in pilottrials. The positive symptom portionof the manual consists of phenome-nologic descriptions drawn from tra-ditional sources in descriptive psy-chopathology for the positivesymptoms listed above (Hamilton1976; Wing et al. 1974; AmericanPsychiatric Association 1980). Thevalidity of symptom ratings based onthis manual is supported by our pre-

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vious research, which found the pre-dicted relationships between theseratings and attentional measures(Cornblatt et al. 1985) and geneticinfluences for schizophrenia(Dworkin and Lenzenweger 1984;Dworkin et al. 1988).

Two experienced clinicians—a clin-ical psychologist and a psychiatrist—were trained to rate the 302 case his-tories for the presence or absence ofeach of the five negative and the fivepositive symptoms. The two raterswere not informed of any theoreticalorganization concerning positive andnegative symptoms that might influ-ence their assessments, and they wereinstructed to rate as present onlythose symptoms that were clearlydescribed in the case history mate-rial. The data used to make the posi-tive and negative symptom ratingswere confined exclusively to the mor-bid period of the lifespan (i.e., thepost-onset period). The raters wereinstructed to avoid any form of hy-pothetical inference in their phenom-enological assessments if the presenceof a symptom was equivocal. Thefollowing analyses make use of theaverage of their ratings for eachsymptom (for each of the positiveand negative symptoms each patientreceived a symptom rating that wasthe average of the two raters' assess-ments). Average ratings were usedbecause of their greater reliability.Acceptable levels of interrater reli-ability for each of the 10 symptomswere demonstrated with intraclasscorrelation coefficients (ICC) (Shroutand Fleiss 1979) for the averagesymptom ratings ranging from 0.68to 0.91 (the mean of the reliabilitiesacross the 10 symptoms was 0.79).Following Shrout and Fleiss (1979),the formula ICC[3,k] was used tocalculate the ICCs we report;ICC[3,k] is equivalent to Cronbach'salpha for average ratings.

Each case was rated by two newraters, a clinical psychologist and anadvanced doctoral student in clinicalpsychology, using both the PhillipsAbbreviated Scale of Premorbid Sex-ual Adjustment (Harris 1975) and theZigler-Phillips Social CompetenceScale (Zigler and Phillips 1960). Thecase history data used for these rat-ings were confined exclusively to thepremorbid period (Lenzenweger andDworkin 1987), and interrater reli-abilities for the average ratings were0.95 (Phillips) and 0.82 (Zigler-Phillips). The premorbid period wasdefined as that phase of the lifespanbefore the first psychiatric hospital-ization for an individual or the firstappearance of clear-cut psychoticsymptoms. In the vast majority ofcases, the premorbid period and on-set of schizophrenia were unambigu-ously noted in the case history mate-rial. Each case was also rated forparanoid phenomenology (an addi-tional positive symptom) by a clini-cal psychologist and an advanceddoctoral clinical student using theVenables-O'Connor Scale for RatingParanoid Schizophrenia (Venablesand O'Connor 1959). The reliabilityof the average Venables-O'ConnorScale ratings was 0.87.

Statistical Analysis. Of the 302 indi-viduals represented in the case his-tory material, 220 (151 schizophrenicprobands and 69 schizophrenic co-twins) had received a diagnosis ofschizophrenia based on traditionallyconservative European diagnosticcriteria for the illness, and most hadreceived a hospital diagnosis ofschizophrenia. Complete positive andnegative symptom, paranoid phe-nomenology, and premorbid socialadjustment ratings based on themean of the two raters' ratings wereavailable for 192 of the 220 schizo-phrenic individuals; these average

ratings were used in the followinganalyses.

To evaluate four nested competingmeasurement models of the latentstructure underlying positive symp-toms, negative symptoms, and pre-morbid social relations, the confir-matory factor analysis (CFA) routineof the statistical system and com-puter program LISREL VI (Linearand Structural Relations VI)(Joreskog and Sorbom 1984) wasused. CFA provides the most directand informative statistical approachto evaluating competing measure-ment models. In CFA an investigatorconstructs a measurement model(i.e., a factor structure) that is de-rived from assumptions of the theoryof interest and specifies an impliedmodel of how covariances between agroup of variables should have beencaused by latent variables (i.e., un-derlying factors). The LISREL CFAprogram estimates a solution covari-ance matrix based on the measure-ment model and then, using maxi-mum likelihood-based procedures,compares the estimated covariancematrix with the actual input covari-ance matrix. A measurement modelproducing a solution closely match-ing the input covariance matrix is agood fit to the data. The quality ofthe fit between estimated and solu-tion matrices can be evaluated statis-tically; the appropriate test is thechi-square test (Long 1983; Joreskogand Sorbom 1984).

The goal of a model is to explainas much of the covariance present inthe obtained data as possible withinthe specifications of the model. Inthis instance, the null hypothesis isthat all of the population covariancehas been extracted from the correla-tion matrix by the prespecifiedmeasurement model. If the chi squareis statistically significant (e.g., p <0.05), then the residual matrix still

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has significant covariance in it andone may conclude that the modelbeing tested does not fit the datawell (Gorsuch 1983, p. 129). If thechi square is not statistically signifi-cant, then the null hypothesis is ac-cepted and one may conclude thatthe prespecified model fits the ob-served data well, leaving little cova-riance in the residual matrix. Whenlarge samples are being studied, amodel may provide a good fit to ob-served data but will generate a statis-tically significant chi-square value(Bentler and Bonett 1980; Marsh etal. 1988). In such instances,chi-square contrasts and incrementalfit indexes are typically used to as-sess the relative fits of competingmodels (Bentler and Bonett 1980;Marsh et al. 1988). Extensive reviewsand introductions to the mathemati-cal approach to parameter estimationinvolved in CFA and the CFA ap-proach to statistical comparisons ofcompeting substantive models arereadily available elsewhere (see Long1983; Joreskog and Sorbom 1984;Hayduk 1987; Bollen 1989).

Using the data contained in table1, we estimated four models. We be-gan by estimating a null model(Bentler and Bonett 1980), whichevaluates the fit of a model that as-sumes no structure underlyingschizophrenic phenomenology. Inthis instance the null model positsthat each of the 13 phenomenologicfeatures represented an independentdimension (i.e., a "13-factor" model),thereby implying that no underlyingstructure related the symptoms andsigns. Though clinically implausible,estimation of the null model estab-lishes a useful baseline against whichone can compare alternative modelsthat do make assumptions concern-ing latent structure.

Model 1 was a basic single-factormodel predicting one common

process (or factor) underlying schizo-phrenic symptoms and premorbidsocial adjustment. This model is con-sistent with Andreasen's model ofschizophrenic phenomenology (An-dreasen and Olsen 1982), which pre-dicts a bipolar (or inverse) relation-ship between positive symptoms andboth negative symptoms and premor-bid adjustment. It is also consistentwith a general "vulnerability" model(Zubin 1985), which predicts directrelationships among positive symp-toms, negative symptoms, and pre-morbid adjustment. Model 2 was atwo-factor model predicting two un-derlying pathological processes, oneconsisting of positive phenomenologyand the other consisting of both neg-ative symptoms and premorbid defi-cits. This model is consistent withresearch finding that deficits in pre-morbid adjustment are related tonegative symptoms, whereas positivesymptoms are unrelated to both neg-ative symptoms and poor premorbidadjustment (Walker and Lewine1988). Model 3 was the three-factormodel proposed by Strauss et al.(1974), predicting three independentpathological processes underlyingpositive symptoms, negative symp-toms, and premorbid adjustment.Model 3 is also consistent withCrow's (1985, 1987) recent theoreti-cal approach suggesting that somedeficits in social relations are bestdistinguished from positive and nega-tive symptoms.

Because symptom ratings in psy-chopathology research can be skewedin ways that may violate the statisti-cal assumption of multivariate nor-mality underlying LISREL computa-tions, we conducted a completelyparallel set of CFAs for all modelsdescribed above using Bentler's(1985) structural equations program,EQS. EQS allows an investigator toconduct CFAs using data that may

deviate from multivariate normalityby employing elliptical distributiontheory-based computational proce-dures, thereby verifying the robust-ness of the LISREL results.

Finally, in addition to model 3, weestimated two supplementary three-process models to clarify the associa-tion between post-onset asociality-withdrawal and premorbid socialimpairment. Model 3 held that post-onset asociality-withdrawal repre-sents a genuine negative symptomand should be associated with othernegative phenomena (e.g., Andreasenand Olsen 1982). The first supple-mentary model placed asociality-withdrawal with the positive symp-tom factor, testing the possibilitythat this symptom may be"secondary" and closely related topositive phenomena (e.g., Crow1985, 1987; Zubin 1985; Carpenter etal. 1988). Placement of this symptomwith the premorbid social impair-ment factor in the second supplemen-tary model reflected the hypothesisthat post-onset asociality-withdrawalmight be a post-onset extension orreemergence of premorbid adjustmentdifficulties (Strauss et al. 1974; Zubin1985).

Results

Results of the LISREL analyses evalu-ating goodness of fit for each modelare contained in the upper left sideof table 21. The first model

aThe present sample consisted of twinsdiagnosed with schizophrenia and, notinfrequently, both a proband and his orher affected co-twin were included. Itcould be argued on an a priori basis thatinclusion of twin pairs concordant forschizophrenia might have weighted oursample toward the more severely affectedend of the schizophrenia liability contin-uum. Such an imbalance might be hy-

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estimated, the null model, revealed arelatively large and highly significantchi square and relatively low LISRELgoodness-of-fit index (a "perfect" fitbetween model and data would gen-erate a fit index of 1.000). Thesedata indicate that a model assumingno latent structure underlying schizo-phrenic symptomatology fits the datapoorly and, in fact, they suggest thepresence of latent structure is likely.Model 1, the unidimensional model,produced a smaller chi square rela-tive to the null model and an im-proved goodness-of-fit index. Inspec-tion of the factor loadings did notreveal the bipolar pattern for positiveand negative symptoms predicted byAndreasen's model (Andreasen andOlsen 1982); rather, all factor load-ings were positive in direction as pre-dicted by a vulnerability model (e.g.,Zubin 1985). Model 2, the two-factormodel, revealed an even smaller chisquare relative to both the null andunidimensional models and yieldedan improved goodness-of-fit index.Finally, model 3, the Strauss et al.(1974) model, produced the smallestchi-square value and the highestgoodness-of-fit index, indicating it

pothesized to have affected the results weobtained using the combined sample of n= 192. Therefore, we conducted two par-allel sets of confirmatory factor analysesto evaluate whether the Strauss et al.three-process model continued to providethe best fit to the data when (1) onlyproband (n = 128) symptom data (i.e.,co-twins omitted) and (2) only symptomdata from discordant probands (n = 66)(i.e., concordant pair probands omitted)were analyzed. In both sets of analyses,the Strauss et al. three-process model pro-vided the best fit to the observed data,showing significant improvement in fitover all three competing measurementmodels. These results are available fromDr. Lenzenweger on written request.

provided the best overall fit to theobserved data. Despite the significantchi-square value associated withmodel 3 (a function of large samplesize [Bentler and Bonett 1980; Marshet al. 1988]), model 3 clearly pro-vides the best fit to the data. Exami-nation of the model 3 residual matrixrevealed small estimated residuals,which also indicated that the modelfit the data quite well.

The LISREL program alsoestimates the degree to which thelatent variables underlying positiveand negative symptoms and premor-bid adjustment are correlated inmodels 2 and 3. The correlation be-tween the positive and negative/pre-morbid impairment factors in model2 was estimated as 0.31 (p < 0.001),suggesting that the latent variables inthis model are associated. For model3, the correlations between the threelatent variables were estimated asfollows: positive X negative = 0.34(p < 0.001), positive X premorbidimpairment = —0.02, and negativeX premorbid impairment = 0.35(p < 0.001). These data suggest thatthe latent variables underlying posi-tive and negative symptoms are asso-ciated and that those underlying neg-ative symptoms and premorbidadjustment are associated, whereaspositive symptoms and premorbidadjustment are essentially inde-pendent. These correlations do notreflect a factor rotation; LISREL so-lutions are statistically direct.

Does the three-process model pro-vide a significant improvement in fitto the data relative to its three com-petitors? The four nested modelswere compared by sequentially con-trasting model 1 versus the nullmodel, models 2 versus model 1, andmodel 3 versus model 2. The differ-ences between the chi-square valuesand degrees of freedom associated

with each model were calculated andevaluated for statistical significance(Bentler and Bonett 1980). Such dif-ferences reveal the extent to whichone model fits observed data better(or worse) than another. To assessthe amount of information gained inthe comparison of two competingmodels and to generate an estimateof the improvement in fit that mightbe expected using a hypotheticallybetter model, nonnormed incrementalfit indexes were calculated (Tuckerand Lewis 1973; Bentler and Bonett1980; Marsh et al. 1988). The resultsof the LISREL-based model compari-sons as well as the incremental fitindexes are contained in the upperright side of table 2. All three mod-els that made assumptions about theunderlying structure of schizophrenicphenomenology provided signifi-cantly better fits to the observeddata than the null model (p < 0.001for all comparisons).

As can be seen from table 2,model 2 provided a significantly bet-ter fit to the data than did model 1.The model contrast of central con-cern to the present investigation con-cerned models 3 and 2. Model 3clearly provided a significantly betterfit to the data than did model 2. Theincremental fit indexes in the rightpart of table 2 are consistent withthe sequential chi-square contrasts; itis most important to note that theincrement in fit provided by model 3over model 2 is substantial (Bentlerand Bonett 1980). Moreover, the cu-mulative increment in fit provided bymodel 3 over the null model is ap-preciable, although additional im-provement in fit appears possible.

Results of the parallel EQS CFAsare contained in the lower half oftable 2. The overall pattern of resultsbased on elliptical distributiontheory-based CFAs is highly similarto, and in reasonable accord with,

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Table 1. Correlations among positive, negative, andadjustment in 192 schizophrenic patients

Symptomvariables

- 0 0 1

paranoid symptoms

Symptom variables

premorbid

656 1000

-152 -176

Note.—1 = hallucinations; 2 = delusions; 3 = positive formal thought disorder; 4 = catatonic motor behavior; 5 = bizarre behavior; 6 =flattened affect; 7 = alogia; 8 = avolition; 9 = asociality; 10 = attentional impairment; 11 = Zigler-Phillips Social Competence Scale; 12= Phillips Abbreviated Scale of Premorbid Sexual Adjustment; and 13 = Venables-O'Connor Scale for Rating Paranoid Schizophrenia. Cor-relations reported are Pearson product moment correlation coefficients. Decimal points are omitted.

those obtained using LISREL. Thesedata provide additional evidence sup-porting the superiority of Strauss etal.'s three-process model over models1 and 2 as well as the null model.

Concerning the supplementaryanalyses, the model placing post-onset asociality-withdrawal on thepremorbid impairment factor pro-vided such a poor fit to the data thatthe LISREL program would not con-verge to a solution. The model plac-ing this symptom on the positivesymptom factor could be estimated(chi square = 192.55, df = 62, p <0.001; LISREL goodness-of-fit index= 0.86). These results and those formodel 3 strongly suggest that ob-served post-onset asociality-withdrawal is best classified with theother negative symptoms rather than

with either premorbid impairment orpositive symptomatology.

Discussion

Our results reveal that positivesymptoms, negative symptoms, andpremorbid social impairment repre-sent three relatively independent phe-nomenologic domains in schizophre-nia, thus providing empiricalevidence to support Strauss et al.'s(1974) theoretical conjectures con-cerning the underlying organizationof schizophrenic phenomenology hy-pothesized to reflect three discretedisease processes. Our results arealso consistent with and supportCrow's (1980, 1985, 1987) inde-pendent dual-process model, whichidentifies some forms of pathological

social relations as distinct from thetwo independent dimensions of pa-thology reflected by positive andnegative symptoms. Also, consistentwith a recent summary of univariateresults documenting an associationbetween negative symptoms and pre-morbid impairments (Walker andLewine 1988), our data reveal an as-sociation between the latent variablesunderlying these two domains. Ourconfirmatory analytic approach,however, demonstrates that negativesymptoms and premorbid impair-ment in social relations are bestviewed as relatively independentprocesses. Finally, our results clearlyindicate that single-process models ofschizophrenic symptoms, such as theAndreasen bipolar unidimensionalmodel (Andreasen and Olsen 1982)

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Table 2. Evaluation

LISREL analysis

EQS analysis

of symptom

Model test

Chisquare

529.12

334.30

262.38

170.78

643.57

366.84

273.67

186.65

models

confirmatory

Compari-son

M Q - M ,

M2 -M3

factor analysisModel comparison

Chisquare

194.82

276.73

Note.—Mo = null model; M, = unidimensional model; M2 = two-dimension model; and M3 = three-dimension or Strauss et al.three-process model. All chi-square values are statistically significant (p < 0.001).1GFI indicates the LISREL goodness-of-fit index (GFI values range from 0.000 to 1.000; a GFI = 1.000 would be a perfect fit between ameasurement model and observed data). EQS does not produce a goodness-of-fit index.20M = the Tucker-Lewis incremental fit index, a measure of the degree of improvement in fit (specifically, the proportionate reduction inthe fitting function) obtained when moving from a null model (or less restrictive model) to a maintained (or more restrictive) model.3Cum = cumulative increment in fit (Tucker-Lewis formula) to the observed data by the maintained model relative to the fit provided by thenull model. Using the null model as a baseline comparison model, the Tucker-Lewis incremental fit index has a minimum of 0.000 and willtend toward 1.000 for a perfect fit. See Bollen (1989) for greater detail.

and the general vulnerability model(Zubin 1985), fit actual observedsymptoms rather poorly.

Our data indicate that some degreeof improvement in fit over andabove the Strauss et al. three-processmodel is possible; however, to ourknowledge, no other model ofschizophrenic phenomenology basedexclusively on positive symptoms,negative symptoms, and premorbidsocial adjustment exists currently.The two supplementary three-processmodels we estimated did not fit thedata better than the Strauss et al.model. We also estimated severalquasi-plausible four-factor models,none of which significantly improvedon the fit observed for model 3.Thus, simply adding factors to ameasurement model does not neces-

sarily improve the fit of the model toobserved data.

The present investigation alsosought to clarify the relations be-tween premorbid and post-onset so-cial impairment. Our supplementaryanalyses suggested that post-onsetasociality-withdrawal is more closelyassociated with other negative symp-toms than with either pathologicalpremorbid social relations or positivesymptoms. Unfortunately, our datado not allow us to determine theprecise etiology of post-onset asocial-ity and social withdrawal. It is con-ceivable that such behavior may rep-resent an aspect of the negativesymptom domain, but it could alsorepresent a reaction to learning thatone has a psychiatric illness and thesubsequent purposeful avoidance of

social interaction (Link et al. 1989).Furthermore, in a previous analysisof these symptom data, one of us(R.H.D.) reported gender differencesboth in premorbid adjustment and inthe negative symptom asociality-withdrawal (Dworkin 1990). Differ-ences in mean levels of social func-tioning across gender are intriguing(see Zigler and Glick 1986) in lightof the fact that the symptom covari-ance matrices for our male and fe-male subjects do not differ signifi-cantly; the Strauss et al. (1974)three-process model provides the bestfit in both the male and female sam-ples taken separately. Although ourdata support the existence of premor-bid social functioning as a third classof schizophrenic phenomenology,they clearly raise questions about

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Strauss et al.'s proposal that socialfunctioning is a longitudinally consis-tent psychological process. Prospec-tive developmental research is neededto illuminate the nature and causesof social impairments across the life-span of schizophrenic patients.

Three methodological aspects ofour study should be kept in mindwhen our results are being evaluated.First, the symptom ratings weremade from case history data. Al-though case histories can often betapped profitably to extract meaning-ful data in psychopathology research(e.g., Spitzer et al. 1979; Strauss andHarder 1981; Loranger et al. 1982;Lenzenweger and Loranger 1989),those data obtainable from case his-tories and hospital charts can be sub-ject to noteworthy limitations (seeAndreasen et al. 1977). For example,the case histories we examined werenot originally prepared with this re-search in mind, and it is possiblethat some histories might have omit-ted symptom descriptions. However,the case histories generally containedrelatively rich phenomenological ac-counts of symptoms and premorbidsocial functioning. This was proba-bly so because the histories were re-corded within a European psychiatriccontext that emphasized careful at-tention to phenomenology, particu-larly deficit symptoms, in the diag-nosis of schizophrenia (Essen-Moller1941; Langfeldt 1953). Second, as isthe case with essentially all assess-ment procedures in clinical psycho-pathology research (e.g., clinical andstructured interviews, rating scales),the possibility that some degree ofmethod-related covariation mightexist among the symptom ratingsused in our study could be consid-ered.

A third feature of these data isthat the patients were originally diag-nosed as schizophrenic using pre-

DSM-III criteria. Although the pa-tients were diagnosed within aEuropean context that traditionallyemployed a "narrow" concept ofschizophrenia, it is possible that di-agnostic criteria for the illness variedacross the original study researchsettings. We recommend, therefore,that future investigations of the mod-els we evaluated use symptom rat-ings derived from structured psychi-atric interviews with patients whohave been diagnosed for schizo-phrenia using modern operationalcriteria. Future research, however,must attend to the possibility thatthe DSM-III and DSM-M-R (Amer-ican Psychiatric Association 1987)definitions of schizophrenia largelyexclude negative symptoms from thediagnostic criteria for the illness; thisfeature of the newer operational defi-nitions may, in fact, substantiallyreduce observable variation in nega-tive symptoms among study popula-tions (see Dworkin and Lenzenweger1984, p. 1545).

The role of neuroleptic medicationin relation to the underlying struc-ture of schizophrenic phenomenologycould also be considered in statisticalanalyses, provided detailed and reli-able knowledge of dosage regimens isavailable. Overall, despite the possi-ble limitations of our data base, ourresults are highly consistent with anaccumulating literature, which sug-gests that positive symptoms, nega-tive symptoms, and social function-ing reflect three relatively separateunderlying processes in both themanifestation and the pathogenesisof schizophrenia (Pogue-Geile andZubin 1988; Walker and Lewine1988; Lenzenweger et al. 1989; Bel-lack et al. 1990). We offer our find-ings for their heuristic value andemphasize that replication of ourfindings is warranted and encour-aged.

By translating rich, clinically basedtheoretical positions into testable sta-tistical models, we were able to ob-jectively evaluate competing viewsconcerning the underlying organiza-tion of schizophrenic symptoms. Al-though our data do not address thespecific etiologies of each of Strausset al.'s three putative pathologicalprocesses, they do provide empiricalsupport for the hypothesized rela-tions among symptoms predicted bythe three-process model. Moreover,they are consistent with Crow's(1980, 1985, 1987) dual-processmodel of schizophrenic phenomenol-ogy, and they support the utility ofa multidimensional approach in un-derstanding schizophrenic symptoms(Strauss et al. 1974; Dworkin et al.1988).

Finally, while our data may be ofuse in theoretical discussions ofschizophrenic symptoms, we suggestthat they have an important clinicalimplication as well. As clinicians,through careful differential attentionto the three relatively independentdimensions of schizophrenic phenom-enology described by Strauss et al.and supported by our data, wemight further refine our understand-ing of our schizophrenic patients andthereby better tailor our therapeuticinterventions to their needs.

References

American Psychiatric Association.DSM-III: Diagnostic and StatisticalManual for Mental Disorders. 3rded. Washington, DC: The Associa-tion, 1980.American Psychiatric Association.DSM-lIl-R: Diagnostic and Statisti-cal Manual of Mental Disorders. 3rded., revised. Washington, DC: TheAssociation, 1987.

nloaded from

VOL. 17, NO. 3, 1991 523

Andreasen, N.C. Scale for the As-sessment of Negative Symptoms(SANS). Iowa City, IA: Universityof Iowa, 1981.

Andreasen, N.C; Endicott, ].;Spitzer, R.L.; and Winokur, G. Thefamily history method using diagnos-tic criteria: Reliability and validity.Archives of General Psychiatry,34:1229-1235, 1977.

Andreasen, N.C, and Olsen, S. Neg-ative v. positive schizophrenia: Defi-nition and validation. Archives ofGeneral Psychiatry, 39:789-794,1982.Bellack, A.S.; Morrison, R.L.;Wixted, J.T.; and Mueser, K.T. Ananalysis of social competence inschizophrenia. British Journal of Psy-chiatry, 156:809-818, 1990.

Bentler, P.M. Theory and Implemen-tation of EQS: A Structural Equa-tions Program. Los Angeles: BMDPStatistical Software, Inc., 1985.

Bentler, P.M., and Bonett, D.G. Sig-nificance tests and goodness-of-fit inthe analysis of covariance structures.Psychological Bulletin, 88:588-606,1980.

Bollen, K.A. Structural EquationsWith Latent Variables. New York:John Wiley & Sons, Inc., 1989.Carpenter, W.T., Jr.; Heinrichs,D.W.; and Wagman, A.M.I. Deficitand nondeficit forms of schizophre-nia: The concept. American Journalof Psychiatry, 145:578-583, 1988.Cornblatt, B.A.; Lenzenweger, M.F.;Dworkin, R.H.; and Erlenmeyer-Kimling, L. Positive and negativeschizophrenic symptoms, attention,and information processing. Schizo-phrenia Bulletin, 11:397-408, 1985.Crow, T.J. Molecular pathology ofschizophrenia: More than one dis-ease process? British Medical Journal,280:66-68, 1980.

Crow, T.J. The two-syndrome con-cept: Origins and current status.Schizophrenia Bulletin, 11:471-486,1985.

Crow, T. Two syndromes of schizo-phrenia as one pole of the continuumof psychosis: A concept of the na-ture of the pathogen and its genomiclocus. In: Henn, F.A., and DeLisi,L.E., eds. Handbook of Schizophre-nia: Neurochemistry and Neurophar-macology of Schizophrenia. Vol. 2.Amsterdam: Elsevier Science Pub-lishers, 1987. pp. 17-48.

Dworkin, R.H. Patterns of sex differ-ences in negative symptoms and so-cial functioning consistent with sepa-rate dimensions of schizophrenicpsychopathology. American Journalof Psychiatry, 147:347-349, 1990.

Dworkin, R.H., and Lenzenweger,M.F. Symptoms and the genetics ofschizophrenia: Implications for diag-nosis. American Journal of Psychia-try, 141:1541-1546, 1984.

Dworkin, R.H.; Lenzenweger, M.F.;Moldin, S.O.; Skillings, G.F.; andLevick, S.E. A multidimensional ap-proach to the genetics of schizophre-nia. American Journal of Psychiatry,145:1077-1083, 1988.

Essen-Moller, E. Psychiatrische unter-suchungen an einer serie von zwil-lingen [Psychiatric investigations of aseries of twins]. Ada Psychiatrica etNeurologica, 16(Suppl. 23):l-203,1941.

Gorsuch, R.L. Factor Analysis. 2nded. Hillsdale, NJ: Lawrence ErlbaumAssociates, 1983.

Hamilton, M. Fish's Schizophrenia.Bristol, England: Wright & Sons,1976.Harris, J.G., Jr. An abbreviated formof the Phillips rating scale of premor-bid adjustment in schizophrenia.

Journal of Abnormal Psychology,117:515-525, 1975.

Hayduk, L.A. Structural EquationModeling With LISREL: Essentialsand Advances. Baltimore, MD: JohnsHopkins University Press, 1987.

Joreskog, K.G., and Sorbom, D.LISREL VI: Analysis of Linear Struc-tural Relationships by MaximumLikelihood, Instrumental Variables,and Least Squares Methods. 3rd ed.Mooresville, IN: Scientific Software,1984.

Langfeldt, G. Some points regardingthe symptomatology and diagnosis ofschizophrenia. Ada Psychiatrica etNeurologica Scandinavica, 28(Suppl.80): 7-26, 1953.

Lenzenweger, M.F., and Dworkin,R.H. Assessment of premorbid socialcompetence in schizophrenia: Amethodological note. Journal of Ab-normal Psychology, 96:367-369,1987.

Lenzenweger, M.F.; Dworkin, R.H.;and Wethington, E. Models of posi-tive and negative symptoms inschizophrenia: An empirical evalua-tion of latent structures. Journal ofAbnormal Psychology, 98:62-70,1989.

Lenzenweger, M.F., and Loranger,A.W. Detection of familial schizo-phrenia using a psychometricmeasure of schizotypy. Archives ofGeneral Psychiatry, 46:902-907,1989.

Link, B.G.; Cullen, F.T.; Struening,E.; Shrout, P.E.; and Dohrenwend,B.P. A modified labeling theory ap-proach to mental disorders: An em-pirical assessment. American Socio-logical Review, 54:400-423, 1989.

Long, J.S. Confirmatory FactorAnalysis. Beverly Hills, CA: SagePublications, 1983.

nloaded from

Loranger, A.W.; Oldham, J.M.; andTulis, E.H. Familial transmission ofDSM-H1 borderline personality disor-der. Archives of General Psychiatry,39:795-799, 1982.

Marsh, H.W.; Balla, J.R.; and Mc-Donald, R.P. Goodness-of-fit indexesin confirmatory factor analysis: Theeffect of sample size. PsychologicalBulletin, 103:391-410, 1988.

Pogue-Geile, M.F., and Zubin, J.Negative symptomatology andschizophrenia: A conceptual andempirical review. International Jour-nal of Mental Health, 16:3-45,1988.

Shrout, P.E., and Fleiss, J.L. Intra-class correlations: Uses in assessingrater reliability. Psychological Bulle-tin, 86:420-428, 1979.

Spitzer, R.L.; Endicott, J.; and Gib-bon, M. Crossing the border intoborderline personality and borderlineschizophrenia. Archives of GeneralPsychiatry, 36:17-24, 1979.

Strauss, J.S.; Carpenter, W.T., Jr.;and Bartko, J.J. The diagnosis andunderstanding of schizophrenia. PartIII. Speculations on the processesthat underlie schizophrenic signs andsymptoms. Schizophrenia Bulletin,l(Experimental Issue No. ll):61-69,1974.

Strauss, J.S., and Harder, D.W. Thecase history rating scale: A method

for rating symptom and social func-tioning data from case records. Psy-chiatry Research, 4:333-345, 1981.

Tucker, L.R., and Lewis, C.A. Areliability coefficient for maximumlikelihood factor analysis. Psycho-metrika, 38:1-10, 1973.

Venables, P.H., and O'Connor, N. Ashort scale for rating paranoidschizophrenia. Journal of MentalScience, 105:815-818, 1959.

Walker, E., and Lewine, R.J. Thepositive/negative symptom distinc-tion in schizophrenia: Validity andetiological relevance. SchizophreniaResearch, 1:315-328, 1988.

Wing, J.K.; Cooper, J.E.; and Sarto-rius, N. The Measurement and Clas-sification of Psychiatric Symptoms.London: Cambridge UniversityPress, 1974.

Zigler, E., and Phillips, L. Socialeffectiveness and symptomatic be-haviors. Journal of Abnormal andSocial Psychology, 61:231-238,1960.

Zigler, E., and Glick, M. A Develop-mental Approach to Adult Psychopa-thology. New York: John Wiley &Sons, Inc., 1986.

Zubin, J. Negative symptoms: Arethey indigenous to schizophrenia?Schizophrenia Bulletin, 11:461-470,1985.

Acknowledgments

Preliminary results of this study werepresented at the 3rd annual meetingof the Society for Research in Psy-chopathology, Cambridge, Novem-ber 10-13, 1988. We thank BonnieEggena, Psy.D., Stephen Levick,M.D., Deborah Lichtenberger, A.B.,Steven Moldin, Ph.D., and GeraldSkillings, Psy.D., for their assistancein the early phases of this researchand Milton Strauss, Ph.D., for hishelpful comments. Computing re-sources for the present study wereprovided by the Cornell Institute forSocial and Economic Research,which is funded jointly by the Na-tional Science Foundation and Cor-nell University.

The Authors

Mark F. Lenzenweger, Ph.D., is As-sistant Professor, PsychopathologyArea, Department of Human Devel-opment, Cornell University, Ithaca,NY. Robert H. Dworkin, Ph.D., isAssistant Professor of Clinical Psy-chology, Departments of Anesthesiol-ogy and Psychiatry, College of Phy-sicians and Surgeons, ColumbiaUniversity, New York, NY. ElaineWethington, Ph.D., is Assistant Pro-fessor, Family Studies Area, Depart-ment of Human Development, Cor-nell University.

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