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Schizophrenia Research

Letter to the Editors

Interpreting the PANSS: Measures, factors and

models

Dear Editors,

Given the wide spread use of the PANSS in

research and treatment assessment in schizophrenia

and related disorders, sophisticated understanding of

the psychometric properties of the scale is of

considerable interest. Factor analytic solutions of

symptom rating scales are in part scale-dependent,

disease-dependent, and state-dependent. Several

papers recently published in Schizophrenia Research

have examined external variables that might modify

the factorial structure of the PANSS. Fresan et al.

(2005) used principal components exploratory meth-

ods (EFA) to examine the cross-cultural validity of the

PANSS for assessing Mexican patients with schizo-

phrenia. They find that five factors are necessary to

account for the variation obtained in the PANSS

ratings of their sample of 150 Mexican patients. Based

upon the many previous studies that have reported a

5-factor structure for the PANSS, Fesnan et al.

conclude that PANSS is valid for assessment of

Mexican patients with schizophrenia. However due

to the limitations of EFA the findings of Fresnan et al.

are insufficient basis to establish the cross-cultural

validity of the PANSS in schizophrenia. Although

there is general agreement that the PANSS contains

five factors the PANSS study group (White et al.,

1997) previously pointed out that each study uniquely

specifies the number and content of items within each

factor. For example, although both Bell et al. (1994)

and Peuskens (1992) find five PANSS factors, Bell et

al. retains 20 items while Peuskens et al., include all

30 of the PANSS items. Lykouras et al. (2000) place

the items of anxiety, guilt and depression in the

0920-9964/$ - see front matter D 2005 Elsevier B.V. All rights reserved.

doi:10.1016/j.schres.2005.03.018

Depression component of their five factors but the

depression component of the Lindenmayer et al.

(1995) 5-factors adds the items of somatic concern

and preoccupation.

To determine which of 20 previous EFA models

best accounted for variations in PANSS ratings the

PANSS study group used the methods of confirma-

tory factor analysis (CFA) that provides fit statistics

to determine how close the model corresponds to the

empirical data. In its early form, factor analysis is an

exploratory technique (EFA) concerned with finding

the smallest number of common factors to account

for variation in a set of variables. Factor analysis has

evolved into a hypothesis testing tool through use of

CFA for modeling the correlations and covariances

between measured variables. A more precise exami-

nation of the structure of symptoms of schizophrenia

and transcultural validity of PANSS ratings is

possible using CFA methodology to evaluate the

equivalence of model parameters between groups.

CFA methods yield various dgoodness of fit indexesTthat report the degree to which each model

corresponds or accounts for the associations occur-

ring in the sample data. In the same large sample

multi-site study a new 5-factor model was presented

that met the existing criteria for a good fit model. To

differentiate this model from other five factor

models we adopted the term dpentagonal modelT.Because this was the first use of the term and the

model represents the most rigorous 5-factor solution

for the PANSS in schizophrenic patients the term

dpentagonal model should be reserved for this

model. Just such a distinction is maintained in the

studies of Fitzgerald et al. (2003) and Drake et al.

(2003).

The Fitzgerald et al. (2003) study concerned with

independent examination of the goodness of fit of the

79 (2005) 349–351

Letter to the Editors350

pentagonal model as well as alternative models in

PANSS ratings of Australian patients. Fitzgerald finds

that neither the pentagonal model nor any alternative

model examined met criteria for good fit. The results

of the study also show the pentagonal model of our

group achieved the highest level of fit and most

desirable scores on two indices of parsimony. More

recently, Drake et al. found the pentagonal model

(also referred to as White et al., 1997) to provide a

good fit to PANSS ratings at 18 months after the first

episode of hospitalization but not to the ratings at the

first episode. As in the Fitzgerald study, alternative 5-

factor models were also examined. The White et al.

model met good fit criteria, and was superior to

alternatives by goodness of fit and parsimony indices.

Drake and colleagues write that the bWhite et al.

model is the most validly derived and tested and it

probably best approximates the general underlying

structure of psychopathology in the later stages of the

disorderQ.Our claim of a good fit model was based upon the

rule of thumb criterion of Bentler that suggested a

cutoff of .90 as a standard for a good fit model.

Psychiatric rating scale data, especially when items

rated are not included in the diagnosis of the disorder

are included in the scale, are not likely to be normally

distributed. We used the Satorra–Bentler robust fit

index, a statistic that corrects for the bias in other

indices when data are markedly non-normal in

distribution. Bollen (1990) has observed that recom-

mended cut-offs are arbitrary. Bollen suggests that a

more salient criterion may be simply to compare the

fit of one’s model to the fit of other, prior models of

the same phenomenon. For example, a fit of .85 may

represent progress in a field where the best prior

model had a fit of .70.

Hu and Bentler (1999) based upon parametric

study of fit indices have suggested new criteria for a

good model fit that considers the use of two indices

and a fit of .95. In a recent critical discussion of the

use of fit indices, Marsch et al. (2004) caution against

using rules of thumb as absolute criteria for goodness

of fit. In view of the current understanding of the

interpretation of fit indices and the findings of

Fitzgerald et al. and Drake et al. the conclusions of

White et al. should perhaps be amended to state the

pentagonal model as the best fit model rather than the

a model meeting good fit criteria.

White et al. (2004) have reported on behavioral

dyscontrol in schizophrenia as measured by the

pentagonal model Activation factor as an important

variable in the prevention of discharge in elderly

chronic patients and note the importance of this

syndrome as an important dimension in the treat-

ment of schizophrenia separate from positive symp-

toms. Lindenmayer et al. (2004) identified an

Excitement factor also separate from positive

symptoms in both acute mania and schizophrenia.

The Excitement factor is composed of four of the

six item of the Activation factor.

Using CFA methods we examined the question of

whether PANSS rated negative symptoms and dys-

phoric mood of schizophrenia also occurred in major

depressive disorder and dementia (Galynker et al.,

2003). The findings suggest that although these

syndromes are similar each group reacts differently

to the scale and the syndromes are not equivalent

across the groups, Although the PANSS was found

suitable for assessment of dysphoric mood in schiz-

ophrenia, dementia and depression, PANSS items that

provide a measurement of negative symptoms of

schizophrenia are not suited to measurement of a

comparable syndrome in major depression. EFA

methodology is inadequate to determine if similar

distinctions exist between acute mania and behavioral

dyscontrol in schizophrenia.

In summary we emphasize important distinc-

tions between the questions amenable to EFA and

CFA analysis and make the point that the

terminology bpentagonal modelQ should not be

used in referring to all 5-factor PANSS models,

but rather should be used only when referring to

the 5-factor model of White, Harvey, Opler,

Lindenmayer, and the PANSS Study Group. Even

though this model may not provide a good model

fit it is the most rigorously derived model and has

repeatedly been found to provide the best fit in

chronic schizophrenia.

References

Bell, M.D., Lysaker, P.H., Beam-Goulet, J.L., Milstein, R.M.,

Lindenmayer, J.P., 1994. Five-component model of schizophre-

nia: assessing the factorial invariance of the positive and

negative syndrome scale. Psychiatry Research 52, 295–303.

Letter to the Editors 351

Bollen, K.A., 1990. Overall fit in covariance structure models:

two types of sample size effects. Psychological Bulletin 107,

225–256.

Drake, R.J., Dunn, G., Tarrier, N., Haddock, G., Haley, C.,

Lewis, S., 2003. The evolution of symptoms in the early

course of non-affective psychosis. Schizophrenia Research 63,

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Fitzgerald, P.B., de Castella, A.R., Brewer, K., Filia, K., Collins, J.,

Davey, P., Rolfe, T., Kulkarni, J., 2003. A confirmatory factor

analytic evaluation of the pentagonal PANSS model. Schizo-

phrenia Research 61, 97–104.

Fresan, A., De la Fuente-Sandoval, C., Loyzaga, C., Garcia-Anaya,

M., Meyenberg, N., Nicolini, H., Apiquian, R., 2005. A forced

five-dimensional factor analysis and concurrent validity of the

Positive and Negative Syndrome Scale in Mexican schizo-

phrenic patients. Schizophrenia Research 72, 123–129.

Galynker, I., White, L., Milak, M., Prinkhojian, A., Stein, J.,

Harvey, P.D., 2003. An empirical study of the factor

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White, L., Opler, L.A., Harvey, P.D., Parella, M., Friedman, J.,

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schizophrenic inpatients. Journal of Nervous and Mental

Disease 192, 880–883.

Leonard White

Clinical Neuroscience Center, Bldg. 47,

998 Crooked Hill Road,

Brentwood, NY 11711, United States

E-mail address: pgcnlww@omh.state.ny.us.

9 February 2005