Evidence for the continuous latent structure of mania in the Epidemiologic Catchment Area from multiple latent structure and construct validation methodologies.
BACKGROUND
Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM) and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study.


METHODS
Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses, including factor analyses, taxometric procedures and ITLDM, in 10105 ECA community participants. In addition, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e. health service utilization, internalizing and externalizing disorders, and suicidal behavior).


RESULTS
Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6.52:1 odds over the best-fitting latent class model (LCM) of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models.


CONCLUSIONS
The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed.
Prisciandaro
J J
JJ
Department of Psychology, University at Buffalo, The State University of New York, Amherst, NY 14260-4110, USA.
Roberts
J E
JE
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001714:Bipolar Disorder / Q000145:classification / Q000175:diagnosis* / Q000453:epidemiology / Q000523:psychology; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D011569:Psychiatric Status Rating Scales; D012044:Regression Analysis; D055815:Young Adult