Psychopathology in anxiety disorders

Complaints of anxiety, often meetingDiagnostic and Statistical Manual of Mental Disorders, 3rd ed. (DSM-III), criteria for anxiety disorder, are among the most common problems presenting to health practitioners. In spite of the frequency of anxiety and anxiety disorders, little is known about the basic psychopathology of these conditions that would lead to the development of more efficient and effective treatments and possible preventive efforts. Recently, there has been an increase in research on the psychopathology of anxiety disorders from biological, psychological, and social perspectives. The National Institute of Mental Health's Clinical Research Branch sponsored a 2-day workshop of investigators representing diverse research approaches to discuss emerging issues and research practices within the anxiety disorders. Discussions centered on a review of the general areas of classification, phenomenology, and etiology. A selective summary of this workshop is presented along with recommendations for specific research directions.     

Forced classification: A simple application of a quantification method

This study formulates a property of a quantification method, the principle of equivalent partitioning (PEP). When the PEP is used together with Guttman's principle of internal consistency (PIC) in a simple way, the combination offers an interesting way of analyzing categorical data in terms of the variate(s) chosen by the investigator, a type of canonical analysis. The study discusses applications of the technique to multiple-choice, rank-order, and paired comparison data.This study was supported by the Natural Sciences and Engineering Research Council of Canada (Grant No. A7942). Comments on the earlier drafts from anonymous reviewers and the editor were much appreciated.     

Effects of diagnostic classification systems on clinical hypothesis-generation

In this study it was determined whether (a) classification as opposed to absence of classification has an effect on the quality of clinical hypotheses (b) the DSM-III-R and the CBCL have a different effect on the quality of clinical hypotheses, and (c) the potential difference between the DSM-III-R and the CBCL is moderated by the different number of syndromes identified by these systems. To investigate these questions, an experiment was conducted in which 86 clinicians generated hypotheses for six cases. The clinicians were divided into a DSM-III-R, a CBCL, and a control group. Of the six cases, two were classified by both classification systems as one syndrome, two were classified as one syndrome by the DSM-III-R but as two syndromes by the CBCL, and two were classified as two syndromes by the DSM-III-R but as one syndrome by the CBCL. The quality of the hypotheses was determined by means of four dependent variables selected from an overview of qualitative criteria: explanatory value, redundancy, possibility of operationalization, and specificity. No differences between the CBCL and the control groups were found. The DSM group performed better than the control group regarding explanatory value and redundancy. The DSM-III-R group also scored better than the CBCL group regarding explanatory value, particularly when the number of identified syndromes was two for the CBCL and one for the DSM-III-R.     

U-statistic hierarchical clustering

A monotone invariant method of hierarchical clustering based on the Mann-Whitney U-statistic is presented. The effectiveness of the complete-link, single-link, and U-statistic methods in recovering tree structures from error perturbed data are evaluated. The U-statistic method is found to be consistently more effective in recovering the original tree structures than either the single-link or complete-link methods.     

A note on analyzing ordered alternatives

A general method of devising stepwise multiple testing procedures with fixed experimentwise error is applied to the problem of non-parametric randomized block design with ordered alternatives. In addition, the method is applied to other models with ordered alternatives.The author wishes to thank the referees for helpful suggestions.     

Two simple classes of mastery scores based on the beta-binomial model

Two simple classes of mastery scores which are suitable for hand calculations are presented for beta-binomial test score distributions combined with linear and cubic referral success. The models provide a simple way to explore the consequences of selecting an arbitrary mastery score. Such assessment would be useful whenever the test user is not willing to posta priori a loss ratio, but wishes to look at the various consequences before aiming at a particular score.     

Stopping rules for multi-category computerized classification testing

Computerized classification testing (CCT) aims to classify persons into one of two or more possible categories to make decisions such as mastery/non-mastery or meet most/meet all/exceed. A defining feature of CCT is its stopping criterion: the test terminates when there is enough confidence to make a decision. There is abundant research on CCT with a single cut-off, and two common stopping criteria are the sequential probability ratio test (SPRT) statistic and the generalized likelihood ratio statistic (GLR). However, there is a relative scarcity of research extending the SPRT to the multi-hypothesis case for when there is more than one cut-off. In this paper, we propose a new multi-category GLR (mGLR) statistic as well as a stochastically curtailed version of the CCT with three or more categories. A simulation study was conducted to show that the mGLR statistic outperformed the existing stopping rules by generating shorter average test length without sacrificing classification accuracy. Results also revealed that the stochastically curtailed mGLR successfully increased test efficiency in certain testing conditions.     

Is monkey maternal abuse of offspring aggressive behavior?

This study was intended to probe the aggressive nature of monkey infant abuse by comparing the morphology of abusive behavior patterns with that of patterns allocated to both aggression and other categories of behavioral repertoires of macaques. This morphological analysis indicated that most abusive patterns should not be classified in the aggression category as they, at the motor end, differ greatly from macaque aggressive acts. In contrast, they perfectly resemble behaviors that monkeys usually display while manipulating inanimate objects. The implications of this finding for the pathogenic study of monkey infant abuse are discussed.     

Consciousness as a logically consistent and prognostic model of reality

The work demonstrates that brain might reflect the external world causal relationships in the form of a logically consistent and prognostic model of reality, which shows up as consciousness. The paper analyses and solves the problem of statistical ambiguity and provides a formal model of causal relationships as probabilistic maximally specific rules. We suppose that brain makes all possible inferences from causal relationships. We prove that the suggested formal model has a property of an unambiguous inference: from consistent premises we infer a consistent conclusion. It enables a set of all inferences to form a consistent model of the perceived world. Causal relationships may create fixed points of cyclic inter-predictable properties. We consider the “natural” classification introduced by John St. Mill and demonstrate that a variety of fixed points of the objects’ attributes forms a “natural” classification of the external world. Then we consider notions of “natural” categories and causal models of categories, introduced by Eleanor Rosch and Bob Rehder and demonstrate that fixed points of causal relationships between objects attributes, which we perceive, formalize these notions. If the “natural” classification describes the objects of the external world, and “natural” concepts the perception of these objects, then the theory of integrated information, introduced by G. Tononi, describes the information processes of the brain for “natural” concepts formation that reflects the “natural” classification. We argue that integrated information provides high accuracy of the objects identification. A computer-based experiment is provided that illustrates fixed points formation for coded digits.     

Classification of Antisocial Behaviors Along Severity and Frequency Parameters

Antisocial behaviors were systematically classified along a hierarchy of seriousness or severity that also accounted for frequency of occurrence and heterogeneity of behaviors. Items from the CD and ODD schedules of the NIMH DISC-IV and from the Elliot Delinquency Scales were listed at specified frequencies. Nine mental health clinicians rated the level of seriousness of each alternative on a scale from 0 (trivial) to 5 (very serious). Reliability of the ratings was assessed. Over two thirds of the items showed excellent agreement among the raters, 8% showed poor agreement and 21% showed fair to moderate agreement. The overall reliability of a single rater’s score was 0.56 and the reliability of the average was 0.84. The classification meets high psychometric standards for reliability and has face validity. The final output provides a classification along a spectrum that takes into account severity, frequency of occurrence during the previous year, and presence of multiple behaviors. It is useful for classification purposes and for longitudinal tracking of antisocial behavior.