Measurement and structure of pathological gambling behavior

The serious effects of pathological gambling on both gamblers and their families warrants research on the disorder. This study aimed at identifying components of pathological gambling with the goal of developing methods for early detection and preventive strategies. A factor analysis of behaviors hypothesized to relate to pathological gambling resulted in a multidimensional model of the disorder. Eight factors were identified, including distinct neurotic, psychopathic, and impulsive components, and used in a comparative analysis of 83 admitted compulsive gamblers and 61 nongamblers. Five of the factors differentiated the two groups even when sex, age, and education were controlled. Implications of these findings are discussed.     

Amount of information about the attitude object and attitude-behavior consistency

The synthesis of two separate lines of inquiry--research on information integration and longitudinal studies of attitudes--prompted the hypothesis that the degree of consistency between attitudes and behavior will increase as a function of the amount of information available about the attitude object. The hypothesis was tested in three separate longitudinal studies, ranging in length from 4 days to 4 months, that investigated the following behaviors: voting for candidates for political office, voting for two social policy election initiatives, and having an influenza vaccination. In support of the hypothesis, in each study, amount of information moderated the consistency between attitudes and behavior; and the significance of this relation remained even after controlling for the effects of a number of other potential moderators, including prior direct behavioral experience with the attitude object and attitude certainty. Consistent with previous research, direct behavioral experience was also a determinant of attitude-behavior consistency, and for the behavior of having an influenza vaccination, this relation was independent of the effect of amount of information. The discussion focuses on the interrelation among moderators of attitude-behavior consistency and on the theoretical implications of the findings.     

On the self-serving function of social anxiety: shyness as a self-handicapping strategy

We tested the hypothesis that socially anxious or shy individuals use their anxiety symptoms as a strategy to control attributions made about their performances in social-evaluative settings (i.e., self-handicapping strategies). Specifically, we predicted that trait-socially anxious or shy persons would report more symptoms of social anxiety in an evaluative setting in which anxiety or shyness could serve as an excuse for poor performance than would individuals in (a) an evaluative setting in which shyness was precluded as an excuse or (b) a nonevaluative setting. Furthermore, we predicted that this self-protective pattern of symptom reporting would not occur for individuals who were not trait-socially anxious because these persons would not commonly use such symptoms as a self-handicapping strategy. Results supported these predictions for male subjects, but not for female subjects. Sex differences in the strategic use of shyness are discussed in relation to other research on sex differences in the etiology and correlates of social anxiety.     

Statistical consistency and hypothesis testing for nonmetric multidimensional scaling

The properties of nonmetric multidimensional scaling (NMDS) are explored by specifying statistical models, proving statistical consistency, and developing hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. For these models, statistical consistency often depends crucially upon how error enters the model and how data are collected and summarized (e.g., by means, medians, or rank statistics). A maximum likelihood estimator for NMDS is developed, and its relationship to the standard Shepard-Kruskal estimation method is described. This maximum likelihood framework is used to develop a method for testing the overall fit of the model.