Scenario descriptor and laboratory studies evaluated a decision-theoretic model of stress arousal and coping propensity composed of 2 stress expectancies; namely, expected stress given engagement in coping activity and expected stress given nonengagement in coping activity. The model predicted (a) that coping propensity would vary inversely with the ratio of the first stress expectancy to the second and (b) that stress arousal would vary with the lesser of the 2 stress expectancies. It was also predicted that the smallest stress expectancy would dictate coping activity and that the proximity of the stress expectancies would engender stressing response conflict. Results supported the first hypothesis when differences in ratio values were salient. The second hypothesis also was supported, but in the scenario descriptor study only. Proximity of stress expectancies as sources of stress arousal received little or no support.

Valid clinical inferences may be said to emanate directly from both substantive and quantitative considerations. To the extent that either component houses deficiencies, clinical inferences will be undermined. The quantitative literature has reiterated the need to strive for homogeneity in the "objective-analysisinference" chain. However, in spite of its importance to valid clinical inference, this reminder has been overlooked with alarming frequency. This paper outlines three of the most common cases where quantitative errors have undermined data-based inferences. These cases include precomputational data aggregation, data rcsidualization of one form or another, and post hoc significance testing. In each instance, errors may be corrected so as to redress violation of the homogeneity of quantitative research components. Solutions in each case are discussed and illustrated with reference to published and unpublished examples. It is suggested that deployment of these solutions will enhance the quality of quantitative information and thus, the quality of clinical inferences.

According to attribution theory, controllability, locus, and stability are important dimensions underlying causal explanations. The extent to which these theoretical dimensions underlie lay explanations for physical symptoms is unclear. Accordingly, in this study, attributes relevant to the lay public were empirically derived using a multidimensional scaling (MDS) procedure. Undergraduates (N = 194) provided similarity judgments for 18 potential causes of physical discomfort. The MDS analysis yielded a three-dimensional solution. The first dimension captured the distinction between "physical" and "nonphysical" causes. The second dimension distinguished either "variable" versus "stable" causes or those that are "controllable" versus "uncontrollable" by health care professionals. The third dimension differentiated causes under "low" versus "high" personal control. These findings empirically confirm the theoretically proposed dimensions of "personal control" and "stability" and suggest the utility of considering the "physical/nonphysical" and "controllability by health care professional" distinctions in future work on attributions in the health domain.

The present study was conducted to examine the dimensionality of overt Type A behaviors elicited in a simulated stressful work environment. University students played a managerial role while being subjected to time and work-load pressures, and completed the Survey of Work Styles (SWS; Jackson & Gray, 1989). Eighteen behaviors, coded by two raters based on audiovisual recordings, yielded relatively high interrater reliabilities. Principal components analysis revealed four primary factors: Hurriedness, Irritability, Tension of the Lower Extremities, and Restlessness. These factors contribute to an understanding of Type A behavior in that they are the first to be derived from a purely observational approach rather than a combination of observational and self-report methods. Consistent with previous research, differential correlations between the factors and the SWS subscales supported a multi-dimensional interpretation of the Type A behavior pattern. Present findings are compared to those of previous studies of Type A dimensionality.

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