Summary And Conclusions

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In this chapter we presented three broad categories of measures of emotion, including language, behavior, and physiology. We argued that the construct of emotion presents several challenges for assessment, the largest of which is the fact that emotions are reflected in multiple response systems, which are themselves loosely coupled and complexly interacting. Moreover, emotions can be thought of and measured as states or traits, as broad dimensions, or as unique specific emotions and as points along a temporal cascade of change. These challenges make issues of measurement reliability and validity especially complex.

Emotion constructs have multiple indicators, and each indicator reflects varying degrees of the intended construct, as well as more than the intended construct. Consequently, researchers cannot proceed with a monomethod approach or assume that one indicator is as good as any other indicator. Multimethod approaches are especially necessary in emotion research, though clearly such an approach will require a good deal of technical expertise and skillful collaborators. Nevertheless, multimethod assessment in emotion is starting to have important theoretical payoffs. Examples can be found in the work of Vrana, who has used multiple methods to differentiate negative emotions (1993, 1995) as well as locating multiple emotion assessment methods within the dimensional space defined by valance and arousal (Vrana & Rollock, 2002; Witvliet & Vrana, 1995, 2000). Modeling multiple methods within a consensual or methodinvariant space will be an important contribution to this area as well as provide researchers with a parsimonious system for organizing multiple methods. Until then, researchers should always consider using multiple methods in emotion research because doing so will almost always lead to gains in our knowledge of emotion.

Chapter 24


Aaron S. Benjamin

Similar to many scientific pursuits within psychology, the study of human cognition is an exercise that is equal parts imagination, deduction, and salesmanship. Theoretical claims are bootstrapped onto the elaborate but typically freewheeling artifices constructed by fellow psychologists who maintain equally fragile footing. Despite the blustery nature of cognitive theorizing, a central question remains unresolved: What constitutes necessary and sufficient evidence for the existence of a psychological mechanism?

Even the earliest theorists encountered situations in which multiple measures of nominally equivalent cognitive processes had different psychometric properties and showed differential effects of a common manipulation. Ebbinghaus (1885) noted, for example, that measures of relearning were much more sensitive to distant prior experience than measures of recall. Much of the history of cognitive psychology can be interpreted in the context of debates about how to reconcile such differences. The purpose of this chapter is to provide an illustration of how modern cognitive psychology deals with the divergences and convergences made apparent by the use of multiple measures and, in doing so, how those effects can be used profitably in the development of theory and the postulation of mental systems.

I will not attempt to address well-developed statistical tools that are the focus of chapters 18 to 21 and others in this volume. Rather, I will concentrate on model-based interpretations of multiple measures and how the application of such techniques has advanced theoretical development in cognitive psychology. In doing so, I will review four topics related to the specific problems addressed by and applications of multimethod approaches to understanding cognition. In the first and largest section, I will examine several modern examples of how measurements that combine systematically related dependent variables can yield functions that are more reliable and more informative than ones that can be derived from single measures. The second section will focus on the evaluation of the theories of cognition, most specifically on the question of how formal models can be tested in such a way that emphasizes their ability to account for extant data patterns without being so powerful that they predict other invalid data sets. Third, we will address the question of how traditional behavioral measurements in cognitive psychology can be meaningfully integrated with brain-based measures assessing electromagnetic properties of cellular material in the brain or hemodynamic properties of blood flow to the brain. Finally, we will examine one domain in which prominent theorists have tried to establish guidelines for what kind of and how much evidence is necessary for the postulation of a mental system.

To tie these sections together, the accompanying examples in each section will draw on current and historical developments in research on memory, with the objective of illustrating to the reader how the judicious combination of different measures has motivated important theoretical developments in that field.

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