Academic journal article Human Factors

Configural Displays Can Improve Nutrition-Related Decisions: An Application of the Proximity Compatibility Principle

Academic journal article Human Factors

Configural Displays Can Improve Nutrition-Related Decisions: An Application of the Proximity Compatibility Principle

Article excerpt

INTRODUCTION

To help consumers make informed decisions regarding food nutrition, the federal government enacted legislation requiring that food labels contain data on a minimum set of 12 nutrients (Nutrition Labeling and Education Act, 1990). The required information was intended to support a variety of decision-making activities, such as daily dietary planning, managing a medical or special diet, comparing brands and different product categories, evaluating the healthfulness of a specific product, and learning about specific nutritional characteristics of a product (Institute of Medicine, 1990; Levy, Fein, & Schucker, 1996). A format for the label was adopted, but it was based on practical constraints rather than on theoretical models of display design and decision making. Consequently, little information is available concerning how label designs might be optimized. Additionally, the lack of theoretical structure has resulted in contradictory interpretations of experimental results. For example, bar graph labels have been shown to be superior to numeric labels in some tasks (Mohr, Wyse, & Hansen, 1980) but not in others (Levy, Fein, & Schucker, 1992). It seems reasonable to expect that using label designs that more closely match the tasks for which the labels are intended to support would result in improved decision performance.

The proximity compatibility principle (PCP) is a general formulation of research findings that decision performance using a particular display type is best when the display of information matches the demands of the task (Boles & Wickens, 1987; Carswell & Wickens, 1987; Wickens & Andre, 1990; Wickens & Carswell, 1995). The PCP may then be understood as a set of principles that incorporates a variety of psychological mechanisms, such as attention, object perception, and working memory, to link the visual processing of display characteristics to the cognitive processing of decision task characteristics.

Display proximity and task proximity are two important aspects of the PCP (Carswell & Wickens, 1987; Wickens & Andre, 1990: Wickens & Carswell, 1995). Task proximity refers to the way an individual piece of information is used to perform a task. For example, task proximity is high when multiple pieces of information must be combined, compared, or integrated into a holistic judgment. High-proximity tasks divide attentional resources because multiple pieces of information from an array need to be considered simultaneously to make a decision. In contrast, task proximity is low when multiple pieces of information must be considered independently or when a set of information must be filtered to extract a single value. Low-proximity tasks require focused attention because individual pieces of information need to be considered to the exclusion of the remaining information in the array.

In a similar way, display proximity refers to the level of integration of display features. When different features of the same object represent multiple pieces of information, display proximity is high. When separate perceptual objects, such as individual numbers, represent multiple pieces of information, the display proximity is low. The PCP posits that a match between the task and display proximity will result in better performance than will mismatched task-display tandems. That is, high-proximity tasks should be best supported by high-proximity displays, and low-proximity tasks should be best supported by low-proximity displays.

This distinction for display proximity is based in part on research involving separable and configural stimulus dimensions (Pomerantz & Pristach, 1989). Separable relationships are defined by a lack of interaction among stimulus dimensions (Garner & Felfoldy, 1970). For example, color and shape are separable dimensions because the perception of color does not depend on the perception of shape. Hence, a square can be identified with equal speed regardless of whether it is blue or green: the color dimension does not interact with the shape dimension. …

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