The primary aim of this study was to examine the contributions of individual characteristics and strategic processing to the prediction of decision quality. Data were provided by 176 adults, ages 18 to 93 years, who completed computerized decision-making vignettes and a battery of demographic and cognitive measures. We examined the relations among age, domain-specific experience, working memory, and three measures of strategic information search to the prediction of solution quality using a 4-step hierarchical linear regression analysis. Working memory and two measures of strategic processing uniquely contributed to the variance explained. Results are discussed in terms of potential advances to both theory and intervention efforts. 1. Introduction 1.1. Decision Making Processes and Outcomes A significant body of research has examined problem solving and decision making performance in adulthood (see [1, 2] for reviews). Both problem solving and decision making are concerned with the ways in which people interpret problems, form goals, search information, and combine information to arrive at solutions. Researchers often employ think-aloud and other process-tracing techniques to investigate the processes governing information search and cessation [3, 4]. The extant literature demonstrates that relative to younger and middle-aged adults, older adults approach decision making with different goals, apply different heuristics, seek different amounts and types of information in the predecision phase, and offer different decisions (e.g., [4–6]). Research has examined several possible mechanisms to explain this age difference, including the role of cognitive resources (e.g., [5, 7]), the social context and personal experience [8, 9], affective context [10], and the decision domain [11]. Sophisticated studies have examined these factors individually and in combination [12]. For many decision tasks, basic and intermediate cognitive skills such as working memory and speed of processing often are the strongest predictor of decision outcome [13]. Process-tracing techniques may allow a more thorough examination of task performance and strategic processing [3, 4, 14, 15]. In the standard decision making task, materials are structured to reflect those available in the real-world, similar to the ecologically-rich social vignettes used in the everyday problem solving approach. Although in actual real-world information searches, people are able to view all of the available information simultaneously, an advantage to the process-tracing technique is that one is able to
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