Running Head: Pressure and Regulatory Focus What is Pressure? Evidence for Social Pressure as a Type of Regulatory Focus

Previous research suggests that pressure leads to choking when learning to classify items based on an explicit rule, but leads to excelling when learning to classify based on an implicit strategy. In this paper we relate social pressure to regulatory focus theory. We propose that the effects of pressure on performance arise because pressure induces a prevention focus that interacts with the more local reward structure of the task. To test this hypothesis, we repeat this previous research with a losses reward structure, so that participants under pressure are now in a regulatory fit. We also successfully replicate previous results with a gains reward structure. In contrast to participants who were attempting to maximize gains on each trial, participants attempting to minimize losses choked on the implicit learning task but excelled on the explicit learning tasks. The results suggest a three-way interaction between pressure level, task type, and reward structure. Pressure and Regulatory Focus 3 Pressure affects performance on several cognitive and motor tasks (e.g., Markman, Maddox, & Worthy, 2006; Beilock and Decaro, 2007; Beilock and Carr, 2005; Beilock, Kulp, Holt, & Carr, 2004; Beilock and Carr, 2001; Masters, 1992). In these tasks participants often choke under pressure whereby they underperform on a task relative to their normal performance level because of an acute stressor. Intriguingly, participants can also excel under pressure by performing better than they would otherwise perform without pressure. For example, Markman et al. (2006) found that participants choked under pressure when performing a classification task that required an explicit rule-based strategy, but excelled under pressure when performing a task that required an implicit information-integration strategy. These results are consistent with the Distraction Hypothesis (Beilock & Carr, 2005; Beilock et al., 2004; Markman et al., 2006; Wine, 1971), which proposes that pressure decreases available executive attention or working-memory resources leading to performance decrements on tasks that require an explicit strategy. A decline in available executive attention resources also increases people’s reliance on implicit strategies, which enhances performance on implicit information integration tasks. Relating Pressure to Regulatory Focus In this paper, we explore the possibility raised by Markman et al. (2006) that pressure manipulations induce a situational regulatory focus in participants (Higgins, 1997; Maddox, Baldwin, & Markman, 2006; Worthy, Maddox, & Markman, 2007; Markman, Baldwin, & Maddox, 2005; Grimm, Markman, Maddox, & Baldwin, 2008). Regulatory focus theory posits that people adopt one of two distinct regulatory foci: a promotion focus whereby one becomes sensitive to potential gains in the environment and a prevention focus whereby one becomes sensitive to potential losses in the environment. The pressure manipulation used in a number of studies hinges on the potential for a negative social outcome if the participant lets down a partner (e.g. Beilock & Carr, 2001; Markman et al., 2006; Gray, 2004; Beilock et al., 2004). This social pressure may induce a prevention focus. In contrast, participants who are not given a pressure manipulation are more likely to have a promotion focus because they are simply trying to complete the experiment and earn the required credit for participation. Previous research suggests that a person’s global regulatory focus interacts with the more local gains or losses available on each trial of the task that is being performed (Higgins, 2000; Maddox et al., 2006; Worthy et al., 2007). When there is a fit between regulatory focus and reward structure (i.e., a global promotion focus and gains or a global prevention focus and losses), then people are more capable of solving complex problem solving tasks which require executive attention than when there is a mismatch (i.e., a global prevention focus and gains or a global promotion focus and losses; Maddox et al., 2006; Markman et al., 2005; Worthy et al., 2007; Grimm et al., 2008). Previous research finds that participants in a regulatory fit are better than those in a mismatch at explicit rule-based learning tasks, but worse at implicit information integration learning tasks (Grimm et al., 2008; Maddox et al., 2006; Markman et al., 2005). There is also evidence that increased working memory capacity may enhance performance on rule-based tasks, but actually hinder performance on information–integration tasks (e.g. Decaro, Thomas, & Beilock, 2007; but see Tharp & Pickering, in press). One explanation for the improved performance on explicit rule-based tasks for participants in a regulatory fit is that a fit leads to an increase in executive working-memory resources. Pressure and Regulatory Focus 4 Thus, the results from Markman et al. (2006) are consistent with both the Distraction hypothesis and the Regulatory Fit hypothesis. In this paper, we distinguish these possibilities by replicating the previous study with a losses reward structure. In a losses reward structure, people lose points throughout the task and must minimize their losses. The Regulatory Fit hypothesis adds an intermediate step to the Distraction hypothesis. On this view, pressure does not decrease available working memory directly, but rather it induces a prevention focus which interacts with the reward structure of the task to create either a regulatory fit or mismatch. The regulatory mismatch causes decrements in available executive resources. Thus, we propose that participants performing the task under low and high pressure have different regulatory foci. Those performing under low pressure have a situational promotion focus while those performing under high pressure have a situational prevention focus. These distinct foci interact with the local reward structure to produce either a regulatory fit or mismatch. Participants who are in a pressure-induced prevention focus performing a task where responses result in losses should actually be in a regulatory fit. Thus, these participants should actually have an increased amount of available executive attention resources. Those performing rule-based tasks should now excel under pressure, while those performing information-integration tasks should choke. The Distraction hypothesis predicts the opposite because pressure should lead directly to decrements in available executive attention resources regardless of the reward structure of the task. We test these two contrasting hypotheses in the current experiment. Experiment 1 Participants learned to classify stimuli into one of two categories. Half the participants classified stimuli from a rule-based category structure. Figure 1a depicts a simple rule-based task in which the participant must focus on one of the two dimensions and determine the location on that dimension that separates the two categories. This task is typically thought to involve explicit hypothesis testing, and so it should be harmed by any procedure that decreases executive attention resources (Ashby, Alfonso-Reese, Turken, & Waldron, 1998; Maddox & Ashby, 2004; Maddox, Filoteo, Hejl, & Ing, 2004). The other participants classified stimuli from an information-integration category structure. The stimulus structure in Figure 1b rotates the category boundary 45-degrees in stimulus space. Thus, the rule that separates the categories cannot be stated easily. This stimulus configuration is thought to be best learned by a procedural or similaritybased process that is limited in its demands on working memory (Maddox & Ashby, 2004; Maddox, Ashby, & Bohil, 2003). Explicit hypothesis testing strategies can be used to solve these tasks, but they lead to suboptimal performance. In the current experiment participants lost points on each trial, but they lost fewer points for a correct classification than for an incorrect one. Their goal was to minimize how many points they lost. Participants were placed under low pressure or high pressure. Those under low pressure were simply asked to do their best by trying to lose as few points as possible. Participants under high pressure were told that they could earn a monetary bonus if both they and a (fictional) partner lost no more than a certain number of points. Furthermore, they were informed that their partner had already performed the task and had reached the criterion so it was up to them to earn the bonus for themselves and their partner. This type of manipulation has been used in numerous previous studies Pressure and Regulatory Focus 5 and has been shown to induce pressure (e.g. Beilock and Carr., 2001; Gray; 2004; Beilock et al., 2004; Beilock and Carr, 2005; Beilock and Decaro, 2007). Method Participants were 80 members of the University of Texas community who received course credit for their participation. Participants were randomly assigned to one of four between-subjects conditions which consisted of the factorial combination of two category types (Rule-Based vs. Information-Integration) and two types of pressure (High vs. Low). One participant in the Information-Integration Control condition was excluded because of experimenter error. Participants in the Low Pressure condition were asked to do their best. Participants in the High Pressure condition were told that they could earn a monetary bonus ($6) if both they and a (fictional) partner achieved a performance criterion (80% correct) over the final 80-trial block of the experiment. They were then informed that their partner had already completed the experiment and had reached the performance criterion, so the participant’s partner was relying on him or her to receive the bonus. Stimuli were Gabor patches varying in the frequency of the bars and their orientation relative to the computer screen shown. Participants performed eight blocks of 80 trials. On each trial a stimulus was presented on the screen and participants were asked to indicate which category they thought the stimulus belonged to by pressing a key. They were given corrective feedback. Participants under high pressure also heard a ‘ching’ or ‘buzzer’ sound as feedback for correct and incorrect classifications on each trial. Participants were told that they would lose points on each trial and that their goal was to minimize their losses. Participants lost only one point for a correct response, but three points for an incorrect response. A point meter on the right-hand side of the screen indicated how many points had been lost, and a line indicated how many points had to remain for reception of the bonus. The meter was reset before the beginning of each block.