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A key characteristic of democratic politics is competition between groups, first of all political parties. Yet, the unavoidably partisan nature of political conflict has had too little influence on scholarship on political psychology. Despite more than 50 years of research on political parties and citizens, we continue to lack a systematic understanding of when and how political parties influence public opinion. We suggest that alternative approaches to political parties and public opinion can be best reconciled and examined through a richer theoretical perspective grounded in motivated reasoning theory. Clearly, parties shape citizens' opinions by mobilizing, influencing, and structuring choices among political alternatives. But the answer to when and how parties influence citizens' reasoning and political opinions depends on an interaction between citizens' motivations, effort, and information generated from the political environment (particularly through competition between parties). The contribution of motivated reasoning, as we describe it, is to provide a coherent theoretical framework for understanding partisan influence on citizens' political opinions. We review recent empirical work consistent with this framework. We also point out puzzles ripe for future research and discuss how partisanmotivated reasoning provides a useful point of departure for such work.

Whenever we see voters explain away their preferred candidate's weaknesses, dieters assert that a couple scoops of ice cream won't really hurt their weight loss goals, or parents maintain that their children are unusually gifted, we are reminded that people's preferences can affect their beliefs. This idea is captured in the common saying, “People believe what they want to believe.” But people don't simply believe what they want to believe. Psychological research makes it clear that “motivated beliefs” are guided by motivated reasoning—reasoning in the service of some self-interest, to be sure, but reasoning nonetheless. People generally reason their way to conclusions they favor, with their preferences influencing the way evidence is gathered, arguments are processed, and memories of past experience are recalled. Each of these processes can be affected in subtle ways by people's motivations, leading to biased beliefs that feel objective. In this symposium introduction, we set the stage for discussion of motivated beliefs in the papers that follow by providing more detail about the underlying psychological processes that guide motivated reasoning.

The CONSORT statement is used worldwide to improve the reporting of randomised controlled trials. Kenneth Schulz and colleagues describe the latest version, CONSORT 2010, which updates the reporting guideline based on new methodological evidence and accumulating experience

Some researchers have argued that anchoring in economic valuations casts doubt on the assumption of consistent and stable preferences. We present new evidence that explores the strength of certain anchoring results. We then present a theoretical framework that provides insights into why we should be cautious of initial empirical findings in general. The model importantly highlights that the rate of false positives depends not only on the observed significance level, but also on statistical power, research priors, and the number of scholars exploring the question. Importantly, a few independent replications dramatically increase the chances that the original finding is true.

We believe that journal reviewers (as well as editors and dissertation or thesis committee members) have to some extent perpetuated misconceptions about common method bias in self-report measures, including (a) that relationships between self-reported variables are necessarily and routinely upwardly biased, (b) other-reports (or other methods) are superior to self-reports, and (c) rating sources (e.g., self, other) constitute measurement methods. We argue against these misconceptions and make recommendations for what reviewers (and others) should reasonably expect from authors regarding common method bias. We believe it is reasonable to expect (a) an argument for why self-reports are appropriate, (b) construct validity evidence, (c) lack of overlap in items for different constructs, and (d) evidence that authors took proactive design steps to mitigate threats of method effects. We specifically do not recommend post hoc statistical control strategies; while some statistical strategies are promising, all have significant drawbacks and some have shown poor empirical results.

People base many decisions on affective forecasts, predictions about their emotional reactions to future events. They often display an impact bias, overestimating the intensity and duration of their emotional reactions to such events. One cause of the impact bias is focalism, the tendency to underestimate the extent to which other events will influence our thoughts and feelings. Another is people's failure to anticipate how quickly they will make sense of things that happen to them in a way that speeds emotional recovery. This is especially true when predicting reactions to negative events: People fail to anticipate how quickly they will cope psychologically with such events in ways that speed their recovery from them. Several implications are discussed, such as the tendency for people to attribute their unexpected resilience to external agents.

Recommender systems are becoming a salient part of many e-commerce websites. Much research has focused on advancing recommendation technologies to improve accuracy of predictions, although behavioral aspects of using recommender systems are often overlooked. In our studies, we explore how consumer preferences at the time of consumption are impacted by predictions generated by recommender systems. We conducted three controlled laboratory experiments to explore the effects of system recommendations on preferences. Studies 1 and 2 investigated user preferences for television programs across a variety of conditions, which were surveyed immediately following program viewing. Study 3 investigated the granularity of the observed effects within individual participants. Results provide strong evidence that the rating presented by a recommender system serves as an anchor for the consumer's constructed preference. Viewers' preference ratings are malleable and can be significantly influenced by the recommendation received. The effect is sensitive to the perceived reliability of a recommender system and, thus, not a purely numerical or priming-based effect. Finally, the effect of anchoring is continuous and linear, operating over a range of perturbations of the system. These general findings have a number of important implications (e.g., on recommender systems performance metrics and design, preference bias, potential strategic behavior, and trust), which are discussed.

One way to make judgments under uncertainty is to anchor on information that comes to mind and adjust until a plausible estimate is reached. This anchoring-and-adjustment heuristic is assumed to underlie many intuitive judgments, and insufficient adjustment is commonly invoked to explain judgmental biases. However, despite extensive research on anchoring effects, evidence for adjustment-based anchoring biases has only recently been provided, and the causes of insufficient adjustment remain unclear. This research was designed to identify the origins of insufficient adjustment. The results of two sets of experiments indicate that adjustments from self-generated anchor values tend to be insufficient because they terminate once a plausible value is reached (Studies 1a and 1b) unless one is able and willing to search for a more accurate estimate (Studies 2a-2c).

Human reasoning has been characterized as often biased, heuristic, and illogical. In this article, I consider recent findings establishing that, despite the widespread bias and logical errors, people at least implicitly detect that their heuristic response conflicts with traditional normative considerations. I propose that this conflict sensitivity calls for the postulation of logical and probabilistic knowledge that is intuitive and that is activated automatically when people engage in a reasoning task. I sketch the basic characteristics of these intuitions and point to implications for ongoing debates in the field.

This research examines how the body type of consumers affects the food consumption of other consumers around them. We find that consumers anchor on the quantities others around them select but that these portions are adjusted according to the body type of the other consumer. We find that people choose a larger portion following another consumer who first selects a large quantity but that this portion is significantly smaller if the other is obese than if she is thin. We also find that the adjustment is more pronounced for consumers who are low in appearance self‐esteem and that it is attenuated under cognitive load.