Data quality is one of the major concerns of using crowdsourcing websites such as Amazon Mechanical Turk (MTurk) to recruit participants for online behavioral studies. We compared two methods for ensuring data quality on MTurk: attention check questions (ACQs) and restricting participation to MTurk workers with high reputation (above 95% approval ratings). In Experiment 1, we found that high-reputation workers rarely failed ACQs and provided higher-quality data than did low-reputation workers; ACQs improved data quality only for low-reputation workers, and only in some cases. Experiment 2 corroborated these findings and also showed that more productive high-reputation workers produce the highest-quality data. We concluded that sampling high-reputation workers can ensure high-quality data without having to resort to using ACQs, which may lead to selection bias if participants who fail ACQs are excluded post-hoc.

The consumption of a food typically leads to a decrease in its subsequent intake through habituation--a decrease in one's responsiveness to the food and motivation to obtain it. We demonstrated that habituation to a food item can occur even when its consumption is merely imagined. Five experiments showed that people who repeatedly imagined eating a food (such as cheese) many times subsequently consumed less of the imagined food than did people who repeatedly imagined eating that food fewer times, imagined eating a different food (such as candy), or did not imagine eating a food. They did so because they desired to eat it less, not because they considered it less palatable. These results suggest that mental representation alone can engender habituation to a stimulus.

People appear to be unrealistically optimistic about their future prospects, as reflected by theory and research in the fields of psychology, organizational behavior, behavioral economics, and behavioral finance. Many real-world examples (e.g., consumer behavior during economic recessions), however, suggest that people are not always overly optimistic. I suggest that people can be both overly optimistic and pessimistic in their beliefs about future events, depending on whether they focus on success or on failure. More specifically, people judge the likelihood of desirable and undesirable events to be higher than similar neutral events because they misattribute the arousal those events evoke to their greater perceived likelihood. I demonstrated this stake-likelihood effect in 4 studies. In Study 1, arousal was shown to increase likelihood judgments. Study 2 demonstrated that such elevated likelihood judgments are due to misattribution of the arousal from having a stake in the outcome. Study 3 demonstrated that such misattribution of arousal occurs for desirable and undesirable events. Study 4 showed the effects of optimism and pessimism on likelihood judgments in a field setting with soccer fans. Together, the findings suggest that wishful thinking might be less prevalent than previously believed. Pessimism might be as likely as optimism in subjective probabilities.

Defaults effects can be created by social contexts. The observed choices of others can become social defaults, increasing their choice share. Social default effects are a novel form of social influence not due to normative or informational influence: participants were more likely to mimic observed choices when choosing in private than in public (experiment 1) and when stakes were low rather than high (experiment 2). Like other default effects, social default effects were greater for uncertain rather than certain choices (experiment 3) and were weaker when choices required justification (experiment 4). Social default effects appear to occur automatically as they become stronger when cognitive resources are constrained by time pressure or load, and they can be sufficiently strong to induce preference reversals (experiments 5 and 6). D ecisions often occur in a social context. Whether in a local hardware store or a foreign restaurant, people routinely make choices in the presence of other people. Many of the processes and influences on choices made in isolation should apply to choices made in social contexts, but social contexts (even when only inferred) can have potent and unique influences on perception and behavior. We suggest that when a person is deciding between options for which her preferences are not well formed, observing the

Several researchers have relied on, or advocated for, internal meta-analysis, which involves statistically aggregating multiple studies in a paper to assess their overall evidential value. Advocates of internal meta-analysis argue that it provides an efficient approach to increasing statistical power and solving the file-drawer problem. Here we show that the validity of internal meta-analysis rests on the assumption that no studies or analyses were selectively reported. That is, the technique is only valid if (a) all conducted studies were included (i.e., an empty file drawer), and (b) for each included study, exactly one analysis was attempted (i.e., there was no p-hacking). We show that even very small doses of selective reporting invalidate internal meta-analysis. For example, the kind of minimal p-hacking that increases the false-positive rate of 1 study to just 8% increases the false-positive rate of a 10-study internal meta-analysis to 83%. If selective reporting is approximately zero, but not exactly zero, then internal meta-analysis is invalid. To be valid, (a) an internal meta-analysis would need to contain exclusively studies that were properly preregistered, (b) those preregistrations would have to be followed in all essential aspects, and (c) the decision of whether to include a given study in an internal meta-analysis would have to be made before any of those studies are run.