"Company motivates the miserable": the impact of consensus information on help seeking for psychological problems

Based on an attribution theory analysis, it was predicted that normal individuals (people who do not evidence a particular target problem) would be least motivated to seek help for a psychological problem when they believe that the problem is actuarially common (i.e., high consensus). Based on an analysis of how target problem people evaluate their psychological problem, however, it was predicted that such individuals (unlike normal individuals) should be maximally motivated to seek help when they believe that the problem is common. To test these predictions, target problem and normal individuals (high vs. average test anxious females) were given feedback that they possessed a problem (test anxiety). Individuals were then told that their problem was either common, uncommon, or given no consensus information. As predicted, the higher consensus information led to the least help-seeking behavior for the normal individuals and to the most help-seeking behavior for the target problem individuals.     

Relevance-driven information search in "pseudodiagnostic" reasoning

When faced with two competing hypotheses, people sometimes prefer to look at multiple sources of information in support of one hypothesis rather than to establish the diagnostic value of a single piece of information for the two hypotheses. This is termed pseudodiagnostic reasoning and has often been understood to reflect, among other things, poor information search strategies. Past research suggests that diagnostic reasoning may be more easily fostered when participants seek data to help in the selection of one of two competing courses of action as opposed to situations where they seek data to help infer which of two competing hypotheses is true. In the experiment reported here, we provide the first empirical evidence demonstrating that manipulating the relevance of the feature for which participants initially receive information determines whether they will make a nominally diagnostic or pseudodiagnostic selection. The discussion of these findings focuses on implications for the ability to engage in diagnostic hypothesis testing.     

The plausibility of the implausible: A critique of Snyder and Swann (1978)

Snyder and Swann (1978) advance an argument that individuals display a cognitive bias in testing hypotheses about the personal attributes of other people, i.e. they seek out information which is supportive of their hypothesis (hypothesis-confirming strategy). It is argued here that these authors confound the hypothesis a person might entertain (belief) with a hypothesis the person is asked to test (assigned task). The findings of two experimental studies in which task and belief were manipulated independently suggest that Snyder and Swann's (1978) results are due to the task manipulation and not to an hypothesis-confirming bias.     

Relevance-driven information search in “pseudodiagnostic” reasoning

When faced with two competing hypotheses, people sometimes prefer to look at multiple sources of information in support of one hypothesis rather than to establish the diagnostic value of a single piece of information for the two hypotheses. This is termed pseudodiagnostic reasoning and has often been understood to reflect, among other things, poor information search strategies. Past research suggests that diagnostic reasoning may be more easily fostered when participants seek data to help in the selection of one of two competing courses of action as opposed to situations where they seek data to help infer which of two competing hypotheses is true. In the experiment reported here, we provide the first empirical evidence demonstrating that manipulating the relevance of the feature for which participants initially receive information determines whether they will make a nominally diagnostic or pseudodiagnostic selection. The discussion of these findings focuses on implications for the ability to engage in diagnostic hypothesis testing.     

On people’s understanding of the diagnostic implications of probabilistic data

Two lines of prior research into the conditions under which people seek information are examined in light of two statistical definitions of diagnosticity. Five experiments are reported. In two, subjects selected information in order to test a hypothesis. In the remaining three, they selected information in order to convince someone else of the truth of a known hypothesis. A total of 567 university students served as subjects. The two primary conclusions were as follows: (1) When the task is highly structured by the environment, subjects select information diagnostically, and (2) when the task is less structured, so that subjects must seek relevant information not manifest, they select information pseudodiagnostically. Possible relations to other laboratory inference tasks and to clinical judgment are discussed.     

The role of learning data in causal reasoning about observations and interventions

Recent studies have shown that people have the capacity to derive interventional predictions for previously unseen actions from observational knowledge, a finding that challenges associative theories of causal learning and reasoning (e.g., Meder, Hagmayer, & Waldmann, 2008). Although some researchers have claimed that such inferences are based mainly on qualitative reasoning about the structure of a causal system (e.g., Sloman, 2005), we propose that people use both the causal structure and its parameters for their inferences. We here employ an observational trial-by-trial learning paradigm to test this prediction. In Experiment 1, the causal strength of the links within a given causal model was varied, whereas in Experiment 2, base rate information was manipulated while keeping the structure of the model constant. The results show that learners’ causal judgments were strongly affected by the observed learning data despite being presented with identical hypotheses about causal structure. The findings show furthermore that participants correctly distinguished between observations and hypothetical interventions. However, they did not adequately differentiate between hypothetical and counterfactual interventions.     

Implicit Theories and Their Role in Judgments and Reactions: A Word From Two Perspectives

In this target article, we present evidence for a new model of individual differences in judgments and reactions. The model holds that people's implicit theories about human attributes structure the way they understand and react to human actions and outcomes. We review research showing that when people believe that attributes (such as intelligence or moral character) are fixed, trait-like entities (an entity theory), they tend to understand outcomes and actions in terms of these fixed traits ("I failed the test because I am dumb" or "He stole the bread because he is dishonest"). In contrast, when people believe that attributes are more dynamic, malleable, and developable (an incremental theory), they tend to focus less on broad traits and, instead, tend to understand outcomes and actions in terms of more specific behavioral or psychological mediators ("I failed the test because of my effort or strategy" or "He stole the bread because he was desperate"). The two frameworks also appear to foster different reactions: helpless versus mastery-oriented responses to personal setbacks and an emphasis on retribution versus education or rehabilitation for transgressions. These findings are discussed in terms of their implications for personality, motivation, and social perception.     

Causal attribution from covariation information: the evidential evaluation model

It is hypothesized that causal attributions are made by transforming covariation information into evidence according to notions of evidential value, and that causal judgement is a function of the proportion of instances that are evaluated as confirmatory for the causal hypothesis under test: this is called the evidential evaluation model. An experiment was designed to test the judgemental rule in this model by setting up problems presenting consensus, distinctiveness, and consistency information in which the proportion of confirmatory instances varied but the objective contingency did not. It was found that judgements tended to vary with the proportion of confirmatory instances. Several other current models of causal judgement or causal attribution fail to account for this result. Similar findings have been obtained in studies of causal judgement from contingency information, so the present findings support an argument that the evidential evaluation model provides a unified account of judgement in both domains. Copyright © 2002 John Wiley & Sons, Ltd.     

Individual differences in causal learning and decision making

In judgment and decision making tasks, people tend to neglect the overall frequency of base-rates when they estimate the probability of an event; this is known as the base-rate fallacy. In causal learning, despite people's accuracy at judging causal strength according to one or other normative model (i.e., Power PC, DeltaP), they tend to misperceive base-rate information (e.g., the cause density effect). The present study investigates the relationship between causal learning and decision making by asking whether people weight base-rate information in the same way when estimating causal strength and when making judgments or inferences about the likelihood of an event. The results suggest that people differ according to the weight they place on base-rate information, but the way individuals do this is consistent across causal and decision making tasks. We interpret the results as reflecting a tendency to differentially weight base-rate information which generalizes to a variety of tasks. Additionally, this study provides evidence that causal learning and decision making share some component processes.     

Lay Theories of Personality: Cornerstones of Meaning in Social Cognition

Lay theories (or ‘implicit theories’) are cornerstones for social cognition: people use lay theories to help them make sense of complex and ambiguous behavior. In this study, we describe recent research on the entity and incremental theories (the belief that personality is fixed or malleable). In so doing, we demonstrate that each theory does not act alone. Instead, each is associated with a set of allied beliefs, the sum total of which cohere into two distinct meaning systems. We present evidence that these meaning systems produce systematic differences in a range of fundamental social cognition processes, with important implications for the field’s understanding of trait/situation attribution, moral judgment, person memory, and stereotyping. We further argue that because meaning systems serve a central meaning‐making function, people are motivated to believe that the meaning system they are using is effective and accurate. Accordingly, we present evidence that people exhibit processing distortions and compensatory mechanisms to minimize the impact of information that violates their meaning system. We discuss the implications of these findings for the field’s understanding of basic social cognition.     

Social comparison after success and failure: Biased search for information consistent with a self-serving conclusion

Based on the traditional and attributional perspectives on social comparison, it was hypothesized that the search for social comparison information after performance outcomes is biased so as to provide evidence consistent with a favorable self-evaluation. In Experiment 1, subjects were led to believe that they obtained 16 or 8 out of 20 items correct on a bogus social sensitivity test and were then led to expect that most other students performed either well or poorly on the test. They were then given the opportunity to inspect up to 50 scored answer sheets from previous subjects. Consistent with the hypothesis, failure subjects requested more information when they expected it to reveal that most students performed poorly than when they expected it to reveal that most students performed well; success subjects showed little interest in this additional information, regardless of their expectancies as to what it would reveal. Experiment 2 employed a different approach to manipulating performance outcomes and led subjects to expect that most other subjects performed better, the same, or worse than themselves. Regardless of their own performance, subjects showed the least interest in additional information in the higher score expectancy condition and the most interest in additional information in the lower score expectancy condition. The role that this information search bias may play in producing self-serving attributions for success and failure and maintaining positive self-evaluations was discussed.     

Strategy selection in causal reasoning: when beliefs and covariation collide.

The present study investigated how people combine covariation information (Cheng & Novick, 1990, 1992) with pre-existing beliefs (White, 1989) when evaluating causal hypotheses. Three experiments, using both within- and between-subjects designs, found that the use of covariation information and beliefs interacted, such that the effects of covariation were larger when people assessed hypotheses about believable than about unbelievable causal candidates. In Experiment 2, this interaction was observed when participants made judgments in stages (e.g., first evaluating covariation information about a causal candidate and then evaluating the believability of a candidate), as well as when the information was presented simultaneously. Experiment 3 demonstrated that this pattern was also reflected in participants' metacognitive judgments: Participants indicated that they weighed covariation information more heavily for believable than unbelievable candidates. Finally, Experiments 1 and 2 demonstrated the presence of individual differences in the use of covariation- and belief-based cues. That is, individuals who tended to base their causality judgments primarily on belief were less likely to make use of covariation information and vice versa. The findings were most consistent with White's (1989) causal power theory, which suggests that covariation information is more likely to be considered relevant to believable than unbelievable causes.     

Frequency of judgment as a context-like determinant of predictive judgments

Several studies have shown that predictive and causal judgments vary depending on whether the question used to assess the relationship between events is presented after each piece of information or only after all the available information has been observed. This effect could be understood by assuming that in the two cases people perceive that the test question requires that different sets of evidence be taken into account. This hypothesis is tested in the present experiments through contextual manipulations that take place at the time of training and at the time of test. Our results show that people use this contextual information to infer which set of events should be considered when making their subjective assessments. The results are at odds with current theoretical approaches, but it is possible to develop mechanisms that would allow these models to account for the observed evidence.     

Category transfer in sequential causal learning: the unbroken mechanism hypothesis

The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for the target effect in the transfer relation, we here propose an alternative explanation, the unbroken mechanism hypothesis. This hypothesis claims that categories are transferred from a previously learned causal relation to a new causal relation when learners assume a causal mechanism linking the two relations that is continuous and unbroken. The findings of two causal learning experiments support the unbroken mechanism hypothesis.     

Information-gathering processes: Diagnosticity,hypothesis-confirmatory strategies,and perceived hypothesis confirmation

Recent research has investigated the information-gathering strategies that people employ as they attempt to test hypotheses. Three such strategies of information seeking were examined. Two kinds of hypothesis-confirmation strategies were considered. The first of these concerned evidence being sought to the extent that it is more likely under the hypothesis being tested than under the alternative. The second kind of hypothesis-confirmation strategy refers to the tendency to ask questions that will have the effect of making the hypothesis under test appear to be true. In addition, a third kind of strategy is a diagnosing strategy under which people prefer evidence that is most differentially probable under the hypothesis and the alternative. Important changes in methodology from past work were made, and the data supported a predominant diagnosing strategy and a less significant, but nonetheless strong and consistent, tendency to ask hypothesis-confirming questions. In addition, subjects' choice of questions made it likely that they would perceive as confirmed the specific hypotheses they were testing. This occurred even though the questions employed were not constraining. Discussion involves the strategies of information gathering and the reasons underlying them as well as the implications of these strategies for the inferences people make about their predictive abilities.     

Illusory causation: why it occurs

Considerable evidence indicates that people overattribute causality to a given stimulus when it is salient or the focus of their attention—the so-called illusory-causation phenomenon. Although illusory causation has proved to be quite robust and generalizable, a compelling explanation for it has not been empirically documented. Four social-attribution studies were conducted to test the hypothesis that illusory causation occurs because salient information is initially registered, or perceptually organized, differently than nonsalient information. The results provide considerable support for the notion that people's literal point of view affects how they initially perceive, or extract, information from an observed interaction, which in turn affects their judgments regarding the causal influence exerted by each interactant.     

Information Seeking in a Non-Hypothesis Testing Task

The information gain model (Oaksford and Chater, Psychological Review 101, 608–631, 1994) advocates that participants attempt to achieve a larger expected information gain when they have to test an if-then rule or hypothesis. However, acquisition of larger expected information gain could also be operational when participants do not have to test a hypothesis. This study devised a new task to investigate whether participants would seek larger expected information gain when they were not required to test a hypothesis. The task required participants to select one out of two balance scales for weighing coins in order to detect an underweight coin. We discovered that participants more frequently selected the balance scale that provided smaller expected information gain. This finding suggests that the preference for larger expected information gain may not apply to non-hypothesis testing settings.     

Pick Your Poison: Choice of Activity Determines Mood Management Following a Stressful Task

People routinely seek out activities they believe will relieve stress. There has always been debate regarding the extent to which different activities, particularly those with aggressive content, successfully manage mood or worsen it. It is routinely believed that engaging in highly aggressive activities after becoming stressed worsens mood. However, unlike experiments, in real life people generally select activities that match their interests. In the present study, 105 university students were exposed to an acute stressor then randomized to either (a) a time filler control task; (b) to hit a bobo doll; or (c) given a choice of five different activities, some aggressive, some not. Results indicated that those who were given a choice of activities experienced the greatest reductions in stress and hostility. Furthermore, evidence did not suggest that more aggressive activities made participants more hostile, stressed, or aggressive.     

Behavioural consequences of motivated self-concept change

The present study examines how motivated self-concept changes are reflected in actual behaviour. Subjects were led to believe that either extroversion or introversion was related to success. Their preferences for others as interaction partners were then examined. The findings suggest that people seek others who confirmed the belief that they possessed the success-related attribute. Self-verification, as a possible strategy to confirm a desired self, was partially supported. © 1998 John Wiley & Sons, Ltd.     

Non-bayesian inference: causal structure trumps correlation

The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more probable when it was linked to evidence by a causal chain than when both variables shared a common cause; (b) predictive chains in which evidence is a cause of the hypothesis gave rise to higher judgments than diagnostic chains in which evidence is an effect of the hypothesis; and (c) direct chains gave rise to higher judgments than indirect chains. A Bayesian learning model was applied to our data but failed to explain them. An explanation-based hypothesis stating that statistical information will affect judgments only to the extent that it changes beliefs about causal structure is consistent with the results.