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EXPRESS: Unidirectional rating scales overestimate the illusory causation phenomenon
Abstract
Illusory causation is a phenomenon in which people mistakenly perceive a causal relationship between a cue and outcome even though the contingency between them is actually zero. Illusory causation studies typically use a unidirectional causal rating scale, where one endpoint refers to no relationship and the other to a strongly positive causal relationship. This procedure may bias mean causal ratings in a positive direction, either by censoring negative ratings or by discouraging participants from giving the normative rating of zero which is at the bottom extreme of the scale. To test this possibility, we ran two experiments that directly compared the magnitude of causal illusions when assessed with a unidirectional (zero - positive) versus a bidirectional (negative - zero - positive) rating scale. Experiment 1 used high cue and outcome densities (both 75%) whereas Experiment 2 used neutral cue and outcome densities (both 50%). Across both experiments, we observed a larger illusory causation effect in the Unidirectional group compared to the Bidirectional group, despite both groups experiencing the same training trials. The causal illusions in Experiment 2 were observed despite participants accurately learning the conditional probabilities of the outcome occurring in both the presence and absence of the cue, suggesting that the illusion is driven by the inability to accurately integrate conditional probabilities to infer causal relationships. Our results indicate that although illusory causation is a genuine phenomenon that is observable with either a undirectional or bidirectional rating scale, its magnitude may be overestimated when unidirectional rating scales are used.
... A scale from -100 to 100 for the contingency judgment has also been used in the past, considering the possibility of a negative contingency. Although new research suggests bidirectional scales should be used (Ng et al., 2023), previous research indicated that limiting the scale to the 0 to 100 range is unlikely to lead to a floor effect . Therefore, the unidirectional 0 to 100 scale was employed, which is the most commonly used range in comparable contingency judgment experiments. ...
Objectives: The purpose of this study was to examine the effect of task content in the illusion of control effect (i.e. the tendency to overestimate our chances of success beyond the objective probabilities). A secondary exploratory objective was to analyze individual differences in task performance. Methods: A total of 88 participants (36 aerospace engineers and 52 undergraduate psychology students) participated in this experiment performing a standard drug-related contingency judgment task (with a fictitious drug that could be effective for a fictitious disease) and a novel analogue task with aerospace content. In both tasks, there was a null contingency between treatment and recovery. However, the chance of spontaneous recovery was 70%, a baseline rate which tends to produce strong illusion of control effects in null contingency setups. The participants were tasked to identify the treatment effectivity (the normative answer was no effectivity at all). Results: The data showed a strong illusion of control with no significant difference between groups and tasks. A non-negligible number of participants displayed inefficient strategies during task performance. Discussion: Both tasks produced comparable results with no significant differences. Our data suggests that inter-individual effects need to be considered in future research and measures of central tendency must be used with caution.
... Although unidirectional scales have been habitually used in contemporary studies on causal illusions (e.g. Barberia et al., 2019;Moreno-Fernández et al., 2021;Vicente et al., 2023), Ng et al. (2024) recently showed that these scales, compared to their bidirectional analogues, can inflate the magnitude of the observed illusions. In our medical scenario, a bidirectional scale might involve values ranging from −100 to +100, the negative ones indicating a preventive relationship (i.e. a harmful influence of the drug over the disease). ...
In this research, we investigated individual differences in the formation and persistence of causal illusions. In a re‐analysis of existing data, we identified two clusters of participants – persistent and adjusting – based on their trajectories in learning from repeated exposure to null contingencies. The persistent cluster maintained stable causal illusions, while the adjusting cluster demonstrated a reduction over time. This re‐analysis provided a nuanced understanding of individual differences in causal learning, emphasizing the differential role of probability estimations in predicting causal judgements. These findings were replicated in a subsequent study, highlighting the robustness of the identified effects. In a pre‐registered study, we extended the paradigm to include a second phase (active phase) to assess how individual differences in causal illusion trajectories in the passive phase would manifest when participants had agency in the information gathering process. The results were consistent with those of the two previous studies and confirmed our primary hypothesis that the adjusting cluster would exhibit a lower tendency to introduce the candidate cause on learning trials, and would, therefore, observe a higher frequency of cause–absent trials. Together, these studies provide comprehensive insights into the underpinnings of causal illusion development and persistence, potentially informing de‐biasing interventions.
... The midpoint was marked with a tick and labelled "has NO effect on". A bidirectional rating scale was used to provide a conservative measure of the illusory causation effect (see Ng et al., 2023). Once participants were happy with their rating they could click Continue to progress. ...
The illusory causation effect describes the tendency to judge an unrelated cue and outcome to be causally related. The standard procedure for assessing the illusion is based on the implicit assumptions that participants start as naïve observers with no prior beliefs about the likely relationship between the cue and outcome, and that learning can be adequately captured as a point-estimate causal rating after null contingency training. Here, we use a novel distributional measure to assess participants' beliefs over a range of causal relationships prior to, as well as after, exposure to non-contingent cues and outcomes. Across two experiments with different causal scenarios and 50% cue and outcome density, we show that participants have an initial bias towards expecting a causal relationship between the cue and outcome, and that this bias is mostly corrected after exposure to the null contingency. We conclude that distributional measures of causal beliefs can offer novel insights in understanding the illusory causation effect.
Traditional associative learning theories predict that training with feature negative (A+/AB-) contingencies leads to the feature B acquiring negative associative strength and becoming a conditioned inhibitor (i.e., prevention learning). However, feature negative training can sometimes result in negative occasion setting, where B modulates the effect of A. Other studies suggest that participants learn about configurations of cues rather than their individual elements. In this study, we administered simultaneous feature negative training to participants in an allergist causal learning task and tested whether evidence for these three types of learning (prevention, modulation, configural) could be captured via self-report in the absence of any procedural manipulation. Across two experiments, we show that only a small subset of participants endorse the prevention option, suggesting that traditional associative models that predict conditioned inhibition do not completely capture how humans learn about negative contingencies. We also show that the degree of transfer in a summation test corresponds to the implied causal structure underlying conditioned inhibition, occasion-setting, and configural learning, and that participants are only partially sensitive to explicit hints about causal structure. We conclude that feature negative training is an ambiguous causal scenario that reveals individual differences in the representation of inhibitory associations, potentially explaining the modest group-level inhibitory effects often found in humans.
Judgments of a treatment's effectiveness are usually biased by the probability with which the outcome (e.g., symptom relief) appears: even when the treatment is completely ineffective (i.e., there is a null contingency between cause and outcome), judgments tend to be higher when outcomes appear with high probability. In this research, we present ambiguous stimuli, expecting to find individual differences in the tendency to interpret them as outcomes. In Experiment 1, judgments of effectiveness of a completely ineffective treatment increased with the spontaneous tendency of participants to interpret ambiguous stimuli as outcome occurrences (i.e., healings). In Experiment 2, this interpretation bias was affected by the overall treatment-outcome contingency, suggesting that the tendency to interpret ambiguous stimuli as outcomes is learned and context-dependent. In conclusion, we show that, to understand how judgments of effectiveness are affected by outcome probability, we need to also take into account the variable tendency of people to interpret ambiguous information as outcome occurrences.
Rationale
Self-limited diseases resolve spontaneously without treatment or intervention. From the patient's viewpoint, this means experiencing an improvement of the symptoms with increasing probability over time. Previous studies suggest that the observation of this pattern could foster illusory beliefs of effectiveness, even if the treatment is completely ineffective. Therefore, self-limited diseases could provide an opportunity for pseudotherapies to appear as if they were effective.
Objective
In three computer-based experiments, we investigate how the beliefs of effectiveness of a pseudotherapy form and change when the disease disappears gradually regardless of the intervention.
Methods
Participants played the role of patients suffering from a fictitious disease, who were being treated with a fictitious medicine. The medicine was completely ineffective, because symptom occurrence was uncorrelated to medicine intake. However, in one of the groups the trials were arranged so that symptoms were less likely to appear at the end of the session, mimicking the experience of a self-limited disease. Except for this difference, both groups received similar information concerning treatment effectiveness.
Results
In Experiments 1 and 2, when the disease disappeared progressively during the session, the completely ineffective medicine was judged as more effective than when the same information was presented in a random fashion. Experiment 3 extended this finding to a new situation in which symptom improvement was also observed before the treatment started.
Conclusions
We conclude that self-limited diseases can produce strong overestimations of effectiveness for treatments that actually produce no effect. This has practical implications for preventative and primary health services. The data and materials that support these experiments are freely available at the Open Science Framework (https://bit.ly/2FMPrMi)
Illusory causation refers to a consistent error in human learning in which the learner develops a false belief that two unrelated events are causally associated. Laboratory studies usually demonstrate illusory causation by presenting two events—a cue (e.g., drug treatment) and a discrete outcome (e.g., patient has recovered from illness)—probabilistically across many trials such that the presence of the cue does not alter the probability of the outcome. Illusory causation in these studies is further augmented when the base rate of the outcome is high, a characteristic known as the outcome density effect. Illusory causation and the outcome density effect provide laboratory models of false beliefs that emerge in everyday life. However, unlike laboratory research, the real-world beliefs to which illusory causation is most applicable (e.g., ineffective health therapies) often involve consequences that are not readily classified in a discrete or binary manner. This study used a causal learning task framed as a medical trial to investigate whether similar outcome density effects emerged when using continuous outcomes. Across two experiments, participants observed outcomes that were either likely to be relatively low (low outcome density) or likely to be relatively high (high outcome density) along a numerical scale from 0 (no health improvement) to 100 (full recovery). In Experiment 1, a bimodal distribution of outcome magnitudes, incorporating variance around a high and low modal value, produced illusory causation and outcome density effects equivalent to a condition with two fixed outcome values. In Experiment 2, the outcome density effect was evident when using unimodal skewed distributions of outcomes that contained more ambiguous values around the midpoint of the scale. Together, these findings provide empirical support for the relevance of the outcome density bias to real-world situations in which outcomes are not binary but occur to differing degrees. This has implications for the way in which we apply our understanding of causal illusions in the laboratory to the development of false beliefs in everyday life.
Electronic supplementary material
The online version of this article (10.1186/s41235-018-0149-9) contains supplementary material, which is available to authorized users.
We carried out an experiment using a conventional causal learning task but extending the number of learning trials participants were exposed to. Participants in the standard training group were exposed to 48 learning trials before being asked about the potential causal relationship under examination, whereas for participants in the long training group the length of training was extended to 288 trials. In both groups, the event acting as the potential cause had zero correlation with the occurrence of the outcome, but both the outcome density and the cause density were high, therefore providing a breeding ground for the emergence of a causal illusion. In contradiction to the predictions of associative models such the Rescorla-Wagner model, we found moderate evidence against the hypothesis that extending the learning phase alters the causal illusion. However, assessing causal impressions recurrently did weaken participants’ causal illusions.
Response styles are a source of contamination in questionnaire ratings, and therefore they threaten the validity of conclusions drawn from marketing research data. In this article, the authors examine five forms of stylistic responding (acquiescence and disacquiescence response styles, extreme response style/response range, midpoint responding, and noncontingent responding) and discuss their biasing effects on scale scores and correlations between scales. Using data from large, representative samples of consumers from 11 countries of the European Union, the authors find systematic effects of response styles on scale scores as a function of two scale characteristics (the proportion of reverse-scored items and the extent of deviation of the scale mean from the midpoint of the response scale) and show that correlations between scales can be biased upward or downward depending on the correlation between the response style components. In combination with the apparent lack of concern with response styles evidenced in a secondary analysis of commonly used marketing scales, these findings suggest that marketing researchers should pay greater attention to the phenomenon of stylistic responding when constructing and using measurement instruments.
In 4 experiments, 144 depressed and 144 nondepressed undergraduates (Beck Depression Inventory) were presented with one of a series of problems varying in the degree of contingency. In each problem, Ss estimated the degree of contingency between their responses (pressing or not pressing a button) and an environmental outcome (onset of a green light). Depressed Ss' judgments of contingency were suprisingly accurate in all 4 experiments. Nondepressed Ss overestimated the degree of contingency between their responses and outcomes when noncontingent outcomes were frequent and/or desired and underestimated the degree of contingency when contingent outcomes were undesired. Thus, predictions derived from social psychology concerning the linkage between subjective and objective contingencies were confirmed for nondepressed but not for depressed Ss. The learned helplessness and self-serving motivational bias hypotheses are evaluated as explanations of the results. (4½ p ref)
We present here "Just Another Tool for Online Studies" (JATOS): an open source, cross-platform web application with a graphical user interface (GUI) that greatly simplifies setting up and communicating with a web server to host online studies that are written in JavaScript. JATOS is easy to install in all three major platforms (Microsoft Windows, Mac OS X, and Linux), and seamlessly pairs with a database for secure data storage. It can be installed on a server or locally, allowing researchers to try the application and feasibility of their studies within a browser environment, before engaging in setting up a server. All communication with the JATOS server takes place via a GUI (with no need to use a command line interface), making JATOS an especially accessible tool for researchers without a strong IT background. We describe JATOS' main features and implementation and provide a detailed tutorial along with example studies to help interested researchers to set up their online studies. JATOS can be found under the Internet address: www.jatos.org.
In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena.
Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion.
Researchers have warned that causal illusions are at the root of many superstitious beliefs and fuel many people's faith in pseudoscience, thus generating significant suffering in modern society. Therefore, it is critical that we understand the mechanisms by which these illusions develop and persist. A vast amount of research in psychology has investigated these mechanisms, but little work has been done on the extent to which it is possible to debias individuals against causal illusions. We present an intervention in which a sample of adolescents was introduced to the concept of experimental control, focusing on the need to consider the base rate of the outcome variable in order to determine if a causal relationship exists. The effectiveness of the intervention was measured using a standard contingency learning task that involved fake medicines that typically produce causal illusions. Half of the participants performed the contingency learning task before participating in the educational intervention (the control group), and the other half performed the task after they had completed the intervention (the experimental group). The participants in the experimental group made more realistic causal judgments than did those in the control group, which served as a baseline. To the best of our knowledge, this is the first evidence-based educational intervention that could be easily implemented to reduce causal illusions and the many problems associated with them, such as superstitions and belief in pseudoscience.
The illusion of control consists of overestimating the influence that our behavior exerts over uncontrollable outcomes. Available evidence suggests that an important factor in development of this illusion is the personal involvement of participants who are trying to obtain the outcome. The dominant view assumes that this is due to social motivations and self-esteem protection. We propose that this may be due to a bias in contingency detection which occurs when the probability of the action (i.e., of the potential cause) is high. Indeed, personal involvement might have been often confounded with the probability of acting, as participants who are more involved tend to act more frequently than those for whom the outcome is irrelevant and therefore become mere observers. We tested these two variables separately. In two experiments, the outcome was always uncontrollable and we used a yoked design in which the participants of one condition were actively involved in obtaining it and the participants in the other condition observed the adventitious cause-effect pairs. The results support the latter approach: Those acting more often to obtain the outcome developed stronger illusions, and so did their yoked counterparts.
Previous investigations have shown that perceived contingency between responses and outcomes increases with the frequency of positive outcomes in the absence of actual contingency. In the present experiment with 30 undergraduates, judgments were obtained when both response alternatives were active choices (as in previous experiments), and when one alternative was to make no response. In the latter case, judgments were more accurate and less influenced by the frequency of positive outcomes. This result was predicted by the hypothesis that when both alternatives are active, Ss tend to assume that in the absence of any response no positive outcomes would occur. This faulty assumption, which is hypothesized to be one source of distortion in the judgment of contingency, is ruled out when no response is an explicit alternative within the task. (French abstract) (9 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
It is well known that certain variables can bias judgements about the perceived contingency between an action and an outcome, making them depart from the normative predictions. For instance, previous studies have proven that the activity level or probability of responding, P(R), is a crucial variable that can affect these judgements in objectively noncontingent situations. A possible account for the P(R) effect is based on the differential exposure to actual contingencies during the training phase, which is in turn presumably produced by individual differences in participants' P(R). The current two experiments replicate the P(R) effect in a free-response paradigm, and show that participants' judgements are better predicted by P(R) than by the actual contingency to which they expose themselves. Besides, both experiments converge with previous empirical data, showing a persistent bias that does not vanish as training proceeds. These findings contrast with the preasymptotic and transitory effect predicted by several theoretical models.
Active contingency tasks, such as those used to explore judgments of control, suffer from variability in the actual values of critical variables. The authors debut a new, easily implemented procedure that restores control over these variables to the experimenter simply by telling participants when to respond, and when to withhold responding. This command-performance procedure not only restores control over critical variables such as actual contingency, it also allows response frequency to be manipulated independently of contingency or outcome frequency. This yields the first demonstration, to our knowledge, of the equivalent of a cue density effect in an active contingency task. Judgments of control are biased by response frequency outcome frequency, just as they are also biased by outcome frequency.
In 4 experiments, 144 depressed and 144 nondepressed undergraduates (Beck Depression Inventory) were presented with one of a series of problems varying in the degree of contingency. In each problem, Ss estimated the degree of contingency between their responses (pressing or not pressing a button) and an environmental outcome (onset of a green light). Depressed Ss' judgments of contingency were suprisingly accurate in all 4 experiments. Nondepressed Ss overestimated the degree of contingency between their responses and outcomes when noncontingent outcomes were frequent and/or desired and underestimated the degree of contingency when contingent outcomes were undesired. Thus, predictions derived from social psychology concerning the linkage between subjective and objective contingencies were confirmed for nondepressed but not for depressed Ss. The learned helplessness and self-serving motivational bias hypotheses are evaluated as explanations of the results. (41/2 p ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
Previous experiments have shown that educated adults generally fail to show an intuitive appreciation of correlation or contingency when judging the relation between events on the basis of a serial presentation. The effect on judgment of displaying information serially or in a summary form was examined. In contrast with some previous experiments, the events to be judged were identified in a way which should strongly suggest that the operation of chance must be taken into account. The Ss judged the amount of control exerted by cloud seeding over rainfall. The events (seeding or no seeding followed by rain or no rain) were presented to 1 group only serially, to a 2nd group in both ways with the serial display preceding the summary. Only in the group which received the summary without the serial display were the judgments of a majority of Ss more consistent with an appropriate rule of judgment involving a comparison of probabilities than with 1 or another of several inappropriate rules involving the frequency of certain favourable events.
3 experiments are reported in which Ss were asked to judge the degree of contingency between responses and outcomes. They were exposed to 60 trials on which a choice between 2 responses was followed by 1 of 2 possible outcomes. Each S judged both contingent and noncontingent problems. Some Ss actually made response choices while others simply viewed the events. Judgments were made by Ss who attempted to produce a single favorable outcome or, on the other hand, to control the occurrence of two neutral outcomes. In all conditions the amount of contingency judged was correlated with the number of successful trials, but was entirely unrelated to the actual degree of contingency. Accuracy of judgment was not improved by pretraining Ss on selected examples, even though it was possible to remove the correlation between judgment and successes by means of an appropriate selection of pretraining problems. The relation between everyday judgments of causal relations and the present experiment is considered.
In cause-outcome contingency judgement tasks, judgements often reflect the actual contingency but are also influenced by the overall probability of the outcome, P(O). Action-outcome instrumental learning tasks can foster a pattern in which judgements of positive contingencies become less positive as P(O) increases. Variable contiguity between the action and the outcome may produce this bias. Experiment 1 recorded judgements of positive contingencies that were largely uninfluenced by P(O) using an immediate contiguity procedure. Experiment 2 directly compared variable versus constant contiguity. The predicted interaction between contiguity and P(O) was observed for positive contingencies. These results stress the sensitivity of the causal learning mechanism to temporal contiguity.
A number of studies using trial-by-trial learning tasks have shown that judgments of covariation between a cue c and an outcome o deviate from normative metrics. Parameters based on trial-by-trial predictions were estimated from signal detection theory (SDT) in a standard causal learning task. Results showed that manipulations of P(c) when contingency (ΔP) was held constant did not affect participants' ability to predict the appearance of the outcome (d′) but had a significant effect on response criterion (c) and numerical causal judgments. The association between criterion c and judgment was further demonstrated in 2 experiments in which the criterion was directly manipulated by linking payoffs to the predictive responses made by learners. In all cases, the more liberal the criterion c was, the higher judgments were. The results imply that the mechanisms underlying the elaboration of judgments and those involved in the elaboration of predictive responses are partially dissociable.
Causal illusion has been proposed as a cognitive mediator of pseudoscientific beliefs. However, previous studies have only tested the association between this cognitive bias and a closely related but different type of unwarranted beliefs, those related to superstition and paranormal phenomena. Participants (n = 225) responded to a novel questionnaire of pseudoscientific beliefs designed for this study. They also completed a contingency learning task in which a possible cause, infusion intake, and a desired effect, headache remission, were actually non‐contingent. Volunteers with higher scores on the questionnaire also presented stronger causal illusion effects. These results support the hypothesis that causal illusions might play a fundamental role in the endorsement of pseudoscientific beliefs.
Online experiments are growing in popularity, and the increasing sophistication of Web technology has made it possible to run complex behavioral experiments online using only a Web browser. Unlike with offline laboratory experiments, however, few tools exist to aid in the development of browser-based experiments. This makes the process of creating an experiment slow and challenging, particularly for researchers who lack a Web development background. This article introduces jsPsych, a JavaScript library for the development of Web-based experiments. jsPsych formalizes a way of describing experiments that is much simpler than writing the entire experiment from scratch. jsPsych then executes these descriptions automatically, handling the flow from one task to another. The jsPsych library is open-source and designed to be expanded by the research community. The project is available online at www.jspsych.org .
Studies of human contingency judgment often reveal substantial bias and inaccuracy in ratings of cause-effect relationship. This study examined the effects of different rating procedures on contingency judgment. In two experiments, college students responded to and rated a range of positive, negative, and zero contingencies presented in a free-operant format. Experiment 1 found that judgments made along a unidirectional 0 to 100 “control” scale were less sensitive to variations in contingency (especially negative ones) and were based on less sophisticated judgment strategies than judgments made along a bidirectional − 100 to + 100 “prevent-cause” scale. Experiment 2 found that informing subjects given the unidirectional scale that their responding may either cause or prevent the outcome eliminated the tendency to underestimate negative contingencies and improved the sophistication of strategy use but did not increase judgment sensitivity to the level of subjects given the bidirectional scale. Taken together, these results suggest that the bidirectional “prevent-cause” scale contributes to highly accurate and unbiased ratings of response-outcome contingency.
This chapter discusses that experimental psychology is no longer a unified field of scholarship. The most obvious sign of disintegration is the division of the Journal of Experimental Psychology into specialized periodicals. Many forces propel this fractionation. First, the explosion of interest in many small spheres of inquiry has made it extremely difficult for an individual to master more than one. Second, the recent popularity of interdisciplinary research has lured many workers away from the central issues of experimental psychology. Third, there is a growing division between researchers of human and animal behavior; this division has been primarily driven by contemporary cognitive psychologists, who see little reason to refer to the behavior of animals or to inquire into the generality of behavioral principles. The chapter considers the study of causal perception. This area is certainly at the core of experimental psychology. Although recent research in animal cognition has taken the tack of bringing human paradigms into the animal laboratory, the experimental research is described has adopted the reverse strategy of bringing animal paradigms into the human laboratory. A further unfortunate fact is that today's experimental psychologists are receiving little or no training in the history and philosophy of psychology. This neglected aspect means that investigations of a problem area are often undertaken without a full understanding of the analytical issues that would help guide empirical inquiry.
Overestimations of null contingencies between a cue, C, and an outcome, O, are widely reported effects that can arise for multiple reasons. For instance, a high probability of the cue, P(C), and a high probability of the outcome, P(O), are conditions that promote such overestimations. In two experiments, participants were asked to judge the contingency between a cue and an outcome. Both P(C) and P(O) were given extreme values (high and low) in a factorial design, while maintaining the contingency between the two events at zero. While we were able to observe main effects of the probability of each event, our experiments showed that the cue- and outcome-density biases interacted such that a high probability of the two stimuli enhanced the overestimation beyond the effects observed when only one of the two events was frequent. This evidence can be used to better understand certain societal issues, such as belief in pseudoscience, that can be the result of overestimations of null contingencies in high-P(C) or high-P(O) situations.
Misperceptions of causality are at the heart of superstitious thinking and
pseudoscience. The main goal of the present work is to show how our
knowledge about the mechanisms involved in causal induction can be used
to hinder the development of these beliefs. Available evidence shows that
people sometimes perceive causal relationships that do not really exist. We
suggest that this might be partly due to their failing to take into account
alternative factors that might be playing an important causal role. The
present experiment shows that providing accurate and difficult-to-ignore
information about other candidate causes can be a good strategy for reducing
misattributions of causality, such as illusions of control.
Studies concerned with judgments of contingency between binary variables have often ignored what the variables stand for. The two values of a binary variable can be represented as a prevailing state (nonevent) or as an active state (event). Judgments under the four conditions resulting from the combination of a binary input variable that can be represented as event-nonevent or event-event with an outcome variable that can be represented in the same way were obtained. It is shown in Experiment 1, that judgments of data sets which exhibit the same degree of covariation depend upon how the input and output variables are represented. In Experiment 2 the case where both the input and output variables are represented as event-nonevent is examined. Judgments were higher when the pairing of the input event was with the output event and the input nonevent with the output nonevent that when the pairing was of event with nonevent, suggesting a causal compatibility of event-event pairings and a causal incompatibility of event-nonevent pairings. Experiment 3 demonstrates that judgments of the strength of the relation between binary input and output variables is not based on the appropriate statistical measure, the difference between two conditional probabilities. The overall pattern of judgments in the three experiments is mainly explicable on the basis of two principles: (1) judgments tend to be based on the difference between confirming and disconfirming cases and (2) causal compatibility in the representation of the input and output variables plays a critical role.
Illusory correlation refers to an erronous inference about the relationship between categories of events. One postulated basis for illusory correlation is the co-occurrence of events which are statistically infrequent; i.e., obserbers overestimate the frequency of co-occurence of distinctive events. If one group of persons “occurs” less frequently than another and one type of behavior occurs infrequently, then the above hypothesis predicts that observers would overestimate the frequency that that type of behavior was performed by members of that group. This suggested that the differential perception of majority and minority groups could result solely from the cognitive mechanisms involved in processing information about stimulus events that differ in their frequencies of co-occurrences. Results of two experiments testing this line of reasoning provided strong supprt for the hypothesis. Implications of the experiments for the acquisition of stereotypes are discussed.
Pseudoscience, superstitions, and quackery are serious problems that threaten public health and in which many variables are involved. Psychology, however, has much to say about them, as it is the illusory perceptions of causality of so many people that needs to be understood. The proposal we put forward is that these illusions arise from the normal functioning of the cognitive system when trying to associate causes and effects. Thus, we propose to apply basic research and theories on causal learning to reduce the impact of pseudoscience. We review the literature on the illusion of control and the causal learning traditions, and then present an experiment as an illustration of how this approach can provide fruitful ideas to reduce pseudoscientific thinking. The experiment first illustrates the development of a quackery illusion through the testimony of fictitious patients who report feeling better. Two different predictions arising from the integration of the causal learning and illusion of control domains are then proven effective in reducing this illusion. One is showing the testimony of people who feel better without having followed the treatment. The other is asking participants to think in causal terms rather than in terms of effectiveness.
There are four kinds of contingency information: occurrences and nonoccurrences of an effect in the presence and in the absence of a cause. Previous studies have shown that these four kinds are not given equal weight in causal judgment. The present research was designed to test two hypotheses about this unequal weighting: that weightings are influenced by the form of the question and other features of the stimulus materials and that unequal weightings occur, in part, because individual differences in the use of contingency information are not evenly distributed across the four kinds of information. Support was found for both hypotheses. However, the effects of question wording were not always as had been predicted, indicating that more needs to be learned about how people interpret the task, instructions, and materials they are given.
There are four kinds of contingency information: occurrences and nonoccurrences of an effect in the presence and absence ofa cause. In two experiments participants made judgements about sets of stimulus materials in which one of these four kinds had zero frequency. The experiments tested two kinds of predictions derived from the evidential evaluation model of causal judgement, which postulates that causal judgement depends on the proportion of instances evaluated as confirmatory for the cause being judged. The model predicts significant effects of manipulating the frequency of one kind of contingency information in the absence of changes in the objective contingency. The model also predicts that extra weight will be given to one kind of confirmatory information when the other kind has zero frequency, and to one kind of disconfirmatory information when the other kind has zero frequency. Results supported both sets of predictions, and also disconfirmed predictions of the power probabilistic contrast theory of causal judgement. This research therefore favours an account of causal judgement in which contingency information is transformed into evidence, and judgement is based on the n et confirmatory or disconfirmatoryvalue of the evidence.
Health beliefs and decision making
- M B Goldwater
- A Perfors
- Z Horne
- C H Legare
- E M Markman
Illusion of control: The role of personal involvement
- I. Yarritu
- H. Matute
- M. A. Vadillo