the inﬂuence of control threat on contingency learning · memory manipulation (kay et al., 2008)....

The Influence of Control Threat on Contingency LearningInternship Report Researchmaster Psychology

Lodder, P. (Paul) & van Elk, M. (Michiel)University of Amsterdam, Amsterdam, The Netherlands

The present study aims to shed light on the influence of control threat on magicalthinking. We focus on a specific kind of magical thinking called the overestimation ofcontingencies. In two studies, we manipulate personal control through a memory taskparadigm and investigate whether this manipulation influences the extent to whichpeople learn contingencies. We measured contingency learning with slightly alteredversions of a medicine paradigm (experiment 1; Blanco, Matute, and Vadillo, 2011)and a mousetrap paradigm (experiment 2; Brugger and Graves, 1997). We expectedthat participants in the control threat conditions would overestimate the contingen-cies more than participants in the control conditions. Our results show that controlthreat did not influence the extent to which participants overestimated contingencies.By using Bayesian analyses, we even found support for the null hypotheses that thecontrol threat manipulation has no influence. However, in both experiments we didfind significant relationships between scores on the magical ideation scale and theoverestimation of contingencies. These results imply that people prone to magicalthinking tend to overestimate contingencies. Future research could implement thecontrol threat manipulation in a within subjects design or focus on the relationbetween magical ideation and contingency learning.

Most people are familiar with the feeling of losingcontrol. Some people experience a loss of control duringa traffic accident, some after realizing they are going tofail an exam, and others after a loved one ends theirrelationship. In these situations, people have the feelingthat they are unable to control the world around them.Because such feelings of randomness can be psychologi-cally stressful, people tend to overestimate the extent towhich they can control their lives (Presson & Benassi,1996; Whalen, 1998). Furthermore, people who lackcontrol may try to restore their implicit sense of con-trol through attributional biases (Pittman & Pittman,1979) or by adjusting the perception of the externalworld (Taylor & Brown, 1988), a phenomenon calledcompensatory control (Kay, Gaucher, Napier, Callan, &Laurin, 2008; Kay, Gaucher, McGregor, & Nash, 2010).In one study, people with lower levels of experiencedcontrol tended to perceive more images in pictures thatonly contained noise, than people with normal levelsof control (Whitson & Galinsky, 2008), which suggeststhat people tend to compensate their loss of control byperceiving order and patterns that are in fact illusory.Different types of a loss of control can be distinguished,such as learned helplessness (Dudley, 1999) or a feel-ing of losing personal control, induced by for example a

I would like to thank Michiel van Elk for giving me usefulfeedback on every aspect of the research process.

� E-mail: [email protected]

memory manipulation (Kay et al., 2008).The feeling of losing control can be compensated if

people indulge in activities that restore the feeling ofcontrol. Examples of these kinds of activities are a be-lief in religion (Kay et al., 2008), the government (Kayet al., 2008) or science (Rutjens, van der Pligt, & vanHarreveld, 2010). Another powerful belief system pro-viding people with a feeling of control can be found inmagical thinking – the idea that our thoughts and ac-tions influence the world around us, while in fact they donot (Matute, 1996). Examples of magical thinking arethe belief that a sun dance will cause the sun to shineafterwards, or the belief that hurting a voodoo doll willlead to similar feelings of pain in a real person. A com-mon denominator of most forms of magical thinking isthat they involve beliefs about causal influences that areconsidered unfounded by scientific standards (Lindeman& Svedholm, 2012). Because magical thinking involvescausality (i.e. the effect of A on B), we can distinguish itfrom paranormal beliefs, that are also unfounded by sci-entific standards, but do not necessarily include a causalcomponent.

Some studies have related magical thinking to feel-ings of threatened control. In one study, Israeli citizensfilled in questionnaires about magical thinking duringthe Gulf War (Keinan, 1994). The citizens were dividedover two groups: a high stress group located in areasexposed to missile attack and a low stress group locatedin relatively safer areas. It turned out that citizens inthe high stress areas were more prone to magical think-ing than citizens in low stress areas. These results imply

2 THE INFLUENCE OF CONTROL THREAT ON CONTINGENCY LEARNING

that people are more prone to magical thinking in situa-tions in which they experience stress due to factors theycannot control. In another study, people were primedwith superstitious thoughts, which resulted in an in-crease in reported feelings of personal control (Damisch,Stoberock, & Mussweiler, 2010). Together these studiessuggest a close relation between magical thinking andthe feeling of control.

A key feature of magical thinking is an overesti-mation of the contingency between two objectively re-lated events. People prone to magical thinking tend toperceive more illusory contingencies than non-magicalthinkers (Brugger & Graves, 1997). In an ingenious ex-periment about hypotheses testing, Brugger and Gravesshowed that participants who scored high on a magicalideation scale tested fewer hypotheses – but retrospec-tively believed in many more hypotheses – than partic-ipants who scored low on that scale.

In summary, these studies show that there exist aclose relation between magical thinking and the feelingof control and that people prone to magical thinkingtend to perceive more illusory contingencies than non-magical thinkers. However, the studies mentioned abovehave several limitations. First, they did not experimen-tally manipulate control threat. In this regard, earlierstudies were problematic because these results mightalso be explained by confounding factors, such as in-dividual differences in locus of control. Second, earlierstudies focused mainly on illusory contingencies and didnot shed light on the influence of control threat on theperception of real contingencies. Therefore, the presentstudy experimentally manipulates control threat and in-vestigates its influence on the learning of both illusoryand real contingencies, so we can find out whether thereare differences in the way control threat affects bothtypes of contingency learning.

Based on earlier research (Brugger & Graves, 1997;Matute, 1996; Blanco et al., 2011; Whitson & Galin-sky, 2008) we hypothesize that people who experiencea threat in personal control will tend to overestimateboth illusory (experiment 2) and real (experiment 1 and2) contingencies, compared to people with normal lev-els of personal control. This relationship between con-trol threat and the overestimation of contingencies isexpected to be mediated by the presence of magicalthinking. People who have lower personal control areexpected to compensate this loss of control with magi-cal modes of thinking, specifically the overestimation ofcontingencies.

Experiment 1

Method

Participants. We recruited 81 participants (59 womenand 22 men; 18-51 years old; mean age = 22.5; 76 Dutchand 5 other) through advertisements on the universitycampus and on the research participation website. Par-

ticipants were either paid 5 euros or they received .5course credits.

Materials. To manipulate control threat we used amemory task (Kay et al., 2008; Rutjens et al., 2010) inwhich participants in the control threat condition wereasked to think about a negative situation that they hadabsolutely no control over. Conversely, in the controlcondition, participants were asked to think about a neg-ative situation in which they were in control. In bothconditions we asked participants to describe the eventin about 100 words. This manipulation resulted in abetween subjects design with two conditions (controlthreat condition and control condition). We used fouritems on a 1–7 Likert scale to check whether our con-trol threat manipulations were successful. These itemsturned out to be an adequate manipulation check in ear-lier research (Rutjens et al., 2010).

To measure contingency learning, we used a free re-sponse paradigm (Blanco et al., 2011), in which partic-ipants were presented with a scenario about a virtualpatient who was given one of four different medicines.Subsequently, participants saw whether the virtual pa-tient was healed by the particular medicine or not (seefigure 1). We used different medicine-healing contin-gencies (see table 1) and after observing 80 medicine-outcome contingencies, participants were asked to indi-cate on a scale of 0 to 100 to what extent they thoughtthat each medicine was effective in healing the virtualpatient.

To take into account individual differences in mag-ical thinking, we used questionnaires about fan-tasy proneness (Merkelbach, Horselenberg, and Muris(2001); test-retest reliability = 0.95, Cronbach’s al-pha=0.72; convergent validity established), paranormalbeliefs (Tobacyk and Milford (1983); test-retest relia-bility=0.89; construct validity established) and magicalideation (Eckblad and Chapman (1983); Cronbach’s al-pha=0.83).

We programmed the experiment in Neurobehavioralsystems Presentation 16.3. The stimuli we designedand developed were inspired by stimuli used in similarparadigms (Blanco et al., 2011). We ran the experimentson multiple computers, each located in a cubicle hostedby the University of Amsterdam.

Procedure. Upon arrival, we briefly instructed par-ticipants about the experiment and they signed an in-formed consent. In the first part of the experiment, werandomly presented participants with either the controlthreat or the control manipulation. Subsequently, theyparticipated in the medicine task and filled out the threequestionnaires, after which we thanked and debriefedthem.

Expectations. Based on previous research (Matute,1996; Blanco et al., 2011), we expected that partici-pants in the control threat condition would overesti-

LODDER (2013) 3

Figure 1. Stimuli in the Medicine Task.

mate the effectiveness of medicine 2 and 3 more thanparticipants in the control condition, because the ef-fectiveness of those two medicines is objectively almostat chance level. We expected that participants in bothconditions would discover equally well that medicine 1was effective and medicine 4 ineffective. However, ifcontrol threat lead people to overestimate contingen-cies in general – and not merely illusory contingencies– then the results would reflect a pattern in which par-ticipants in the control threat condition would overes-timate the contingencies of every medicine, comparedto participants in the control condition. Furthermore,based on research linking magical and paranormal be-liefs to illusory pattern perception (Brugger & Graves,1997; Riekki, Lindeman, Aleneff, Halme, & Nuortimo,2012) we expected that people who score high on thethree magical thinking scales would overestimate the ef-fectiveness of the medicine more than people who scorelow on those scales.

Results

81 psychology students participated in our first exper-iment. We excluded one participant from further analy-ses because this participant failed to describe a situationduring the control threat manipulation. After exclusion,both experimental conditions contained 40 participants.There were no differences between conditions with re-spect to gender, age, spirituality and religiosity.

In our dependent measure, Medicine 1 obviously wasthe most effective, with a healing success of 80%. Fur-thermore, Medicine 4 was considered as obviously theleast effective, with a healing success of 20%. One wayin which we could check whether participants paid at-tention to the different medicine-healing contingencies isto look at whether participants rated Medicine 1 as moreeffective than Medicine 4. It turned out that 3 partici-pants rated Medicine 4 as more effective than Medicine1. The exclusion of those three participants from fur-ther analyses did not alter our results and subsequentanalyses include the data from all subjects.

Our control threat manipulation was successful. Par-ticipants in the control threat condition reported lower

feelings of control (M=9.43, SD=11.01) than partici-pants in the control condition (M=74.78, SD=16.54;t(78)=-20.8, p<.001). All participants were asked tothink and describe a negative situation, yet participantsin the control threat condition reported the situationto be more negative (M=92.65, SD= 8.5) than partic-ipants in the control condition (M=82.83, SD=19.92;t(78)=2.78, p=.005). General feelings of personal con-trol did not differ between conditions (t(78)=-1.73,p=.088; t(78)=-.7, p=.483 for respectively the 2 ques-tions assessing feelings of personal control).

We used a mixed ANOVA to analyze the differencesbetween the two conditions in rating the effectivenessof the four different medicines. The assumption ofsphericity holds because Mauchly’s test of sphericity wasnot significant (χ2(5) = 3.587, p=.61). Box’s test ofthe equality of covariance matrices indicates that thecovariance matrices of both conditions are not equal(F (10,29087)=2.249, p=.013). However, because Box’stest is very sensitive, only highly significant results com-bined with unequal group sizes will be problematic. Be-cause we have equal group sizes and only a moderatelyhigh Box’s test F -value, we can assume our data to berobust against violating the assumption of equal covari-ance matrices,

A Mixed ANOVA indicates a significant multivariateeffect for medicine (F (3,76)=90.07, p<.001). On aver-age, participants were able to correctly identify the effec-tiveness of each medicine relative to the other medicines.A polynomial contrast analysis revealed that only a lin-ear trend fits the data (F (1,78)=269.55, p<.001), whichimplies that participants correctly identified the pro-grammed linear trend underlying the medicine effective-ness. Figure 2 shows the rated effectiveness of each ofthe four medicines in both conditions.

Overall, the two conditions did not differ signifi-cantly with respect to their ratings of the four medicines(F (1,78)=.05, p=.83) and the interaction between Con-dition and Rating was not significant (F (3,76)=1.298,p=.28). Thus, our control threat manipulation did notinfluence the extent to which participants overestimated

Table 1Percentage of Trials in which a Particular Medicine was

followed by a Particular Outcome.


Table 2Strength of Evidence for Different Ranges of pBIC Values (Raftery, 1995) and the Present Study

the effectiveness of the medicines. Frequentist statisticsp-values cannot be used to provide evidence in favor ofa (null) hypothesis, so we used a Bayesian informationcriterion (BIC; (Wagenmakers, 2007; Mason, 2011)) toinvestigate whether there was any support for the nullhypothesis that the control threat manipulation doesnot influence the effectiveness ratings of each of the fourmedicines. For the first medicine, the posterior probabil-ity in favor of the null hypothesis was pBIC(H0|D) = .85.For the second, third, and fourth medicine, the proba-bilities were .9, .88 and .54, respectively. Table 2 showsthe strength of evidence for different ranges of pBIC val-ues and the strength of evidence for each of the fourtested hypotheses. The Bayesian analyses imply thatfor the first three medicines there is positive evidencefor the null hypothesis that the control threat manipu-lation does not influence the medicine effectiveness rat-ing. For the fourth medicine, the Bayesian analysis indi-cates weak evidence in favor of the null hypothesis, yetweaker evidence in favor of the alternative hypothesispBIC(Ha|D) = .46.

Figure 2. Rated Medicine Effectiveness in Two Conditions

We performed bivariate correlational analyses to findout whether the experienced control during the ma-nipulation, as well as individual differences in magicalideation, fantasy proneness and paranormal beliefs arerelated to the overestimation of the effectiveness of eachmedicine. It turned out that the experienced loss ofcontrol and scores on both the paranormal belief scaleand fantasy proneness scale, were all not associated withbeliefs in the effectiveness of each of the four medicines.However, participants who scored higher on the magicalideation scale overestimated the effectiveness of the twoleast effective medicines (medicine 1: r = .268, p = .016;medicine 2: r = .222, p = .048). We have to interpretthese results carefully, however, given that a total num-ber of 16 correlational analyses might influence type Ierror rates.

Experiment 2

In our first experiment, we looked at the influence ofa control threat manipulation on the extent to whichpeople were able to perceive real contingencies betweenfour medicines and different healing rates. It turned outthat the control threat manipulation did not influencethe extent to which people learned the contingencies.The failed manipulation effect might be explained bythe fact that in the dependent task we focused on real

contingencies. It could be possible that our manipula-tion will only affect the extent to which people learnillusory contingencies, because magical thinking couldbe defined as involving believes that are ’illusory’ ac-cording to scientific standards (Lindeman & Svedholm,2012). Therefore, in our second experiment we inves-tigate whether a threat to personal control influencesthe extent to which people perceive both existing andillusory contingencies. The paradigm we use in this ex-periment also enables us to take a closer look at theprocesses underlying the learning of illusory contingen-cies, because we will investigate the actual beliefs peoplehold onto and not merely study the behavior resultingfrom beliefs, as we did in experiment 1.

LODDER (2013) 5

Method

Participants. We recruited 71 participants (46 womenand 25 men; 18-41 years old; mean age = 22.7; 68 Dutchand 3 other) through advertisement on the universitycampus and on the research recruitment website. Thisexperiment was part of a larger sequence of experimentsfor which participants were either paid 10 euros or re-ceived 1 course credit.

Materials. We measured contingency learning witha food trap paradigm as used by Brugger and Graves,(1997; citeHeltzer94. In addition to the mousetrap task(figure 3) used by Brugger, we also created a rabbit-trap task (figure 4). Participants were presented witha 3x3 matrix in which the lower-left corner representedan animal (mouse/rabbit) and the upper right corner atrap with food (cheese/carrot). Participants were askedto move the animal towards the food by using the arrowkeys on the keyboard. When the animal arrived at thetrap, participants either received the feedback that theanimal got the food, or that the animal was trapped.Furthermore, their task was to get the animal as muchfood as possible, and to find out the rule that deter-mined whether the animal got the food or not. Bothtasks used a rule that determined whether the animalwould get the food or not. In the mousetrap task, thisrule was that the mouse would get the cheese only whentrial time exceeded 3.5 seconds. In the rabbit-trap taskthe rule was that the rabbit had to walk a minimum of8 steps before moving to the field with the trap.

Figure 3. Stimuli for Mouse trap Task

Prior to the foodtrap paradigm, the same controlthreat manipulation and manipulation check as in ourprevious experiment were used. To take into ac-count individual differences in magical thinking, we alsoused the same questionnaires about fantasy proneness(Merkelbach et al., 2001), paranormal beliefs (Tobacyk& Milford, 1983) and magical ideation (Eckblad &Chapman, 1983), as in our first experiment. We againprogrammed the experiment in Neurobehavioral sys-tems Presentation 16.3. The stimuli we designed and

Figure 4. Stimuli for Rabbit trap Task

developed were inspired by stimuli used in a similarparadigm (Brugger & Graves, 1997). We ran the exper-iments on multiple computers, each located in a cubiclehosted by the University of Amsterdam.

Procedure. Upon arrival, participants filled out aninformed consent and we briefly instructed them aboutthe experiment. In the first part of the experiment, werandomly presented participants with either the controlthreat manipulation or the control manipulation. Afterthat participants were presented with a total of 80 traptrials, divided over 4 blocks of 20 trials. Participantswere either first presented 40 mousetrap trials, followedby 40 rabbit-trap trials, or vice versa. We counterbal-anced the order in which we presented participants witheach of the two trial types. After completing the 80trials, we asked participants to answer some questionsassessing the rules they tested during the trials and therules they retrospectively believed to apply to the games(see Appendix A). Besides these multiple answer ques-tionnaires, we also asked participants to describe therule they believed to be most correct. Finally, after theparticipants filled out the three magical thinking ques-tionnaires, we thanked and debriefed them.

Expectations. Based on previous research, we ex-pected that participants who scored high on the magicalthinking scales would test fewer rules, but would ret-rospectively believe in more rules (Brugger & Graves,1997). Furthermore, because control threat has beenlinked to magical thinking (Keinan, 1994; Damisch etal., 2010), we expected that participants in the controlthreat condition would test fewer rules, but would retro-spectively believe in a higher number of rules (perceivemore illusory contingencies; in line with the results ofBrugger & Graves, 1997) than participants in the con-trol condition.


Results

We excluded two participants from further analysesbecause these participants failed to describe a situationduring the control threat manipulation. After exclusion,the control threat condition contained 35 participantsand the control condition 34. There were no differencesbetween conditions with respect to gender, age, spiritu-ality and religiosity.

Our control threat manipulation was successful. Par-ticipants in the control threat condition reported lowerfeelings of control (M=14.57, SD=22.67) than partic-ipants in the control condition (M=74.94, SD=23.72;t(67)=-10.81, p<.001). The negativity of the situationdid not differ between participants in the control threatcondition (M=83.17, SD= 23.92) and the control con-dition (M=84.29, SD=18.71; t(67)=2.78, p=.83), nordid generalized feelings of personal control (t(78)=-1.67,p=.1; t(78)=-1.14, p=.26).

We used a MANOVA to analyze the differences be-tween the two conditions in the number of tested andbelieved hypothesis. Box’s test of the equality of covari-ance matrices was not significant (F (10,21418)=1.06,p=.39), so the assumption of equal covariance matricesacross conditions holds. The multivariate effect for con-dition on the number of believed (Threat: M=8.14, SD=4.05; Control: M=10.5, SD= 5.05) and tested hypothe-ses (Threat: M=12.49, SD= 4.05; Control: M=12.62,SD= 3.67) did not reach significance (F (4,64)=1.73,p=.154). Thus, the number of believed and tested hy-potheses did not differ between participants in the con-trol threat and control condition. We found similar re-sults after looking at both trap tasks (mouse & rabbit) inisolation. The order in which we presented participantswith both tasks (mouse – rabbit vs. rabbit – mouse) didnot influence the abovementioned results.

We again used a Bayesian information criterion (BIC;(Wagenmakers, 2007; Mason, 2011)) to investigatewhether there was any support for the null hypothesisthat the control threat manipulation did not influencethe amount of believed and tested rules. The posteriorprobability in favor of the null hypothesis of the testedrules was pBIC(H0|D) = .89, which implies positive evi-dence in favor of the null hypothesis. The control threatmanipulation did not influence the extent to which par-ticipants tested rules. For the number of believed rulesthe posterior probability in favor of the null hypothesiswas pBIC(H0|D) = .46 and pBIC(Ha|D) = .54 for the alter-native hypothesis. This implies that both the evidencein favor of the null- and the alternative hypotheses isweak, so it remains an open question whether the con-trol threat manipulation influences the extent to whichparticipants believe in illusory rules.

Trial data enabled us to look at changes in behaviorover time, specifically at trial time, the number of stepsand the percentage of errors. It turned out there were nodifferences between conditions on these three measures.

Figure 5. Time per Trial, Step Count, and Number of Er-rors per trial within the Four Blocks for both the ControlThreat Condition (Solid Line) and Control Condition (Dot-ted Line)

Figure 5 shows for participants in both conditions andfor each block of 20 trials the average trial time, theaverage number of steps, and the percentage of errors.Polynomial analyses indicate that a linear trend best fitsthe overall average trial time (F (1,67)=30.97, p<.001),step count (F (1,67)=62.92, p<.001), and percentage oferrors (F (1,67)=9.15, p=.004). These analyses implythat participants take longer routes and make longertrials and more errors over time. There were no differ-ences between conditions with respect to trial time, stepcount and error percentage.

To check whether people sustain their belief in partic-ular routes, we calculated for each participant the num-ber of repeated routes during the trap tasks. It turnedout that the number of repetitions showed a strong neg-ative correlation with both the step count (r = -.587,p<.001) and the number of correct trials (r = -.777,p<.001). People who repeat the same routes over andover again seem to take fewer steps during each trial andfail on more trials than people who do not take routesrepetitively. One explanation for this result might bethat people at one point during the game believe thatthey found the correct rule and subsequently stop play-ing the game seriously and hence finish it as fast as possi-ble. One way to quickly finish the game is to repeatedlytake the shortest route to the cell with the trap. Thisresults in a low step count and a high number of failures,exactly the pattern we found with participants who re-peat the same routes over and over again. Therefore, itseems that route repetition does not provide us with anyvaluable information about whether participants sustaintheir belief in illusory rules.

LODDER (2013) 7

Table 3 shows a selection of (illusory) rules that par-ticipants believed to apply to the foodtrap tasks. Inthe mousetrap task, 28,6% of the participants correctlyidentified the rule that determined whether the mousewould get the cheese (take longer than 3.5 seconds toreach the field with the trap). In the rabbit trap task,25,7% of the participants correctly identified the rule(take more than 9 steps to reach the field with the trap).The control threat manipulation did not influence theextent to which participants correctly identified the rule.

We performed bivariate correlational analyses to findout whether individual differences in magical thinking,fantasy proneness or paranormal beliefs are related totrial time, step count, the percentage of errors, the num-ber of correct trials, the number of repeated routes, theexperienced loss of control during the manipulation andto the number of tested and believed rules. It turnedout that a high score on the magical ideation scale wasstrongly associated with a believe in more rules (r =.427, p<.001) but not with the testing of more rules(r = .218, p = .071). Figure 6 visualizes the correla-tion between magical thinking and the belief in morehypotheses.

High magical ideation scores were also significantlyrelated to the trial time, step count and the numberof correct trials. It turned out that participants whoscored higher on the magical ideation scale, took lesssteps (r = -.267, p=.027), used less time (r = -.287,p=.017), and had less correct trials (r = -.266, p=.027)than people who scored low on the scale. We have to

Figure 6. Correlation between Magical Ideation Scale Scoreand Number of Believed Hypotheses

interpret the last three correlations carefully however,given that a total number of 36 correlational analyseslikely influenced type I error rates.

Discussion

In two experiments, we tested the hypothesis that athreat to personal control invokes magical thinking inparticipants in such a way that they will overestimatethe effectiveness of medicine or believe in the existenceof rules that in fact do not exist. It turned out that thecontrol threat manipulation did in no way influence theextent to which people engaged in magical thinking. Byusing a Bayesian Information Criterion (Wagenmakers,2007), we even found positive evidence for the null hy-pothesis that a threatened personal control does not in-fluence magical thinking.

These non-significant results can be explained in dif-ferent ways. First, because our control threat manipu-lation has never been used in conjunction with the con-tingency learning paradigms, it might be possible thatthe manipulation simply does not influence the extent towhich people learn contingencies. A second explanationcould be that the control threat manipulation does in-fluence contingency learning, but that the memory taskused in our two experiments was not powerful enough toelicit an adequate effect. This explanation is supportedby the fact that the control threat manipulation did notinfluence generalized feelings of personal control. Peo-ple indicated that they experienced a loss of control incertain situations, but this memory did not influence

Table 3A Selection of Rules that People believed during the

Foodtrap Tasks


the general feeling of being in control over life. Per-haps the control threat manipulation will only influencecontingency learning if it also affects personal controlin a more general way. A third explanation of the non-significant results is that the control threat manipulationis effective, but does not last long enough to influencecontingency learning. The dependent tasks used in ourexperiments both take approximately 8 minutes. A con-trol threat manipulation lasting shorter than 8 minutesmight fail to adequately influence our dependent mea-sure.

An explanation of the failure of our control threat ma-nipulation could be that our control threat manipulationdoes not influence personal control, but instead inducespeople with a feeling of learned helplessness. Interest-ingly, even if this were the case, then our data wouldindicate that learned helplessness too does not influencecontingency learning.

With respect to the control threat manipulation, fu-ture research could focus on discovering the strengthand duration of different kinds of manipulations. Ifwe have a better understanding of both manipulationlength and strength, then we can make more informedchoices about the kind of control threat manipulationthat best suits the experiment. Another interesting areaof future inquiry is the use of a within design to manip-ulate control threat. Examples of control threat ma-nipulations suitable for a within subjects design are theconcept identification task (Pittman & Pittman, 1979;Whitson & Galinsky, 2008) and priming control threatrelated pictures (e.g. IAPS; Lang, Bradley, & Cuth-berth, 1999). By taking into account within subjectsvariation we will get a more powerful experimental de-sign (Stevens, 2009), but we will also have to find acontingency learning measure that is suitable for multi-ple measurement over time. The food trap tasks usedin our second experiment are difficult to implement ina within subjects design, because people behave differ-ently on later trials, compared to earlier trials. As a re-sult, it will be difficult to isolate the effect of the withinsubjects variation from the effect of repeatedly playingthe same task.

Despite the absence of a control threat effect, wefound in both experiments that individual differencesin magical thinking predicted differences on our depen-dent measures. In our first experiment, people who weremore likely to engage in magical thinking also tendedto overestimate the effectiveness of the two ineffectivemedicines. This overestimation is related to a specifickind of magical thinking that comprises a belief in formsof causation that by conventional standards are invalid(Eckblad & Chapman, 1983). Indeed, we could viewthe belief in the effectiveness of ineffective medicine as aform of causation invalid by conventional scientific stan-dards. This result is in line with earlier research indi-cating that people who believe in complementary andalternative medicine tend to have more paranormal be-

liefs (Saher & Lindeman, 2005) and a more non-rationalthinking style (Aarnio & Lindeman, 2004; Lindeman,2011). We can compare the invalid causal beliefs inour experiment to the belief in the effectiveness of al-ternative medicine, because in both scenarios there isno empirical support. The overestimated medicines inthe present study did not have a real effect, nor do al-ternative medicine (such as homeopathy; Ernst, 2002).

In our second experiment, we found a similar associa-tion between magical thinking and contingency learning.After playing the food trap tasks, people who are likelyto engage in magical thinking tended to believe in moreillusory contingencies. Again, we can see that believingin illusory rules is a good example of an invalid formof causation (Eckblad & Chapman, 1983). The kind ofrules people started to believe in sometimes took ratherextreme forms. For example, one participant believed”there were six different ways to give the animal foodin a minimal amount of steps. All these routes mir-rored each other and in each new trial one of these sixroutes is the correct way to give the animal the food.If a particular route proves to be correct during a trial,then the mirrored route will be correct during the sub-sequent trial”. Another participant granted the animalsome mental capacities: ”the mouse first has to walk afew rounds before making an attempt to get the food.The mouse does this in order to observe the trap so itcan discover the best way to approach it”.

Our discovered association between magical thinkingand the belief in more rules is a direct replication ofthe study by Brugger and Graves (1997), except thatthey also found the slightly significant effect that peopleprone to magical thinking test fewer rules. We did find,however, that people likely to engage in magical think-ing completed the food trap trials faster and used fewersteps. That finding could indicate that those people didnot test very complex rules, because those rules usuallytake more time and steps to test. We have to interpretthese finding carefully, however, due to the high numberof computed correlations. Future research could there-fore focus on directly testing the influence of the specifickind of magical thinking (i.e. believing invalid forms ofcausation; Eckblad, 1983) on contingency learning.

The present study has several limitations. First, theoperationalization of control threat has low ecologicalvalidity. We are interested in whether people who ex-perience loss of control in real life, tend to engage inmore magical modes of thinking. In our lab, we oper-ationalized the loss of control by letting people thinkabout situations in which they experienced a lack ofcontrol. However, a memory of a situation is less pow-erful than the situation itself. Therefore, future studiescould try to perform a control threat manipulation thatinduces the loss of control as a result of a real life sit-uation resulting from the manipulation. Unfortunately,ethical considerations prevent us from inducing controlthreat in the way most people remember themselves to

LODDER (2013) 9

lack control. Ethically viable alternatives to stealingpeople’s bikes or killing their family members can beto present them with unsolvable puzzles (Pittman &Pittman, 1979; Whitson & Galinsky, 2008) or – in thefuture – by using the virtual reality priming of controlthreatening situations.

A limitation of some research on magical thinking– including our first experiment – is that the way inwhich we measure magical thinking has low ecologicalvalidity. We want to study people making decisions inreal life situations that are based on beliefs consideredinvalid by conventional scientific standards. Those deci-sions are most often operationalized in such a way thatwe present participants with a task and observe the re-sulting behaviour. We conclude the behaviour resultsfrom magical thinking if the behaviour itself conformsto particular ’magical thinking’ criteria we determinedbeforehand. However, we are not so much interested inthe behaviour itself, as we are in the beliefs that resultinto the behaviour. Take for instance our first exper-iment: because participants overestimate the effective-ness of certain medicines (behaviour), we infer that thisoverestimation is the result of magical beliefs, but wedo not know the beliefs that participants base their de-cision on. Therefore, we have to be careful in drawingconclusions about people’s beliefs based on behaviouraldata. Our second experiment overcomes this problemby directly asking participants what kind of rules theybelieved.

In sum, the present study found no support for theinfluence of control threat on contingency learning. Infact, Bayesian analyses even supported a null result. Wedid find significant associations between magical modesof thinking and the overestimation of contingencies, butfuture research will have to shed more light on this par-ticular effect. So when it comes to the irrationality thatsome people show in the choices they make, we can ei-ther magically believe in the truth of one of our currentexplanations, or wisely admit we do not yet know theanswer.

References

Aarnio, K., & Lindeman, M. (2004). Magical food and healthbeliefs: a portrait of believers and functions of the beliefs.Apetite, 43 , 65–74.

Blanco, F., Matute, H., & Vadillo, M. A. (2011). Making theuncontrollable seem controllable: The role of action in theillusion of control. The Quarterly Journal of Experimental

Psychology , 64 , 1290–1304.Brugger, P., & Graves, R. E. (1997). Testing vs. believing

hypotheses: Magical ideation in the judgment of contin-gencies. Cognitive Neuropsychiatry , 2 , 251–272.

Damisch, L., Stoberock, B., & Mussweiler, T. (2010). Keepyour fingers crossed!: how superstition improves perfor-mance. Psychological Science, 21 , 1014–1020.

Dudley, T. D. (1999). The effect of superstitious belief onperformance following an unsolvable problem. Personalityand Individual Differences, 26 , 1057–1064.

Eckblad, M., & Chapman, L. J. (1983). Magical ideationas an indicator of schizotypy. Journal of Consulting and

Clinical Psychology , 51 , 215–225.Ernst, E. (2002). A systematic review of systematic reviews

of homeopathy. British Journal of Clinical Pharmacology ,54 , 577–582.

Kay, A. C., Gaucher, D., McGregor, I., & Nash, K. (2010).Religious belief as compensatory control. Personality and

Social Psychology Review , 14 , 37–48.Kay, A. C., Gaucher, D., Napier, J. L., Callan, M. J., & Lau-

rin, K. (2008). God and the government: Testing a com-pensatory control mechanism for the support of externalsystems. Journal of Personality and Social Psychology ,95 , 18–35.

Keinan, G. (1994). Effects of stress and tolerance of am-biguity on magical thinking. Journal of Personality and

Social Psychology , 67 , 48–55.Lindeman, M. (2011). Biases in intuitive reasoning and belief

in complementary and alternative medicine. Psychology

& Health, 26 , 371–382.Lindeman, M., & Svedholm, A. M. (2012). What’s in a term?

paranormal, superstituous, magical and supernatural be-liefs by any other name would mean the same. Review of

General Psychology , 16 , 241–255.Mason, M. E. J. (2011). A tutorial on a practical bayesian al-

ternative to null-hypothesis significance testing. BehaviorResearch Methods, 43 , 679–690.

Matute, H. (1996). Illusion of control: Detecting response-outcome independence in analytic but not in naturalisticconditions. Psychological Science, 7 , 289–293.

Merkelbach, H., Horselenberg, R., & Muris, P. (2001).The creative experiences questionnaire (ceq): a brief self-report measure of fantasy proneness. Personality and In-

dividual Differences, 31 , 987–995.Pittman, N. L., & Pittman, T. S. (1979). Effects of amount

of helplessness training and internal-external locus of con-trol on mood and performance. Journal of Personality

and Social Psychology, 37 , 39–47.Presson, P. K., & Benassi, V. A. (1996). Illusion of control:

A meta- analytic review. Journal of Social Behavior and

Personality , 11 , 493–510.Riekki, T., Lindeman, M., Aleneff, M., Halme, A., & Nuor-

timo, A. (2012). Paranormal and religious believers aremore prone to illusory face perception than skeptics andnon-believers. Applied Cognitive Psychology , 27 , 150–155.

Rutjens, B. T., van der Pligt, J., & van Harreveld, F. (2010).Deus or darwin: Randomness and belief in theories aboutthe origin of life. Journal of Experimental Social Psychol-

ogy , 46 , 1078–1080.Saher, M., & Lindeman, M. (2005). Alternative medicine:

A psychological perspective. Personality and Individual

Difference, 39 , 1169–1178.Stevens, J. P. (2009). Applied multivariate statistics for the

social sciences. New York: Routledge.Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being:

a social psychological perspective on mental health. Psy-chological Bulletin, 103 , 193–210.

Tobacyk, J., & Milford, G. (1983). Belief in paranormal phe-nomena: Assessment instrument development and impli-cations for personality functioning. Journal of Personalityand Social Psychology, 44 , 1029–1037.


Wagenmakers, E.-J. (2007). A practical solution to the per-vasive problems of p values. Psychonomic Bulletin & Re-

view , 14 , 779–804.

Whalen, P. J. (1998). Fear, vigilance, and ambiguity: Initialneuroimaging studies of the human amygdala. Current

Directions in Psychological Science, 7 , 177–188.Whitson, J. A., & Galinsky, A. D. (2008). Lacking control

increases illusory pattern perception. Science, 322 , 115–117.

LODDER (2013) 11

Figure 7. Appendix A.1: Questions about Tested Rules during Foodtrap Tasks


Figure 8. Appendix A.2: Questions about Believed Rules during Foodtrap Tasks

the inﬂuence of control threat on contingency learning · memory manipulation (kay et al., 2008)....

Documents