Regulatory Focus and Illusions of Control 1 Regulatory Focus and Illusions of Control ... ·...

Regulatory Focus and Illusions of Control 1

Running head: Regulatory Focus and Illusions of Control

Regulatory Focus and Illusions of Control

Thomas A. Langens

University of Wuppertal, Germany

(In press: Personality and Social Psychology Bulletin)

Word count: 8847 words.


Abstract

Regulatory focus theory (Higgins, 1997, 1998) suggests that individuals in a promotion focus

emphasize a congruence between an action and an intended outcome, which may foster illusions of

control (IOC) even in the absence of an objective relationship between action and outcome.

Individuals in a prevention focus should demonstrate a reverse bias which buffers against the

development of IOC. Three studies were conducted to test this hypothesis, which either measured

chronic individual differences in regulatory focus (Study 1) or manipulated regulatory focus

(Studies 2 and 3). All studies found evidence that promotion-focused individuals report higher IOC

concerning an uncontrollable outcome than prevention-focused individuals. In addition, Study 3

showed that IOC developed in a promotion focus buffer against the emotional consequences of

failure. The results suggest that IOC evolve in a way which increases regulatory fit (Higgins, 2000).

Keywords: Regulatory focus, illusion of control, mood regulation, regulatory fit.


Regulatory Focus and Illusions of Control

Illusions of control (IOC) are defined as overestimations of control over an outcome

(Thompson, Armstrong & Thomas, 1998; Thompson, 2004). Empirical studies demonstrate the

prevalence of IOC, for example by showing that people generally overestimate the amount of

control they have in gambling situations (Langer, 1975), when driving a car (McKenna, 1993) or

when trying to get a light to come on in a laboratory situation (Alloy & Abramson, 1979).

Thompson and colleagues (1998) identified five conditions which influence the development of

IOC. According to their review, IOC are likely to develop if (1) the task seems to involve skill

factors, (2) feedback seems to indicate success in controlling the outcome, (3) individuals have a

strong need or desire for the outcome, (4) people are in a positive mood, and (5) intrusions of reality

can be prevented. Thompson and colleagues (1998) also offered an explanation of IOC based on a

“control heuristic”: if people intend to achieve a certain outcome (e.g., they want a light to come

on) and this outcome occurs in temporal proximity (the light goes on), then people are inclined to

attribute the outcome to their actions rather than to other factors (such as chance).

The control heuristic suggests that people are especially likely to develop IOC when they

focus on instances in which a behavior carried out to attain a certain goal is indeed followed by the

desired event while neglecting or simply forgetting instances in which their behavior had no effects

(or undesired ones). In the present research, I will argue that, in addition to the conditions identified

by Thompson and colleagues, the formation of illusions of control is also influenced by an

individual’s regulatory focus (Higgins, 1997, 1998). More specifically, I will suggest that illusions

of control are likely to develop when people are focused on the attainment of nurturance rather

security and safety – that is, when people are in a promotion focus rather than in a prevention focus.

Regulatory Focus and the Detection of Behavior-Outcome Contingencies

Regulatory focus theory (Higgins, 1997, 1998) proposes that self-regulation can either be

tuned to the attainment of nurturance or governed by a concern for security. According to the

theory, nurturance-related self-regulation involves a promotion focus, a regulatory orientation


which is characterized by a sensitivity to positive outcomes (their presence and absence), which

translates into a concern for ideals, advancement, accomplishment, and aspirations. In contrast,

security-related self-regulation involves a prevention focus, a regulatory orientation which is

characterized by a sensitivity to negative outcomes (their presence and absence), which translates

into a concern with oughts, protection, safety, and responsibility. According to regulatory focus

theory, promotion focus and prevention focus are associated with different strategic inclinations for

attaining desired end-states. Because a promotion focus is characterized by a sensitivity to positive

outcomes, the typical strategy associated with promotion self-regulation is a preference for

eagerness-related means of goal pursuit (i.e., approaching matches to desired end-states). In

contrast, because a prevention focus is characterized by a sensitivity to negative outcomes, the

strategy typically associated with prevention self-regulation is a preference for vigilance-related

means of goal pursuit (i.e., avoiding mismatches to undesired end-states). For example, while

driving a car to a friend’s home, individuals in a promotion focus may go a high speed in an effort

to arrive early, whereas individuals in a prevention focus may slow down in an effort to avoid being

in an accident or getting caught in a speed trap.

Empirical studies support the claim that regulatory focus induces a differential sensitivity to

positive and negative outcomes. For example, studies have found that individuals in a promotion

focus are more sensitive to positive feedback signaling advancement toward a goal, whereas

individuals in a prevention focus are especially sensitive to negative feedback signaling possible

failure (Förster, Grant, Idson & Higgins, 2001; Van-Dijk & Kluger, 2004). In another study

(Higgins, Roney, Crowe & Hymes, 1994), participants were asked to recall stories containing both

episodes about approaching matches to desired end-states and episodes about avoiding a mismatch

to a desired end-state. Individuals in a promotion focus remembered episodes about approaching a

match rather than episodes about avoiding a mismatch, whereas the reverse was true for individuals

in a prevention focus.

Differences in strategic inclination associated with regulatory focus also give rise to


differences in processing style. In a promotion focus, individuals are biased towards a “risky”

processing style, in which novel alternatives are eagerly and actively sought, whereas individuals in

a prevention focus resort to a “conservative” processing style which is characterized by vigilance

and risk-aversion. In signal-detection terms (Tanner & Swets, 1954), individuals in a promotion

focus are motivated to achieve hits and to ensure against errors of omission. In contrast, individuals

in a prevention focus are motivated to achieve correct rejections and to ensure against errors of

commission (Higgins, 1997). Empirical evidence supports this analysis. For example, Roese, Hur

and Pennington (1999, Study 1) found that promotion failure – failure to obtain a desired outcome –

provoked additive counterfactuals centering on actions which should have been taken in order to

attain the outcome (i.e., errors of omission). In contrast, prevention failure – failure to prevent an

undesirable outcome – provoked subtractive counterfactuals centering on the curtailment of actions

that had been taken (i.e., errors of commission). In a recognition-memory signal-detection task,

Crowe and Higgins (1997) found that individuals in a promotion focus had a risky bias of saying

“Yes” in the recognition task (thereby securing many hits while also making more errors of

commission) while individuals in a prevention focus had a conservative bias of saying “No” (which

helped them to correctly reject a false stimulus while also provoking errors of omission). Building

on this finding, Liberman, Molden, Idson and Higgins (2001) found that regulatory focus is

associated with the number of hypotheses generated in ambiguous situations. Participants had to

work on an object-naming task in which they had to guess what object was depicted in ambiguous

photographs (Liberman et al., 2001, Studies 1 and 2). Individuals in a promotion focus named more

objects, thereby maximizing the probability to secure a hit (naming the correct object) while also

increasing the probability of making an error of commission (naming objects not shown in a

picture). In contrast, individuals in a prevention focus named comparably fewer objects, which

increased the number of correct rejections (not naming objects not shown in a picture), while also

provoking errors of omission (not naming the correct object).

Regulatory focus theory, along with the empirical findings summarized thus far, suggest the


possibility that, in addition to the factors identified by Thompson and colleagues (1998), IOC may

be influenced by regulatory focus. The basic principle may best be explained by using an example.

Imagine you want to find out whether you can control the toss of a coin, and you want heads to

come up more often than tails. In all probability, you will end up with as many ‘heads’ outcomes as

‘tails’ outcomes; an unbiased assessment of this result would lead to the conclusion that you have

no control over the toss of a coin. However, regulatory focus theory suggests that individuals in a

promotion focus transform an objective non-contingency between behavior and outcome into a

subjective contingency which, on the basis of the control heuristic (Thompson et al., 1998), creates

an illusion of control. There are two arguments which support such a hypothesis.

First, individuals in a promotion focus may be more likely to develop IOC because of their

sensitivity to matches to desired end-stated. In a promotion focus, tossing heads (the desired

outcome) is congruent with the goal of influencing the coin, and should thus receive more attention

and be recalled better at the end of the task (Houghton & Tipper, 1998) then tossing tails. Even if

heads and tails come up equally, individuals in a promotion focus may tend to recall having tossed

more heads than tails due to their subjective interpretation of the events. On the other hand,

individuals in a prevention focus are sensitive to mismatches to desired end-states. Because tossing

tails is incongruent with the goal of influencing the coin, individuals in a prevention focus should

emphasize tossing tails rather than tossing heads and, overall, should better recall instances of

tossing tails (rather than heads). Thus, given that heads and tails came up equally, individuals in a

promotion focus may perceive subjective evidence for a contingency between their actions and the

desired outcome and may thus develop IOC. In contrast, individuals in a prevention focus may see

less evidence for a contingency between their actions and desired outcomes and should develop no

or weaker IOC.

Another way to explore the effect of regulatory focus on IOC is to liken the attempt to

influence the toss of a coin to a signal detection task. In this example, the signal to be detected is

actual control over the toss of a coin. Because individuals in a promotion focus are eager to achieve


hits (assuming control when tossing heads) and ensure against errors of omission (not assuming

control when tossing heads), they may be inclined to interpret a congruence between action and

outcome as an instance of realized control. A different picture emerges for individuals in a

prevention focus. Because prevention focused individuals are motivated to achieve correct

rejections (not assuming control when tossing heads) and to ensure against errors of commission

(assuming control when tossing heads), they may be less inclined to interpret a congruence of

action and outcome as an instance of realized control.

Thus, both arguments lead to a simple prediction, which will be called the regulatory focus

hypothesis of IOC: Even when there is no objective contingency between an action and a desired

outcome, individuals in a promotion focus (as compared to individuals in a prevention focus) may

perceive a subjective contingency between action and outcome, which should give rise to IOC.

Moreover, regulatory focus may be most influential in determining IOC if the desired outcome

occurs as often as it doesn’t. As noted above, a central condition which fosters the development of

IOC is success feedback (Thompson et al., 1998): if the coin could be manipulated to come up

heads in 90 percent of the trials, most people would infer control of the coin on the basis of the

control heuristic. Note that in the light-onset task employed by Alloy and Abramson (1979), people

succumbed to an illusion of control when they seemed to be successful (the light came on in 75% of

the trials), but not when they seemed to fail (the light came on in 25% of the trials). However, when

there is equal evidence of success and failure, then regulatory focus should be most influential in

affecting IOC.

The Present Research

Three studies were conducted to test the hypothesis that regulatory focus influences

perceived control over uncontrollable outcomes. Study 1 sought to relate chronic individual

differences in regulatory focus to perceived control over an uncontrollable outcome. In Study 2,

regulatory focus was manipulated by having participants work on a task which provided either

promotion cues or preventions cues. In Study 3, regulatory focus was manipulated by providing


either gain/non-gain information or non-loss/loss information in a judgment-of-control task. To

assess illusions of control, participants had to rate the amount of control over an uncontrollable

outcome and were asked whether they had identified a rule to influence the outcome. Study 3

explored whether IOC induced by regulatory focus have similar effects as naturally occurring IOC.

Since there is evidence that IOC buffer against the emotional consequences of failure (Alloy &

Clements, 1992), Study 3 tested whether IOC induced by a promotion focus also buffer against the

emotional consequences of failure experiences.

Study 1: Chronic Individual Differences in Regulatory Focus and IOC

Study 1 sought to relate chronic individual differences in regulatory focus to the

development of IOC in a judgment-of-control task. Individual differences in regulatory focus were

assessed by employing a procedure originally devised by Higgins, Shah and Friedman (1997), in

which reaction times to questions about ideal self-guides and ought self-guides are aggregated for a

measure of ideal strength and ought strength, respectively. The underlying assumption is that

shorter response latencies reflect higher accessibility of ideal vs. ought self-guides. For example, an

individual who responds quickly to questions about her ideal self and takes longer to respond to

questions about her ought self is supposed to have relatively strong ideal self-guides, and can hence

be said to be predominantly promotion-focused. This procedure has proved to be a valid

operationalization of individual differences in regulatory focus in a number of studies (e.g., Higgins

et al., 1997; Liberman et al., 2001; Shah & Higgins, 1997).

IOC were assessed by having participants complete a judgment-of-control task originally

devised by Heltzer and Vyse (1994), in which participants were asked to maneuver a gray-colored

face through a matrix. When the face reached the lower-right-hand corner of the matrix, the face

either remained gray or it turned yellow. Participants were asked to make the face turn yellow on as

many trials as possible and received non-contingent feedback on this task on 50 percent of the

trials. Immediately after the task, participants were asked to rate how much control they exerted

over the change in the face’s color and whether they had found a rule to influence the face. This


task is similar to the light-onset task originally employed by Alloy and Abramson (1979; see also

Thompson et al., 2004) in that participants tried to attain an outcome which occurred independently

of their behavior. It was expected that strength of ideal self-guides was positively related to the

development of IOC, whereas strength of ought self-guides was negatively related to IOC.

Method

Participants and Procedure

Eighty-one individuals (31 men and 50 women), the majority of which were students at the

University of Wuppertal, participated in this study. The study took place in a computer lab at the

University of Wuppertal, and students received course credit for participation. To assess individual

differences in regulatory focus, participants completed the Strength of Self-Guide measure (Higgins

et al., 1997). Participants then worked on a judgment-of-control task and rated perceived control on

this task. Finally, participants were carefully debriefed and dismissed.

Strength of Self-Guide Measure

Individual differences in regulatory focus were assessed using a procedure initially devised

by Higgins et al. (1997) in which participants are asked to provide attributes describing certain self-

representations from their own standpoint. Participants were first given definitions of their ideal self

and their ought self. The ideal self was defined as the type of person they ideally would like to be,

the kind of person they hoped, wished or aspired to be. The ought self was defined as the type of

person they believed they ought to be, based on a sense of duty, obligation or responsibility.

Participants were told they were to provide attributes describing their ideal self and their ought self,

and that attributes had to be given as quickly and accurately as possible.

To practice this task, participants were first asked to provide three attributes describing

another person. Then, participants were asked to list attributes describing their own self-

representations in the following order: ideal, ought, ought, ideal, ought, ideal (see Higgins et al.,

1997; Liberman et al., 2001). After listing an ideal attribute, participants were asked to rate the

extent to which they ideally would posses this attribute and the extent to which they actually


possessed this attribute on a 4-point scale ranging from (1) slightly to (4) extremely. Similarly, after

listing an ought attribute, participants were asked to rate the extent to which they believed they

ought to posses this attribute and the extent to which they believed they actually possessed this

attribute. The computer recorded the amount of time a participant took to produce an attribute and

recorded response latencies for the two extent ratings. Because the response time distributions were

positively skewed, all reaction time measures were log transformed to approximate a normal

distribution (Fazio, 1990). A total ideal strength measure was derived by summing attribute reaction

times and extent reaction times across the three attributes describing the ideal self. Similarly, a total

ought strength measure was calculated by summing attribute reaction times and extent reaction

times across the three attributes describing the ought self. Since slower response times indicate

weaker self-guides, response times were multiplied by –1 so that higher scores reflect stronger self-

guides. Raw scores for ideal strength (M = -17.35, SD = 2.79) and ought strength (M = -17.58, SD =

3.42) were z-transformed for further analysis. Because scores for ideal strength and ought strength

reflect response times, they were positively correlated (r = .71) and were hence simultaneously

entered in a hierarchical regression analysis to eliminate common variance (see Liberman et al.,

2001)

Judgment-of-Control Task and Ratings of Perceived Control

To assess the degree to which participants showed an illusion of control, they were asked to

complete a judgment-of-control task illustrated in Figure 1. On the computer screen, they saw a

matrix made up of eight columns and five rows. At the beginning of a trial, a schematic face

colored in gray appeared in the upper-left-hand corner of the matrix. The face could be moved

through the matrix by pressing the X-key (which moved the face one step down) and the Y-key

(which moved the face one step to the right), so that it eventually reached the lower-right-hand

corner, which was termed the “goal field”. Eight fields of the matrix were colored (four in red, four

in green)1. In the goal field, the face either remained gray or it turned yellow. Participants were

instructed to make the face turn yellow on as many trials as possible. In reality, a change in the


color of the face was triggered independently of participants’ behavior according to a fixed

schedule in 12 of the 24 trials, so that half of the trials were congruent with the intended outcome

and the other half was incongruent with the intended outcome.

Perceived control was assessed by having participants rate three items on a 9-point-scale

immediately after the control task. The three items (“I was able to control the color of the face”, “I

could predict whether the face would change its color”, “I was able to induce a change in the color

of the face”) had sufficient internal consistency (α = .87) and were hence combined to give a

measure of perceived control (M = 4.73, SD = 2.17). Also, participants were asked whether they

had identified a rule to change the face’s expression. Overall, 44 participants (54 percent) reported

to have identified a rule to influence the expression of the face. Examples for rules to change the

color of the face were: “Walking through one colored field only”, “Going three steps down and

three steps to the right”, “Changing the faces direction as often as possible”.

Results and Discussion

Preliminary analyses revealed that neither gender nor age had significant impact on the

results reported below. The main dependent variable – perceived control developed in response to

the judgment-of-control task – was regressed on standardized ideal strength and standardized ought

strength in a simultaneous regression analysis. Taken together, the two self-guide measures were

significantly related to perceived control, R2 = .089, F(2, 78) = 3.81, p < .05. Consistent with

predictions, ideal strength was positively related to perceived control, b = .81, seb = .33, t(78) =

2.42, p < .05. In addition, ought strength was negatively related to perceived control, b = -.89, seb =

.34, t(78) = 2.66, p < .05. Thus, two independent effects of the self-guide measures were obtained:

Ideal strength promoted the development of perceived control in the judgment-of-control task,

whereas ought strength decreased perceived control. To illustrate this result, a median split was

performed on the difference between participants’ ideal strength and ought strength, which yielded

groups of participants who predominantly had a promotion focus or who predominantly had a

prevention focus. The control ratings of predominantly promotion-focused participants were above


the midpoint of the 9-point scale (M = 5.27, SD = 1.99), whereas the control ratings of

predominantly prevention-focused participants were below the midpoint of the scale (M = 4.21, SD

= 2.34).

In addition, a logistic regression analysis was performed with identification of a rule to

influence the face (dummy coded) to be predicted by standardized ideal strength and standardized

ought strength, which were again entered simultaneously in the regression equation. A test of the

full model with the two predictors against a constant-only model was significant, χ2(1, N = 81) =

8.08, p < .05. Ideal strength was positively related to identification of a rule, b = .80, seb = .37,

Wald(1) = 4.76, p < .05. An increase in ideal strength of 1 SD increased the probability to identify a

rule by a factor of 2.22. In addition, ought strength was negatively related to identification of a rule,

b = -.99, seb = .38, Wald(1) = 6.69, p < .05. An increase in ought strength of 1 SD decreased the

probability to identify a rule by a factor of 2.69. In sum, the results of Study 1 provided initial

evidence that regulatory focus is related to the development of IOC.

Study 2: Promotion and Preventions Cues and IOC

In Study 2, regulatory focus was manipulated by having participants complete an ostensibly

separate and unrelated task before asking them to work on the judgment-of-control task also

employed in Study 1. Similar to a procedure introduced by Friedman and Förster (2001), this task

was designed to activate the semantic and procedural representations associated with striving for

nurturance (promotion) or security (prevention). In both conditions, participants played a computer

game (called the “desert game”) in which they had to move a circle through a matrix made up of

four rows and four columns in which yellow squares appeared a vanished regularly in random

locations. The matrix was said to represent different locations in a desert. In the promotion focus

condition, participants learned that the yellow squares represent gold bars and that their task was to

collect as many gold bars as possibly by moving the circle on a field which contained a yellow

square. It was assumed that this task activated the semantic concept of “seeking nurturance” as well

as procedural representations of moving toward the desired end-state of nurturance. In the


prevention focus condition, participants were told that the yellow squares represented quicksand

and that their task was to avoid getting caught in it by moving the circle away from yellow squares.

This version of the task was designed to activate the semantic concept of “seeking security” as well

as procedural representations of moving toward the desired end-state of safety. It was assumed that

inducing a promotion focus would lead to higher control ratings in a judgment-of-control task

completed afterwards than inducing a prevention focus.

Method

Participants and Procedure

Forty-five students (29 women and 16 men, mean age = 23.5 years, SD = 3.2) participated

for course credit. The experiment took place in a computer lab of the University of Wuppertal.

Participants first worked on the desert-game to manipulate regulatory-focus cues. Participants were

randomly assigned to the promotion-cue condition (N = 22) or the prevention-cue condition (N =

23). Then, all participants completed the judgment-of-control task which was also employed in

Study 1. Participants were carefully questioned at the completion of the study, and none of the

participants revealed suspicions that the two tasks may have been related.

Manipulation of Regulatory-Focus Cues

In the desert game, participants had to move a circle through a 4 by 4 matrix using the

cursor keys of the computer keyboard. Periodically, yellow squares appeared randomly in half of

the 16 locations and vanished after 1 second. After a pause of .5 seconds, the next trial was

initiated, and the yellow squares appeared in different locations. In the promotion-cue condition,

participants were told that the yellow squares represented gold bars, and that they were to collect as

many gold bars as possible. Notably, the yellow squares did not appear in the present location of the

circle, so participants always had to move the circle toward a yellow square to successfully

accomplish the task. In the prevention-cue condition, participants were told that the yellow squares

represented quicksand, and that they were to move the circle to a safe place. In this condition, one

of the yellow squares always appeared in the present location of the circle, so that participants had


to continually move the circle away from the yellow squares. Participants played the desert game

for a total of two minutes (or 80 trials).

Judgment-of-Control Task

To assess illusions of control, participants completed the control task employed in Study 1.

Perceived control was assessed by having participants rate the same three items employed in Study

1 on a 9-point-scale immediately after the control task. Items had sufficient internal consistency (α

= .77) and were hence combined to give a measure of perceived control (M = 4.90, SD = 1.65).

Also, participants were asked if they had found a rule to influence the face. Overall, 20 participants

(44 percent) reported to have identified a rule.

Results and Discussion

Preliminary analyses revealed that neither age nor gender had any significant impact on the

results reported below. To assess the experimental hypothesis that promotion focus cues are related

to higher IOC relative to prevention focus cues, a t test was conducted on mean perceived control

ratings. Consistent with predictions, participants in the promotion-cue condition reported higher

perceived control (M = 5.44, SD = 1.63) than participants in the prevention-cue condition (M =

4.38, SD = 1.51), d = 0.64, t(43) = 2.27, p < .05. In addition, participants in the promotion-cue

condition were more likely to report a rule to influence the face (15 of 22 participants, or 68

percent) as compared to participants in the prevention-cue condition (5 of 23 participants, or 22

percent), χ2(1, N = 45) = 9.82, p < .01. Thus, manipulating regulatory focus by providing promotion

cues or prevention cues had similar effects on IOC as chronic individual differences in regulatory

focus. Overall, these results provide further support for the hypothesis that a promotion focus

fosters the development of IOC as compared to a prevention focus.

Study 3: Regulatory Focus, IOC, and Mood Following Failure

Study 3 had two goals. The first goal was to test whether framing a task in a way to induce

either a promotion focus or a prevention focus affects control ratings on a judgment-of-control task.

To this end, the control task employed in Studies 1 and 2 was modified so that when the face


reached the goal field, it would either remain neutral (both prevention focus and promotion focus),

turn happy (promotion focus), or turn sad (prevention focus). In the promotion focus condition,

participants were instructed to make the face smile as often as possible. Hence, they either received

gain feedback (the face turned happy) or non-gain feedback (the face remained neutral). In the

prevention focus condition, they were asked to keep the face from frowning, and hence participants

received either non-loss feedback (the face remained neutral) or loss feedback (the face turned sad).

In both conditions, a change in the expression of the face was triggered independently of

participants’ behavior in half of the trials, so that subjective success was equal in both conditions.

The second goal of Study 3 was to explore whether IOC induced by the manipulation of

regulatory focus have similar effects as those reported in the empirical literature. For example,

Alloy and Clements (1992) found that IOC buffer against the emotional consequences of failure.

Study 3 thus tested whether IOC induced by a promotion focus also buffer against the emotional

consequences of failure. To this end, Study 3 replicated part of the procedure developed by Alloy

and Clements (1992): After working on the matrix task, participants were asked to solve verbal

problems which were in fact unsolvable and received failure feedback on most of the trials. IOC

developed in a promotion focus can be assumed to buffer against the emotional consequences of

failure if the following conditions were met: First, of course, a promotion focus should be

associated with higher IOC than a prevention focus (see above). Second, individuals in a promotion

focus should report less emotional impairment following failure than individuals in a prevention

focus. And third, among individuals in a promotion focus, high (relative to low) IOC should be

related to less mood impairment following failure.

Method

Participants and Overview of Procedure

Ninety students (61 women and 29 men; mean age = 19 years, SD = 3.8) participated in this

study for course credit. At the beginning of the experiment, participants were asked to rate their

current mood. Then, all participants worked on a modified version of the judgment-of-control task


employed in Study 2. Participants were randomly assigned to the promotion focus condition (N =

44) or the prevention focus condition (N = 46). All of the participants received non-contingent

feedback on 12 of the 24 trials. Immediately after this task, ratings of perceived control were

collected and participants were asked whether they had identified a rule to control the face. Then,

mood was assessed again. Participants were then instructed to solve seven verbal problems. All but

the first two problems were unsolvable; for unsolvable trials, participants received feedback that

they did not find the optimal solution. Finally, mood measures were collected a third time.

Participants were carefully debriefed at the end of the experiment.

Mood Measures

To assess fluctuations in mood, self-ratings of mood were collected at three times over the

course of the experiment: at the beginning of the experiment (T1), after the matrix-task (T2) and

after the laboratory failure (T3). As Alloy and Clements (1992) point out, self-ratings of mood are a

valid indicator of mood after a laboratory failure. The mood adjective checklist employed in this

study was taken from Matthews, Jones, and Chamberlain (1990). Since mood was assessed three

times in Study 3, the list of adjectives was shortened, so that there were three items assessing

positive mood (happy, joyful, satisfied) and three items assessing negative mood (sad, frustrated,

disappointed). According to Mathews and colleagues (1990), these items reflect the hedonic tone of

self-reported moods. Note that the adjective checklist was employed to assess emotional responses

to experimental failure, and not to test the hypothesis derived by regulatory focus theory that

promotion and prevention states are associated with different positive and negative moods. The aim

of Study 3 was to test whether IOC induced by a promotion focus have similar effects in coping

with failure as naturally occurring IOC. To this end, an overall measure of positive and negative

mood seemed appropriate (see also Alley and Clements, 1992). Participants were asked to rate how

intensely they experienced this particular mood “at the present moment” on a five-point scale

ranging from (1) not at all to (5) very much. Mood scores were derived by averaging responses to

the three items for each of the two scales. Internal consistencies for the scales assessing positive


mood were acceptable (T1: α = .73; T2: α = .84; T3: α = .81), as were internal consistencies for

scales assessing negative mood (T1: α = .68; T2: α = .76; T3: α = .76).

Illusions of Control

The judgment-of-control task employed in Studies 1 and 2 was modified so that the face,

once it reached the goal field, either remained neutral or turned happy (promotion focus condition)

or remained neutral or turned sad (prevention focus condition). A change in the expression of the

face was triggered independently in half of the 24 trials, so that in both conditions, half of the trials

were congruent with the intended outcome (the face turning happy in the promotion condition or

the face remaining neutral in the prevention condition) and the other half was incongruent with the

intended outcome (the face remaining neutral in the promotion focus condition or the face turning

sad in the prevention focus condition). Importantly, the sequence of events indicating “success” or

“failure” was identical in both regulatory focus conditions. For example, if the face remained

neutral in trial 4 of the promotion focus condition (indicating a failure to make the face smile), it

turned sad in trial 4 of the prevention focus condition (indicating a failure to prevent the face from

frowning). Furthermore, if the face turned happy in trial 5 for promotion focused participants

(indicating success), it remained neutral for prevention focused participants (also indicating

success).

Perceived control over the face was assessed using two items (“How successful were you in

making the face happy (preventing the face from turning sad)?” and “How much control did you

have over the face?”) which had to be rated on a 9-point-scale, with endpoints labeled (1) not at all

and (9) extremely (M = 4.73, SD = 1.43, α = .68). Also, participants were again asked whether they

had identified a rule to control the face and, if so, to briefly describe their rule. Fifty-six participants

(62 %) reported having found a rule to influence the face.

Induced Failure Task

Participants were next asked to work on verbal exercises presented on a computer screen.

Participants were shown five words and asked to find the one word which did not belong with the


other words. They were told that there was an optimal solution for each problem, and that they

should find this optimal solution for each set of words. The items were taken from a subtest of a

common German intelligence inventory. It was decided to present two solvable problems (e.g.,

cherry, plum, tulip, apple, pear) first in order to minimize suspicion that the following problems

may be unsolvable. If a participant found the correct word for these first two sets, the computer

gave the feedback that the optimal solution was found. The following five sets of words were

changed by substituting the deviant word with a synonym of the remaining words (e.g., brush,

canvas, paint, dilution, easel). Participants responses were always followed by the feedback that

they did not find the optimal solution for this task.

Results

Preliminary Analyses

Neither age nor gender had any impact on the results reported below.

Illusions of Control

Participants in the promotion focus condition reported higher perceived control (M = 5.19,

SD = 1.13) than participants in the prevention focus condition (M = 4.26, SD = 1.55), d = 0.65, t(88)

= 3.24, p < .01. Also, participants in the promotion focus condition were more likely to report an

incorrect rule to influence the face (33 of 44 participants, or 75%) than participants in the

prevention-focus condition (23 of 46 participants, or 50%), χ2(1, N = 90) = 5.98, p < .05.

Mood

To test for the effect of regulatory focus on reported mood, a 2 (regulatory focus: promotion

versus prevention) × 3 (time: mood at T1, T2, and T3) mixed factorial analysis of variance

(ANOVA) was conducted. For positive mood, this analysis revealed a significant main effect for

time, F(2, 176) = 27.86, p < .001. On average, ratings of positive mood declined over the course of

the experiment (T1: M = 3.47, SD = 0.84; T2: M = 3.26, SD = 0.95; T3: M = 2.84, SD = 1.00). This

main effect was qualified by a significant Regulatory Focus × Time interaction, F(2, 176) = 3.31, p

< .05. As can be seen in Figure 2, positive mood dropped markedly after failure for participants


with a prevention focus, but less so for participants with a promotions focus. The difference in

positive mood between the two conditions was not significant at T1 (t(88) = .87, p > .30) and T2

(t(88) = 1.40, p > .15). However, participants in a promotion focus reported a more positive mood

than prevention-focused participants at T3 (t(88) = 2.86, p < .01); this effect was still significant

when positive mood at T2 was covaried out (F(1, 87) = 6.62, p < .05). For negative mood, a similar

ANOVA yielded a significant main effect for time F(2, 176) = 27.86, p < .001. On average, ratings

of negative mood increased over the course of the experiment (T1: M = 1.65, SD = 0.79; T2: M =

1.64, SD = 0.78; T3: M = 1.99, SD = .96). There was no interaction of time and regulatory focus for

negative mood.

To test whether perceived control predicted positive mood following failure, participants’

positive mood at T3 was analyzed by employing the following hierarchical regression approach:

after controlling for positive mood at T2 (Step 1), perceived control and the experimental condition

(dummy-coded) were entered into the regression equation (Step 2), followed by the multiplicative

interaction of perceived control and the experimental condition (Step 3). Following suggestions by

Cohen et al. (2003), continuous variables were centered before subjecting them to the hierarchical

regression. This analysis yielded significant effects for positive mood at T2 and the experimental

condition (see Table 1). Most importantly, the interaction of perceived control and the experimental

condition significantly predicted positive mood at T3, R2 = .076, b = .62, seb = .15, t(85) = 4.00, p <

.001. To probe this interaction, partial correlations between perceived control and positive mood at

T3 (controlling for positive mood at T2) were calculated separately for the two experimental

conditions. For promotion-focused participants, the partial correlation between perceived control

and positive mood at T3 was positive (pr = .45, p < .01), whereas for prevention-focused

participants, this correlation was negative (pr = -.35, p < .05). Thus, high IOC were associated with

a more positive mood after failure for promotion-focused participants, whereas high IOC were

related to a less positive mood following failure for prevention focused participants.

To further explore the nature of this interaction, predicted values of positive mood at T3


were calculated using the regression weights from the final regression equation by employing a

procedure proposed by Cohen, Cohen, West and Aiken (2003), in which values at one standard

deviation above or below the mean of continuous predictor variables are entered in the regression

equation. The result of this procedure is illustrated in Figure 3, which suggests that participants in

the two experimental conditions did not differ in positive mood following failure when they

reported low perceived control. However, high perceived control was associated with a more

positive mood at T3 for promotion-focused participants and with a less positive mood for

prevention-focused participants. Supplementary post-hoc analysis employing a variant of the

Johnson-Neyman technique (see Aiken & West, 1991, p. 132) revealed that the difference between

the two experimental conditions was not significant for individuals low in perceived control (one

SD below the mean), t(85) = 1.24, p > .20, but highly significant for individuals high in perceived

control (one SD above the mean), t(85) = 4.77, p < .001.

Brief Discussion

The results of Study 3 replicate and extend the results of Studies 1 and 2. Participants in the

promotion focus condition developed higher IOC concerning an objectively uncontrollable outcome

and were more likely to report an incorrect rule to influence this outcome than participants in the

prevention focus condition. Moreover, illusions of control over the outcome seemed to buffer

individuals in a promotion focus against the mood-impairing effect of failure. In the promotion

focus condition, IOC were positively related to a better mood following failure. This result is fully

in accord with Alloy and Clements’ (1992) finding that IOC developed in response to the light-

onset task shield participants against mood-impairment following failure. In contrast, this

correlation was negative in the prevention focus condition. Prevention-focused participants who

developed high IOC reported the least positive mood after failure. This result may be explained by

assuming that IOC which result from a prevention focus are more fragile than IOC which arise from

a promotion focus. Thus, if IOC result from a prevention focus, the illusion may break down very

easily in the face of undesired events (like failure), which may leave an individual all the more


disappointed or helpless. The course of the mood ratings found in Study 3 rules out the possibility

that the effects of the experimental conditions on IOC were due to changes in mood induced by the

framing of the experimental task. Overall, mood was essentially the same in both regulatory focus

conditions after the matrix task, whereas IOC at this point differed significantly. The effects of IOC

on mood were only evident after participants experienced failure on the verbal problems.

General Discussion

The present research has demonstrated that regulatory focus has an influence on illusions of

control over an outcome which occurs regularly, yet independently of an individual’s behavior.

Importantly, the effect of regulatory focus on IOC could be demonstrated using a measure of

chronic individual differences in regulatory focus (Study 1), as well as by providing promotion cues

or prevention cues (Study 2) and by providing either gain/non-gain or non-loss/loss information

(Study 3). Regulatory focus not only influenced ratings of perceived control, but also determined

whether participants believed to have found a rule to influence an outcome which was in reality

determined by chance. The fact that converging results were obtained in all three Studies instills

confidence in the robustness of the effect. Furthermore, Study 3 found that IOC induced by a

promotion focus buffer against the emotional consequences of failure experiences, which replicates

research by Alloy and Clements (1992). Thus, IOC developed in a promotion focus seem to have

the same functional significance as naturally occurring IOC.

The present research is in accord with empirical evidence (e.g., Crowe & Higgins, 1987;

Liberman et al., 2001) showing that a promotion focus is associated with eagerness to attain a goal

(i.e., ensure “hits”), whereas a prevention focus is associated with vigilance to detect mistakes that

could lead to failure (i.e., “correct rejections”). These differences in strategic inclination seem to

provoke higher IOC in individuals with a promotion focus as compared to individuals with a

prevention focus. Presumably, regulatory focus influences the development of IOC through biasing

information processing towards either matches to desired end-states (promotion focus) or

mismatches to desired end-states (prevention focus), which, in conjunction with the control


heuristic (Thompson et al., 1998), facilitates the development of IOC in promotion-focused

individuals.

The overall evidence suggests that regulatory focus influences the development of IOC

through differences in information processing and not through differences in motivational factors.

As Thompson et al. (1998) have demonstrated, a strong desire for control may facilitate the

occurrence of IOC. However, most individuals have a strong desire to obtain control over important

environmental outcomes (Bandura, 1998), and there is no evidence so far which suggests that

prevention-focused individuals have a weaker desire for control than promotion-focused

individuals. To empirically address this issue, future studies may independently manipulate desire

for control and regulatory focus to explore the interaction of both factors. Along with the results of

the present research, regulatory focus theory suggests that the difference between promotion-

focused individuals and prevention-focused individuals in IOC increases as desire for control

increases.

More generally, the present studies suggest that perceptions of control tend to evolve in a

way that increases regulatory fit. Higgins (2000) theory of regulatory fit proposes that when the

general means employed to pursue a goal fit (vs. do not fit) an individual’s regulatory orientation,

then the value of these strategies increases. Moreover, this increased sense of value is assumed to

translate into higher motivational intensity to pursue a goal and ultimately should facilitate higher

performance. In support of this notion, research has found that promotion-focused individuals are

more motivated to pursue a goal and show a higher performance when eagerness-related means

(rather than vigilant-related means) are required for successful goal pursuit. In addition, prevention-

focused individuals demonstrate a higher motivation and better performance when vigilant means

(rather then eagerness means) are required for goal pursuit (see Förster, Higgins & Idson, 1998;

Spiegel, Grant-Pillow & Higgins, 2004). Clearly, developing high perceptions of control reflects

eagerness to pursue one’s goals, whereas developing low perceptions of control reflects a more

vigilant means. In effect, then, control perceptions seem to develop in a way that fits a persons


dominant regulatory orientation.

However, since IOC are codetermined by other factors than regulatory focus (see Thompson

et al., 1998), there may be instances in which promotion-focused individuals develop low IOC (e.g.,

feedback seems to indicate failure to control an outcome) and, similarly, instances in which

prevention-focused individuals develop high IOC (e.g., feedback seems to indicate success to

control an outcome). Such circumstances may lower regulatory fit with respect to IOC, which may

in turn have adverse consequences for motivation and performance. This reasoning may help to

explain some of the inconsistencies reported in the empirical literature on the effects of IOC.

Whereas Taylor and Brown (1998, see also Taylor, 1989) have argued that positive illusions (which

include illusions of control and unrealistic optimism) are generally beneficial, this assertion has not

been left unchallenged (Colvin & Block, 1994). Indeed, the empirical evidence suggests that

positive illusions and high optimism can be more detrimental than beneficial in the long run

(Robins & Beer, 2001; Weinstein & Lyon, 1999). Regulatory fit theory may help to resolve this

apparent inconsistency. Positive illusions in general and high IOC in particular are instances of

eagerness-related means of goal pursuit and may hence facilitate emotional well-being and goal

pursuit if adopted by promotion-focused individuals. On the other hand, positive illusions may be of

less value to prevention-focused individuals who prefer vigilant (i.e., more cautious) means of goal

pursuit. The results of Study 3 generally support this reasoning by showing that high IOC seem to

buffer against the emotional consequences of failure in promotion-focused participants, whereas

high IOC were related to more emotional impairment after failure in prevention-focused

individuals. However, future research should gauge the generality of this finding.

In sum, the present research found encouraging results which show that regulatory focus

may play an important role in the development of IOC, thereby having an influence on more

general motivational and emotional processes. By extending the scope of the present research, we

may be able to better understand the origins of illusions of control and their adaptive or less

adaptive functions in emotional and motivational processes.


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Authors’ Note

Thomas A. Langens, University of Wuppertal, Wuppertal, Germany.

I wish to thank Petra Höger and Dorothea Krämer for their help in data collection.

Correspondence concerning this article should be addressed to Thomas A. Langens, Department of

Psychology, University of Wuppertal, Gauss-Strasse 20, 42097 Wuppertal, Germany. Email:

[email protected]


Footnotes

1 A preliminary study found that the task yielded higher ratings of perceived control when some of

the fields in the matrix were colored.


Table 1

Hierarchical Regression of Positive Mood at T3 (Study 3).

Step Variable ΔR2 df ΔF ba

1 Positive Mood T2 .482 1, 88 81.97 .70***

2 Main Effects .038 2, 86 3.37*

Perceived Control -.04

Experimental Condition (EC) .20*

3 Perceived Control × EC .076 1, 85 16.02** .36**

Cumulative R2

.596

4, 85

13.19***

Note. a b is the standardized regression coefficient in the regression equation.

* p < .05. ** p < .01. *** p < .001.


Figure Captions

Figure 1. An illustration of the computer task employed in Studies 1 to 3. The task was to

maneuver the face through the matrix to the lower-right-hand corner in which the face either did or

did not change its color (Studies 1 and 2) or remained neutral or changed its expression (Study 3).

Figure 2. Positive mood at the beginning of the experiment (T1), after the matrix task (T2)

and following failure (T3) as a function of regulatory focus. The dashed line indicates the

prevention focus condition; the solid line the promotion focus condition (Study 3).

Figure 3. Positive mood after failure as a function of regulatory focus and perceived control,

computed for values one SD below (low) and above (high) the mean of perceived control. The

dashed line indicates the prevention focus condition; the solid line the promotion focus condition

(Study 3).


goal

Figure 1.


1

2

3

4

T1 T2 T3

Posi

tive

Moo

d

Figure 2.


1

2

3

4

low high

Perceived Control

Posi

tive

Moo

d T3

Figure 3.

Running head: Regulatory Focus and Illusions of Control Regulatory Focus and Illusions of ControlMood Measures Table 1Positive Mood T2

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