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ON METACOGNITION AND CULTURE
Aner Sela
Jonah Berger
Running Head: Metacognition and Culture
Aner Sela, University of Florida, 267 Stuzin Hall, Gainesville, FL 32611
(aner.sela@warrington.ufl.edu).
Jonah Berger, University of Pennsylvania, 700 Jon M. Huntsman Hall, 3730 Walnut Street,
Philadelphia, PA 19104 (jberger@wharton.upenn.edu).
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Metacognition impacts judgment and decision making, but might its effects vary by
culture? Culture shapes the meaning people extract from experiences, and as a result, we suggest
it may impact the inferences people draw from metacognitive perceptions. Specifically, whereas
cultures with a disjoint agency model (e.g., European-American) see choice as diagnostic of the
inner self, cultures with a conjoint agency model (e.g., South-East Asian) see choice more as
reflecting external considerations. Consequently, conjoint agency contexts are less likely to use
metacognitive experiences that accompany choice as an input to judgments about inner
preferences and priorities. Accordingly, we show that Americans – but not Indians – interpreted
metacognitive perceptions of choice difficulty, thoughtfulness, and decision-effort as an
indication of inner states such as preference certainty and decision importance. Further, priming
participants with agency models from the other culture reversed these effects. These findings
further understanding of metacognition, culture, and the meaning of choice.
Keywords: Metacognition, Culture, Lay Theories, Models of Agency, Inferences, Choice
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Metacognitive experiences have an important impact on attitudes, judgment, and
decision-making. People form evaluations not only based on the content of their thoughts, but
also on their perceptions of cognitive experiences accompanying those thoughts (Schwarz 2004).
How difficult information is to process or recall, for example, influences perceptions of
truthfulness (Reber & Schwarz, 1999), distance (Alter & Oppenheimer, 2008), and liking and
choice (Labroo, Dhar, & Schwarz, 2007).
Based on existing research, one might assume metacognitive effects are universal. But
could they differ by culture? For example, might the meaning people draw from processing
difficulty depend on cultural background?
We suggest this possibility based on two literature streams: Research demonstrating that
metacognitive effects are largely inference-based and driven by people’s lay-theories (Schwarz
2004) and research demonstrating that culture shapes the meaning people draw from experiences
(Markus & Kitayama, 2003).
People often attend to metacognitive experiences, but what they infer from such
experiences depends on accessible lay-theories. Experiencing cognitive effort while recalling
childhood memories, for example, can lead people to infer that their childhood was either
pleasant or unpleasant depending on whether they believe that pleasant events are purged from
memory or that unpleasant events tend to be repressed (Briñol, Petty & Tormala 2006;
Winkielman & Schwarz, 2001).
Culture may influence the inferences people draw from metacognitive experiences
because it shapes the meaning drawn from experience more generally (Markus & Kitayama,
2003; Gelfand et al., 2011). Consider the act of choice. In Individualistic European-American
middle-class cultural contexts, or contexts characterized by disjoint models of agency (Markus &
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Kitayama, 2003; Markus et al., 2006; Savani, Markus, & Conner 2008; Stephens, Markus, &
Townsend, 2007), choice is seen as self-expressive and contingent on one’s inner preferences,
goals, and priorities.1 Accordingly, choice in individualistic cultures is seen as diagnostic of
one’s inner preferences (Snibbe & Markus, 2005). In collectivistic cultural contexts,
characterized by conjoint models of agency (e.g., Indian or East-Asian middle-class cultures, as
well as working-class American contexts), however, choice is seen less as an act of selfexpression and more as reflecting social considerations and obligations (Kim & Drolet, 2003;
Kim & Markus, 1999; Riemer et al., 2014; Savani et al., 2010). Indian contexts, for example,
“are less likely to encourage people to act according to their internal attributes and private states”
(Savani et al., 2008, p. 863). Thus, in collectivistic cultures the link between choice and
preference is weaker. People are less likely to use preference as an input to choice (Savani et al.
2008) and less likely to infer preference from the act of choice (Snibbe & Markus, 2005).
Building on these perspectives, we suggest that culture may also moderate certain
inferences from metacognitive perceptions that accompany choice. Specifically, whether people
see cognitive experiences such as choice difficulty as diagnostic of their inner preferences may
depend on the cultural context in which they are embedded. We test this proposition using
several established metacognitive effects, in which people infer (1) their ability to form a
preference based on their perceptions of decision difficulty (Novemsky et al., 2007), (2) their
level of certainty from their perceived amount of thoughtfulness (Barden & Petty, 2008), and (3)
how important a decision is to them based on how much effort they spent deciding (Sela &
Berger, 2012). While distinct, these various metacognitive effects are all based on perceived
1
Research on socioeconomic status and agency models (Conner Snibbe & Markus, 2005; Stephens et al., 2007)
uses college degree attainment as an indicator of middle-class SES, so we compare middle-class Americans to
middle-class Indians, as indicated by college degree attainment. We discuss social class in the general discussion.
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links between a particular metacognitive experience (i.e., choice difficulty, thoughtfulness,
decision effort) and a corresponding inner state that is being inferred (i.e., preference strength,
certainty, or subjective decision importance, respectively).
We hypothesize that such links are weaker in collectivistic contexts, in which a conjoint
model of agency is dominant (e.g., India). Just as people in collectivistic contexts are less likely
to infer preference from the act of choice, they should be less likely to use metacognitive
experiences that accompany choice as input to judgments about attributes of their inner
preferences and priorities (e.g., how strong my preference is, how certain I am). Individuals from
collectivistic cultures should still be sensitive to the metacognitive experience itself (e.g., choice
difficulty), they should just be less likely to use that information as a cue to judgments about
their inner preferences.
Experiments 1–4 test whether culture (American/Indian) moderates inferences regarding
inner preferences from metacognitive experiences accompanying choice. Experiment 5 tests the
underlying mechanism by directly priming models of agency. .Experiment 6 demonstrates that
Indians do draw metacognitive inferences that concern the external world and not inner
preferences. Thus, whether members of different cultures make the same metacognitive
inferences depends on specific lay-theories that exist in those cultures around specific
metacognitive experiences.
EXPERIMENT 1: PREFERENCE DISFLUENCY AND CHOICE DEFERRAL
Prior work using Americans found that preference disfluency (i.e., cognitive difficulty
during choice) is often attributed to difficulty forming a preference, leading to choice deferral
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(Novemsky et al. 2007). We predicted preference disfluency would increase deferral among
Americans, but not Indians.
Method
Participants were 150 MBA students who completed the study in their respective
countries. All participants had a college degree and were either fluent (Indian) or native
(American) English speakers. One participant failed to complete the session, leaving a total of
149 participants (Americans/Indians: N = 72/77; mean age = 29/28, 40%/39% women, none
significantly different).
First, we manipulated preference disfluency using a paradigm adapted from prior work
(Novemsky et al. 2007, study 2). Participants were randomly assigned to one of two Reasons
conditions (two vs. ten). They saw descriptions and pictures of two microwave ovens, and
before choosing, rated on a seven-point scale how difficult or easy it would be to list either two
(easy) or ten (difficult) reasons for choosing a specific option (1 = very difficult; 7 = very easy).
Consistent with Novemsky et al. (2007), participants were not asked to list reasons but merely
rated how difficult it would be to generate them. Prior research suggests that imagining how
difficult it would be to generate ten reasons leads to similar metacognitive effects as actually
generating them (Wänke, Bohner, & Jurkowitsch, 1997).
After rating difficulty, participants completed our key dependent variable, choice
deferral. They indicated whether they would “pick one of the two [microwave oven] options” or
“keep looking for other options”. Finally, participants reported demographic information
including their level of English.
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Results
Perceptions of Difficulty. We first examined whether the manipulation of decision
difficulty influenced subjective perceptions of difficulty. A Reasons x Culture ANOVA on
perceived difficulty revealed only a main effect of Reasons (F(1, 145) = 46.72, p < .001, η2 =
.24), suggesting that both Americans (Mten = 2.92 vs. Mtwo = 4.72; F(1, 145) = 27.08, p < .001)
and Indians (Mten = 2.71 vs. Mtwo = 4.21; F(1, 145) = 19.82, p < .001) perceived listing ten
reasons as more difficult. There was no Reasons x Culture interaction (F(1, 145) = .40, p > .52).
Choice Deferral. These subjective feelings of difficulty, however, only carried over to
impact choice deferral among Americans. As predicted, a Reasons x Culture logistic regression
on choice deferral revealed the predicted Reasons x Culture interaction (χ2(1) = 5.48, p < .02,
Exp(B) = .19; see fig. 1). Thinking about generating ten versus two reasons increased deferral
among Americans (Mten = 77.8% vs. Mtwo = 52.8%; χ2(1) = 4.79, p < .03, Exp(B) = 3.13), but
not among Indians (Mten = 57.1% vs. Mtwo = 69.0%; χ2(1) = 1.16, p > .28, Exp(B) = .59).
Moderated Mediation. A moderated mediation analysis (Hayes 2012, model 15) using
bootstrapping with 5000 samples and 95% confidence intervals (in brackets), revealed the
predicted moderated mediation on choice deferral (B = .84 [.002, 1.94]). Specifically, there was
an indirect effect of reasons on deferral, through difficulty, among Americans (B = -.67 [-1.54, .06]) but not Indians (B = .17 [-.42, .90]).
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Fig. 1:
Effect of Decision Difficulty on Choice Deferral (Experiment 1) 2 Reasons
% Choice Deferral
100%
77.8%
52.8%
10 Reasons
69.0%
57.1%
0%
Americans
Indians
Note: error bars represent 95% confidence intervals
Alternative Explanation. Casting doubt on the notion that cultural differences in effort or
task compliance drove the effects, there were no main effects or interaction involving either
culture or number of reasons on time spent on the task (all F(1, 145) < 1.57, p > .21). American
and Indian participants spent a similar amount of time on the task in both ten reasons condition
(MIndians = 84.68 vs. MAmericans = 60.09 seconds, F(1, 145) = 1.19, p > .27) and two reasons
condition (MIndians = 71.76 vs. MAmericans = 57.32 seconds, F(1, 145) = .45, p > .50). A nonparametric Kruskal-Wallis omnibus test confirmed that the distribution of time did not differ
across conditions (χ2(3, 149) = 5.91, p > .12).
Taken together, results of Experiment 1 suggest that while Americans and Indians are
both sensitive to experiences of cognitive difficulty during choice, this increased difficulty only
increased choice deferral among Americans.
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Follow-Up Study: Metacognitive Experiences versus Thought Content
Study 1 suggests that perceived decision difficulty is less likely to impact choice deferral
among Indians. But what drives Indians’ behavior? If our theorizing is correct that
collectivistic cultural contexts see metacognitive experiences accompanying choice as less
relevant for judgments about inner preferences, then members of such cultures should be more
likely to rely on thought content (e.g., the reasons generated) when forming preference certainty
judgments (Schwarz 1998).
A follow-up study confirmed this notion. Participants were recruited through Amazon’s
Mechanical Turk. We established participants’ culture using the country of origin filter, validated
by asking participants to indicate their home country, and sample sizes were based on prior work
on similar effects. We excluded participants based on the same criteria described in Experiment
1 as well as participants who listed bogus reasons (e.g., “NO”, “ok”), leaving 237 participants
(Americans/Indians: N = 137/100, mean age = 31/31, 40%/37% women). The procedure was
identical to Experiment 1, except that participants actually listed two versus ten reasons for
choosing a specific option instead of merely thinking about how difficult it would be to generate
those reasons. A non-parametric Kruskal-Wallis omnibus test on the average amount of text
entered for each reason confirmed that the distribution of text did not differ across cultures (p >
.64).
A Reasons x Culture logistic regression on choice deferral revealed the predicted Reasons
x Culture interaction (χ2(1) = 14.22, p < .001, Exp(B) = 8.03). Consistent with Experiment 1 and
prior research (e.g., Schwarz 1998; Schwarz et al., 1991), listing more reasons (ten versus two)
to choose a specific option increased choice deferral among Americans (Mten = 73.4% vs. Mtwo =
45.2%; χ2(1) = 11.19, p < .001). This effect reversed, however, among Indians. Listing more
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reasons (ten versus two) to choose a specific option decreased choice deferral among Indians
(Mten = 43.5% vs. Mtwo = 64.8%; χ2(1) = 4.57, p < .05), consistent with the notions that they
attend to thought content.
These results suggest that culture can shape the degree to which people rely on the
content of their thoughts versus their perceptions of cognitive experiences accompanying those
thoughts.
EXPERIMENT 2: INFERRING CERTAINTY FROM THOUGHTFULNESS
Prior work using Americans found that believing more thought has gone into a judgment
increases certainty about that judgment (Barden & Petty, 2008). In Experiment 2, we gave
Americans and Indians a choice and manipulated perceived thoughtfulness. We predicted that
perceiving increased thoughtfulness would increase decision certainty for Americans, but not
Indians.
Method
Participants (N = 245) were recruited through Amazon’s Mechanical Turk. We
established participants’ culture using the country of origin filter, validated by asking
participants to indicate their home country, and sample sizes were based on prior work on similar
effects. We excluded participants based on the same criteria described in Experiment 1 as well as
participants who listed bogus reasons (e.g., “NO”, “ok”), leaving 243 participants
(Americans/Indians: N = 125/118, mean age = 32/31, 53%/36% women). Participants were
randomly assigned to one of two thoughtfulness feedback conditions (high vs. low).
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First, participants completed a simple choice task that allowed us to manipulate perceived
thoughtfulness. They were told that the experimenters were interested in testing items for use in
future studies and wanted to see which option people found more attractive. Participants saw
four Mturk assignments (Appendix) and picked the most attractive one. Before choosing,
participants were asked to write pro and con arguments for each option2.
Second, we manipulated perceived thoughtfulness using a false feedback manipulation
validated in prior metacognition research (Barden & Petty 2008, study 4). False feedback enables
us to manipulate perceived thoughtfulness independent of actual thought (i.e., after thinking had
already occurred; see also Tormala & Petty, 2002). Participants in the high (low) effort condition
were told that, based on the arguments they listed, their choice process was more (less)
thoughtful and deliberative than that of 82% of other participants, such that most people
listed fewer (more) or shorter (longer) arguments than they did.
Third, participants completed our key dependent variable, decision certainty (i.e., how
certain they felt about their choice, how sure they were of their opinion about the options, and
how confident they were of their opinion about the options, all on nine-point scales, adapted
from Barden & Petty (2008); averaged to an index, αAmericans = .90, αIndians = .90). They also rated
perceived thoughtfulness: the extent to which they thought a lot about the options and took the
time to carefully deliberate about the decision (rAmericans = .77, rIndians = .56, averaged to an index).
2
Casting doubt on the possibility that the thoughtfulness manipulation did not affect Indians because they did not
pay attention or take the task seriously, Indians and Americans wrote similar amounts in all subsequent experiments.
In experiment 2, for example, Indians and Americans wrote similar amounts in both high feedback (MIndians = 174.45
vs. MAmericans = 208.54 characters, F(1, 239) = 1.96, p > .16) and low feedback conditions (MIndians = 181.21 vs.
MAmericans = 185.12 characters, F(1, 239) = .02, p > .88). A Kruskal-Wallis omnibus test confirmed that the
distribution of text entered was the same across conditions (χ2(3, 243) = 5.02, p > .17).
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Results
Perceived Thoughtfulness. A 2 (feedback) x 2 (culture) ANOVA on perceived
thoughtfulness revealed a main effect of feedback (Mhigh = 7.00 vs. Mlow = 6.00; F(1, 239) =
23.88, p < .001, η2 = .086). As in Experiment 1, there was no feedback x culture interaction (F(1,
239) = 1.16, p > .28, η2 = .004), suggesting the manipulation similarly impacted perceived
thoughtfulness among Indians (Mhigh = 6.49 vs. Mlow = 5.72; F(1, 239) = 7.04, p < .009, η2 =
.025) and Americans (Mhigh = 7.51 vs. Mlow = 6.30; F(1, 239) = 18.37, p < .001, η2 = .066).
Decision Certainty. These perceptions of thoughtfulness, however, only carried over to
impact certainty among Americans. A 2 (feedback) x 2 (culture) ANOVA on certainty revealed a
main effect of feedback (F(1, 239) = 6.26, p < .02, η2 = .025) which was qualified by the
predicted interaction (F(1, 239) = 6.98, p < .009, η2 = .027; see fig. 2). Specifically, feeling like
they engaged in more thoughtful deliberation increased certainty among Americans (Mhigh = 7.93
vs. Mlow = 7.01; F(1, 239) = 13.68, p < .001, η2 = .054) but not among Indians (Mhigh = 7.66 vs.
Mlow = 7.69; F(1, 239) = .01, p > .92, η2 < .001).
Moderated Mediation. A bootstrapping moderated mediation analysis (Hayes 2012)
revealed the predicted moderated mediation on choice deferral (B = -.22 [-.51, -.012]).
Specifically, there was an indirect effect of feedback on certainty, through thoughtfulness,
among Americans (B = .26 [.10, .50]) but not Indians (B = .04 [-.10, .20]).
Similar to Experiment 1, these results indicate that while culture did not impact
perceptions of the cognitive experience itself (i.e., feedback equally impacted perceived
thoughtfulness for both Americans and Indians), only Americans attributed this experience to
certainty.
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Given that people in collectivistic cultures often put more weight on information
regarding others, one may wonder whether providing a social comparison cue should have
impacted Indians’ judgment. Note, however, that participants were not given information about
in-group members. Rather, they were only told that they deliberated more or less than other
anonymous Mechanical Turkers. Although collectivists heavily weigh inputs from relevant and
important in-group members, they do not do the same for other people who are not meaningful
in-groups (Iyengar & Lepper, 1999; Savani et al, 2008; Wong & Hong, 2005). If Indians were
given information about what relevant in-group members think, they should respond to that
information. We test this idea more explicitly in Experiment 4. We also show that dropping the
mention of anonymous Mechanical Turkers leads to similar results in a replication of Experiment
3 below.
Fig. 2:
Effect of Thoughtfulness on Attitude Certainty (Experiment 2) Low Feedback
Certainty
9
8
7.93 High Feedback
7.69 7.66 7.01 7
6
5
Americans
Indians
Note: error bars represent 95% confidence intervals
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EXPERIMENT 3: INFERRING DECISION IMPORTANCE FROM EFFORT
Prior work using Americans found that perceiving greater decision effort leads people to
perceive decisions as more personally important (Sela & Berger, 2012). In Experiment 3, we
predicted that perceiving increased decision effort (manipulated using a false feedback paradigm
similar to that used in Experiment 2) would lead American, but not Indian participants to
perceive those decisions as more important.
Method
American and Indian participants (N = 456) were recruited using the same procedure
described in Experiment 2. We excluded participants based on the same criteria described in
Experiment 2, leaving 431 participants (Americans/Indians: N = 161/270, mean age = 33/32,
53%/42% women).
First, participants completed the choice task from Experiment 2, listing reasons for
choosing each option. Casting doubt on the notion that the effort manipulation did not affect
Indians because they did not pay attention or take the task seriously, there were no main effects
or interaction involving either culture or feedback (all F(1, 427) < .90, p > .35) on amount
written (also see footnote 2).
Second, we manipulated perceived decision effort using a false feedback manipulation
similar to that used in Experiment 2, only this time feedback referred to decision effort rather
than thoughtfulness. In the high (low) effort condition, we told participants that based on the
reasons they listed, they spent more (less) effort on the decision than 82% of the other
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participants in this study, such that most people listed fewer (more) or shorter (longer) reasons
than they did.
Third, participants rated on a nine-point scale how important the decision was for them,
which was our key dependent variable.
Fourth, we also measured the process or how hard participants thought and how much
effort they spent thinking about the decision (averaged to form an index).
Results
Perceived Effort. Validating our decision effort manipulation, a 2 (Effort Feedback) x 2
(Culture) ANOVA on perceived effort revealed a main effect of effort feedback (Mlow-effort = 6.76
vs. Mhigh-effort = 7.28; F(1, 427) = 12.16, p < .001, η2 < .039). Consistent with the previous
experiments, there was no interaction due to culture (F(1, 427) = .38, p > .53), suggesting that
both Americans (Mlow-effort = 6.35 vs. Mhigh-effort = 6.95; F(1, 427) = 6.71, p = .01) and Indians
(Mlow-effort = 7.00 vs. Mhigh-effort = 7.42; F(1, 427) = 5.52, p < .02) perceived decision effort as
higher in the high feedback condition.
Decision Importance. These perceptions of decision effort, however, only carried over to
impact perceived importance among Americans. In addition to main effects of culture (F(1, 427)
= 89.77, p < .001, η2 = .167) and effort feedback (F(1, 427) = 12.02, p < .001, η2 = .022), a 2
(Effort) x 2 (Culture) ANOVA on perceived decision importance revealed the predicted Effort x
Culture interaction (F(1, 427) = 5.47, p < .02, η2 = .010; see fig. 3). Specifically, perceived
decision effort increased perceived decision importance among Americans (Mlow-effort = 5.94 vs.
Mhigh-effort = 6.84; F(1, 427) = 13.43, p < .001, η2 = .025), but not among Indians (Mlow-effort = 7.76
vs. Mhigh-effort = 7.94; F(1, 427) =.85, p > .36, η2 = .001).
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Fig. 3:
Effect of Decision Effort on Perceived Decision Importance (Experiment 3) Low Feedback
Decision Importance
High Feedback
9
7.76 7.94 8
6.84 7
5.94 6
5
Americans
Indians
Note: error bars represent 95% confidence intervals
Moderated Mediation. A bootstrapping moderated mediation analysis (Hayes 2012)
revealed a significant moderated mediation term (B = -.14 [-.25, -.06]), suggesting that the
indirect effect of feedback on perceived decision importance, through perceived effort, was
significantly larger among Americans (B = .19 [.08, .31]) than among Indians (B = .05 [.01,
.12]).
Consistent with the first two experiments, results of Experiment 3 indicate that while
Americans and Indians are equally sensitive to perceived decision effort, this perceived effort
had a greater impact on perceived decision importance among Americans more than among
Indians.
Replication. Note that we found the same results when the false feedback manipulation
did not reference others at all. In a replication of Experiment 3, participants (N = 279) were
simply told that, based on the arguments they listed, their decision process was quite effortful
17
[effortless]. Results were identical. Although everyone perceived decision effort as higher in the
high feedback condition (main effect of effort feedback, F(1, 275) = 5.36, p < .05; no feedback X
culture interaction, F(1, 275) = .36, p = .55), perceptions of decision effort carried over to impact
perceived importance among Americans (F(1, 275) = 10.55, p < .001) but not Indians (F(1, 275)
= .45, p = .50). A bootstrapping moderated mediation analysis (Hayes 2012) revealed significant
moderated mediation (B = -.22 [-.52, -.05]), suggesting that perceived effort mediated the effect
of feedback on perceived decision importance for Americans (B = .24 [.06, .52]) but not for
Indians (B = .02 [-.04, .14]).
These findings bolster the validity of our main manipulation and underscore our
suggestion that referencing anonymous Mechanical Turkers – who are not meaningful in-group
members – should not lead collectivists to heavily weigh that information. Experiment 4 tests
whether referencing meaningful in-group members has different effects.
EXPERIMENT 4: CONTRASTING METACOGNITIVE EXPERIENCES AND SOCIAL
IMPERATIVES
Experiment 4 independently manipulates perceived decision effort and input about
decision importance from relevant in-groups. We predicted that perceiving increased decision
effort would lead American, but not Indian participants to perceive the decision as more
important. Given that Indians seem to rely more of social imperatives (Savani et al 2008),
perceiving that relevant in-groups see the decision as more versus less important should have a
larger effect on Indians than Americans.
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Method
American and Indian participants (N = 464) were recruited using the same procedure
described in Experiment 2. We excluded participants based on the same criteria described in
Experiment 2, leaving 435 participants (Americans/Indians: N = 248/187, mean age = 32/33,
42%/36% women).
The procedure was identical to that described in Experiment 3, in which we manipulated
perceived decision effort using a false feedback manipulation, with one important difference.
After participants listed reasons for choosing each option, but before they received feedback
about the amount of decision effort spent, we manipulated a relevant social cue for decision
importance. Specifically, in the important (unimportant) cue condition, we asked participants to
imagine that one or both of their parents were asked to evaluate the same four options they had
evaluated on the previous page, and to take a moment to think about why their parents might
think that it was an important (unimportant) decision. Participants then wrote down at least one
reason their parents might have thought it was an important (unimportant) decision. Thus, the
experiment had a 2 (Effort Feedback: high vs. low) x 2 (Parental Importance Cue: high vs. low)
x 2 (Culture) between-subjects design.
As in Experiment 3, participants rated on a nine-point scale how important the decision
was for them, which was our key dependent variable. As a manipulation check, participants also
rated the extent to which they thought their parents would say it was an important decision, if
they had actually taken the study (1 = not at all important; 7 = very important).
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Results
Manipulation Check. Validating our parental importance manipulation, a 2 (Effort
Feedback) x 2 (Parental Importance) x 2 (Culture) ANOVA on the perceived importance of the
decision for one’s parents revealed main effects of parental importance cue (F(1, 427) = 60.97, p
< .001, η2 = .125) and culture (F(1, 427) = 106.58, p < .001, η2 = .200), with no parental
importance x culture interaction (F(1, 427) = 2.15, p > .14, η2 = .005). Both Americans
(Mparents_unimportant = 3.07 vs. Mparents_important = 4.51; F(1, 427) = 50.58, p < .001, η2 = .106) and
Indians (Mparents_unimportant = 4.89 vs. Mparents_important = 5.88; F(1, 427) = 17.48, p < .001, η2 = .039)
believed that their parents would perceive the decision as more important in the high parental cue
condition than in the low parental cue condition.
Perceived Decision Importance. Consistent with Experiment 3, we expected that
perceived decision effort would impact perceived decision importance among Americans but not
among Indians. Parental importance, however, should have a larger effect on Indians than
Americans.
Results are consistent with both these predictions. In addition to main effects of culture
(F(1, 427) = 83.11, p < .001, η2 = .163), effort feedback (F(1, 427) = 3.93, p < .05, η2 = .009),
and parental importance cue (F(1, 427) = 5.55, p < .02, η2 = .013), a 2 (Effort) x 2 (Parental
Importance) x 2 (Culture) ANOVA on perceived decision importance revealed the predicted
effort x culture interaction (F(1, 427) = 4.13, p < .05, η2 = .010) and parental importance cue x
culture interaction (F(1, 427) = 3.29, p = .07, η2 = .008).
Consistent with Experiment 3, decision effort feedback influenced perceived decision
importance for Americans (Mlow-effort = 5.68 vs. Mhigh-effort = 6.39; F(1, 427) = 9.47, p < .005, η2 =
.022) but not Indians (Mlow-effort = 7.65 vs. Mhigh-effort = 7.64; F(1, 427) = .001, p = .97, η2 = .000).
20
Further, parental importance cue influenced perceived decision importance among
Indians (Mparents_unimportant = 7.28 vs. Mparents_important = 8.02; F(1, 427) = 7.56, p < .01, η2 = .017)
but not among Americans (Mparents_unimportant = 5.99 vs. Mparents_important = 6.08; F(1, 427) = .17, p =
.68, η2 = .000).
Of note, whereas for Americans, effort feedback had a larger effect (.39, 95% C.I. [.14,
.64]) than parental importance cue (.05 [-.20, .30]; pdifference < .06; Hedges & Olkin, 1985),
parental importance cue had a larger effect than effort feedback for Indians (.40 [.11, .69] vs. .00
[-.29, .28]; pdifference < .055).
Experiments 1–4: Discussion
Using various metacognitive paradigms, Experiments 1–4 demonstrate that culture
moderates inferences of inner states from metacognitive experiences that accompany choice.
While culture did not impact perceptions of the cognitive experiences themselves, the
consequences of those perceptions varied by culture. Americans, who typically have a disjoint
model of agency, interpreted choice difficulty, thoughtfulness, and decision effort as indicating
preference weakness, certainty, and decision importance (respectively). Indians, however, who
typically have a conjoint model of agency in which choice is not seen as reflecting inner
preferences, did not draw similar inferences based on the same perceived experiences. In
contrast, Indians were more likely to infer properties of their inner preferences from information
about the preferences and priorities of important in-group members (Experiment 4).
To more directly test our suggestion that these effects are driven by models of agency,
and rule out alternative explanations, the next experiment primes different agency models within
members of the same culture. Prior work (Brewer & Gardner, 1996; Oyserman & Lee, 2008)
21
shows certain constructs may vary cross-culturally, but priming those constructs directly (thereby
making them accessible) provides stronger evidence for the causal impact of culture.
EXPERIMENT 5: PRIMING AGENCY MODELS
In Experiment 5, we primed Indian and American participants with either a disjoint (i.e.,
that choice reflects inner preferences) or conjoint model of agency (i.e., that choice reflects
societal imperatives). If agency models underlie the observed effect of culture, as we suggest,
then priming agency models should have a similar effect to culture itself. For Americans,
priming a conjoint model should lead them to behave more like Indians, namely, eliminate their
baseline tendency to perceive more effortful decisions as more important. Priming Americans
with a disjoint model, however, should have no impact on inferences relative to the baseline.
For Indians, the reverse should occur. Priming a disjoint model should lead Indians to
behave more like Americans and perceive more effortful decisions as more important. Priming
Indians with a conjoint model should have no impact on inferences relative to the baseline.
Method
Participants (N = 370) were recruited using the method from experiment 2. We excluded
participants based on the same criteria described in Experiment 2, leaving 369 participants
(Americans/Indians: N = 196/173, mean age = 31/30, 62%/41% women). They were randomly
assigned to condition in a 2 (Effort Feedback: high vs. low) x 3 (Prime: disjoint agency vs.
conjoint agency vs. control) between-subjects design. Participants completed a sequence of
purportedly unrelated tasks.
22
First, we manipulated agency model through priming. Participants were told that the
experimenters were interested in learning about their life experiences. In the disjoint (conjoint)
agency condition, participants reflected on a choice they made that strongly expressed their
individual identity or inner preferences (that was strongly influenced by an external or societal
imperative), and described it in detail. Control participants listed the food items they consumed
that day.
Second, participants completed the choice task from experiment 3. They chose from four
possible assignments, provided pros and cons for each, and were given false feedback that they
expended either high or low effort.
Finally, participants rated our key dependent variable, decision importance, using the
measure from experiment 3.
Results
Decision Importance. A 2 (Effort Feedback: high vs. low) x 3 (Prime: disjoint agency vs.
conjoint agency vs. control) x 2 (Culture: Indians vs. Americans) ANOVA revealed main effects
of culture (F(1, 357) = 9.47, p < .005, η2 = .024) and feedback (F(1, 357) = 10.61, p < .001, η2 =
.027) and a feedback x prime interaction (F(2, 357) = 4.79, p < .01, η2 = .024)3. For ease of
interpretation, we next test our predictions for each culture separately.
Because American culture is characterized by a disjoint agency model, priming this
model should not impact Americans’ metacognitive inferences. Just as in the control condition,
3
As predicted, the only condition in which the two cultures differed was the control. There, analysis revealed a
significant effort feedback x culture interaction similar to Experiment 3 (F = 4.45, p < .04). In the other two
conditions, Indians and Americans behaved similarly: In the disjoint condition, there was only a main effect of effort
feedback (F = 16.24, p < .001) with no effort feedback x culture interaction (F = 1.43, p > .23); in the conjoint prime
condition, there were no main or interaction effects (all F’s < .33, p > .57).
23
they should perceive more effortful decisions as more important. Priming a conjoint model of
agency, however, should attenuate Americans’ tendency to draw such inferences.
Consistent with our theorizing, for Americans, in addition to a main effect of effort
feedback (F(1, 190) = 10.07, p < .002), a 2 (effort feedback) x 3 (prime) ANOVA on perceived
decision effort revealed the predicted effort x prime interaction (F(2, 190) = 3.21, p < .05). See
fig. 5A.
As expected, manipulating perceived decision effort influenced perceived decision
importance in both the control (Mhigh-effort = 7.55 vs. Mlow-effort = 6.38; F(1, 190) = 7.83, p < .006)
and disjoint prime condition (Mhigh-effort = 7.43 vs. Mlow-effort = 5.89; F(1, 190) = 12.50, p < .001).
Priming a conjoint model of agency, however, led Americans to behave more like Indians. For
these participants, the tendency to infer decision importance from decision effort disappeared
(Mhigh-effort = 7.14 vs. Mlow-effort = 7.29; F(1, 190) = .09, p > .77).
Fig. 5A:
Priming Models of Agency, American Participants (Experiment 5)
Low Effort Feedback High Effort Feedback
Decision Importance
9
8
7
7.55
7.43
5.89
7.29
7.14
6.38
6
5
4
Disjoint Agency Prime
Control
Conjoint Agency Prime
Note: error bars represent 95% confidence intervals
24
We next examined the results among Indians. Because Indian culture is characterized by
a conjoint agency model, priming this model should not impact Indians’ metacognitive
inferences. Just as in the control condition, there should be no effect of effort feedback on
perceived decision importance. Priming a disjoint model, however, should lead Indians to see
more effortful decisions as more important (because they should see their choice as more closely
reflective of inner states).
Consistent with this theorizing, a 2 (Effort Feedback) x 3 (Prime) ANOVA on perceived
decision importance revealed a marginally significant Effort x Prime interaction for Indians (F(2,
167) = 2.26, p = .1; see fig. 5B). As expected, manipulating perceived decision effort did not
influence Indians’ perceived decision importance in either the control (Mhigh-effort = 7.57 vs. Mloweffort
= 7.49; F(1, 167) = .06, p > .80) or conjoint prime conditions (Mhigh-effort = 7.32 vs. Mlow-effort
= 7.48; F(1, 167) = .14, p > .71). Priming a disjoint model of agency, however, led Indians to
behave more like Americans. For these participants, increasing perceived decision effort
increased perceived decision importance (Mhigh-effort = 8.13 vs. Mlow-effort = 7.05; F(1, 167) = 5.74,
p < .02).
These results suggest that the effect of culture on metacognitive inference reflects cultural
differences in lay-theories and models of agency people recruit to interpret their experiences.
Americans interpreted decision effort as indicating decision importance. Priming Indians with a
disjoint agency model led them to behave like Americans and show similar effects. Unprimed
Indian participants, however, did not draw the same inference nor did Americans primed with a
conjoint agency model.
25
Fig. 5B:
Priming Models of Agency, Indian Participants (Experiment 5)
Low Effort Feedback
High Effort Feedback
Decision Importance
9
8
8.13
7.05
7.49 7.57
7.48 7.32
Control
Conjoint Agency Prime
7
6
5
4
Disjoint Agency Prime
Note: error bars represent 95% confidence intervals
EXPERIMENT 6: THE EFFECT OF CULTURE DEPENDS ON JUDGMENT TYPE
We have demonstrated a cultural difference in metacognition, but we are not suggesting
that collectivistic contexts never rely on metacognitive cues. Rather, we suggest more
specifically that members of collectivistic contexts are less likely to use metacognitive
experiences accompanying choice as an input to judgments about inner preferences.
To test this point, Experiment 6 investigates how perceptual disfluency influences two
types of judgments, those related to inner preferences (i.e., preference certainty) and those that
are not (i.e., distance judgments, which concern the external world and not inner preferences). If
our theorizing is correct, culture should moderate the former but not the latter.
26
Method
Participants (N = 404) were recruited using the method from Experiment 2
(Americans/Indians: N = 199/205, mean age = 35/33, 52%/43% women). They were randomly
assigned to condition in a 2 (Perceptual Disfluency: fluent vs. disfluent) x 2 (Judgment: distance
vs. preference certainty) between-subjects design.
We used a manipulation adapted from prior research (Alter & Oppenheimer, 2008), in
which presenting city names in disfluent font led people to estimate that the cities were farther
away than when the same names were presented in fluent font. We used the same disfluency
manipulation but varied whether the focal judgment concerned distance (i.e., an external
property) or perceptions of one’s own preferences (i.e., an inner state).
Twenty pairs of European city names (e.g., Porto/Lisbon; Zurich/Geneva;
Florence/Rome) were sequentially presented to participants using the same fluent versus
disfluent font used by Alter & Oppenheimer (2008; study 1a). The cities in each pair were in the
same country and fairly close to one another in relation to participants’ location (USA or India).
Participants in the distance judgment condition were asked to estimate how far away, in
miles or kilometers, their current location was from the average location of the two cities in each
pair. They entered a number for each pair. Following Alter & Oppenheimer (2008), to reduce
variance across estimates, the sequence began with a sentence stating that the average distance
between the US [India] and Europe is approximately 4,000 miles or 6,500 kilometers.
Participants in the preference judgment condition were asked to enter a number from 1 to
100 representing how certain they were about which of the two cities they would rather visit if
given the opportunity to choose. To illustrate, they were instructed to enter a number close to 100
27
if they were completely certain which city they preferred to visit, but to enter a number close to 1
if they were completely uncertain which city they preferred to visit.
In both judgment conditions, we asked participants to refrain from looking up online any
information about the cities because we were interested in learning about people’s spontaneous
estimates and preferences, and emphasized that “there are no extra points for getting it exactly
right”. To eliminate unit (miles versus kilometers) and scale differences (distance versus rating),
we averaged and standardized participants’ responses. We reversed the preference ratings to
yield a comparable index to the distance estimates, such that in both cases, prior findings would
predict lower values in the fluent compared to the disfluent condition.
Results
In addition to main effects of culture (F(1, 396) = 4.29, p < .05, η2 = .01), fluency (F(1,
396) = 10.57, p < .001, η2 = .025), and judgment type (F(1, 396) = 6.33, p < .05, η2 = .015), a 2
(Perceptual Disfluency: fluent vs. disfluent) x 2 (Judgment: distance vs. preference) x 2 (Culture:
Indians vs. Americans) ANOVA revealed the predicted culture x fluency x judgment interaction
(F(1, 396) = 3.54, p = .06, η2 = .01). For ease of interpretation, we test our predictions separately
for each judgment condition.
First, we examined judgments of preference certainty. Consistent with our other studies,
in addition to main effects of fluency (F(1, 231) = 4.14, p < .05) and culture (F(1, 231) = 6.62, p
< .01), a 2 (fluency) x 2 (culture) ANOVA on preference certainty revealed the predicted fluency
x culture interaction (F(1, 231) = 5.79, p < .02). As expected, perceptual disfluency decreased
preference certainty (represented here in reversed form such that higher values reflect decreased
28
certainty) for Americans (Mfluent = -.147 vs. Mdisfluent = .131; F(1, 231) = 8.78, p < .003) but not
Indians (Mfluent = .164 vs. Mdisfluent = .141; F(1, 231) = .08, p = .78).
Second, we examined judgments of distance. Because distance judgments concern
external properties rather than inner states and preferences, we did not expect differences
between our American and Indian participants. As predicted, a 2 (fluency) x 2 (culture) ANOVA
on distance estimate revealed only a main effect of fluency (F(1, 165) = 8.42, p < .005), with no
fluency x culture interaction (F(1, 165) = .05, p = .82). Compared to fluency, experiencing
disfluency increased distance estimates for both Americans (Mfluent = -.116 vs. Mdisfluent = .026;
F(1, 165) = 4.12, p < .05) and Indians (Mfluent = -.110 vs. Mdisfluent = .056; F(1, 165) = 4.33, p <
.04).
These results underscore our theorizing that members of collectivistic context are less
likely to use metacognitive experiences accompanying choice as an input to judgments about
inner preferences (e.g., preference certainty). Judgments unrelated to inner preferences (e.g.,
distance estimates), however, were equally affected by disfluency in both collectivistic and
individualistic cultural contexts.
GENERAL DISCUSSION
Metacognition impacts judgment and decision making. But while existing research
implicitly assumes that metacognitive effects are universal, could they differ by culture?
This paper demonstrates how culture may influence metacognition. While Americans
deferred choice following choice disfluency (Experiments 1), saw thoughtfulness as an indicator
of certainty (Experiment 2), and inferred effortful decisions were more important (Experiments
29
3–5), Indians did not. These differences seem to be driven by culture-borne models of agency
that people recruit to examine their cognitive experiences: Priming those models shapes the
meanings people draw from cognitive experiences accompanying choice (Experiment 5).
Whether members of different cultural contexts make the same metacognitive inferences
will depend on the specific lay-theories that exist in those cultures around a given cognitive
experience. Indeed, in Experiment 6, culture did not moderate fluency effects on distance
judgments because the lay-theories that underlie those judgments do not vary by culture in the
same way that lay-theories about inner preferences do.
While we focused on cross-cultural differences, future work may examine social classes
within the same culture. Within American culture, for example, higher socioeconomic status is
associated with a more disjoint model of agency whereas lower SES is associated with a more
conjoint model (Conner et al., 2005; Stephens et al., 2007; Stephens et al., 2011). Indeed,
additional data we collected found that compared to higher SES individuals, lower SES
individuals are less likely to infer decision importance from decision effort.
This work integrates research on metacognition and culture to provide a deeper
understanding of how cognitive experiences shape judgment and behavior. Just as studying
culture provided deeper insight into choice (Kim & Markus, 1999), attribution (Morris & Peng
1994), and motivation (Markus & Kitayama, 1991), it may also shed light on the underpinnings
of metacognition. Lay-theories play an important role in metacognition, and culture-specific
models of agency are one important determinant of lay-theories that can shape inferences.
30
AUTHOR CONTRIBUTIONS
Aner Sela and Jonah Berger both contributed to the conceptual development and study
design. Data collection and analysis were performed by Aner Sela. Both authors crafted the
manuscript and approved the final version for submission.
31
REFERENCES
Alter, A.L., & Oppenheimer, D.M. (2009). Uniting the Tribes of Fluency to Form a
Metacognitive Nation. Personality and Social Psychology Review, 13 (3), 219–235.
Barden, J. & Petty, R.E. (2008). The Mere Perception of Elaboration Creates Attitude Certainty:
Exploring the Thoughtfulness Heuristic. Journal of Personality and Social Psychology,
95 (3), 489–509.
Brewer, M. B., & Gardner, W. (1996). Who is this “We”? Levels of collective identity and self
representations. Journal of personality and social psychology, 71 (1), 83–93.
Brinõl, P., Petty, R.E., & Tormala, Z.L. (2006). The Malleable Meaning of Subjective Ease.
Psychological Science, 17 (3), 200–206.
Conner Snibbe, A., & Markus, H.R. (2005). You can’t always get what you want: Educational
attainment, agency, and choice. Journal of Personality and Social Psychology, 88
(4), 703-720.
Gelfand, M.J., Raver, J.L., Nishii, L., Leslie, L.M., Lun, J., Lim, B.C., Duan, L., Almaliach, A.,
Ang, S., Arnadottir, J., Aycan, Z., Boehnke, K., Boski, P., Cabecinhas, R., Chan, D.,
Chhokar, J., D’Amato, A., Ferrer, M., Fischlmayr, I.C., Fischer, R., Fülöp, M., Georgas,
J., Kashima, E.S., Kashima, Y., Kim, K., Lempereur, A., Marquez, P., Othman, R.,
Overlaet, B., Panagiotopoulou, P., Peltzer, K., Perez-Florizno, L.R., Ponomarenko, L.,
Realo, A., Schei, V., Schmitt, M., Smith, P.B., Soomro, N., Szabo, E., Taveesin, N.,
Toyama, M., Van de Vliert, E., Vohra, N., Ward, C., Yamaguchi (2011). Differences
Between Tight and Loose Cultures: A 33-Nation Study. Science, 332, 1100–1104.
32
Hayes, A. F. (2012). Process: a versatile computational tool for observed variable mediation,
moderation, and conditional process modeling. white paper, retrieved from
http://www.afhayes.com/public/process2012.pdf
Hedges, L.V., & Olkin, I. (1985). Statistical Models for Meta-Analysis. New York: Academic
Press.
Iyengar, S.S., & Lepper, M.R. (2000). When Choice Is Demotivating: Can One Desire Too
Much of a Good Thing? Journal of Personality and Social Psychology, 79 (6), 995–1006.
Kim, H.S. & Drolet, A.(2003). Choice and Self-Expression: A Cultural Analysis of VarietySeeking. Journal of Personality and Social Psychology, 85 (2), 373-382.
Kim, H.S. & Markus, H.R. (1999). Deviance or Uniqueness, Harmony or Conformity? A
Cultural Analysis. Journal of Personality and Social Psychology, 77 (4), 785-800.
Kitayama, S., Conner Snibbe, A., Markus, H.R., & Suzuki, T. (2004). Is There Any “Free”
Choice? Self and Dissonance in Two Cultures. Psychological Schience, 15 (8), 527-533.
Labroo, A.A., Dhar, R., & Schwarz, N. (2008). Of frowning watches and frog wines: Semantic
priming, perceptual fluency, and brand evaluation. Journal of Consumer Research, 34,
819–831.
Markus, H.R. & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion,
and motivation. Psychological Review, 98 (2), 224-253.
Markus, H.R. & Kitayama, S. (2003). Culture, Self, and the Reality of the Social. Psychological
Inquiry, 14 (3), 277–83.
Markus, H.R., Uchida, Y., Omoregie, H., Townsend, S.S.M., & Kitayama, S. (2006). Going for
the Gold: Models of Agency in Japanese and American Contexts. Psychological Science,
17 (2), 101–112.
33
Morris, M.W., Peng, K. (1994). Culture and cause: American and Chinese attributions for social
and physical events. Journal of Personality and Social Psychology, 67 (6), 949-971.
Novemsky, N., Dhar, R., Schwarz, N., & Simonson, I. (2007). Preference Fluency in Choice.
Journal of Marketing Research, 44 (August), 347–356.
Oyserman, D. & Lee, S. W. (2008). Does culture influence what and how we think? Effects of
priming individualism and collectivism. Psychological bulletin,134 (2), 311–342.
Reber, R. & Schwarz, N. (1999). Effects of Perceptual Fluency on Judgments of Truth.
Consciousness and Cognition, 8, 338–342.
Riemer, H., Shavitt, Sharon, Koo, M., & Markus, H.R. (2014). Preferences Don’t Have to Be
Personal: Expanding Attitude Theorizing With a Cross-Cultural Perspective.
Psychological Review, 121 (4), 619–648.
Savani, K., Markus, H.R. & Conner, A.L. (2008). Let your preference be your guide?
Preferences and choices are more tightly linked for North Americans than for Indians.
Journal of Personality and Social Psychology, 95 (4), 861-876.
Savani, K., Markus, H.R., Naidu, N.V.R., Kumar, S. & Berlia, N. (2010). What Counts as a
Choice? U.S. Americans Are More Likely Than Indians to Construe Actions as Choices.
Psychological Science, 21 (3), 391-398.
Schwarz, N. (1998). Accessible Content and Accessibility Experiences: The Interplay of
Declarative and Experiential Information in Judgment. Personality and Social
Psychology Review, 2 (1), 87-99.
Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making.
Journal of Consumer Psychology, 14, 332–348.
34
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991).
Ease of retrieval as infonnation: Another look at the availability heuristic. Journal of
Personality and Social Psychology, 61, 195-202.
Sela, A. & Berger, J. (2012). Decision Quicksand: How Trivial Choices Suck Us In. Journal of
Consumer Research, 39 (2), 360-370.
Stephens, N.M., Fryberg, S.A., & Markus, H.R., (2011). When Choice Does Not Equal Freedom:
A Sociocultural Analysis of Agency in Working-Class American Contexts. Social
Psychological and Personality Science, 2 (1), 33-41.
Stephens, N.M., Markus, H.R., & Townsend, S.S.M. (2007). Choice as an Act of Meaning: The
Case of Social Class. Journal of Personality and Social Psychology, 93 (5), 814–830.
Tormala, Z.L. & Petty, R.E. (2002). What Doesn’t Kill Me Makes Me Stronger: The Effects of
Resisting Persuasion on Attitude Certainty. Journal of Personality and Social
Psychology, 83 (6), 1298–1313.
Wänke, M., Bohner, G., & Jurkowitsch, A. (1997). There Are Many Reasons to Drive a BMW:
Does Imagined Ease of Argument Generation Influence Attitudes? Journal of Consumer
Research, 24 (September), 170–177.
Winkielman, P. & Schwarz, N. (2001). How Pleasant Was Your Childhood? Beliefs About
Memory Shape Inferences From Experienced Difficulty of Recall. Psychological
Science, 12 (2), 176-179. 35
Appendix: Choice options used in experiments 2, 3, 4, and 5