Metacognition and Culture
Transcription
Metacognition and Culture
1 ON METACOGNITION AND CULTURE Aner Sela Jonah Berger Running Head: Metacognition and Culture Aner Sela, University of Florida, 267 Stuzin Hall, Gainesville, FL 32611 ([email protected]). Jonah Berger, University of Pennsylvania, 700 Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, PA 19104 ([email protected]). 2 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 3 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 & 4 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. 5 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 6 (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. 7 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]). 8 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. 9 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 10 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). 11 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). 12 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. 13 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 14 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 15 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). 16 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. 18 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). 19 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. 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