Journal of Experimental Psychology: Learning, Memory, and Cognition 2016, Vol. 42, No. 1, 140 –148

© 2015 American Psychological Association 0278-7393/16/$12.00 http://dx.doi.org/10.1037/xlm0000161

RESEARCH REPORT

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Language Switching—But Not Foreign Language Use Per Se—Reduces the Framing Effect Y. Oganian

C. W. Korn

Freie Universität and Bernstein Center for Computational Neuroscience, Berlin, Germany

Freie Universität and University of Zurich

H. R. Heekeren Freie Universität Recent studies reported reductions of well-established biases in decision making under risk, such as the framing effect, during foreign language (FL) use. These modulations were attributed to the use of FL itself, which putatively entails an increase in emotional distance. A reduced framing effect in this setting, however, might also result from enhanced cognitive control associated with language-switching in mixed-language contexts, an account that has not been tested yet. Here we assess predictions of the 2 accounts in 2 experiments with over 1,500 participants. In Experiment 1, we tested a central prediction of the emotional distance account, namely that the framing effect would be reduced at low, but not high, FL proficiency levels. We found a strong framing effect in the native language, and surprisingly also in the foreign language, independent of proficiency. In Experiment 2, we orthogonally manipulated foreign language use and language switching to concurrently test the validity of both accounts. As in Experiment 1, foreign language use per se had no effect on framing. Crucially, the framing effect was reduced following a language switch, both when switching into the foreign and the native language. Thus, our results suggest that reduced framing effects are not mediated by increased emotional distance in a foreign language, but by transient enhancement of cognitive control, putting the interplay of bilingualism and decision making in a new light. Keywords: decision-making, foreign language, cognitive control, emotional distance, framing effect Supplemental materials: http://dx.doi.org/10.1037/xlm0000161.supp

It is well established that decision making under risk is systematically altered by the logically irrelevant wording of choice alternatives, giving rise to irrational decision biases, such as the fram-

ing effect (Tversky & Kahneman, 1981). Two recent studies report a reduction of the framing effect when participants make decisions in a foreign language (FL), suggesting more rational decisionmaking behavior in an FL than in a native language (L1, Costa, Foucart, Arnon, Aparici, & Apesteguia, 2014; Keysar, Hayakawa, & An, 2012). These intriguing findings suggest a previously unknown interplay between language and decision-making systems and thus raise a pertinent question: Which linguistic and contextual factors mediate the effects of FL use on decision-making? Here, we report two experiments to address this question. First, we assess the influence of a central linguistic factor by investigating how individual differences in FL proficiency modulate the framing effect. Second, we manipulate an important contextual factor by inducing an unexpected switch in the task language immediately prior to the decision-making problem. Classically, the framing effect is demonstrated with the Asian disease problem: Participants make a hypothetical decision about which of two types of medicine the government should develop in response to the outbreak of a new disease (Tversky & Kahneman, 1981, Table 1). One medicine entails a sure outcome and the other medicine entails a risky outcome of the same expected value. Typically, participants choose the sure option more often when the

This article was published Online First June 22, 2015. Y. Oganian, Department of Education and Psychology, Freie Universität and Bernstein Center for Computational Neuroscience, Berlin, Germany; C. W. Korn, Department of Education and Psychology, Freie Universität and Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich; H. R. Heekeren, Department of Education and Psychology, Freie Universität. Y. Oganian and C. W. Korn contributed equally. We thank B. Keysar and S. Hayakawa for kindly providing us with their stimulus material. We thank B. Keysar and A. Costa for discussions of the results of Experiment 1. We thank L. La Rosée, F. Albers, and U. Schlickeiser for help with data acquisition as well as H. Saalbach, M. Conrad, K. Spalek, and D.R. Bach for helpful discussions. We thank D. Leiner for help with setting up the online experiment. We thank G. Seher and the tutors from the law department of the Freie Universität for their assistance in data acquisition. Y. Oganian was funded by a doctoral stipend from DFG (GRK 1589/1). Correspondence concerning this article should be addressed to Y. Oganian, Habelschwerdter Allee 45, 14195 Berlin, Germany. E-mail: yulia.oganian@ fu-berlin.de 140

LANGUAGE SWITCH EFFECT ON DECISION MAKING

141

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Table 1 English Wording of the Framing Tasks Problem Asian disease problem Recently, a dangerous new disease has been going around. Without medicine, 600,000 people will die from it. In order to save these people, two types of medicine are being made. Now you have to choose, which one to use. If you choose Medicine A, 200,000 people will be saved. (Gain frame) 400,000 people will die. (Loss frame) If you choose Medicine B, There is a 33.3% chance that 600,000 people will be saved and a 66.6% chance that no one will be saved. (Gain frame) There is a 33.3% chance that no one will die and a 66.6% chance that 600,000 will die. (Loss frame) Which medicine do you choose? Unemployment problem (control problem) Imagine that the government is preparing to respond to an economic crisis. The government expects that 300 000 people will lose their jobs. The government is considering two programs to reduce unemployment. Now you have to choose which one to follow. If you choose program A, 10,000 jobs will be saved. (Gain frame) 290,000 jobs will be lost. (Loss frame) If you choose program B, Which program do you choose? Damaged paintings problem A large museum is damaged by fire. 1,000 famous paintings are at the risk of being destroyed. Two alternative programs have been proposed to restore the paintings. Now you have to choose, which one to use. If you choose program A, 400 paintings will be saved. (Gain frame) 600 paintings will be destroyed. (Loss frame) If you choose program B, There is a 40% chance that 1,000 paintings will be saved and a 60% chance that no painting will be saved. (Gain frame) There is a 40% chance that no painting will be destroyed and a 60% chance that 1000 paintings will be destroyed. (Loss frame) Which program do you choose? Computer virus problem There is a new computer virus which can infect certain computer software. At the moment, this software is installed on 2 000 000 computers. Two types of antivirus software are being developed. Now you have to choose, which one to use. If you choose antivirus software A, 800,000 computers will remain virus-free. (Gain frame) 1,200,000 computers will be infected. (Loss frame) If you choose antivirus software B, There is a 40% chance that 2,000,000 computers will remain virus-free and a 60% chance that no computer will remain virus-free. (Gain frame) There is a 40% chance that no computer will be infected and a 60% chance that 2,000,000 computers will be infected. (Loss frame) Which antivirus software do you choose? Note. In all framing problems except for the control problem, the two options have the same expected value but different wording depending on the frame.

problem is formulated in terms of people saved (gain frame) than when it is formulated in terms of people dying (loss frame), although the economic variables are identical in both frames. According to prominent dual-process accounts, framing effects arise when fast, intuitive, and emotion-driven processes compete with slow, deliberate, and rational processes (De Martino, Kumaran, Seymour, & Dolan, 2006; De Neys & Bonnefon, 2013; Kahneman, 2003; Stanovich & West, 2008; Whitney, Rinehart, & Hinson, 2008). In line with this dual-process account, Keysar and colleagues (2012) as well as Costa and colleagues (2014) interpret their finding of a reduced framing effect in terms of an “emotional distance” account (i.e., a purportedly reduced emotionality in an FL setting). They argue that the reduced involvement of emotional processes makes room for controlled, rational, processing thereby diminishing the susceptibility to decision biases. Critically, this interpretation hinges on the assumption that FL use increases emotional distance compared with L1 use. Indeed, several studies found that emotion processing in a subordinate FL can be reduced (for a review, see Pavlenko, 2012), as evidenced by reduced

interference by emotional stimuli in an FL (Colbeck & Bowers, 2012), and altered EEG waveforms (Opitz & Degner, 2012). Similarly, Wu and Thierry (2012) found that coactivation of the L1 by FL words can be reduced for negative stimuli, providing evidence for an emotional modulation of lexical access in the L1. Importantly, additional evidence also suggests that emotional distance during FL use is a function of individual differences in FL proficiency and experience in FL communication—with low but not high FL proficiency resulting in reduced emotional involvement (Conrad, Recio, & Jacobs, 2011; Degner, Doycheva, & Wentura, 2012; Pavlenko, 2012). This account thus predicts that individual differences in FL proficiency should influence the size of the framing effect. However, bilingualism not only influences emotional processes but can also affect cognitive control abilities (Costa & SebastiánGallés, 2014). Most prominently, knowledge of more than one language entails enhanced cognitive control abilities in the longterm (Bialystok, Craik, & Freedman, 2007; Hilchey & Klein, 2011, but see de Bruin, Treccani, & Della Sala, 2015) in all language contexts. These enhanced control abilities are thought to result

OGANIAN, KORN, AND HEEKEREN

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

142

from the need to manage the concomitant activation of both languages, particularly during language switching or in multilingual settings (Meuter & Allport, 1999; Kiesel, Steinhauser, Wendt, Falkenstein, Jost, et al., 2010). Moreover, Wu and Thierry (2013) recently showed that in the short-term cognitive control is enhanced in a bilingual context that requires frequent language switching as compared to monolingual native or FL settings. Building on these findings, we suggest a “cognitive control” account of reduced framing effects in bilingual settings. Namely, we reasoned that a language switch might reduce framing effects by temporarily enhancing cognitive control, leading to a relatively reduced involvement of fast, emotion-driven processes. In summary, FL influences on the framing effect could be the result of emotional distance induced by FL use per se and/or the result of enhanced cognitive control in mixed-language contexts. These two hypotheses do not necessarily contradict each other. The “emotional distance” account predicts that the framing effect should be reinstalled with sufficient proficiency and entails no specific predictions for mixed-language contexts. On the contrary, the “cognitive control” account predicts a reduction of the framing effect in the context of language switching, independent of proficiency. The latter effect may not directly depend on the language in which the framing task is presented. That is, enhanced cognitive control could lead to a reduced framing effect even when the problem is presented in the L1. Here we independently tested both hypotheses in two separate experiments with native speakers of German who were either tested in their L1 or in their FLs (French or English). As the previous studies of FL effects on decision-making have demonstrated effects across various language combinations, we focused on German native speakers for reasons of participant availability. In Experiment 1, we tested participants across a vast range of FL proficiency to assess the prediction of the emotional distance account that the framing effect should increase with proficiency. In Experiment 2, we tested the cognitive control account by comparing bilinguals that had to switch languages between task instructions and the Asian disease problem with those that were immersed in one language throughout the experiment. The cognitive control account predicts a reduced framing effect after a language switch.

Experiment 1 Materials and Methods Participants. Participants were recruited via the panel of an online survey system (www.soscisurvey.de) with a German recruitment text. Participants of this panel do not receive monetary reimbursement but participate out of interest. Out of 927 initial participants (589 female) who completed the study, 183 were excluded because they did not fulfill at least one of the following criteria: (a) German is the only mother tongue, (b) current residence is a German-speaking country, (c) age lies between 18 and 60 years, or (d) no prior knowledge about the framing effect, as shown by the answer to a probing question at the end of the study. Participants were also excluded if their reaction time (RT) in the Asian disease task deviated more than 2 standard deviations from the group mean. Thus, data from 744 (445 female) participants were included in the analyses. Participants who completed the survey in an FL (English or French) were assigned to the lowproficiency (LP) group if their self-reported proficiency in the test language was below 5 (out of 7), and to the high-proficiency (HP) group otherwise, resulting in 183 participants in the HP group, 312 participants in the LP, and 249 participants in the L1 group. Procedure. After following the link to the online test system, participants saw a general instruction in German and rated their proficiency in English and French (see Table 2). They were then pseudorandomly assigned to the German, English, or French version of the task and saw a specific instruction in the respective language (English: 124 words, French: 93 words, German: 77 words). They were only assigned to an FL condition if their self-rated proficiency in that language was above 2 on a Likertscale from 1 (single words) to 7 (mother-tongue-like). They then answered the Asian disease problem (see Table 1), followed by a control problem, in which the expected values of the two options differed (“unemployment problem” as used by Keysar et al. (2012); Table 1). In the control problem, the expected value of the risky option was higher than the expected value of the sure option, such that participants should choose the risky option more often irrespective of frame. Following the control problem, participants answered two further framing problems (see Table 1): The “dam-

Table 2 Summary of Participants’ Language Profiles for Experiments 1 and 2 Self-report of test language proficiencya

Participants’ profile Study

Test language

n

Sex in % female

Age in years (SD)

Read

Write

Speak

Listen

M

Experiment 1

L1 HP LP

249 183 312

56 68 68

31 (10.2) 30 (9.0) 29 (8.1)

— 6.0 (0.6) 3.7 (1.0)

— 5.3 (0.8) 2.8 (0.9)

— 5.4 (0.9) 2.8 (0.8)

— 5.7 (0.7) 3.2 (1.0)

— 5.7 (0.6) 3.1 (0.8)

L1 FL L1 FL

203 218 193 180

74 81 58 62

28 (7.9) 24 (5.7) 25 (5.6) 24 (5.1)

5.6 (1.0) 5.6 (1.0) —

5.0 (1.2) 4.9 (1.1) —

4.9 (1.2) 4.9 (1.3) —

5.3 (1.2) 5.0 (1.2) —

b

b

b

b

5.2 (1.0) 5.1 (1.0) — 5.1 (0.9)

Experiment 2 Online Lab/classroom

Note. L1 ⫽ native language; HP ⫽ high proficiency; LP ⫽ low proficiency; FL ⫽ foreign language; sign. ⫽ significance. Data are given as counts, percentages, or Ms (SDs). a On a Likert scale of 1 (single words) to 7 (native level). b Only overall proficiency ratings collected.

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

LANGUAGE SWITCH EFFECT ON DECISION MAKING

aged paintings problem” was adapted from a previous study (Rönnlund, Karlsson, Laggnäs, Larsson, & Lindström, 2005). The “computer virus problem” was newly developed. The framing problems were followed by further tasks that will be reported elsewhere. In the end, participants provided demographic information and a detailed description of their language history (Li, Sepanski, & Zhao, 2006), on which the assignment of proficiency groups was based. They also had the opportunity to indicate whether they had previously encountered any of the tasks, in which case their data were excluded from all analyses. Analyses. Data were separately analyzed for each of the test scenarios in logistic regression models with the independent variables proficiency (L1, HP, LP), frame (gain vs. loss), and their interaction. Chi-square tests were used to assess the increase in explained variance by addition of each of the factors to a model including all other factors (corresponding to Type 3 analysis of variance [ANOVA]). This analysis determines the percentage of variance explained by a single factor after all other factors are partialed out and is the standard choice for multiple-regression designs (Cohen, Cohen, West, & Aiken, 2013). The control question was used to ensure that all three proficiency groups gave the correct answer when expected values were not the same in the risky and sure response options. Furthermore, to ensure that potential differences between groups would not be the result of differences between groups performing the task in English and French, we repeated the analysis with a separation by Language ⫻ Proficiency. Finally, we also tested whether the overall number of languages spoken by the participants affected the results. The results of the latter analysis can be found in the Supplementary Online Material.

Results and Discussion Participants’ language profiles are summarized in Table 2. Out of the 183 participants in the HP condition, 127 participants performed the task in English and 56 in French. Out of the 312 participants in the LP condition, 99 performed the task in English and 213 in French. This pattern reflects the fact that most Germans have higher proficiency in English than in French. Out of 744 participants, 710 were either university students or had a university degree (or equivalent). The remaining 34 participants were equally distributed across the three language conditions. Moreover, education level did not differ between the three language conditions (one-way ANOVA, p ⫽ .14). Framing problems. In line with a considerable amount of research (Rönnlund et al., 2005; Tversky & Kahneman, 1981), we found a highly significant main effect of frame in the Asian disease problem, ␤ ⫽ ⫺.61, 95% confidence interval (CI): ⫺.92, ⫺.3, ␹2(1) ⫽ 15.63, p ⬍ .001, indicating that the risky option was chosen more often in the loss frame than in the gain frame. To our surprise, we could not replicate the FL effect on the framing effect since we found neither a significant frame by proficiency interaction (p ⫽ .1) nor a significant main effect of proficiency (p ⫽ .2). The framing effect was of equal magnitude in all three groups (all ps in pairwise comparisons ⬍.001, see Figure 1 and Table 3). Note that the factor proficiency included a comparison between L1 and FL conditions. The same pattern was obtained for the two additional framing problems that followed the control problem, although the framing

143

Figure 1. Experiment 1: Results of the Asian disease problem in three proficiency groups. All three groups showed a significant main effect of frame. However, the main effect of proficiency and the frame by proficiency interaction did not reach significance. The y-axis reflects the percentage of participants in each condition who chose the sure option in the Asian disease problem (i.e., the remaining participants chose the risky option). Error bars indicate ⫾ 1 standard error of the mean (SEM). LP ⫽ low proficiency; HP ⫽ high proficiency; L1 ⫽ native language.

effect only emerged at trend level for the third problem, which we had developed for this study (damaged paintings problem: ␤ ⫽ ⫺.40, 95% CI: ⫺.71, ⫺.1, ␹2(1) ⫽ 6.7, p ⫽ .009; computer virus problem: ␤ ⫽ ⫺.26, 95% CI: ⫺.56, ⫺.03, ␹2(1) ⫽ 3.1, p ⫽ .08, all ps for the interaction and the main effect of language were ⬎ .1 for both problems). Control problem. The control question showed that participants indeed read and understood the questions because more than 70% of participants chose the risky option, which had a higher expected value. In addition the main effect of proficiency was significant, ␹2(2) ⫽ 6.78, p ⫽ .03, which was due to less correct responses in the LP group (66% vs. 75% in HP and NL groups, respectively), b ⫽ 0.28, 95% CI: 0.06, 0.49, p ⫽ .01. To ensure that the results of the framing problems were not biased by participants who might not have correctly understood the task, we repeated the above analyses of the framing problems by including only participants with correct responses in the control problem. The analyses yielded the same pattern of results (main effect of frame, p ⬍ .001, all other effects ns, ps ⬎ .05). Analysis by test language and by number of FLs known. The high proficiency group contained 127 English data sets and 56

OGANIAN, KORN, AND HEEKEREN

144

Table 3 Summary of Results for the Framing Problems in Experiment 1 by Group and Condition Asian disease problem

Damaged paintings problem

Computer virus problem

n in condition

Study Online

% sure answer % sure answer % sure answer Language Switching condition condition Gain Loss Gain Loss Gain ⫺ loss sign. Gain Loss Gain ⫺ loss sign. Gain Loss Gain ⫺ loss sign. L1 HP LP

Nonswitch

125 87 153

124 96 159

67 72 66

37 44 35

30 28 31

ⴱⴱ ⴱⴱ ⴱⴱ

62 72 62

50 53 50

⫹

12 19 12

ⴱ ⴱⴱ

55 54 56

32 41 39

23 13 17

ⴱⴱ ⫹ ⴱ

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Note. L1 ⫽ native language; HP ⫽ high proficiency; LP ⫽ low proficiency; sign. ⫽ significance. Data are given as counts or percentages. ⫹ p ⬍ .1. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .001.

French data sets, whereas the low proficiency group contained 99 English and 213 French data sets. This asymmetry reflects the typical proficiency levels of the two languages in the German population, as English is commonly the first FL learned in school. To ensure that test language was unrelated to our findings, we repeated the above analysis with the factors language and frame. We found neither a main effect of language nor an interaction effect of frame and language (p ⬎ .4). Moreover, the framing effect was significant in all four combinations of proficiency level (high/low) and FL (English/French; all Bonferroni-corrected ps ⬍ .01; see Supplementary Table S1). We also tested whether the FL effect on the framing effect would be affected by the number of FLs known by our participants and the relative level of proficiency in the test language. We found comparable magnitude of the framing effect when tested in a FL in bilinguals, trilinguals, and multilinguals. Moreover the framing effect was independent of whether participants were tested in their best-spoken FL (see Supplementary Online Material for a detailed description of this analysis).

Discussion of Experiment 1 In sum, Experiment 1 provides no evidence for an effect of proficiency on the framing effect and thus speaks against the “emotional distance” account. To our surprise, our results indicated framing effects of similar magnitude in L1 and FL conditions and thus do not replicate previous findings. We deem it unlikely that Experiment 1 lacked power with respect to the previous studies because in our study more than 500 participants responded to the Asian disease problem in the FL, which is more than in both previous studies combined (Keysar et al. (2012): approximately 150 FL participants; Costa et al. (2014): approximately 200 FL participants). Note also, in their replication of Keysar and Hayakawa’s (2012) findings, Costa et al. (2014) reported no direct comparison between the native and FL groups, which would, however, be essential to justify their conclusions (Nieuwenhuis, Forstmann, & Wagenmakers, 2011). Indeed, a calculation of the missing interaction effect based on the data reported in their article did not reach significance (see Supplementary Online Material), limiting the interpretation of their findings. We considered two possible reasons for the discrepancy between our results and previous studies. First, a methodological reason might be that we collected data online whereas previous studies collected data in a classroom setting. Therefore, in Experiment 2 we collected a part of the data in a classroom or a laboratory setting and a part online.

Second, and more importantly, we reasoned that subtle differences in language context might underlie the discrepancies between our and previous results. This reasoning thus provided an important additional motivation to directly assess the contextual effects of language switching on the framing task in Experiment 2.

Experiment 2 Methods and Materials Participants. Online data collection. Participants for online data collection were recruited via mailing lists and social media with a German recruitment text. As in Experiment 1, they received no reimbursement for participation but participated out of interest. Out of initially 442 participants, 22 were excluded based on the same exclusion criteria as in Experiment 1, resulting in the inclusion of 420 participants (326 female). Offline data collection. For offline data collection, participants were either recruited in relation to ongoing studies in our laboratory or in a classroom setting in courses at the Freie Universitaet and the Humboldt-Universitaet zu Berlin. As suggested during the review process, to provide a balanced sample with at least 40 participants in each task condition, the initial data set of 398 participants was extended post hoc to include 151 additional participants. These additional participants were recruited in B.A. seminars at the law faculty of the Freie Universitaet. Participants in the two data sets were of similar age, language proficiency, and educational background. In the initial dataset, 140 participants were excluded based on the same criteria as in Experiment 1, except for the RT cut-off because RTs could not be collected in the paper-and-pencil version of the task. Similarly, 33 participants were excluded from the second data set. Overall, data from 376 participants (228 female, 258 from first data set and 118 from second data set) were included in the analyses. In the main text, results are reported pooled across both data sets. For completeness, we provide the same analyses for the original first data set in the Supplementary Online Material. Results followed the same pattern in the original and the extended data sets. Procedure. Participants received instructions in German (77 words) or English (94 words), which were followed by the Asian disease problem in either the same (no switch condition) or the other language (switch condition), resulting in a 2 (switch

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

LANGUAGE SWITCH EFFECT ON DECISION MAKING

mode) ⫻ 2 (task language) ⫻ Frame (gain, loss) between-subjects design. After the Asian disease problem, participants answered a control problem, in which the expected value of the two options differed (“unemployment problem” as in Experiment 1). For some participants, the framing problems were followed by unrelated tasks that will be reported elsewhere. In the end, participants answered questions regarding their demographics and their language skills as in Experiment 1 and had the opportunity to indicate whether they had previously encountered any of the tasks. In the classroom/laboratory, participants were verbally instructed in German or English prior to receiving written instructions in the same language. In case of the laboratory studies, participants (n ⫽ 86) had performed an unrelated task of approximately 1 hr 30 min in the respective language before answering the Asian disease problem and the control problem in a paper-and-pencil version (i.e., the language of the Asian disease problem was the same as the language of the unrelated task and participants were thus assigned to the nonswitch conditions). To facilitate immersion into the FL in the laboratory studies, English instructions were given by an experimenter with native-like proficiency and accent in English, who did not speak German during the testing session.

Results and Discussion Proficiency. Participants’ self-reported proficiency is summarized in Table 2. English proficiency did not differ between the laboratory/classroom and online samples. Framing problem. A first analysis of the Asian disease problem that included sample as a factor showed no significant effects of the factor sample (all ps for main and interaction effects ⬎ .4).

145

Thus, we collapsed data across samples to increase power and analyzed them in a logistic regression including the factors switch, test language, and frame (see Figure 2 and Table 4). As in Experiment 1, the main effect of frame was highly significant, ␤ ⫽ 0.53, 95% CI: 0.39, 0.68, ␹2(1) ⫽ 52.37, p ⬍ .001. We also found a main effect of test language, ␤ ⫽ ⫺0.15, 95% CI: ⫺0.30, ⫺0.004, ␹2(1) ⫽ 4.06, p ⫽ .04, which was due to slightly more choices of the sure option in the L1 than in the FL (58% vs. 52%). Crucially for our research question, the interaction between switch and frame was significant, ␤ ⫽ ⫺0.19, 95% CI: ⫺0.34, ⫺0.04, ␹2(1) ⫽ 6.40, p ⫽ .01, due to smaller framing effects in the switch than in the nonswitch groups. All other effects were not significant (all ps ⬎ 0.09). To further elucidate the interaction effect between frame and language switch, we ran two separate regression analyses within each level of the switch condition. In the nonswitch condition, only the main effect of framing was significant, ␤ ⫽ 1.42, 95% CI: 0.86, 2.01, ␹2(1) ⫽ 24.98, p ⬍ .001. There was no significant main effect of language (p ⫽ .76, 95% CI: ⫺0.65, 0.47) nor an interaction effect of language and frame (p ⫽ .92, 95% CI: ⫺0.78, 0.86). In contrast, in the switch condition, we did not find a main effect of frame (p ⫽ .09, 95% CI: ⫺0.08, 1.09), but a main effect of language, ␤ ⫽ ⫺0.72, 95% CI: ⫺1.34, ⫺0.11, ␹2(1) ⫽ 5.53, p ⫽ .02. The latter effect was due to more choices of the sure option following a language switch into L1 (63%), than following a language switch into the FL (51%). Within the switch condition, there was no interaction of frame and language (p ⫽ .38, 95% CI: ⫺0.47, 1.22), suggesting that language switching affected the framing effect irrespective of the actual language in which the problem was presented.

Figure 2. Experiment 2: Results of the Asian disease problem when the problem was presented in participants’ native language (German, left panel) or in a foreign language (English, right panel). When the language context was consistent (no switch condition), the framing effect emerged in both languages. However, the framing effect disappeared when the language of the test question differed from the language of preceding instructions (switch condition), as reflected in a significant frame ⫻ switch interaction effect. The y-axis reflects the percentage of participants in each condition who chose the sure option in the Asian disease problem (i.e., the remaining participants chose the risky option).

OGANIAN, KORN, AND HEEKEREN

146

Table 4 Summary of Results for the Asian Disease Problem in Experiment 2 by Group and Condition Asian disease problem

Study Online

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Lab/classroom

Overall

Language condition L1 FL L1 FL L1 FL L1 FL L1 FL L1 FL

n in condition

% sure answer

Switching condition

Gain

Loss

Gain

Loss

Gain ⫺ loss

sign.

Nonswitch

58 71 50 51 53 49 48 43 111 120 98 111

48 45 47 51 49 48 45 41 97 93 92 97

72 66 72 59 66 69 74 55 69 68 73 57

34 39 52 41 31 35 47 41 34 33 53 45

38 27 20 18 35 34 27 14 35 35 20 12

ⴱ

Switch Nonswitch Switch Nonswitch Switch

ⴱ

n.s. n.s. ⴱ ⴱ ⴱ

n.s. ⴱ ⴱ ⴱ

n.s.

Note. L1 ⫽ native language; FL ⫽ foreign language; sign. ⫽ significance. Data are given as counts or percentages. p ⬍ .05.

ⴱ

Following the discrepancy between the results of Experiment 1 and previous studies, an important question was whether the framing effect would completely disappear in a FL or following a language switch. Thus, we analyzed the framing effect independently in each of the four language-by-switch combinations although there were no effects of test language in the omnibus analysis. We found that the framing effect was highly significant in both nonswitch groups (both Bonferroni-corrected ps ⬍ .0001) but disappeared in the switch-into-FL group (corrected p ⫽ .36). Although the framing effect was significant in the switch-into-L1 group (corrected p ⫽ .01), numerically it was about half the size of the framing effect in the nonswitch conditions (20% difference in number of risky choices between gain and loss frame, compared to 35% in both nonswitch groups). As some of the participants in the nonswitch condition were participating in the framing experiment only, whereas others had performed an unrelated task in the same language, we assessed possible difference between these two groups. Although the limited number of participants who had performed an unrelated task did not allow for statistical comparisons, the framing effect was numerically similar in both groups. Specifically, the framing effect in the sample that performed the English framing task after another English experiment (n ⫽ 46, gain: 74%, loss: 43% choices of sure option) was as large as in the sample that performed the German framing task after another German experiment (n ⫽ 40, gain: 88%, loss: 36%). Importantly, this pattern did not differ from the pattern observed in the complete nonswitch sample (see Table 4). Finally, the pattern of results obtained in the complete data set did not differ from the pattern obtained in the originally collected smaller sample (see Supplementary Online Material, Supplementary Table S2, for statistical results in the original classroom sample). Control problem. Again, participants overall read and understood the questions because 80% of participants chose the response with the higher expected value in the control problem independently of test language (p ⫽ .44, 95% CI: ⫺0.42, 0.95). To exclude that the above results were driven by participants with incorrect responses in the control problem, we repeated the analysis of the

Asian disease problem without these participants. We found the same interaction effect of language switch and framing condition as in the complete data set (p ⫽ .008). In summary, the results of Experiment 2 suggest that the framing effect is reduced when the framing task immediately follows a language switch, thus supporting the “cognitive control” account. Importantly, this was the case both after a switch into a FL and— even though to a smaller extent—after a switch into the L1, suggesting that reduction of framing effects results from transient changes in the level of cognitive control and not from general processing differences between foreign and L1 use.

General Discussion The aim of the present study was to investigate linguistic and contextual factors mediating the previously reported reduced framing effect during FL use. In Experiment 1, we investigated a prediction of the emotional distance account, namely that the framing effect would be reduced at low proficiency levels but less so at high proficiency levels (Pavlenko, 2012). We found no evidence for a modulation of the framing effect by proficiency. Surprisingly, we also found no evidence for a general reduction of the framing effect during FL use in contrast to previous reports (Costa, Foucart, Arnon, et al., 2014; Keysar et al., 2012). In Experiment 2, we tested the cognitive control account, which predicts a reduced framing effect in situations requiring high cognitive control, such as during switching between languages. Specifically, we investigated whether switching between L1 and FLs immediately on the framing task can induce a reduction of the framing effect. Indeed, as predicted, the framing effect was strongly reduced following a language switch. Crucially, this was the case both for switches into the FL and into the L1. As in Experiment 1, there was no effect of FL use per se on framing, as indicated by an undiminished framing effect in the no-switch FL condition. In contrast to two previous studies (Costa, Foucart, Arnon, et al., 2014; Keysar et al., 2012), both of our experiments do not provide evidence for a general change in decision-making behavior as a

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

LANGUAGE SWITCH EFFECT ON DECISION MAKING

function of pure FL use. Possible reasons for this discrepancy include (a) differences in culture and language combinations, (b) FL proficiency, (c) differences in data collection (online vs. classroom), or (d) differences in language context during the experiment. Regarding culture and language combinations, previous reports of FL effects on decision-making have not tested German native speakers but they have tested several groups from a Western background (including English/French in Keysar et al. (2012), and Spanish/English in Costa et al. (2014)). Based on a large body of literature we deem culture differences in FL effects within Western societies to be very unlikely as these populations are commonly grouped together in cultural psychology (Henrich, Heine, & Norenzayan, 2010; Korn et al., 2014). To our knowledge, cultural differences in the framing effect have not been reported in the cultural psychology literature (Henrich et al., 2010) or in metaanalyses of the framing effect (Kuhberger, 1998). Furthermore, framing effects in the L1 were of similar magnitudes in our and previous reports. FL proficiency does also not hold as explanation, as the low proficiency group in Experiment 1 resembles the FL characteristics of Keysar, Hayakawa, and An’s (2012) sample. We should note, however, that although multilingualism does not explain the difference between our findings in Experiment 1 and previous studies (see Supplementary Online Material), switch effects might be affected by participants’ knowledge of other FLs. As our data from Experiment 2 do not allow probing this hypothesis (due to the high prevalence of multilingualism in our sample, which is typical for German university students), future studies should systematically assess this possibility.1 Finally, the results of Experiment 2 demonstrate the comparability of offline and online data collection, thus ruling out this explanation. Language context, however, is a likely reason for divergence between our results as (possibly unintended) language switches can easily occur when a large group is simultaneously tested in a FL setting— especially in a classroom setting. Our finding of a reduced framing effect due to language switching provides the first evidence for the impact of bilingualism on cognitive control in the domain of decision-making. Most previous research on cognitive effects of bilingualism characterized bilingual influences on executive functions and cognitive control on classical interference tasks that directly measure the ability to cope with conflict (Hilchey and Klein (2011), but see Rubio-Fernández & Glucksberg (2012) for effects of bilingualism on reasoning). A notable exception is the recent work by Wu & Thierry (2013), which found a short-term increase in executive function when bilinguals are placed in a context of frequent language switching. Our data extend their findings from a timed perceptual task to a complex and untimed decision-making task. Recently, the same group (Gao, Zika, Rogers, & Thierry, 2015) reported the intriguing finding that when participants received positive or negative feedback on the outcomes of risky decisions in either a native or FL, the effect of positive feedback on subsequent decisions was reduced in the FL. The theoretical differences between one-shot framing and repeated gambling tasks, as well as the explicit emotional content in the latter task, do not allow for a direct comparison between our and Gao et al.’s results. In combination, these results point toward a complex picture of FL effects. Future research should pinpoint the different influences on framing and gambling tasks, in both one-shot and repeated-measures set-ups.

147

Our data also allow conclusions about the cognitive mechanisms behind framing effects, which are still not well understood. A few previous studies characterized the involvement of working memory processes (Whitney et al., 2008) and emotional processes (Phelps, Lempert, & Sokol-Hessner, 2014) in framing effects and decision-making in general. We now find a reduced framing effect in a setting of enhanced cognitive control, which reflects the dependency of decision processes on yet another processing factor and highlights the need for a systematic investigation of the involvement and interplay of various cognitive faculties in complex decision making multilingualism processes beyond the dualprocess taxonomy. In summary, our findings speak in favor of a cognitive control account of FL effects on framing and raise several important questions to be answered by future studies. First, the reported effects might differ in bilingual groups who are accustomed to frequent language switching, such as interpreters or bilinguals from code-switching communities (such as Turkish immigrant communities in Germany, or Hispanic communities in the United States). Second, our data point toward a possible asymmetry between switching into the native and FLs, which might be due to an easier return to the L1. Whether this effect will change in groups of more balanced bilinguals, or in bilinguals who live in an FL-immersed setting (i.e., immigrants or exchange students) should be a subject of future studies. Third, it is pertinent to understand whether this effect is specific to language switching or can be similarly induced by task switching, or other conditions requiring raised levels of cognitive control, such as perceptual difficulties (Alter, Oppenheimer, Epley, & Eyre, 2007). Finally, as our study focused on the framing effect, we cannot rule out that general FL effects exist for other types of decision patterns, such as observed for moral decisions (Costa, Foucart, Hayakawa, et al., 2014). Future studies should test general and situational language factors mediating other types of irrational behaviors.

Conclusions Overall, the results of our two experiments speak against a pure FL effect and suggest that individual differences in FL proficiency do not influence decision-making biases. Instead, cognitive, situational costs seem to mediate a “language-switch-effect.” Being the first demonstration of such effects, and in light of conflict with previous results, our findings highlight the need for a systematic investigation of similarities and differences in mechanisms underlying different types of decision biases and their dependence on contextual factors, such as language switches, and modulatory factors, such as language proficiency. On a final note, our data suggest that bilinguals’ behavior might after all not be so dependent on the language they use but more on subtle contextual factors.

1 We thank an anonymous reviewer for bringing this alternative explanation to our attention.

References Alter, A. L., Oppenheimer, D. M., Epley, N., & Eyre, R. N. (2007). Overcoming intuition: Metacognitive difficulty activates analytic rea-

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

148

OGANIAN, KORN, AND HEEKEREN

soning. Journal of Experimental Psychology: General, 136, 569 –576. http://dx.doi.org/10.1037/0096-3445.136.4.569 Bialystok, E., Craik, F. I. M., & Freedman, M. (2007). Bilingualism as a protection against the onset of symptoms of dementia. Neuropsychologia, 45, 459 – 464. http://dx.doi.org/10.1016/j.neuropsychologia.2006.10 .009 Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum. Colbeck, K. L., & Bowers, J. S. (2012). Blinded by taboo words in L1 but not L2. Emotion, 12, 217–222. http://dx.doi.org/10.1037/a0026387 Conrad, M., Recio, G., & Jacobs, A. M. (2011). The time course of emotion effects in first and second language processing: A cross cultural ERP study with German-Spanish Bilinguals. Frontiers in Psychology, 2, 351. Costa, A., Foucart, A., Arnon, I., Aparici, M., & Apesteguia, J. (2014). “Piensa” twice: On the foreign language effect in decision making. Cognition, 130, 236 –254. http://dx.doi.org/10.1016/j.cognition.2013.11 .010 Costa, A., Foucart, A., Hayakawa, S., Aparici, M., Apesteguia, J., Heafner, J., & Keysar, B. (2014). Your morals depend on language. PLoS ONE, 9(4), e94842. http://dx.doi.org/10.1371/journal.pone.0094842 Costa, A., & Sebastián-Gallés, N. (2014). How does the bilingual experience sculpt the brain? Nature Reviews Neuroscience, 15, 336 –345. http://dx.doi.org/10.1038/nrn3709 De Bruin, A., Treccani, B., & Della Sala, S. (2015). Cognitive advantage in bilingualism: An example of publication bias? Psychological Science, 26, 99 –107. Degner, J., Doycheva, C., & Wentura, D. (2012). It matters how much you talk: On the automaticity of affective connotations of first and second language words. Bilingualism: Language and Cognition, 15, 181–189. http://dx.doi.org/10.1017/S1366728911000095 De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313, 684 – 687. http://dx.doi.org/10.1126/science.1128356 De Neys, W., & Bonnefon, J.-F. (2013). The “whys” and “whens” of individual differences in thinking biases. Trends in Cognitive Sciences, 17, 172–178. http://dx.doi.org/10.1016/j.tics.2013.02.001 Gao, S., Zika, O., Rogers, R. D., & Thierry, G. (2015). Second language feedback abolishes the “hot hand” effect during even-probability gambling. The Journal of Neuroscience, 35, 5983–5989. http://dx.doi.org/ 10.1523/JNEUROSCI.3622-14.2015 Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61– 83. http://dx .doi.org/10.1017/S0140525X0999152X Hilchey, M. D., & Klein, R. M. (2011). Are there bilingual advantages on nonlinguistic interference tasks? Implications for the plasticity of executive control processes. Psychonomic Bulletin & Review, 18, 625– 658. http://dx.doi.org/10.3758/s13423-011-0116-7 Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. The American Economic Review, 93, 1449 –1475. http://www.jstor.org/stable/3132137; http://dx.doi.org/10.1257/ 000282803322655392 Keysar, B., Hayakawa, S. L., & An, S. G. (2012). The foreign-language effect: Thinking in a foreign tongue reduces decision biases. Psychological Science, 23, 661– 668. http://dx.doi.org/10.1177/0956797611432178 Kiesel, A., Steinhauser, M., Wendt, M., Falkenstein, M., Jost, K., Philipp, A. M., & Koch, I. (2010). Control and interference in task switching—A review. Psychological Bulletin, 136, 849.

Korn, C. W., Fan, Y., Zhang, K., Wang, C., Han, S., & Heekeren, H. R. (2014). Cultural influences on social feedback processing of character traits. Frontiers in Human Neuroscience, 8, 192. http://dx.doi.org/ 10.3389/fnhum.2014.00192 Kühberger, A. (1998). The influence of framing on risky decisions: A meta-analysis. Organizational Behavior and Human Decision Processes, 75, 23–55. http://dx.doi.org/10.1006/obhd.1998.2781 Li, P., Sepanski, S., & Zhao, X. (2006). Language history questionnaire: A web-based interface for bilingual research. Behavior Research Methods, 38, 202–210. http://dx.doi.org/10.3758/BF03192770 Meuter, R. F., & Allport, A. (1999). Bilingual language switching in naming: Asymmetrical costs of language selection. Journal of Memory and Language, 40, 25– 40. Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E.-J. (2011). Erroneous analyses of interactions in neuroscience: A problem of significance. Nature Neuroscience, 14, 1105–1107. http://dx.doi.org/10.1038/ nn.2886 Opitz, B., & Degner, J. (2012). Emotionality in a second language: It’s a matter of time. Neuropsychologia, 50, 1961–1967. http://dx.doi.org/ 10.1016/j.neuropsychologia.2012.04.021 Pavlenko, A. (2012). Affective processing in bilingual speakers: Disembodied cognition? International Journal of Psychology, 47, 405– 428. http://dx.doi.org/10.1080/00207594.2012.743665 Phelps, E. A., Lempert, K. M., & Sokol-Hessner, P. (2014). Emotion and decision making: Multiple modulatory neural circuits. Annual Review of Neuroscience, 37, 263–287. http://dx.doi.org/10.1146/annurev-neuro071013-014119 Rönnlund, M., Karlsson, E., Laggnäs, E., Larsson, L., & Lindström, T. (2005). Risky decision making across three arenas of choice: Are younger and older adults differently susceptible to framing effects? The Journal of General Psychology, 132, 81–93. http://dx.doi.org/10.3200/ GENP.132.1.81-93 Rubio-Fernández, P., & Glucksberg, S. (2012). Reasoning about other people’s beliefs: Bilinguals have an advantage. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 211–217. http://dx .doi.org/10.1037/a0025162 Stanovich, K. E., & West, R. F. (2008). On the relative independence of thinking biases and cognitive ability. Journal of Personality and Social Psychology, 94, 672– 695. http://dx.doi.org/10.1037/0022-3514.94.4 .672 Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453– 458. http://dx.doi.org/10.1126/ science.7455683 Whitney, P., Rinehart, C. A., & Hinson, J. M. (2008). Framing effects under cognitive load: The role of working memory in risky decisions. Psychonomic Bulletin & Review, 15, 1179 –1184. http://dx.doi.org/10 .3758/PBR.15.6.1179 Wu, Y. J., & Thierry, G. (2012). How reading in a second language protects your heart. The Journal of Neuroscience, 32, 6485– 6489. http:// dx.doi.org/10.1523/JNEUROSCI.6119-11.2012 Wu, Y. J., & Thierry, G. (2013). Fast modulation of executive function by language context in bilinguals. The Journal of Neuroscience, 33, 13533– 13537. http://dx.doi.org/10.1523/JNEUROSCI.4760-12.2013

Received December 30, 2014 Revision received May 27, 2015 Accepted May 28, 2015 䡲