Multiple Framing: Verbal, Facial, and Vocal Cues in Risky Choice

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1 Journal Code Article ID Dispatch:.01.1 CE: Fernando C. Galera Jr. B D M 1 No. of Pages: ME: Journal of Behavioral Decision Making, J. Behav. Dec. Making (01) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI:./bdm. Multiple Framing: Verbal, Facial, and Vocal Cues in Risky Choice Q1 STEVEN GARELIK 1 and XIAO TIAN WANG 1 * Q 1 University of South Dakota, USA ABSTRACT Verbal framing effects have been widely studied, but little is known about how people react to multiple framing cues in risk communication, where verbal messages are often accompanied by facial and vocal cues. We examined joint and differential effects of verbal, facial, and vocal framing on risk preference in hypothetical monetary and life death situations. In the multiple framing condition with the factorial design ( verbal frames vocal tones basic facial expressions task domains), each scenario was presented auditorily with a written message on a photo of the messenger s face. Compared with verbal framing effects resulting in preference reversal, multiple frames made risky choice more consistent and shifted risk preference without reversal. Moreover, a positive tone of voice increased risk-seeking preference in women. When the valence of facial and vocal cues was incongruent with verbal frame, verbal framing effects were significant. In contrast, when the affect cues were congruent with verbal frame, framing effects disappeared. These results suggest that verbal framing is given higher priority when other affect cues are incongruent. Further analysis revealed that participants were more risk-averse when positive affect cues (positive tone or facial expressions) were congruently paired with a positive verbal frame whereas participants were more risk-seeking when positive affect cues were incongruent with the verbal frame. In contrast, for negative affect cues, congruency promoted risk-seeking tendency whereas incongruency increased risk-aversion. Overall, the results show that facial and vocal cues interact with verbal framing and significantly affect risk communication. Copyright 01 John Wiley & Sons, Ltd. key words framing effects; risky choice; emotional cues; tone of voice; facial expression INTRODUCTION In their seminal work, Tversky and Kahneman (1) introduced the concept of decision framing with the Asian disease problem. They showed that decision makers show a reversed choice preference to either a risk-seeking or a risk-averse option of equal expected value based on the valence of phrasing in terms of either survival or mortality. Framing effects occur when frames that cast the same critical information in either a positive or a negative light cause individuals to have different choice preferences (Chong & Druckman, 00; Druckman, 001; Levin, Schneider, & Gaeth, 1, p. 1). As illustrated in the Asian disease problem, equivalent choice outcomes can be framed with either positive valence or negative valence (e.g., lives saved vs. lives killed, survival rate vs. mortality rate, gain vs. loss, threat vs. opportunity, success vs. failure, and benefits vs. costs). Such reversals in risk preference due to valence framing of virtually equivalent choice outcomes raise radical doubts about basic assumptions in economic theories of rationality. The classic framing effect is thus viewed as an irrational decision bias and a cognitive illusion because it violates the invariance axiom of expected utility theory, which requires a rational decision maker to have a consistent preference order among identical choice prospects independent of the way the prospects are presented or framed. To determine whether a framing effect is rational or not, an important operational standard is the presence of preference reversal. Some framing effects involve irrational preference reversals (e.g., the opposite choice preferences under different framings) while others involve a shift in choice preference * Corresponding to: XiaoTian Wang, Psychology Department, University of South Dakota, Vermillion, SD, USA. xtwang@usd.edu Copyright 01 John Wiley & Sons, Ltd. (e.g., making one option even more attractive than another). A choice preference shift differs from a preference reversal in that the proportion of risk-averse or risk-seeking choices is significantly greater than % under one framing condition and significantly less than % in an alternative framing condition. Wang (1a) makes the distinction between bidirectional framing effects, which involve a reversal in risk preference, and unidirectional framing effects, which involve a preference shift (e.g., from risk-seeking under positive framing to even more risk-seeking under negative framing, or from risk-averse under negative framing to even more risk-averse under positive framing). Meta-analyses (Kühberger, 1; Levin et al., 1) show that the effect of framing is overall significant, but framing effects have their boundaries and preconditions. Many researchers have explored the premise and moderators of framing effects, which include sex of the decision maker (Fagley & Miller, 1, 1), cognitive ability (Stanovich & West, 1), personal involvement (Levin et al., 1, p. 1), reflection on and rationale for the decision (Fagley & Miller, 1; Miller & Fagley, 1; Sieck & Yates, 1; Takemura, 1), personal knowledge about the risks involved (e.g., Bohm & Lind, ; Levin & Chapman, 1), perceived ambiguity of the values presented in the problem descriptions (Kühberger, 1), task context (e.g., medical vs. statistical, Bless, Betsch, & Franzen, 1), need for cognition (LeBoeuf & Shafir, 00), perceived interdependence between and caring about individuals at risk (Bloomfield, Sager, Bartels, & Medin, 00; Wang, Simons, & Bredart, 001), and social group size and composition (Bloomfield, 00; Shimizu & Udagawa, 0; Wang, 1a, 1b; Zhang & Miao, 00). The aforementioned studies have taken into consideration individual and situational factors that determine the process and magnitude of framing effects. This line of research calls for an overarching theory of framing effects that addresses these ecological, social, and dispositional constraints and Q

2 Journal of Behavioral Decision Making antecedents. This led to the development of the ambiguity ambivalence (AA) hypothesis of framing effects and decision biases (Wang, 00a). The AA hypothesis assumes that (i) decision cues are selected and used in accordance to their priorities. (ii) Cue priority reflects ecological and social validity of a cue in predicting specific risks. Primary cues are valid ecological, social, and life-history variables. Secondary cues are mainly communicational, such as verbal framing, facial expression, tone of voice, and so on. (iii) Decision biases, such as framing effects, tend to occur as a result of secondary cue use when primary cues are either absent in risk communication (i.e., an ambiguity condition) or when primary or secondary cues elicit conflicting preferences (i.e., an ambivalence condition). From this perspective, framing effects would occur as a result of ambiguity and ambivalence in decision cues and preferences. Similar ideas can be seen in fuzzy-trace theory (Reyna & Brainerd, 1) and the discussion on the use of probabilistic mental models (Gigerenzer, Hoffrage, & Kleinbölting, 1) to deal with informational ambiguity as a premise of framing effects (Chang, Yen, & Duh, 00; Kühberger, 1). INTEGRATION OF MULTIPLE CUES IN RISK COMMUNICATION The voluminous studies of framing effects up until now have largely focused on the effects of verbal framing. However, in everyday life, people use multiple communication cues including verbal, facial, and vocal cues. Multiple-cue integration is thus more representative of real-world communication. Transmission of affect-laden information can occur by means of diverse modalities (e.g., visual, auditory, and olfactory) through their respective manifestations, such as facial expressions and vocal intonation (Semin, 00). These modalities, individually or in combination, establish in a receiver a synthetic reproduction of the state of the sender. Researchers have examined the role of emotional cues in risky choice. The mood maintenance hypothesis proposed by Isen and Patrick (1) states that people try to maximize the chance of acquiring or maintaining a positive mood and thus will be more risk-averse in a positive mood (maintenance) and more risk-seeking in a negative mood (acquisition). Lerner and Keltner (000) argue that different emotions have unique effects on decision making beyond a dichotomous division of valence. Emotions of the same valence such as anger, fear, and sadness need to be evaluated separately along several appraisal dimensions (i.e., responsibility, anticipated effort, control, attentional activity, pleasantness, and certainty) to identify their unique effects on risky choice. For example, anger is expected to have high certainty and high control, whereas fear is expected to have low certainty and low control. They found that fear promoted pessimistic risk assessments and risk-averse tendency, while anger promoted optimistic risk assessments and risk-seeking tendency. Assessments from angry people were closer to that of happy people than fearful people. Johnson and Tversky (1) showed that people tend to be more risk-seeking when experiencing positive emotions and more risk-averse when experiencing negative emotions. In similar research, Seo, Goldfarb, and Barrett (0) found that at low or moderate levels of pleasantness, framing effects were strong. But as pleasantness increased, so did risk-seeking tendency, and the risk-averse tendency of framing in gain was eliminated or reversed. In contrast, unpleasant feelings reduced risk-seeking after a loss. Little is known about how affect cues, when combined with verbal framing, would affect risk assessment and risky choice. Most of these previous studies of emotional effects on decision making (Cassotti et al., 0; Druckman & McDermott, 00) focus on the emotional state and emotional reactions of the decision maker. Their findings indicate that affective information is integrated into decision-making processes and can affect risky choice. The present study differs in that it examines the effects of affect cues used in risk communication, rather than the emotional state of the decision maker, on risk preference. For instance, in the Cassotti et al. (0) study, photos of faces were used as mood inducers for the participants, separately from the decision problems they later responded to. In contrast, the facial expressions and tone of voice in the present study were used as affect cues of a messenger who presented the decision problem to the participants. Thus, the current research focused on the effects of affect cues exhibited by the messenger, rather than identifying effects of emotions felt by the recipient (the decision maker) on decision making. Compared with the studies on effects of emotional state on decision making, fewer studies have explored the effects of affect cues besides verbal framing on decision making. Scherer, Ladd, and Silverman (1) showed that vocal cues interact with verbal messages and can jointly affect judgment. Likewise, Haley and Fessler (00) found that visual cues affect generosity in economic games. These studies indicate that both visual and auditory cues interact with verbal information and jointly affect decision making. In this study, we examined framing effects in a communication context involving affect cues (facial expressions and vocal intonation) combined simultaneously with verbal framing while participants answered risky choice questions. We adopted a factorial design to explore the interactive and additive effects of verbal, facial, and vocal cues. We refer to this condition of risky choice with combined communication cues as multiple framing. In particular, we examined joint and differential effects of verbal, facial, and vocal framing on risk preference in hypothetical monetary and life death situations. To study the effects of multiple framing, we adopted a factorial design of verbal frames vocal tones facial expressions task domains. Each scenario was presented by both a written and auditory message with a photo of the messenger s face. HYPOTHESES AND PREDICTIONS Hypothesis 1: Bidirectional versus unidirectional effects The first question we asked was if additional affect cues, when combined with verbal framing, make decisions more consistent. Pham, Cohen, Pracejus, and Hughes (001) found that people make more consistent judgments when focusing on emotional evaluations of stimuli rather than rational evaluations of the Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

3 S. Garelik and X. T. Wang same stimuli. Ragsdale (1) also found that emotions more accurately predict decision outcomes and can even reveal voters preferences before they have finalized their decisions. These findings offer evidence that the inclusion of affect cues would make people more consistent in their judgments. Similarly, Wang (00b) showed that affective heuristics predicted a voter s presidential choice equally well or better than cognitive heuristics. Slovic, Finucane, Peters, and MacGregor (00) argued that rational decision making requires both affective and cognitive processing. All of these studies suggest that affective information supports more consistent decision-making processes. Based on these previous studies, we predict that classic framing effects with a preference reversal (i.e., bidirectional framing effects) would occur when only verbal framing is used. In contrast, when facial and vocal cues are presented simultaneously, the combination of cues would overall help make more consistent choices and thus reduce or eliminate bidirectional framing effects. Hypothesis : Cue congruency effects Hypothesis addresses cue congruency effects. Based upon the AA hypothesis, verbal framing would be most effective when other cues are absent, incongruent, and/or ambiguous (Wang, 00a). Thus, we predict more evident framing effects when the valence of facial and vocal cues is incongruent with the verbal frame (e.g., positive framing accompanied with at least one negative facial expression or tone of voice, and vice versa). Besides verbal framing effects, congruency among cues may also affect risk preference. Because positive frames promote risk-aversion and negative frames enhance risk-seeking (Tversky & Kahneman, 1; Levin et al., 1; Tversky & Kahneman, 1), we predict a stronger risk-averse preference for conditions where positive affect cues are congruent with verbal framing and more risk-seeking preference for conditions where negative affect cues are congruent with verbal framing, and vice versa for conditions where affect cues are incongruent with verbal framing. 1 Hypothesis : Effects of different types of affect Hypothesis examines the effects of different affect cues on risk preference. According to both Johnson and Tversky (1) and Seo et al. (0), one would predict that happiness would increase risk-seeking tendency while sadness would decrease risk-seeking tendency. Based on the cognitive appraisal model (Lerner & Keltner, 001), the certainty and control dimensions are important factors in determining risky choice. Happiness is associated with high levels of certainty and individual control and should promote optimistic risk assessments and thus a risk-seeking preference. Sadness is expected to be associated with high certainty and low individual control and thus result in a relatively risk neutral preference. Fear is characterized by low certainty and low control and should result in 1 The second portion of Hypothesis was developed as an extension of the first portion of that hypothesis, thanks to the suggestion of a reviewer. Verbal, Facial, and Vocal Framing risk-aversion. Surprise, having low certainty with a moderate amount of control, should result in risk-seeking preference. Based on these previous studies, we predict that happiness and surprise are likely to promote risk-seeking preference while sadness and fear are likely to promote risk-averse preference. Similarly, for tone of voice, positive valence (happy voice) is expected to increase risk-seeking tendency while negative valence (sad voice) is expected to increase risk-averse preference. METHODS Participants For the factorial design with multiple frames, students ( men and women) from various undergraduate courses at the University of South Dakota participated in this study for extra credit. The mean age was 0. (ranging from 1 to ) years. A verbal framing only condition was used as a control to test Hypothesis 1 and a separate group of participants (1 men and 1 women) were recruited from the same participant pool. A total of participants were recruited for both experiments. Instrumentation Choice questions were presented by computer to the participants. The MATLAB software program was used for randomizing and presenting the stimuli and recording responses. All answers from the participants were entered by keyboard. MATLAB randomized the order of choice questions for each participant. Experimental design We employed a factorial design involving a total of risky choice scenarios. All the variables in the factorial design were within-subject. Each scenario had two choice options, either a probabilistic outcome or a certain outcome of equal expected value. Each scenario represented one unique combination of the four factors: the verbal frame (positive or negative), the facial expression (happy, sad, fear, or surprised) portrayed in photos of faces, the tone of voice of the auditory message (happy or sad), and the task domain (life death or monetary). We chose the four facial expressions based on previous studies on basic emotions (e.g., Ekman, Friesen, & Ellsworth, ; Fridlund, Ekman, & Oster, 1), without including anger and disgust. The exclusion of the two emotions was due to the possibility of eliciting mixed perceptions (e.g., fear and anger, or fear and disgust). The scenarios were read to the participants via headphone. The pitch of the speaker s voice was edited digitally to sound gender neutral. Sixteen photos of faces ( individuals facial expressions) were used. The scenarios consisted of eight unique decision problems: the Asian disease problem, a natural disaster problem, a nuclear meltdown problem, and a terrorist attack problem in the life death domain, and a potential lawsuit, a business Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

4 T1 Journal of Behavioral Decision Making joint venture, a monetary gain, and a monetary loss problem in the monetary domain (Appendix A). Each decision problem was used a total of four times for the participants in the multiple framing condition and two times for the participants in the verbal framing only condition. The order to present these decision problems was randomized for each participant, to minimize any order effects. Stimulus materials The photographs for the facial expressions of four basic emotions were adopted from databases developed by Ekman and Friesen () and by Biehl et al. (1). The sound clips were first recorded by a female narrator for each scenario. These sound clips were then reduced in pitch by 0% to produce a gender-neutral voice. All photographs and sound clips were tested in a pilot study to validate the emotions. A post-manipulation check was used after the main experiment to further confirm that participants perceived emotions as intended. Experimental procedure First, participants were introduced to the procedure of the experiment. They were instructed to make choices in each decision scenario, which was narrated by a messenger whose photo was also displayed. All questions were presented by computer, so the monitor height and speaker volume were adjusted to a comfortable setting for each person. At the start of every trial, the photograph with the facial expression was displayed for 0 ms before the text of the scenario was F1 brought up on screen (which overlaid the photo, see Figure 1). Then a recorded message (the decision problem for that trial) was presented using the tone of voice selected for that combination. After each message, the photo and scenario text were removed, and participants were prompted to choose between Option A (certain outcome) and Option B (probabilistic outcome). In the verbal framing only condition, the sound clips and photos were removed. Participants responded to 1 choice problems ( verbal frames domains with problems in each domain). RESULTS AND DISCUSSION We first tested the predictions from Hypothesis 1 by comparing the choice results from the verbal framing only condition and the multiple framing condition. The risk preference of the participants in the verbal framing only condition is shown T in Table 1. Table shows the risk preference of the participants in the multiple framing condition across each independent variable (verbal frame, tone of voice, risk domain, and facial expression). Table breaks down participants choices across T risky choice scenarios for both the verbal only and multiple framing conditions. The risk preference data sorted by cue con- T T gruency is presented in Tables and. Similar to the analysis used in the study by Druckman and McDermott (00), a binary logistic regression was conducted to analyze choice data in the verbal framing only condition. Figure 1. Example of a facial expression with the superimposed text of a choice question The choice of participants (risk-seeking or risk-averse) was used as the dependent variable while verbal frame and domain were used as independent variables. The overall model for the binary logistic regression was significant (p <.001) and correctly predicts.% of participants choices. There was no significant interaction between the independent variables. The analysis showed that the classic bidirectional framing effect with a preference reversal, was significant (p =.001, odds ratio (OR) = 1.), in the verbal framing only condition. The majority of participants were more risk-averse in the positive frame but more risk-seeking in the negative frame. Task domain was also significant (p <.001, OR = 0.); participants were more risk-seeking in the life death domain than in the monetary domain (Table 1). This result is consistent with previous findings (Wang, 1b) and suggests that risky choice is task-domain specific (Fagley & Miller, 1; Kruger, Wang, & Wilke, 00; Wang, Kruger, & Wilke, 00; Weber, Blais, & Betz, 00). Risky choice scenarios within domain were not significant overall (p =. in the life death domain and p =. in the monetary domain). We then conducted another binary logistic regression analysis for the multiple framing condition, with verbal frame, facial expression, tone of voice, and task domain as independent variables and choices (riskseeking or risk-averse) as the dependent variable. The overall model for the binary logistic regression was significant (p <.001) and correctly predicts.% of participants choices. There was no significant interaction between the independent variables. Consistent with Hypothesis 1, no preference reversal due to verbal framing was found in the multiple framing condition. A unidirectional framing effect was significant (p <.001, OR = 1.), meaning a shift in risk preference rather than a Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

5 S. Garelik and X. T. Wang Table 1. Choice preference in the framing only condition Table. Risk tendency for factorial condition Frame Frame Tone of voice Domain Facial expression Positive Negative Happy Sad Happy Sad Fear Surprise Life Money Risk-averse.%.%.%.%.%.%.%.%.%.1% Risk-seeking.%.1%.1%.%.%.%.%.%.%.% Table. Choice preference by scenario for both conditions Verbal framing only Domain Positive Negative Life/Death Monetary Risk-averse 1 (.%) (.%) (.%) 1 (.%) Risk-seeking 1 (.%) 1 (.%) 1 (.%) 1 (.%) Note: The total frequency of choice responses was ( questions frames participants). Multiple frames Scenario Risk-averse Risk-seeking Risk-averse Risk-seeking Asian disease.%.1%.%.% Natural disaster.0%.0%.%.% Terrorist attack.0%.0%.%.% Nuclear meltdown.0%.0%.%.% Lawsuit.0%.0%.%.% Joint venture.%.%.%.1% Monetary gain.%.%.%.% Monetary loss.%.%.0%.0% Table. Classification of cue congruency by verbal frame, facial expression, and tone of voice Cue congruency Verbal frame Vocal tone Facial expression Significance Effect size Congruent cue conditions Positive Happy Happy p =.1 Negative Sad Sad Negative Sad Fear Partially incongruent cue conditions Positive Happy Sad p <.001 Odds ratio = 1. Positive Happy Fear Positive Sad Happy Negative Happy Sad Negative Happy Fear Negative Sad Happy Fully incongruent cue conditions Positive Sad Sad p =.00 Odds ratio = 1. Positive Sad Fear Negative Happy Happy Table. Choice preference by cue congruency with verbal frame for each affect cue Emotional cue Risk-seeking preference when consistent with frame Verbal, Facial, and Vocal Framing Risk-seeking preference when inconsistent with frame Significance Effect size Happy tone.%.1% p <.001 Odds ratio = 1. Happy face.1%.% p =. Odds ratio = 1. Sad tone.0%.% p <.001 Odds ratio = 0. Sad face.%.% p =.00 Odds ratio = 0. Fearful face.%.0% p <.001 Odds ratio = 0. Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

6 Journal of Behavioral Decision Making reversal in risk preference was observed. Participants were risk-seeking in the positive frame and even more risk-seeking in the negative frame. The effects of facial expression (p =.) and tone of voice (p =.1) were not significant. Task domain was again significant (p <.001, OR =.); participants were more risk-seeking in the life death domain than in the monetary domain (Table ). Risky choice scenarios within domain were not significant overall (p =. in the life death domain, p =. in F the monetary domain). As shown in Figure, the two verbal framing effects were clearly different between the verbal framing only condition and the multiple framing condition, where additional facial and vocal cues eliminated risk preference reversal. The unidirectional framing effect found under the multiple framing condition suggests that the risk preference of the participants became more consistent with multiple cues. A chi-squared test comparing choice preferences in the verbal framing only and multiple framing conditions confirmed that the choice percentages in the two conditions were significantly different from each other (χ =.0, p =0.001, phi = 0.1). Participants were more risk-seeking in the multiple framing condition than in the verbal framing only condition. Chi-squared tests were also conducted to look at choice data for each condition and validate the results of the logistic regression analyses. The results of these tests were consistent with the results of the logistic regression in both conditions. Hypothesis stated that incongruent valence for facial expression and tone of voice would lead to stronger framing effects. Choice data were classified into three groups according to cue congruency between verbal framing and facial and vocal affect cues. A happy tone and happy facial expression were considered positive while a sad tone, sad facial expression, and fearful facial expression were considered negative. Surprise was not included in these analyses, because its valence is not clearly positive or negative. The trials used in each congruence condition and the overall congruence effects are presented in Table. In the congruent group, the valence of all affect cues was congruent with verbal framing. In the partially incongruent group, the valence of either tone of voice or facial expression was incongruent with verbal framing. In the fully incongruent group, the valence of both tone of voice and facial expression were incongruent with verbal framing. A separate logistic regression was run for trials with each type of congruency. As predicted, the verbal framing effect was still significant for fully incongruent trials (p =.00,OR = 1.) and partially incongruent trials (p <.001, OR = 1.) but was no longer significant for congruent trials (p =.1). This suggests that participants resorted to and relied more on verbal framing when dealing with inconsistent facial and vocal cues. The disappearance of framing effects in the congruent condition was mainly due to the enhanced risk-seeking tendency in the positive verbal frame. Given that cue congruency was a withinsubject manipulation, these results show that participants were more consistent (either risk-seeking or risk-averse) when emotional cues were congruent with verbal framing. We also looked at cue congruency in valence for each individual tone and facial expression with verbal frame. These tones and expressions were coded as either congruent or incongruent with verbal frame. A logistic regression was conducted to compare risk preference under congruent versus incongruent conditions for each positive and negative cue. The results of those analyses are presented in Table below. The results of Table show that cue congruency is affectspecific. Positive cues increased risk-aversion when congruent with verbal frame but promoted risk-seeking tendency when incongruent with verbal frame. In contrast, negative cues increased risk-seeking tendency when congruent with verbal frame but promoted risk-aversion when incongruent with verbal frame. We did a similar analysis for cue congruency between tone of voice and facial expression. Cue congruency between those two cues did not significantly affect framing or choice preference. Hypothesis stated that positive emotions displayed in both facial expression and tone of voice would promote risk-seeking preference while negative emotions for both types of cues would promote risk-averse preference. Using binary logistic regression, the results of the analysis showed that the effect Figure. Percentage of risk-seeking choices in the verbal framing only condition (the left two bars) and the multiple framing condition (the right two bars). A bidirectional framing effect with a risk-preference reversal is observed in the verbal framing only condition (.% riskseeking in the positive frame,.% risk-seeking in the negative frame) while a unidirectional framing effect without a risk-preference reversal is observed in the multiple framing condition (.% risk-seeking in the positive frame,.1% risk-seeking in the negative frame) Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

7 S. Garelik and X. T. Wang of facial expression was not significant (p =.) as was tone of voice (p =.1). These results do not support Hypothesis. However, when a happy facial expression was present, participants became equally risk-seeking under both positive and negative verbal frames and thus eliminated framing effects in the happy facial expression condition (p =.). A closer examination revealed some other effects. Previous research has indicated that men and women may respond to emotional stimuli differently (Fessler, Pillsworth, & Flamson, 00). Logistic regression analyses were conducted looking at the choices made by male and female participants separately. The results of those analyses showed that facial expression was still not significant for either men (p =.1) or women (p =.). Tone of voice was also not significant for men (p =.). However, tone of voice was significant for women (p =.0, OR = 0.). Specifically, a happy voice made women more risk-seeking while a sad voice reduced their risk-seeking preference. GENERAL DISCUSSION In this study, we tested cue use and integration in risky choice in a more natural context where the decision maker received multiple cues: facial, vocal, and verbal. We asked three major questions. First, are affect cues not only integrated into decision making but also prompt more consistent choice preferences? A bidirectional framing effect was observed in the verbal framing only condition while a unidirectional effect was observed in the multiple framing condition. This finding suggests that compared with the verbal framing only condition, additional emotional cues eliminated irrational reversals and made decisions more consistent. Druckman and McDermott (00) found that the decision-makers emotional state can reduce the effects of verbal framing. Our results extend that finding to the affect cues of a messenger. The second question we addressed was related to cue congruency. This question was derived from the AA hypothesis (Wang, 00a) that states that ambiguity in decision cues and preferences is a major precondition for framing effects. Our results revealed that congruency in valence of multiple cues removed verbal framing effects, while verbal framing effects remained strong with any incongruence between verbal framing and facial or vocal cues. Recent studies in neuroscience can shed some light on the role of emotional cues in risky choice. A meta-analysis by Wang, Rao, and Zheng () indicated that one of the major brain regions that is implicated in framing effects is the anterior cingulate cortex, which is often recruited when decision cues are in conflict(e.g.,botvinick,cohen,& Carter, 00). In addition, the cue congruency effects found in this study were affect-specific and affected choice outcome. These results suggest that positive and negative affect cues can shift risk preference toward risk-seeking or risk-aversion depending on their congruency with the verbal frame used in risk communication. The third question we addressed was related to the specific role of emotions in risky choice. Although the overall effects of affect cues did not differentially affect risk preference, there Verbal, Facial, and Vocal Framing was a gender-specific effect of tone of voice. Female participants were more risk-seeking with a positive tone of voice and more risk-averse with a negative tone of voice. This finding indicates that women may be more sensitive than men to hedonic cues in decision making (see also Hall, 1). Gender-specific effects of affect cues on decision making were also found in other studies. Eriksson and Simpson (0) found that emotional reactions to decision outcomes are more evident in women, and this effect mediates gender difference in risk preference. Similarly, Fagley, Coleman, and Simon (0) showed that emotions associated with decision outcomes can moderate framing effects, particularlyinwomen. Although facial expressions did not have a main effect on verbal framing in the present study, a happy facial expression resulted in more risk-seeking choices in the positive frame than other facial expressions. As a result, happy facial expressions diminished verbal framing effects. Cassotti et al. (0) had reported similar findings in an emotional priming context, where a positive emotional prime made framing effects disappear. In addition, we find that the inclusion of affect cues overall promotes risk-seeking preference. This result may be because of a human preference for consistency (e.g., Aronson, 1; Brehm & Cohen, ; Festinger, ; Heider, 1). The inconsistent information (e.g., positive frame and negative facial expression) may be construed negatively as loss in information processing and thus shift choice preference toward risk-seeking (Tversky & Kahneman, 1). It is also possible that participants experienced elevated arousal levels from the emotional cues, causing an overall shift toward risk-seeking preference (Williams, 00). In sum, our results further demonstrate that verbal framing effects are powerful and robust. Verbal framing effects are most evident when the valence of some other communicational cues is incongruent. People are attentive to multiple cues of valence framing when making risky choices. Affect cues overall promote risk-seeking preference and make choices more consistent. These results call for future studies of risky choice in natural communication contexts. ACKNOWLEDGEMENT This research was partially supported by Grant SES- awarded to X. T. Wang. APPENDIX A: FRAMING QUESTIONS Asian Disease Problem (Tversky & Kahneman, 1) Imagine that the USA is preparing for the outbreak of an unusual Asian disease, which is expected to kill 0 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows: If Program A is adopted, 00 people will be saved. If Program B is adopted, there is one-third probability that 0 people will be saved and two-thirds probability that no people will be saved. Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm

8 Journal of Behavioral Decision Making Imagine that the USA is preparing for the outbreak of an unusual Asian disease, which is expected to kill 0 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows: If Program A is adopted, 0 people will die If Program B is adopted, there is one-third probability that nobody will die and two-thirds probability that 0 people will die. Natural Disaster Problem You have just heard news that the region in which you live will be hit by a massive hurricane, which is expected to kill 0 people. One option is to evacuate the region, and the other is to fortify the houses to protect against the storm. If you evacuate, 0 people will be saved. If you fortify, there is one-third probability that 0 people will be saved and two-thirds probability that no people will be saved. You have just heard news that the region in which you live will be hit by a massive hurricane, which is expected to kill 0 people. One option is to evacuate the region, and the other is to fortify the houses to protect against the storm. If you evacuate, 0 people will die. If you fortify, there is one-third probability that nobody will die and two-thirds probability that 0 people will die. Nuclear Meltdown Problem You have just received a report that a nuclear power plant is facing an imminent meltdown, which is expected to kill 0 people. Two alternatives are present for dealing with the situation. The area can be quarantined against radiation or a team can be sent into the plant to prevent the meltdown. If the quarantine is used, 0 people will be saved. If the meltdown is contained, there is one-third probability that 0 people will be saved and two-thirds probability that no people will be saved. You have just received a report that a nuclear power plant is facing an imminent meltdown, which is expected to kill 0 people. Two alternatives are present for dealing with the situation. The area can be quarantined against radiation or a team can be sent into the plant to prevent the meltdown. If the quarantine is used, 0 people will die. If the meltdown is contained, there is one-third probability that nobody will die and two-thirds probability that 0 people will die. Terrorist Attack Problem You have received a report that the USA has received intelligence of an impending terrorist attack, which is expected to kill 0 people. Two countermeasures are proposed. The first is to station the military in the target area, and the second is to launch a pre-emptive strike. The expected results of these plans are as follows: If the military is deployed, 00 people will be saved. If a pre-emptive strike is launched, there is one-third probability that 0 people will be saved and two-thirds probability that no people will be saved. You have received a report that the USA has received intelligence of an impending terrorist attack, which is expected to kill 0 people. Two countermeasures are proposed. The first is to station the military in the target area, and the second is to launch a pre-emptive strike. The expected results of these plans are as follows: If the military is deployed, 0 people will die. If a pre-emptive strike is launched, there is one-third probability that nobody will die, and two-thirds probability that 0 people will die. Lawsuit Problem (adapted from Highhouse & Yuce, 1) Positive Framing: Imagine that you are the senior executive at BTE. Your company is facing a lawsuit for a patent violation. The damages for this infringement are expected to be $m. You can settle outside of court or attempt to win the case. If you settle, $1m will be saved. If you go to trial, there is a one-third probability that you will save all $m and two-thirds probability that no money will be saved. Imagine that you are the senior executive at BTE. Your company is facing a lawsuit for a patent violation. The damages for this infringement are expected to be $m. You can settle outside of court or attempt to win the case. If you settle, $m will be lost. If you go to trial, there is a one-third probability that you will lose nothing, and two-thirds probability that $m will be lost. Joint Venture Problem (adapted from Highhouse & Yuce, 1) Imagine that you are the chief executive officer of a large company. Your company and your main competitor ATC are both interested in investing in a new market. Your analysis indicates that if your company teams up with ATC, the profit on the investment will be % for certain. However, if your company competes with ATC, you will get either a profitmargin of % or a small profit margin of % after tax. Your chance of getting the large profit is quite high, which is one in three. Imagine that you are the chief executive officer of a large company. Your company and your main competitor ATC are Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm Q Q

9 S. Garelik and X. T. Wang both interested in investing in a new market. Your analysis indicates that there is potential for an % profit. If your company teamsupwithatc,theprofit on the investment will be reduced by % for certain. However, if your company competes with ATC, you will either keep a profit margin of % or get an even smaller profit margin of 0%. Your chance of getting the small profit is quite high, which is two in three. Money problem Gain Situation (adapted from Wang, 00) You have gained $00 from one of your stocks and have to choose one of the following options: If you choose bonus Option A, you will receive an additional $. If you choose bonus Option B, there is a % chance that you will receive an additional $00 and a % chance that you will receive no additional money. You have gained $0 from one of your stocks but have to accept one of the following investment costs: If you choose investment Cost A, you must return $00. If you choose investment Cost B, there is a % chance that you will return $0 and a % chance that you will keep all money received. Money Problem Loss Situation (adapted from Wang, 00) One of the investments in your stock portfolio has lost $0, and you must choose one of the following options: If you choose stock insurance, you will gain back $. If you choose reinvestment, there is a % chance that you will gain back $00 and a % chance that you will gain back no money. One of the investments in your stock portfolio has lost $00, and you must choose one of the following options: If you choose stock insurance, you will lose an additional $. If you choose reinvestment, there is a % chance that you will lose $00 and a % chance that you will lose no additional money. REFERENCES Aronson, E. (1). The theory of cognitive dissonance: A current perspective. Advances in Experimental Social Psychology,, 1. Biehl, M., Matsumoto, D., Ekman, P., Hearn, V., Heider, K., Kudoh, T., et al. (1). 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Prifysgol Bangor: Bangor University. Zhang, Y., & Miao, D. (00). Social cues and framing effects in risky decisions among Chinese military students. Asian Journal of Social Psychology,,. Authors biographies: Steven Garelik is a graduate student in the Human Factors Psychology Program at the University of South Dakota. His recent research examines the effects of blood glucose on intertemporal choice and delay discounting and the roles of verbal framing and emotional communication cues in risky choice. XiaoTian Wang is a Professor of Psychology at the University of South Dakota whose research interests involve behavioral decision making, risk management, and evolutionary psychology. His recent research was supported by NSF, Max Planck Institute, the Institute of Psychology of the Chinese Academy of Sciences, Jinan University, Peking University, and Singapore Management University. Authors addresses: Steven Garelik, University of South Dakota, USA. Xiao Tian Wang, University of South Dakota, USA. Copyright 01 John Wiley & Sons, Ltd. J. Behav. Dec. Making (01) DOI:./bdm