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Effects of the BAS and BIS on decision-making in a gambling task
Personality and Individual Differences 50 (2011) 1131–1135
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Effects of the BAS and BIS on decision-making in a gambling task Deok-Yong Kim 1, Jang-Han Lee ⇑ Chung-Ang University, Department of Psychology, 221 Dongjak-gu, Heukseok-dong, 156-756 Seoul, South Korea
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Article history: Received 10 August 2010 Received in revised form 6 January 2011 Accepted 30 January 2011 Available online 22 February 2011 Keywords: Behavioral Approach System Behavioral Inhibition System Impulsivity Anxiety Decision-making Joint subsystem hypothesis Gambling Game of Dice Task
a b s t r a c t The aim of this study was to investigate how the Behavioral Approach System (BAS) and the Behavioral Inhibition System (BIS) affect decision-making in a gambling task. In accordance with the joint subsystem hypothesis, participants were divided into four groups based on their BAS and BIS scores. We used a modified gambling task, which examines decision-making after having winning and losing experiences unknowingly manipulated by the experimenters. We found that the high BAS and low BIS group made the most risky decisions after a winning experience, while the low BAS and high BIS group made more non-risky decisions after a losing experience. On the irrational belief scale, the high BAS groups bet larger amounts and had higher confidence levels in a losing condition. The present study found that relationships between personality traits and winning probabilities influence decisions in the gambling task. These findings may provide evidence that decision making and chasing in gambling situations are affected by personality traits and a perspective on feedback types. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Personality traits and feedback both play important roles in the decision-making process. According to Ernst and Paulus (2005), decision-making consists of three stages: evaluating the options, the actions, and the experience of the outcome. Each of these stages is influenced by different personality traits as well as feedback following the decisions made. Personality traits affect how a person evaluates the options and the actions. Feedback plays a role of monitoring previous results and influencing subsequent choices (Brand, Heinze, Labudda, & Markowitsch, 2008). Previous decisionmaking studies have identified that personality traits, such as the Behavioral Approach System (BAS) and the Behavioral Inhibition System (BIS), are likely to affect either risky or safe decisions following either rewarding or punishing feedback in gambling tasks. Suhr and Tsanadis (2007) suggested that high BAS individuals make more risky choices in the Iowa Gambling Task (IGT). Previous studies on decision-making and personality traits assume that the BAS and the BIS yield independent effects on decision-making, known as the Separable Subsystems Hypothesis (SSH) of the Reinforcement Sensitivity Theory (RST; Corr, 2001; Jackson & Francis, 2004). However, findings have been inconsistent. Brand and Altstötter-Gleich (2008) found no significant correlations between the BIS/BAS subscales and decision-making in ⇑ Corresponding author. Tel.: +82 2 820 5751; fax: +82 2 816 5124. 1
E-mail addresses: [email protected] (D.-Y. Kim), [email protected] (J.-H. Lee). Tel.: +82 2 820 6486.
0191-8869/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2011.01.041
healthy individuals, and Svaldi, Brand, and Tuschen-Caffier (2010) found similar results in individuals with binge eating disorders. One possible reason for these findings is the problems regarding the BIS/BAS scales (Levinson, Rodebaugh, & Frye, 2010). Some studies of the relationship between the BIS and positive affect suggested inconsistent results (Campbell-Sills, Liverant, & Brown, 2004; Carver & White, 1994). Another possible reason is that the SSH has some limitations, one of which may be that the SSH is observed only when stimuli contain strong BIS/BAS cues, or when either reward or punishment is contained in the experimental situation, or when individuals have a hyper-active BIS/BAS (Corr, 2002). The joint subsystems hypothesis (JSH; Corr, 2002) assumes that mutual interplay of the BAS and BIS affect response outcomes. Appetitive responses are likely to be associated with the facilitation of the BAS and the hindrance of the BIS. In contrast, aversive responses are likely to be associated with the hindrance of the BAS and the facilitation of the BIS. For example, individuals with a high BAS and low BIS are more likely to be sensitive to rewards, thereby making more risky decisions (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2006). Van Honk, Hermans, Putman, Montagne, and Schutter (2002) showed that individuals with a high BAS and low BIS made more risky decisions in the IGT than did individuals with BIS/BAS scores in the normal range. Therefore, it is important to consider the relative influences of the BAS and the BIS in gambling tasks. Feedback, such as rewards or punishments, may affect subsequent choices (Ernst & Paulus, 2005). Prior winning or losing experiences may be used to monitor current decision-making behavior
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as well as help with future decision-making strategies (Brand et al., 2009; Xue, Lu, Levin, & Bechara, 2010). The relative strength of the BAS and the BIS may affect decision-making when people overestimate or underestimate the probabilities of winning or losing after a reward or a punishment. One situation related to personality traits and feedback types is gambling. In gambling situations, which offer information about consequences and probabilities for winning and losing, pathological gamblers expect high gains and consistently choose high-risk decisions despite their losing experiences (Källmén, Andersson, & Andren, 2008). A possible reason for risky decisions in pathological gamblers is that their impulsive characteristics (Loxton, Nguyen, Casey, & Dawe, 2008), which tend to prefer positive outcomes and immediate reinforcement while being insensitive to negative consequences, may influence the irrational belief that they will certainly win (Goudriaan et al., 2006). Therefore, we investigated how personality traits may influence decision-making processes and irrational beliefs. The aim of the current study was to investigate how the strength of the relative BIS/BAS affects decision-making following gambling experiences. The hypotheses are as follows. First, we predicted that the high BAS and low BIS group would choose the most risky choices after a winning experience compared to the other groups. Second, we predicted that the low BAS and high BIS group would choose more non-risky choices after losing experiences compared to the other groups. To assess irrational beliefs, at the end of each block, participants were asked to choose an amount of money to bet and their level of confidence for winning the next trial. Our third hypothesis was that we predicted that the high BAS and low BIS group would bet more money and show a higher level of confidence after a losing experience compared to the other groups.
2. Method 2.1. Participants 577 undergraduate students (255 males, 322 females) completed the BIS/BAS scale (Carver & White, 1994). Participants were divided into four groups according to the medians of distribution: High BAS & High BIS, High BAS & Low BIS, Low BAS & High BIS, and Low BAS & Low BIS (medians: BIS = 20; BAS = 38). 92 students (42 males, 50 females) were selected to participate in the experiment. Among them, nine participants (4 males, 5 females) were excluded from the data analysis because of technical malfunctions. The mean age was 21.13 years (SD = 2.06; range = 18–27 years). All participants read and signed a written consent form before beginning the experiment. The mean age and sex were not significantly different among the four groups (age: F(3,79) = 4.55, n.s.; sex: x2(3) = 0.25, n.s.). The BAS scores were significantly different between the high BAS (M = 43.74, SD = 3.34) and the low BAS groups (M = 33.65, SD = 2.40) (t(81)=15.74, p < 0.01), and the BIS scores were also significantly different between the high BIS (M = 23.44, SD = 2.12) and the low BIS groups (M = 16.55, SD = 2.20) (t(81) = 14.52, p < 0.01)
(see Table 1). The participants received plus or minus 10 percent of their winnings/losses at the end of the experiment.
2.2. Materials 2.2.1. The modified Game of Dice Task The original Game of Dice Task (GDT; Brand et al., 2005), which is conducted on a computer, is a decision-making task that explicitly provides information about the rules for winning and losing before beginning the task. Participants are asked to maximize their monetary winnings and minimize their losses by guessing the value of the dice roll before it is rolled. If participants choose the correct combination with lower winning probabilities, they gain more money, but if the combination they choose is incorrect, they lose more money. Participants are instructed to choose a combination among one of four options. One option is a single number that has a winning probability of 1:6 (16.67%) associated the gain/loss of one dollar. The other options are combinations of two numbers (a winning probability of 2:6 (33%)) associated with a gain/loss of 50 cents, combinations of three numbers (a winning probability of 3:6 (50%)) associated with a gain/loss of 20 cents, or combinations of four numbers (a winning probability of 4:6 (67%)) associated with a gain/loss of 10 cents. The amount of gains and losses were presented continuously on the upper right corner of the screen. After each dice throw, audio and visual signals indicated whether the participants had won or lost. The participant’s current monetary balance and the number of remaining trials are also continuously displayed on the screen. We used the net scores, which are the number of non-risk choices (combinations of three numbers and of four numbers) subtracted by the number of risk choices (a single number and combinations of two numbers), in the GDT analysis. A low net score implies that more risk choices were made (see Brand et al., 2005). The participants conducted a modified version of the original GDT. The modified GDT consists of six blocks with different winning probabilities. The six blocks each has 10 trials and is designed to allow the experimenter to manipulate the winning probabilities of each of the trials on the first, third and fifth blocks; this information was unknown to the participants. In this study, we were able to manipulate the first (winning condition) and third blocks (losing condition) to have a high winning probability (66%) and a low winning probability (33%), respectively, while the winning probability on the fifth block (even condition) was fixed at 50% so that participants would not become aware of these presets. In the other three blocks, the GDT program itself set the winning probabilities, depending upon the participants’ responses. Decision-making after experiencing a winning, losing, or even condition could be analyzed using the net scores from the second blocks subtracted by the first blocks, the fourth blocks subtracted by the third blocks, and the sixth blocks subtracted by the fifth blocks. Additionally, the modified GDT contains bonus trials and self-report confidence measures for irrational beliefs on gambling.
Table 1 Demographic data and the BIS/BAS scores. High BAS
Age BAS score BIS score
Low BAS
High BIS(m = 10, f = 12) M (SD)
Low BIS(m = 10, f = 10) M (SD)
High BIS(m = 8, f = 11) M (SD)
Low BIS(m = 10, f = 12) M (SD)
20.91 (2.00) 44.18 (3.29) 23.68 (2.17)
21.80 (2.07) 43.25 (3.42) 15.85 (2.54)
21.16 (2.36) 33.26 (2.33) 23.16 (2.09)
20.73 (1.80) 34.00 (2.47) 17.18 (1.65)
BAS: Behavioral Approach System scales. BIS: Behavioral Inhibition System scales. m: male, f: female.
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Participants were able to adjust their betting ratios by 1, 3, 5, and 10 times in the bonus trials. A high amount of betting was related to irrational beliefs, which were related to the overconfidence that they would be able to win. The confidence of a participant’s own choices and expectations of winning the next trial were also measured using two self-report questionnaires with a seven-point Likert scale.
GDT probabilities (see Fig. 1). They completed the modified GDT to receive a monetary reward, and the task took roughly 10 min to complete. The participants were debriefed and were paid in accordance to how much money they had won or lost during the task.
2.2.2. The BIS/BAS scales The BIS/BAS self-report scales (Carver & White, 1994) assessed individual differences in the sensitivity of impending reward (BAS) or punishment (BIS), and contained 20 items with a fourpoint Likert scale ranging from ‘‘strongly agree’’ to ‘‘strongly disagree.’’ The BAS items were divided into three subcategories: drive, reward sensitivity and fun-seeking. The BIS items had no subcategories and measured punishment sensitivity. Adequate reliability for the BAS (Cronbach’s a = 0.801) and for the BIS (Cronbach’s a = 0.796) was established in this study.
Data analysis was conducted using SPSS 15.0 for Windows. For the analysis of decision-making on the winning, losing, and even conditions, the net scores of the differences between the second and the first blocks, the fourth and the third blocks, and the sixth and the fifth blocks were used. A three-way repeated measures analyses of variance (ANOVA) was used. The between-subject factors were the BAS and BIS groups (median split), and the withinsubject factors were the GDT net scores on the winning, losing, and even conditions. A two-way ANOVA and a simple main effects analysis were used to assess the differences in decision-making between the groups. The self-report scales in the first, third, and fifth blocks were used in the analysis to assess irrational beliefs after each condition. Three-way repeated measures ANOVAs, with the BAS and BIS groups as the between-subject factors on betting, overconfidence of own choices, and the expectation of winning the next trial measure were also used for each condition.
2.2.3. Measure of confidence for own choice and expectation of winning the next trial After the bonus trials in the GDT, participants were asked to rate the confidence of their choice and their expectation of winning the next trial with a seven-point Likert scale on a pop-up window. The confidence of a participant’s own choice and his or her expectation of winning the next trial measure consists of two questions: ‘‘How confident are you in your choice?’’ and ‘‘How confident are you in winning the next trial?’’ Responses ranged from ‘‘very little confidence’’ to ‘‘absolute confidence’’ for both questions. A higher score implied a higher level of confidence. 2.3. Procedure When participants arrived at the laboratory an experimenter explained the directions of the modified GDT, providing information regarding the choices and winning probabilities, the display windows, total number of rounds, bonus trials, and confidence measures. Before starting the task, participants first conducted an exercise block with eight trials, which was made up of the original
2.4. Data analysis
3. Results 3.1. GDT net scores and the relative BIS/BAS groups A three-way repeated measures ANOVA was conducted to investigate whether the relative BAS/BIS groups made different decisions after winning or losing or even experiences. Table 2 contains the means of the GDT net scores from each condition. The results of three-way repeated measures ANOVA revealed that an interaction of condition and the BAS and the BIS was significant, F(2,158) = 4.44, p < 0.05, g2 = 0.05. However, a main effect of condition, the BAS, and the BIS, and interactions between condition and personality traits were not significant. A two-way ANOVA was
Fig. 1. Procedure of the modified GDT.
Table 2 Mean (SD) for the GDT net scores on the winning, losing, and even conditions. High BAS
Condition Winning Losing Even
Low BAS
High BIS(n = 22)
Low BIS(n = 20)
High BIS(n = 19)
Low BIS(n = 22)
M (SD) 0.91 (2.52) 0.64 (3.23) 1.00 (3.48)
M (SD) 2.60 (3.73) 0.40 (4.92) 0.30 (3.92)
M (SD) 0.79 (6.08) 2.63 (5.25) 0.84 (4.34)
M (SD) 0.91 (3.74) 0.55 (4.54) 0.36 (2.87)
BIS: Behavioral Inhibition System. BAS: Behavioral Approach System. Winning condition: the differences of the GDT net score (2nd – 1st block). Losing condition: the differences of the GDT net score (4th – 3rd block). Even condition: the differences of the GDT net score (6th – 5th block).
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conducted to investigate the difference between the groups in each condition. In the winning condition, an interaction between the BAS and the BIS was significant, F(1,79) = 3.96, p = 0.05, g2 = 0.05 (Fig. 2). However, a main effect of the BAS and the BIS was not significant. A simple main effect analysis was conducted to find out the difference between groups. As a result, the high BAS/low BIS group had a significantly lower net score than the high BAS/high BIS group and the low BAS/low BIS group. These results indicate that the high BAS/low BIS group showed more risky decision-making than the high BAS/high BIS group or the low BAS/low BIS group after a winning condition. An analysis of the losing condition also revealed that an interaction between the BAS and BIS was significant, F(1,79) = 4.50, p < 0.05, g2 = 0.05. However, a main effect of the BAS and the BIS was not significant (Fig. 3). As a result of a simple main effect, a main effect of the BAS in the high BIS group, F(1,79) = 5.34, p < 0.05, and a main effect of the BIS in the low BAS group was significant, F(1,79) = 5.05, p < 0.05. These results indicate that the low BAS/high BIS group showed more safe decision-making than both the low BAS/low BIS and the high BAS/high BIS individuals. An analysis of the even condition revealed that a main effect of the BAS and BIS and an interaction between the BAS and BIS were not significant.
3.2. Irrational beliefs and the relative BIS/BAS group Irrational beliefs were measured from the betting amount on the three bonus trials and the two questions before the bonus trials on the winning (the first block), the losing (the third block), and the even condition (the fifth block). To analyze the betting in the
winning, the losing, and the even conditions, three-way repeated-measures ANOVAs were used. An analysis of the betting amount in the winning condition revealed that a main effect of condition was significant, F(2,158) = 9.56, p < 0.001, g2 = 0.11. The betting amount in the winning condition was less than in both the losing condition and the even condition. An interaction between condition and the BAS was also significant, F(2,158) = 4.80, p < 0.01, g2 = 0.06. A two-way ANOVA for each condition revealed a significant main effect of the BAS in the losing, F(1,79) = 9.06, p < 0.01, g2 = 0.10, and even conditions, F(1,79) = 8.12, p < 0.01, g2 = 0.09. The high BAS group bet more than the low BAS group in both the losing and even conditions. As a result of a simple main effect in the even condition, the high BAS/low BIS group bet more than the low BAS/low BIS group. Main effects of the BIS and an interaction between the BAS and BIS in both the losing and even conditions were not significant. To analyze the overconfidence of an individual’s own choices, a three-way repeated-measures ANOVA was used. A main effect of condition was significant, F(2,158) = 21.11, p < 0.001, g2 = 0.21. The overconfidence of an individual’s own choices in the winning condition was significantly more than in both the losing and even conditions. A main effect of the BAS and the BIS were also significant, F(1,79) = 8.42, p < 0.01, g2 = 0.10; F(1,79) = 5.71, p < 0.05, g2 = 0.07. These results indicate that a higher BAS and a lower BIS showed higher overconfidence of own choices. In the expectation of winning the next trials measure, main effects of condition, F(2,158) = 12.69, p < 0.001, g2 = 0.14, the BAS, F(1,79) = 9.38, p < 0.01, g2 = 0.11, and the BIS, F(1,79) = 4.05, p < 0.05, g2 = 0.05, were significant. An interaction between condition and the BAS was also significant, F(2,158) = 3.91, p < 0.05, g2 = 0.05. Two-way ANOVAs were conducted to investigate the differences between groups in each condition. In the winning condition, main effects of the BAS, F(1,79) = 15.67, p < 0.001, g2 = 0.17, and the BIS were significant, F(1,79) = 7.52, p < 0.05, g2 = 0.06. The higher BAS group showed more confidence than the lower BAS group, and a lower BIS group showed more confidence than higher BIS group in expectations of winning the next trial in the winning condition. In the losing condition, a main effect of the BAS was significant, F(1,79) = 11.84, p = 0.001, g2 = 0.13. The high BAS group was more confident in expectations of winning the next trial compared to the lower BAS group in the losing condition. Main effects of the BAS and the BIS in the even condition were not significant. The interaction between the BAS and BIS in all blocks was also not significant. 4. Discussion and conclusions
Fig. 2. GDT net scores of the BAS and BIS groups on a winning condition.
Fig. 3. GDT net scores for the BAS and BIS groups on a losing condition.
The purpose of the present study was to investigate how the relative strength of the BAS and the BIS affect decision-making in gambling tasks after having winning and losing experiences. In the results of the GDT net scores, the high BAS and low BIS group showed more risky decision-making after winning experiences, and the low BAS and high BIS group showed more safe decisions after losing experiences. These results support the JSH (Corr, 2002), suggesting that the effects of the relative strengths of the BAS and BIS affects decision-making. Feedback in particular, may be facilitated or hindered by either the BAS or the BIS. Prior winning or losing experiences in gambling are likely to be associated with strong physiological changes in the automatic nervous system, such as heart rate, skin conductance levels, and blood pressure (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2004). The experience of winning is likely to affect both the facilitation of the BAS, which controls the experience of positive feelings, and the hindrance of the BIS, which is responsible for the experience of negative feelings. The experience of losing may be influenced both to hinder the BAS and also to facilitate the BIS.
D.-Y. Kim, J.-H. Lee / Personality and Individual Differences 50 (2011) 1131–1135
However, in the even condition, where the winning probability was 50%, there was no significant interaction between the BAS and the BIS. These results may provide evidence that facilitation or hindrance of the BAS and the BIS are affected by prior reward or punishment. It is important, therefore, to consider the interplay between the BAS and BIS on decision-making tasks, such as gambling, which provides both reward and punishment. In the results regarding irrational beliefs, the higher BAS individuals showed larger betting amounts and higher expectations in the losing condition. These results may suggest that the losing condition was not enough to facilitate the BIS, because participants were guaranteed to get a minimum reward at the end of the tasks despite losing large amounts of money. The results of the betting amounts in the winning condition, in contrast, were less than in the other conditions. This may be due to the order of the winning, losing, and even conditions not being counter-balanced. The higher betting amount in the losing and even conditions compared to the winning condition might have been affected by previous blocks (second and fourth blocks). Therefore, further studies using decision-making tasks that have taken counter-balancing between conditions into consideration is needed. In the results of the betting amounts, the high BAS and low BIS group showed higher betting in the even condition compared to the losing condition. This result seems to facilitate the effect of the BAS in the even condition compared to the losing condition, because the even condition had higher winning probabilities than the losing condition did. This reflects a chasing behavior, which is to continue to gamble even after losses in order to make up for previous losses (Breen & Zuckerman, 1999; Dickerson, 1993). This kind of chasing behavior is associated with an impaired control of gambling behavior, and is one of the core features of pathological gamblers (PG) (Campbell-Meiklejohn, Woolrich, Passingham, & Rogers, 2008; Lesieur, 1979). Using the IGT, Linnet and colleagues (2006) suggested that PG show more chasing and poor decision-making strategies than do non-PG. However, there were no differences in sensation-seeking scale scores between the PG and non-PG groups. Therefore, further study regarding what kinds of personalities may affect chasing is needed. A limitation of our study is that we did not consider emotional effects. Emotional arousal from experiencing wins and losses may have an effect on decision-making processes (Goudriaan et al., 2006). Gee, Coventry, and Birkenhead (2005) demonstrated that in gambling situations, losing causes increased arousal while winning decreases arousal in experimental participants. Therefore, further research that incorporates psychophysiological measurements, such as heart rate or Galvanic skin response, would greatly benefit the examination of levels of emotional arousal and how these levels affect decision-making processes. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0020633) (No. 2010-0015788). This study was based on the master’s thesis by first author, directed by the corresponding author. References Brand, M., & Altstötter-Gleich, C. (2008). Personality and decision-making in laboratory gambling tasks – Evidence for a relationship between deciding
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Effects of the BAS and BIS on decision-making in a gambling task Deok-Yong Kim 1, Jang-Han Lee ⇑ Chung-Ang University, Department of Psychology, 221 Dongjak-gu, Heukseok-dong, 156-756 Seoul, South Korea
a r t i c l e
i n f o
Article history: Received 10 August 2010 Received in revised form 6 January 2011 Accepted 30 January 2011 Available online 22 February 2011 Keywords: Behavioral Approach System Behavioral Inhibition System Impulsivity Anxiety Decision-making Joint subsystem hypothesis Gambling Game of Dice Task
a b s t r a c t The aim of this study was to investigate how the Behavioral Approach System (BAS) and the Behavioral Inhibition System (BIS) affect decision-making in a gambling task. In accordance with the joint subsystem hypothesis, participants were divided into four groups based on their BAS and BIS scores. We used a modified gambling task, which examines decision-making after having winning and losing experiences unknowingly manipulated by the experimenters. We found that the high BAS and low BIS group made the most risky decisions after a winning experience, while the low BAS and high BIS group made more non-risky decisions after a losing experience. On the irrational belief scale, the high BAS groups bet larger amounts and had higher confidence levels in a losing condition. The present study found that relationships between personality traits and winning probabilities influence decisions in the gambling task. These findings may provide evidence that decision making and chasing in gambling situations are affected by personality traits and a perspective on feedback types. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction Personality traits and feedback both play important roles in the decision-making process. According to Ernst and Paulus (2005), decision-making consists of three stages: evaluating the options, the actions, and the experience of the outcome. Each of these stages is influenced by different personality traits as well as feedback following the decisions made. Personality traits affect how a person evaluates the options and the actions. Feedback plays a role of monitoring previous results and influencing subsequent choices (Brand, Heinze, Labudda, & Markowitsch, 2008). Previous decisionmaking studies have identified that personality traits, such as the Behavioral Approach System (BAS) and the Behavioral Inhibition System (BIS), are likely to affect either risky or safe decisions following either rewarding or punishing feedback in gambling tasks. Suhr and Tsanadis (2007) suggested that high BAS individuals make more risky choices in the Iowa Gambling Task (IGT). Previous studies on decision-making and personality traits assume that the BAS and the BIS yield independent effects on decision-making, known as the Separable Subsystems Hypothesis (SSH) of the Reinforcement Sensitivity Theory (RST; Corr, 2001; Jackson & Francis, 2004). However, findings have been inconsistent. Brand and Altstötter-Gleich (2008) found no significant correlations between the BIS/BAS subscales and decision-making in ⇑ Corresponding author. Tel.: +82 2 820 5751; fax: +82 2 816 5124. 1
E-mail addresses: [email protected] (D.-Y. Kim), [email protected] (J.-H. Lee). Tel.: +82 2 820 6486.
0191-8869/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2011.01.041
healthy individuals, and Svaldi, Brand, and Tuschen-Caffier (2010) found similar results in individuals with binge eating disorders. One possible reason for these findings is the problems regarding the BIS/BAS scales (Levinson, Rodebaugh, & Frye, 2010). Some studies of the relationship between the BIS and positive affect suggested inconsistent results (Campbell-Sills, Liverant, & Brown, 2004; Carver & White, 1994). Another possible reason is that the SSH has some limitations, one of which may be that the SSH is observed only when stimuli contain strong BIS/BAS cues, or when either reward or punishment is contained in the experimental situation, or when individuals have a hyper-active BIS/BAS (Corr, 2002). The joint subsystems hypothesis (JSH; Corr, 2002) assumes that mutual interplay of the BAS and BIS affect response outcomes. Appetitive responses are likely to be associated with the facilitation of the BAS and the hindrance of the BIS. In contrast, aversive responses are likely to be associated with the hindrance of the BAS and the facilitation of the BIS. For example, individuals with a high BAS and low BIS are more likely to be sensitive to rewards, thereby making more risky decisions (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2006). Van Honk, Hermans, Putman, Montagne, and Schutter (2002) showed that individuals with a high BAS and low BIS made more risky decisions in the IGT than did individuals with BIS/BAS scores in the normal range. Therefore, it is important to consider the relative influences of the BAS and the BIS in gambling tasks. Feedback, such as rewards or punishments, may affect subsequent choices (Ernst & Paulus, 2005). Prior winning or losing experiences may be used to monitor current decision-making behavior
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as well as help with future decision-making strategies (Brand et al., 2009; Xue, Lu, Levin, & Bechara, 2010). The relative strength of the BAS and the BIS may affect decision-making when people overestimate or underestimate the probabilities of winning or losing after a reward or a punishment. One situation related to personality traits and feedback types is gambling. In gambling situations, which offer information about consequences and probabilities for winning and losing, pathological gamblers expect high gains and consistently choose high-risk decisions despite their losing experiences (Källmén, Andersson, & Andren, 2008). A possible reason for risky decisions in pathological gamblers is that their impulsive characteristics (Loxton, Nguyen, Casey, & Dawe, 2008), which tend to prefer positive outcomes and immediate reinforcement while being insensitive to negative consequences, may influence the irrational belief that they will certainly win (Goudriaan et al., 2006). Therefore, we investigated how personality traits may influence decision-making processes and irrational beliefs. The aim of the current study was to investigate how the strength of the relative BIS/BAS affects decision-making following gambling experiences. The hypotheses are as follows. First, we predicted that the high BAS and low BIS group would choose the most risky choices after a winning experience compared to the other groups. Second, we predicted that the low BAS and high BIS group would choose more non-risky choices after losing experiences compared to the other groups. To assess irrational beliefs, at the end of each block, participants were asked to choose an amount of money to bet and their level of confidence for winning the next trial. Our third hypothesis was that we predicted that the high BAS and low BIS group would bet more money and show a higher level of confidence after a losing experience compared to the other groups.
2. Method 2.1. Participants 577 undergraduate students (255 males, 322 females) completed the BIS/BAS scale (Carver & White, 1994). Participants were divided into four groups according to the medians of distribution: High BAS & High BIS, High BAS & Low BIS, Low BAS & High BIS, and Low BAS & Low BIS (medians: BIS = 20; BAS = 38). 92 students (42 males, 50 females) were selected to participate in the experiment. Among them, nine participants (4 males, 5 females) were excluded from the data analysis because of technical malfunctions. The mean age was 21.13 years (SD = 2.06; range = 18–27 years). All participants read and signed a written consent form before beginning the experiment. The mean age and sex were not significantly different among the four groups (age: F(3,79) = 4.55, n.s.; sex: x2(3) = 0.25, n.s.). The BAS scores were significantly different between the high BAS (M = 43.74, SD = 3.34) and the low BAS groups (M = 33.65, SD = 2.40) (t(81)=15.74, p < 0.01), and the BIS scores were also significantly different between the high BIS (M = 23.44, SD = 2.12) and the low BIS groups (M = 16.55, SD = 2.20) (t(81) = 14.52, p < 0.01)
(see Table 1). The participants received plus or minus 10 percent of their winnings/losses at the end of the experiment.
2.2. Materials 2.2.1. The modified Game of Dice Task The original Game of Dice Task (GDT; Brand et al., 2005), which is conducted on a computer, is a decision-making task that explicitly provides information about the rules for winning and losing before beginning the task. Participants are asked to maximize their monetary winnings and minimize their losses by guessing the value of the dice roll before it is rolled. If participants choose the correct combination with lower winning probabilities, they gain more money, but if the combination they choose is incorrect, they lose more money. Participants are instructed to choose a combination among one of four options. One option is a single number that has a winning probability of 1:6 (16.67%) associated the gain/loss of one dollar. The other options are combinations of two numbers (a winning probability of 2:6 (33%)) associated with a gain/loss of 50 cents, combinations of three numbers (a winning probability of 3:6 (50%)) associated with a gain/loss of 20 cents, or combinations of four numbers (a winning probability of 4:6 (67%)) associated with a gain/loss of 10 cents. The amount of gains and losses were presented continuously on the upper right corner of the screen. After each dice throw, audio and visual signals indicated whether the participants had won or lost. The participant’s current monetary balance and the number of remaining trials are also continuously displayed on the screen. We used the net scores, which are the number of non-risk choices (combinations of three numbers and of four numbers) subtracted by the number of risk choices (a single number and combinations of two numbers), in the GDT analysis. A low net score implies that more risk choices were made (see Brand et al., 2005). The participants conducted a modified version of the original GDT. The modified GDT consists of six blocks with different winning probabilities. The six blocks each has 10 trials and is designed to allow the experimenter to manipulate the winning probabilities of each of the trials on the first, third and fifth blocks; this information was unknown to the participants. In this study, we were able to manipulate the first (winning condition) and third blocks (losing condition) to have a high winning probability (66%) and a low winning probability (33%), respectively, while the winning probability on the fifth block (even condition) was fixed at 50% so that participants would not become aware of these presets. In the other three blocks, the GDT program itself set the winning probabilities, depending upon the participants’ responses. Decision-making after experiencing a winning, losing, or even condition could be analyzed using the net scores from the second blocks subtracted by the first blocks, the fourth blocks subtracted by the third blocks, and the sixth blocks subtracted by the fifth blocks. Additionally, the modified GDT contains bonus trials and self-report confidence measures for irrational beliefs on gambling.
Table 1 Demographic data and the BIS/BAS scores. High BAS
Age BAS score BIS score
Low BAS
High BIS(m = 10, f = 12) M (SD)
Low BIS(m = 10, f = 10) M (SD)
High BIS(m = 8, f = 11) M (SD)
Low BIS(m = 10, f = 12) M (SD)
20.91 (2.00) 44.18 (3.29) 23.68 (2.17)
21.80 (2.07) 43.25 (3.42) 15.85 (2.54)
21.16 (2.36) 33.26 (2.33) 23.16 (2.09)
20.73 (1.80) 34.00 (2.47) 17.18 (1.65)
BAS: Behavioral Approach System scales. BIS: Behavioral Inhibition System scales. m: male, f: female.
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Participants were able to adjust their betting ratios by 1, 3, 5, and 10 times in the bonus trials. A high amount of betting was related to irrational beliefs, which were related to the overconfidence that they would be able to win. The confidence of a participant’s own choices and expectations of winning the next trial were also measured using two self-report questionnaires with a seven-point Likert scale.
GDT probabilities (see Fig. 1). They completed the modified GDT to receive a monetary reward, and the task took roughly 10 min to complete. The participants were debriefed and were paid in accordance to how much money they had won or lost during the task.
2.2.2. The BIS/BAS scales The BIS/BAS self-report scales (Carver & White, 1994) assessed individual differences in the sensitivity of impending reward (BAS) or punishment (BIS), and contained 20 items with a fourpoint Likert scale ranging from ‘‘strongly agree’’ to ‘‘strongly disagree.’’ The BAS items were divided into three subcategories: drive, reward sensitivity and fun-seeking. The BIS items had no subcategories and measured punishment sensitivity. Adequate reliability for the BAS (Cronbach’s a = 0.801) and for the BIS (Cronbach’s a = 0.796) was established in this study.
Data analysis was conducted using SPSS 15.0 for Windows. For the analysis of decision-making on the winning, losing, and even conditions, the net scores of the differences between the second and the first blocks, the fourth and the third blocks, and the sixth and the fifth blocks were used. A three-way repeated measures analyses of variance (ANOVA) was used. The between-subject factors were the BAS and BIS groups (median split), and the withinsubject factors were the GDT net scores on the winning, losing, and even conditions. A two-way ANOVA and a simple main effects analysis were used to assess the differences in decision-making between the groups. The self-report scales in the first, third, and fifth blocks were used in the analysis to assess irrational beliefs after each condition. Three-way repeated measures ANOVAs, with the BAS and BIS groups as the between-subject factors on betting, overconfidence of own choices, and the expectation of winning the next trial measure were also used for each condition.
2.2.3. Measure of confidence for own choice and expectation of winning the next trial After the bonus trials in the GDT, participants were asked to rate the confidence of their choice and their expectation of winning the next trial with a seven-point Likert scale on a pop-up window. The confidence of a participant’s own choice and his or her expectation of winning the next trial measure consists of two questions: ‘‘How confident are you in your choice?’’ and ‘‘How confident are you in winning the next trial?’’ Responses ranged from ‘‘very little confidence’’ to ‘‘absolute confidence’’ for both questions. A higher score implied a higher level of confidence. 2.3. Procedure When participants arrived at the laboratory an experimenter explained the directions of the modified GDT, providing information regarding the choices and winning probabilities, the display windows, total number of rounds, bonus trials, and confidence measures. Before starting the task, participants first conducted an exercise block with eight trials, which was made up of the original
2.4. Data analysis
3. Results 3.1. GDT net scores and the relative BIS/BAS groups A three-way repeated measures ANOVA was conducted to investigate whether the relative BAS/BIS groups made different decisions after winning or losing or even experiences. Table 2 contains the means of the GDT net scores from each condition. The results of three-way repeated measures ANOVA revealed that an interaction of condition and the BAS and the BIS was significant, F(2,158) = 4.44, p < 0.05, g2 = 0.05. However, a main effect of condition, the BAS, and the BIS, and interactions between condition and personality traits were not significant. A two-way ANOVA was
Fig. 1. Procedure of the modified GDT.
Table 2 Mean (SD) for the GDT net scores on the winning, losing, and even conditions. High BAS
Condition Winning Losing Even
Low BAS
High BIS(n = 22)
Low BIS(n = 20)
High BIS(n = 19)
Low BIS(n = 22)
M (SD) 0.91 (2.52) 0.64 (3.23) 1.00 (3.48)
M (SD) 2.60 (3.73) 0.40 (4.92) 0.30 (3.92)
M (SD) 0.79 (6.08) 2.63 (5.25) 0.84 (4.34)
M (SD) 0.91 (3.74) 0.55 (4.54) 0.36 (2.87)
BIS: Behavioral Inhibition System. BAS: Behavioral Approach System. Winning condition: the differences of the GDT net score (2nd – 1st block). Losing condition: the differences of the GDT net score (4th – 3rd block). Even condition: the differences of the GDT net score (6th – 5th block).
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conducted to investigate the difference between the groups in each condition. In the winning condition, an interaction between the BAS and the BIS was significant, F(1,79) = 3.96, p = 0.05, g2 = 0.05 (Fig. 2). However, a main effect of the BAS and the BIS was not significant. A simple main effect analysis was conducted to find out the difference between groups. As a result, the high BAS/low BIS group had a significantly lower net score than the high BAS/high BIS group and the low BAS/low BIS group. These results indicate that the high BAS/low BIS group showed more risky decision-making than the high BAS/high BIS group or the low BAS/low BIS group after a winning condition. An analysis of the losing condition also revealed that an interaction between the BAS and BIS was significant, F(1,79) = 4.50, p < 0.05, g2 = 0.05. However, a main effect of the BAS and the BIS was not significant (Fig. 3). As a result of a simple main effect, a main effect of the BAS in the high BIS group, F(1,79) = 5.34, p < 0.05, and a main effect of the BIS in the low BAS group was significant, F(1,79) = 5.05, p < 0.05. These results indicate that the low BAS/high BIS group showed more safe decision-making than both the low BAS/low BIS and the high BAS/high BIS individuals. An analysis of the even condition revealed that a main effect of the BAS and BIS and an interaction between the BAS and BIS were not significant.
3.2. Irrational beliefs and the relative BIS/BAS group Irrational beliefs were measured from the betting amount on the three bonus trials and the two questions before the bonus trials on the winning (the first block), the losing (the third block), and the even condition (the fifth block). To analyze the betting in the
winning, the losing, and the even conditions, three-way repeated-measures ANOVAs were used. An analysis of the betting amount in the winning condition revealed that a main effect of condition was significant, F(2,158) = 9.56, p < 0.001, g2 = 0.11. The betting amount in the winning condition was less than in both the losing condition and the even condition. An interaction between condition and the BAS was also significant, F(2,158) = 4.80, p < 0.01, g2 = 0.06. A two-way ANOVA for each condition revealed a significant main effect of the BAS in the losing, F(1,79) = 9.06, p < 0.01, g2 = 0.10, and even conditions, F(1,79) = 8.12, p < 0.01, g2 = 0.09. The high BAS group bet more than the low BAS group in both the losing and even conditions. As a result of a simple main effect in the even condition, the high BAS/low BIS group bet more than the low BAS/low BIS group. Main effects of the BIS and an interaction between the BAS and BIS in both the losing and even conditions were not significant. To analyze the overconfidence of an individual’s own choices, a three-way repeated-measures ANOVA was used. A main effect of condition was significant, F(2,158) = 21.11, p < 0.001, g2 = 0.21. The overconfidence of an individual’s own choices in the winning condition was significantly more than in both the losing and even conditions. A main effect of the BAS and the BIS were also significant, F(1,79) = 8.42, p < 0.01, g2 = 0.10; F(1,79) = 5.71, p < 0.05, g2 = 0.07. These results indicate that a higher BAS and a lower BIS showed higher overconfidence of own choices. In the expectation of winning the next trials measure, main effects of condition, F(2,158) = 12.69, p < 0.001, g2 = 0.14, the BAS, F(1,79) = 9.38, p < 0.01, g2 = 0.11, and the BIS, F(1,79) = 4.05, p < 0.05, g2 = 0.05, were significant. An interaction between condition and the BAS was also significant, F(2,158) = 3.91, p < 0.05, g2 = 0.05. Two-way ANOVAs were conducted to investigate the differences between groups in each condition. In the winning condition, main effects of the BAS, F(1,79) = 15.67, p < 0.001, g2 = 0.17, and the BIS were significant, F(1,79) = 7.52, p < 0.05, g2 = 0.06. The higher BAS group showed more confidence than the lower BAS group, and a lower BIS group showed more confidence than higher BIS group in expectations of winning the next trial in the winning condition. In the losing condition, a main effect of the BAS was significant, F(1,79) = 11.84, p = 0.001, g2 = 0.13. The high BAS group was more confident in expectations of winning the next trial compared to the lower BAS group in the losing condition. Main effects of the BAS and the BIS in the even condition were not significant. The interaction between the BAS and BIS in all blocks was also not significant. 4. Discussion and conclusions
Fig. 2. GDT net scores of the BAS and BIS groups on a winning condition.
Fig. 3. GDT net scores for the BAS and BIS groups on a losing condition.
The purpose of the present study was to investigate how the relative strength of the BAS and the BIS affect decision-making in gambling tasks after having winning and losing experiences. In the results of the GDT net scores, the high BAS and low BIS group showed more risky decision-making after winning experiences, and the low BAS and high BIS group showed more safe decisions after losing experiences. These results support the JSH (Corr, 2002), suggesting that the effects of the relative strengths of the BAS and BIS affects decision-making. Feedback in particular, may be facilitated or hindered by either the BAS or the BIS. Prior winning or losing experiences in gambling are likely to be associated with strong physiological changes in the automatic nervous system, such as heart rate, skin conductance levels, and blood pressure (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2004). The experience of winning is likely to affect both the facilitation of the BAS, which controls the experience of positive feelings, and the hindrance of the BIS, which is responsible for the experience of negative feelings. The experience of losing may be influenced both to hinder the BAS and also to facilitate the BIS.
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However, in the even condition, where the winning probability was 50%, there was no significant interaction between the BAS and the BIS. These results may provide evidence that facilitation or hindrance of the BAS and the BIS are affected by prior reward or punishment. It is important, therefore, to consider the interplay between the BAS and BIS on decision-making tasks, such as gambling, which provides both reward and punishment. In the results regarding irrational beliefs, the higher BAS individuals showed larger betting amounts and higher expectations in the losing condition. These results may suggest that the losing condition was not enough to facilitate the BIS, because participants were guaranteed to get a minimum reward at the end of the tasks despite losing large amounts of money. The results of the betting amounts in the winning condition, in contrast, were less than in the other conditions. This may be due to the order of the winning, losing, and even conditions not being counter-balanced. The higher betting amount in the losing and even conditions compared to the winning condition might have been affected by previous blocks (second and fourth blocks). Therefore, further studies using decision-making tasks that have taken counter-balancing between conditions into consideration is needed. In the results of the betting amounts, the high BAS and low BIS group showed higher betting in the even condition compared to the losing condition. This result seems to facilitate the effect of the BAS in the even condition compared to the losing condition, because the even condition had higher winning probabilities than the losing condition did. This reflects a chasing behavior, which is to continue to gamble even after losses in order to make up for previous losses (Breen & Zuckerman, 1999; Dickerson, 1993). This kind of chasing behavior is associated with an impaired control of gambling behavior, and is one of the core features of pathological gamblers (PG) (Campbell-Meiklejohn, Woolrich, Passingham, & Rogers, 2008; Lesieur, 1979). Using the IGT, Linnet and colleagues (2006) suggested that PG show more chasing and poor decision-making strategies than do non-PG. However, there were no differences in sensation-seeking scale scores between the PG and non-PG groups. Therefore, further study regarding what kinds of personalities may affect chasing is needed. A limitation of our study is that we did not consider emotional effects. Emotional arousal from experiencing wins and losses may have an effect on decision-making processes (Goudriaan et al., 2006). Gee, Coventry, and Birkenhead (2005) demonstrated that in gambling situations, losing causes increased arousal while winning decreases arousal in experimental participants. Therefore, further research that incorporates psychophysiological measurements, such as heart rate or Galvanic skin response, would greatly benefit the examination of levels of emotional arousal and how these levels affect decision-making processes. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0020633) (No. 2010-0015788). This study was based on the master’s thesis by first author, directed by the corresponding author. References Brand, M., & Altstötter-Gleich, C. (2008). Personality and decision-making in laboratory gambling tasks – Evidence for a relationship between deciding
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