Individual differences in decision-making

Transcription

1 Personality and Individual Differences 39 (2005) Individual differences in decision-making Ingmar H.A. Franken *, Peter Muris Department of Psychology, Erasmus University Rotterdam, Woudestein J5-43, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands Received 13 September 2004; accepted 4 April 2005 Available online 16 June 2005 Abstract Behavioral decision-making as measured with a gambling task has been found to be impaired in several pathological conditions such as brain lesions, addiction, and personality disorders. It is not known how individual differences influence performance on behavioral decision-making. The goal of the present study was to examine to what extent performance on behavioral measures of decision-making is predicted by selfreported personality traits of sensitivity for punishment and reward, impulsivity, and decision-making styles. For this goal, performance on the IOWA gambling task was related to the BIS/BAS questionnaire, the Dickman Impulsivity Inventory, and the Adolescent Decision Making Questionnaire in a sample of students (n = 44). The results showed that behavioral decision-making was to some extent predicted by individual differences in sensitivity for reward and self-reported decision-making style. However, behavioral decision-making was not predicted by impulsive personality traits. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Behavioral decision-making; Impulsivity; BIS; BAS; IOWA gambling task 1. Introduction Behavioral decision-making research is concerned with how people make choices. Researchers in the fields of psychology and economics generally agree on the importance of two fundamental * Corresponding author. Tel.: ; fax: address: franken@fsw.eur.nl (I.H.A. Franken) /$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi: /j.paid

2 992 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) human motives, namely the desire to reduce pain/uncertainty and the desire to obtain pleasure (Bentham, 1948). In contrast to earlier theories that viewed decision-making as a rational choice, it is now known that human decision-making is rather based on hedonic motives than on rational motives (Cabanac, 1992). For example, risky sexual behaviors are rather the result of anticipation of short-term reward than based on long-term risk assessment. Recently, there have been numerous attempts to interpret clinical problems such as addictive behaviors, criminal behavior, and brain damage in terms of this reward-based decision theory. These attempts are founded on recent understandings concerning the psychology and neuroscience of decision-making (Bechara, Damasio, Damasio, & Lee, 1999; Rahman, Sahakian, Cardinal, Rogers, & Robbins, 2001; Rogers et al., 1999). Bechara, Damasio, Damasio, and Anderson (1994) demonstrated that patients with frontal lobe damage have problems with reward-based decision-making: they often pursue actions that bring some kind of immediate reward, despite severe long-term consequences such as the loss of job, home, and family. These studies on neurological patients have direct implications for understanding several psychiatric disorders including drug addiction, impulse control disorders (such as gambling), sexual disorders (sexual offenders), psychopathy, bulimia and obesity. The patients with these disorders experience similar problems in reward-based decision-making (Cohen & Blum, 2002). Despite recent scientific progress in this field (Krawczyk, 2002; Rahman et al., 2001), several issues certainly require more research attention. One of these issues is the relation between personality and decision-making. For example, it is unknown to what extent behavioral decision-making, typically measured by the IOWA gambling task (Bechara et al., 1994), is influenced by higher-order personality traits. In the IOWA gambling task, subjects have to select cards from four decks that range in probability and magnitude of rewards and punishments. The decks that provide immediate larger gains also provide net losses in the longer run. Two candidate personality traits that may influence IOWA gambling task performance can be discerned: impulsivity and Behavioral Inhibition System/Behavioral Approach System (BIS/BAS) sensitivity. The first candidate, impulsivity, can be described as the inability to tolerate long delays to reinforcer presentation, or a preference for smaller more immediate rewards over larger but more delayed rewards (Ainslie, 1975). A recent study by Crone, Vendel, and van der Molen (2003) showed that decision-making is modulated by individual differences in disinhibition, which is a key feature of impulsivity. More specifically, performance on the IOWA gambling task was found to be affected by individual differences in cognitive disinhibition, as measured by a subscale of ZuckermanÕs Sensation Seeking Scale (Zuckerman, Eysenck, & Eysenck, 1978). In their discussion, the authors conclude that their findings indicate that subjects who are bad performers on the IOWA gambling task can best be characterized as reward-prone rather than as future-insensitive. However, recent studies among healthy subjects indicate that impulsivity (or cognitive disinhibition) and reward sensitivity do not represent the same construct (Dawe & Loxton, 2004; Franken, Muris, & Rassin, 2005; Quilty & Oakman, 2004). In addition, studies among brain damage patients have indicated that decision-making and impulsivity can manifest themselves independently (Mavaddat, Kirkpatrick, Rogers, & Sahakian, 2000). A second candidate that may influence IOWA gambling task performance is BIS/BAS sensitivity (Carver & White, 1994). The BAS mediates reactions to appetitive stimuli (such as reward), whereas the BIS mediates reactions to aversive stimuli (Gray, 1987). In general, GrayÕs neuropsychological theory of personality predicts that subjects with high BIS are most sensitive to signals of punishments, while subjects with high BAS are most sensitive to signals of reward. Because in the

3 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) IOWA gambling task both rewards (gains) and punishments (losses) are used, it can be hypothesized that BIS/BAS sensitivity mediates performance on the IOWA gambling task. Van Honk, Hermans, Putman, Montagne, and Schutter (2002) showed that non-clinical psychopaths who had a combination of low BIS and high BAS performed worse on the IOWA gambling task than non-psychopathic persons who displayed BIS/BAS scores in the normal range. Yet, it is unknown whether BIS and BAS each have an independent influence on IOWA gambling task performance. The present study further examined the influence of a number of potentially relevant personality traits on behavioral decision-making. For this purpose, a group of students carried out the IOWA gambling task and completed a set of self-report questionnaires for measuring sensitivity for punishment and reward (BIS/BAS), and impulsivity. It is hypothesized that high levels of selfreported BAS and low levels of self-reported BIS, but not self-reported impulsivity, are negatively associated with reward-based behavioral decision-making on the IOWA gambling task. In addition, participants also completed a self-report scale for assessing their decision-making style. In this way, it became possible to study the connection between a self-report and a behavioral measure of decision-making. To summarize, the aim of the present study was to investigate to what extent performance on the IOWA gambling task is predicted by questionnaires that measure general personality traits (BIS/BAS and impulsivity) and self-reported decision-making styles. In addition to a correlational approach, we also used regression analysis in order to study the relative contribution of each of these factors to behavioral decision-making. 2. Methods 2.1. Participants and procedure A sample of 44 psychology students (eight males) volunteered to participate in the present study. The mean age of the sample was 20.0 years (SD = 4.2). Prior to participation, all subjects provided written informed consent. Participants were asked to complete Dutch translations of Carver and WhiteÕs (1994) BIS/BAS Scales, the Adolescent Decision Making Questionnaire (ADMQ; Tuinstra, van Sonderen, Groothoff, van den Heuvel, & Post, 2000), and the Dickman Impulsivity Inventory DII; (Dickman, 1990). Next, subjects completed the IOWA gambling task. A two-tailed t-test did not reveal differences between males and females on IOWA gambling task performance or on any of the self-report measures (all tõs < 1.8). Therefore, no separate analyses for male and female participants were conducted Instruments For the present study we used the computerized version of the IOWA gambling task (Bechara, Tranel, & Damasio, 2000) with a progressive schedule of increased delayed punishments. The IOWA gambling task consists of 100 successive trials in which subjects are required to choose a card from one of four decks. The participants are instructed to try to gain as much money as possible by drawing cards from one of four decks. The decisions to choose from the decks are motivated by reward and punishment schedules inherent in the task. Two of the decks (i.e., A 0 and B 0 ) are disadvantageous, producing immediate gains (large rewards) but these are

4 994 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) accompanied by larger losses in the long run (larger punishments). The C 0 and D 0 decks are advantageous: here, gains are modest but more consistent and losses are smaller. We used the net-score (advantageous decks disadvantageous decks) as dependent variable. A higher score means that a subject is more often choosing advantageous decks. The BIS/BAS Scales are presented as a self-report questionnaire that has been constructed to assess individual differences in personality dimensions that reflect the sensitivity of two motivational systems, the aversive and appetitive system (BIS and BAS; Carver & White, 1994; Gray, 1987). The BIS/BAS Scales consist of 20 items that can be allocated to two primary scales: the Behavioral Inhibition System scale (BIS; 7 items) and the Behavioral Approach System scale (BAS; 13 items). The BAS can be divided into 3 subscales: Fun Seeking (4 items), Reward Responsiveness (5 items), and Drive (4 items). The Dutch version of the BIS/BAS Scales has been described in previous studies (Franken, 2002; Franken et al., 2005). CronbachÕs alphas for various scales were found to range from.61 to.79. The DII (Dickman, 1990) is a 23-item self-report measure that distinguishes two types of impulsivity: functional impulsivity (11 items) and dysfunctional impulsivity (12 items). The functional impulsivity scale contains items such as: People have admired me because I can think quickly and Most of the time, I can put my thoughts into words very rapidly. The dysfunctional impulsivity scale contains items such as: I often say and do things without considering the consequences and I often get into trouble because I donõt think before I act. There were some minor adaptations made in the Dutch translation by Claes, Vertommen, and Braspenning (2000). First, all negative expressions were positively reworded. Second, some typical Flemish expressions were reworded for use in the Dutch population. The psychometric properties of the Dutch DII are good for both subscales (Claes et al., 2000), with a CronbachÕs alpha of.77 for functional impulsivity and an alpha of.80 for dysfunctional impulsivity (see Franken et al., 2005). The ADMQ is a 22-item self-report questionnaire that measures decision-making styles. The ADMQ consists of 4 scales: self-confidence (e.g., I think that I am a good decision maker ), avoidance (e.g., I avoid making decisions ), impulsiveness (e.g., I tend to drift into decisions without thinking of them ), and panic (e.g., I panic if I have to make decisions quickly ). The ADMQ has been shown to be a reliable and valid questionnaire for measuring decisionmaking styles (Tuinstra et al., 2000). CronbachÕs alphas vary between.59 and Data analysis Pearson correlation coefficients were calculated to examine the relations between IOWA gambling task score and ratings of the self-report scales. In order to investigate the relative contribution of the self-report scales to behavioral decision, the significant scales of the correlation analysis were added as independent variables in a linear regression model with the total score on the IOWA gambling task being the dependent variable. 3. Results The mean IOWA scores (SD) were 4.7 (5.4) for the first set of 20 cards,.7 (4.1) for the second set, 3.9 (4.1) for the third set, 7.5 (5.0) for the fourth set, and 8.6 (4.5) for the fifth set.

5 Table 1 Pearson correlation coefficients among IOWA gambling task scores and various self-report scales IOWA score BIS BAS Reward.32 **.13 Responsiveness 3. BAS Drive BAS Fun Seeking ** DII Functional.26 *.57 ** ** impulsivity 6. DII Dysfunctional **.39 **.38 ** impulsivity 7. ADMQ avoidance ** * **.26 * 8. ADMQ self-confidence ** ** ** ** 9. ADMQ panic.28 *.63 ** ** **.53 ** 10. ADMQ impulsiveness **.47 **.29 * Notes. N = 44. BIS = Behavioral Inhibition System, BAS = Behavioral Approach System, DII = Dickman Impulsivity Inventory, ADMQ = Adolescent Decision Making Questionnaire. * p <.10. ** p <.05. I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) Correlations between all variables are displayed in Table 1. As can be seen, scores on the IOWA gambling task were significantly correlated with the BAS Reward Responsiveness scale, whereas a trend towards a significant correlation emerged between IOWA scores on the one hand, and DII functional impulsivity and the panic scale of the ADMQ on the other hand. Furthermore, clearcut inter-scale correlations were found among dysfunctional impulsivity, BAS Drive, and BAS Fun Seeking. In addition, functional impulsivity was correlated in a theoretically meaningful way with all ADMQ scales. The linear regression model indicated that high performance on the IOWA gambling task was associated with higher scores on the BAS Reward Responsiveness scale (standardized beta =.48; t = 3.4, p =.001) and panic decision-making style (standardized beta =.41; t = 3.0; p =.005). The overall model explained a third part of the total variance of the IOWA gambling task performance [R 2 =.32; F(2,39) = 8.6; p =.001]. 4. Discussion In the present study, we found indications that behavioral decision-making is predicted by individual differences in sensitivity for reward, and that behavioral decision-making was not predicted by impulsive personality traits. Furthermore, behavioral decision-making was found to be to some extent correlated to self-reported decision-making style. More specifically, subjects who scored high on a panic decision-making style appeared to be worse decision-makers as measured with a behavioral index. This study indicates that performance on the IOWA gambling task is not only mediated by neurological or psychiatric disorders but is also, to some extent, significantly influenced by individual differences in higher-order personality traits and decision-making style.

6 996 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) Good performance on the IOWA gambling task was found to be positively related to BAS, in particular sensitivity to reward, but not to BIS. This finding is somewhat at odds with the results obtained by Van Honk et al. (2002), who found that subjects with a combination of high BAS and low BIS (i.e., non-clinical psychopaths) performed significantly worse on the IOWA gambling task than persons with the combination of low BAS and high BIS (i.e., normal controls). However, because of the design of their study, Van Honk et al. (2002) were not able to examine the relative contributions of BIS and BAS to IOWA task performance. In contrast, the present study sheds more light on the relative contributions of these personality traits on behavioral decision-making. The current findings showed that performance on the IOWA gambling task is not related to impulsivity. Although Gray (1970) used the term impulsivity to characterize the high BAS sensitivity trait, the present study demonstrates that impulsivity is quite different from reward sensitivity, and thus adds further evidence to the notion that reward sensitivity and impulsivity are allied but separate constructs (Dawe & Loxton, 2004; Franken et al., 2005; Quilty & Oakman, 2004). Impulsivity appears to represent rash and spontaneous behavior and as such is distinct from reward sensitivity (Dawe & Loxton, 2004). There was little overlapbetween self-reported decision-making styles and a behavioral measure of decision-making. Only the self-reported panic style of decision-making was found to be a significant predictor of behavioral decision-making. Higher scores on panic style were associated with lower scores on the IOWA gambling task. This can be explained in three ways. First, it may indicate that persons are less capable of rating their own decision-making processes. This fits with the idea that persons have in general limited insight into their own motives for behavior (Berridge, 2004; Berridge & Winkielman, 2003; Nisbett & Wilson, 1977; Winkielman & Berridge, 2003). Second, it might be that the IOWA gambling task taps a different construct than the ADMQ. Surprisingly, the one scale of the ADMQ that was actually related to performance on the IOWA gambling task was the panic scale. It has not been documented before that bad performance on the IOWA gambling task is related to a panic style of decision-making, and so it may well be the case that sample characteristics (i.e., the use of young college students) account for this finding. Third and finally, several researchers (e.g., Epstein, 1979, 1980) have noted that in the actual assessment of human behavior, sampling error is quite large when behavior is only measured in one specific context. Only the inclusion of various behavioral tasks would make it possible to reliably assess individual differences in decision-making. It should be mentioned that our population performed rather poor on the IOWA task as compared to subjects in previous studies. There may be two explanations for this difference in performance. It is known that high-educated subjects perform worse than low educated subjects on the IOWA task (Bowman & Turnbull, 2004; Evans, Kemish, & Turnbull, 2004). Furthermore, in most other studies the original IOWA task has been used, the so-called ABCD-task. In contrast, in the present study we used the A 0 B 0 C 0 D 0 task. This A 0 B 0 C 0 D 0 task is analogous to the original task (ABCD). The only difference is a change in the frequency and/or magnitude of delayed punishment relative to immediate reward. The change is such that the discrepancy between reward and punishment in the disadvantageous decks (A 0 and B 0 ) is larger in the negative direction. In addition, the discrepancy between reward and punishment in the advantageous decks (C 0 and D 0 ) is larger in the positive direction (Bechara et al., 2000). This probably makes the current task more difficult than the original task. However, it is unlikely that the relatively poor performance of our subjects on the IOWA task had a negative impact on our correlational findings.

7 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) To summarize, the present study showed that behavioral decision-making was to some extent predicted by individual differences in sensitivity for reward but not by impulsive personality traits. Furthermore, behavioral decision-making appeared to be correlated to the self-reported panic style of decision-making. Acknowledgement This study was sponsored by NWO (Netherlands organization for scientific research). References Ainslie, G. (1975). Specious reward: a behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82, Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, Bechara, A., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. Journal of Neuroscience, 19, Bechara, A., Tranel, D., & Damasio, H. (2000). Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain, 123, Bentham, J. (1948). An introduction to the principles of morals and legislation (Original work: 1789 ed.). Oxford: Blackwell. Berridge, K. C. (2004). Motivation concepts in behavioral neuroscience. Physiology & Behavior, 81, Berridge, K. C., & Winkielman, P. (2003). What is an unconscious emotion: the case for unconscious ÔlikingÕ. Cognition and Emotion, 17, Bowman, C. H., & Turnbull, O. H. (2004). Emotion-based learning on a simplified card game: the Iowa and Bangor gambling tasks. Brain and Cognition, 55, Cabanac, M. (1992). Pleasure: the common currency. Journal of Theoretical Biology, 155, Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology, 67, Claes, L., Vertommen, H., & Braspenning, N. (2000). Psychometric properties of the Dickman Impulsivity Inventory. Personality and Individual Differences, 29, Cohen, J. D., & Blum, K. I. (2002). Reward and decision. Neuron, 36, Crone, E. A., Vendel, I., & van der Molen, M. W. (2003). Decision-making in disinhibited adolescents and adults: insensitivity to future consequences or driven by immediate reward? Personality and Individual Differences, 35, Dawe, S., & Loxton, N. J. (2004). The role of impulsivity in the development of substance use and eating disorders. Neuroscience and Biobehavioral Reviews, 28, Dickman, S. J. (1990). Functional and dysfunctional impulsivity: personality and cognitive correlates. Journal of Personality and Social Psychology, 58, Epstein, S. (1979). The stability of behavior: I. On predicting most of the people much of the time. Journal of Personality and Social Psychology, 37, Epstein, S. (1980). The stability of behavior: II. Implications for psychological research. American Psychologist, 35, Evans, C. E. Y., Kemish, K., & Turnbull, O. H. (2004). Paradoxical effects of education on the Iowa gambling task. Brain and Cognition, 54, Franken, I. H. A. (2002). Behavioral approach system (BAS) sensitivity predicts alcohol craving. Personality and Individual Differences, 32,

8 998 I.H.A. Franken, P. Muris / Personality and Individual Differences 39 (2005) Franken, I. H. A., Muris, P., & Rassin, E. (2005). Psychometric properties of the Dutch BIS/BAS Scales. Journal of Psychopathology and Behavioral Assessment, 27, Gray, J. A. (1970). The psychophysiological basis of introversion extraversion. Behaviour Research and Therapy, 8, Gray, J. A. (1987). The psychology of fear and stress. Cambridge: Cambridge University Press. Krawczyk, D. C. (2002). Contributions of the prefrontal cortex to the neural basis of human decision-making. Neuroscience and Biobehavioral Review, 26, Mavaddat, N., Kirkpatrick, P. J., Rogers, R. D., & Sahakian, B. J. (2000). Deficits in decision-making in patients with aneurysms of the anterior communicating artery. Brain, 123, Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: verbal reports on mental processes. Psychological Review, 84, Quilty, L. C., & Oakman, J. M. (2004). The assessment of behavioural activation: the relationshipbetween impulsivity and behavioural activation. Personality and Individual Differences, 37, Rahman, S., Sahakian, B., Cardinal, R., Rogers, R., & Robbins, T. (2001). Decision-making and neuropsychiatry. Trends in Cognitive Science, 5, Rogers, R. D., Owen, A. M., Middleton, H. C., Williams, E. J., Pickard, J. D., Sahakian, B. J., et al. (1999). Choosing between small, likely rewards and large, unlikely rewards activates inferior and orbital prefrontal cortex. Journal of Neuroscience, 19, Tuinstra, J., van Sonderen, F. L. P., Groothoff, J. W., van den Heuvel, W. J. A., & Post, D. (2000). Reliability, validity and structure of the adolescent decision making questionnaire among adolescents in The Netherlands. Personality and Individual Differences, 28, Van Honk, J., Hermans, E. J., Putman, P., Montagne, B., & Schutter, D. J. (2002). Defective somatic markers in subclinical psychopathy. Neuroreport, 13, Winkielman, P., & Berridge, K. C. (2003). Irrational wanting and sub-rational liking: how rudimentary motivational and affective processes shape preferences and choices. Political Psychology, 24. Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46,