Big losses lead to irrational decision-making in gambling situations: relationship between deliberation and impulsivity.

Abstract

In gambling situations, we found a paradoxical reinforcing effect of high-risk decision-making after repeated big monetary losses. The computerized version of the Iowa Gambling Task (Bechara et al., 2000), which contained six big loss cards in deck B', was conducted on normal healthy college students. The results indicated that the total number of selections from deck A' and deck B' decreased across trials. However, there was no decrease in selections from deck B'. Detailed analysis of the card selections revealed that some people persisted in selecting from the "risky" deck B' as the number of big losses increased. This tendency was prominent in self-rated deliberative people. However, they were implicitly impulsive, as revealed by the matching familiar figure test. These results suggest that the gap between explicit deliberation and implicit impulsivity drew them into pathological gambling.

Full text

Page 1

Big Losses Lead to Irrational Decision-Making in
Gambling Situations: Relationship between Deliberation
and Impulsivity
Yuji Takano1*, Nobuaki Takahashi1, Daisuke Tanaka2, Naoyuki Hironaka1
1SHIMOJO Implicit Brain Function Project, Exploratory Research for Advanced Technology, Japan Science and Technology Agency, Atsugi-shi, Kanagawa, Japan,
2Department of Regional Education, Faculty of Regional Sciences, Tottori University, Tottori-shi, Tottori, Japan
Abstract
In gambling situations, we found a paradoxical reinforcing effect of high-risk decision-making after repeated big monetary
losses. The computerized version of the Iowa Gambling Task (Bechara et al., 2000), which contained six big loss cards in deck
B’, was conducted on normal healthy college students. The results indicated that the total number of selections from deck
A’ and deck B’ decreased across trials. However, there was no decrease in selections from deck B’. Detailed analysis of the
card selections revealed that some people persisted in selecting from the ‘‘risky’’ deck B’ as the number of big losses
increased. This tendency was prominent in self-rated deliberative people. However, they were implicitly impulsive, as
revealed by the matching familiar figure test. These results suggest that the gap between explicit deliberation and implicit
impulsivity drew them into pathological gambling.
Citation: Takano Y, Takahashi N, Tanaka D, Hironaka N (2010) Big Losses Lead to Irrational Decision-Making in Gambling Situations: Relationship between
Deliberation and Impulsivity. PLoS ONE 5(2): e9368. doi:10.1371/journal.pone.0009368
Editor: Andreas Reif, University of Wuerzburg, Germany
Received November 16, 2009; Accepted February 1, 2010; Published February 23, 2010
Copyright: ? 2010 Takano et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by Japan Science and Technology Agency. The funders had no role in study design, data collection, analysis, decision to
publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: ytakano@shimojo.jst.go.jp
Introduction
Human decision-making is not always rational. We sometimes
behave irrationally even if we ponder what to do and not to do.
Certainly, our decision-making is influenced by our own cognitive
styles and personality traits. Impulsivity is an important factor that
biases our evaluation of cost and benefit and subsequent decision-
making. A lot of experimental studies show that impulsive persons
preferimmediatesmallrewardsorevenadverse outcomes to delayed
large rewards [1–4]. Impulsivity is thought to be closely related to
addictive behaviors, such as illicit drug use and pathological
gambling [5–8]. However, it is unknown whether impulsivity is a
constant behavioral trait or not. Are there ‘‘impulsive’’ persons and
‘‘deliberate’’ persons? Do ‘‘impulsive’’ persons always behave
impulsively? It is likely that there is dissociation between conscious
reasonable thinking and the unconscious ‘‘implicit’’ origin of actual
decision making.
For example, using the Iowa gambling task (IGT), which is an
experimental tool to investigate risk-taking decision making, somatic
markers, such as palpitation or diaphoresis, precede a person’s
behavioral switch from risky to cautious choices [9–10]. The IGT is
a cardselection task inwhichparticipantsare required to choose one
card at a time from four card decks. Each card depicts imaginary
monetary gain or loss. Participants are encouraged to increase their
monetary gain. Two of the four card decks are high-risk/high-return
(deckA& B),whiletheothertwodecksarelow-risk/low-return(deck
C& D). It is well known that the normal healthy persons shift their
card selection from high-risk/high-return decks to low-risk/low-
return decks. Persisting in high-risk/high-return card choices is
known to represent impulsivity and to relate to brain injuries [9–12],
psychiatric diseases [13–16], and substance abuse [17–20].
Previous studies analyzing the high-risk decks revealed a
phenomenon related to deck B (called ‘prominent deck B’)[21].
Some normal subjects preferred deck B to the good final-outcome
decks C or D. This preference had not been apparent in studies that
used the sum of decks A and B [21]. Consequently, in the present
study, we focused on deck B’s effect on irrational decision-making
and examined the relationship between selection of card decks and
impulsivity. Our overall goal is to reveal the triggers of irrational
decision-making in normal people and how personality traits relate
to it. For this purpose, we used a computer version of IGT that
makes progressive changes in delayed punishment (the decks of this
new version are denoted as A’, B’, C’, and D’) [10]. Thisversion has
more drastic monetary changes than in the original version (the
original decks are denoted without dashes).
In experiment 1, we examined the relationship between beha-
vior in the gambling task and cognitive reflection or impulsivity
[22], sensation seeking [23–24] and trait anxiety [25–26]. In
experiment 2, we examined the relationship between behavior in
the gambling task and multiple personality traits (Neo-PI-R)
[27–28] and conducted a behavioral test of impulsivity, the
Matching Familiar Figure Test (MFFT) [29].
Results
Experiment 1
Card selection.
high-return choices (selections from deck A’ and deck B’)
Consistent with previous findings, high-risk/
PLoS ONE | www.plosone.org1 February 2010 | Volume 5 | Issue 2 | e9368

Page 2

decreased across trials. We defined 20 card selections to be 1 block
and conducted a one-way repeated measure ANOVA with the
mean of high-risk selections in one block as the dependent
variable. The participants became cautious and began to avoid the
risk-taking choices (F(3.42, 191.5)=25.71, P,0.01) (Bonferroni;
block 1.2.3=4=5) (Fig. 1A). However, close analysis of
selections from deck A’ and deck B’ revealed a notable
difference. As shown in Fig. 1B, selections from deck A’ mono-
tonously decreased as trial progressed (F(3.22,180.4)=17.40,
P,0.01) (Bonferroni; block 1.3, 4, 5; block 2.4, 5; block
3.5). On the other hand, selections from deck B’ initially
decreased but did not decrese towards the end of the experiment
(F(3.24, 181.4)=8.42, P,0.01) (Bonferroni; block 1.2, 3, 4, 5)
(Fig. 1C). Overall, a decrease in selections from deck B’ was not
apparent. In addition, the standard deviations of the number of
selections from deck B’ became larger in the latter half of the trials.
This result shows that some participants repeatedly selected cards
from deck B’ while others stopped selecting from this deck.
Card selection from deck B’.
gain and loss of deck B’ equaled that of deck A’, deck B’ contained
six cards that indicated extraordinarily big losses (Fig. 2A). Thus,
we focused on the relationship between personality traits and
behavior of making the choice of deck B’. Fig. 2B shows the results
of a trial-by-trial analysis based on a big loss from deck B’. The
figure plots the number of intervening trials between participant
experiencing big loss from deck B’ and subsequent selection from
the same deck B’ as a function of the number of big losses due to
the deck B’ selections. A big loss was defined as losing more than
100,000 Japanese yen (about 1000 US dollars). As shown in the
figure, the number of intervening trials decreased as the number of
big losses increased. That means participants who experienced
multiple big losses tended to repeat selection from the same risky
deck after a short interval.
Personality and ‘‘lose-persistent’’ behavior.
data presented in Fig. 2B, we tentatively divided participants into
two subgroups: a lose-persistent group numbering 20 participants
and a lose-resistant one numbering 23. The lose-persistent
subgroup experienced big losses more than three times when
selecting from deck B’. In contrast, the lose-resistant subgroup
experienced big losses less than three times. The results are shown
in Fig. 3. The participants in the lose-persistent subgroup showed
significantly higher scores of cognitive reflectivity than those
in the lose-resistant subgroup (t(41)=2.08, P,0.05) (Fig. 3A).
There was no systematic difference as to sensation-seeking score
(t(41)=0.739, P=0.464) (Fig. 3B). The lose-persistent subgroup
showed significantly lower scores in trait anxiety in comparison
with the lose-resistant subgroup (t(41)=2.00, P=0.052) (Fig. 3C).
Although the total monetary
Based on the
Experiment 2
Risky selection.
reproduced in a separate sample of participants (Fig. S1). Similar
to the results of experiment 1, some participants persisted in
selecting cards from deck B’ after big losses. Fig. S2 shows the
results of a trial-by-trial analysis of selections from deck B’. If
participants experienced big losses only once or twice, they did not
choose a card from this deck again after about 4.6 trials. On the
other hand, participants who experienced big losses 4 or 5 times
selected from the deck B’ after making a few more selections from
other decks (or even as their next selection).
Impulsiveness and risky selection: results of MFFT.
divided participants into two subgroups as in the first experiment.
The lose-resistant subgroup (n=11) experienced big losses only once
or twice, while the lose-persistent subgroup (n=13) experienced big
losses more than three times. Fig. 4 shows the mean scores of the
The results of experiment 1 were completely
We
matching familiar figures test (MFFT) together with the standard
deviations in each subgroup. The lose-persistent subgroup members
were more impulsive than those in the lose-resistant subgroup in this
test (t(22)=2.12, P,0.05).
Personality and risky selections: results of NEO-PI-R.
NEO-PI-R consists of five domains. Each domain contains six
subscales. Of the total of 30 subscales, four showed significant
differences between participants in the lose-persistent and lose-
resistant subgroups. Thesubscales
(Fig. 5A), fantasy (Fig. 5B), aesthetics (Fig. 5C), and deliberation
(Fig. 5D). Participants in the lose-persistent subgroup were more
were self-consciousness
Figure 1. Mean number of high-risk/high-return choices across
trials along with standard deviations. A total of 100 trials were
divided into 5 blocks of 20 trials. The total number of selections from
deck A’ and deck B’ decreased across trials (A). Selections from deck A’
monotonously decreased (B). However, selections from deck B’ initially
decreased but later did not decrease. (C). Moreover, towards the end of
the IGT, the deviations became larger regarding selections from deck B’.
doi:10.1371/journal.pone.0009368.g001
Big Losses
PLoS ONE | www.plosone.org2February 2010 | Volume 5 | Issue 2 | e9368

Page 3

deliberate (t(19)=2.14, P,0.05), less self-consciousness (t(19)=2.14,
P,0.05), less fantasy (t(19)=2.33, P,0.05) and less aesthetics
(t(19)=2.33, P,0.05) (Fig. 5). Other subscales did not show
significant differences. Correlation analysis confirmed this finding.
When we pooled data of all subjects and calculated Pearson’s
correlation coefficient between NEO-PI-R scores and the total
numberofhigh-riskchoices(sumofselectionsfromdecksA’and B’),
a significantnegativecorrelation between fantasysubscalesand high
risk selections (r=2.414, P,0.01) and a significant positive
correlation between deliberation subscales and high risk selections
(r=.375, P,0.05) were obtained (Fig. S3). Self-consciousness did
not yield significant correlations in this analysis.
Discussion
Experiment 1
In accordance with studies using the IGT in the traditional way
of summing the choices from the two high-risk decks, most
participants shifted their choices from risky ones to cautious ones
[9–10]. Therefore, the behavior of participants in the present
experiment was normal. Indeed, selections from deck A’ decreased
as the trials progressed. However, a big loss paradoxically worked
as a positive reinforcer in about 35 percent of the participants.
These participants successively selected cards from deck B’ as if
they wanted to experience big losses many times. These results
suggest that the phenomenon of ‘‘prominent deck B’’ appeared
even though the new versions of decks A’, B’, C’, and D’ were
used.
In the personality assessments, quite unexpectedly, cognitive
reflectiveness was significantly related to persistence in big losses in
experiment 1. Reflectiveness is thought to be the opposite of
impulsivity, and it is traditionally believed that impulsivity is
related to risk-taking behaviors [5]. The reason why reflective
persons tended to repeat risky choices is still unclear, but we feel
the concept of reflectiveness should be re-examined. Indeed, some
studies show that there is a discrepancy between reflection and
rumination [30–31]. Reflectiveness seems to be multi-dimensional
in nature.
There was no significant difference between groups as to
sensation seeking behavior in experiment 1. Because sensation
seeking is thought to be an important factor in addictive behaviors
Figure 2. A trial-by-trial analysis based on a big loss for deck B’.
(A) Comparison of losses in deck A’ and deck B’. In deck A’, loss cards are
drawn frequently, whereas in deck B’, loss cards are drawn infrequently,
but include 6 big loss cards. (B) Persistence in the face of big losses from
deck B’: Relationship between number of big losses as a result of
selecting from deck B’ and number of intervening trials before selecting
from the same deck B’ after a big loss. Some participants tended to
repeatedly select from deck B’ even as they experienced big losses.
doi:10.1371/journal.pone.0009368.g002
Figure 3. Personality traits of the lose-persistent and lose-resistant subgroups. (A) The lose-persistent subgroup had a higher cognitive
reflectivity score than that of the lose-resistant subgroup. (B) There was no difference between these two subgroups in sensation seeking. (C) The
lose-persistent subgroup showed a tendency of being less anxious than the lose-resistant subgroup. Statistical analysis was conducted using
Student’s t-test (two-tailed).
doi:10.1371/journal.pone.0009368.g003
Big Losses
PLoS ONE | www.plosone.org3 February 2010 | Volume 5 | Issue 2 | e9368

Page 4

[32–33], the present finding suggests that the difference between
lose-persistent and lose-resistant tendencies in might not directly
relate to addictive behavioral characteristics. The trait anxiety
score was lower in the lose-persistent subgroup in experiment 1.
This is consistent with the previous study showing that anxiety was
positively correlated with risk-avoidant decision-making [34].
However, anxiety and impulsivity are co-morbid of such mental
diseases as bipolar disorder [35], eating disorder [36], and
alcoholism [37]. There might be differences between clinical and
non-clinical samples.
Experiment 2
The behavioral data of the IGT was highly reproducible. In
general, risky choices decreased as the trials progressed in
experiment 2. However, approximately one third of the partici-
pants persisted in making risky choices from Deck B’.
Experiment 2 revealed a distinctive discrepancy between
behavioral impulsiveness and self-rated deliberation. Participants
who persisted in making risky choices had higher impulsiveness
scores in the MFFT test but higher deliberation scores in the
NEO-PI-R. Although we did not assess cognitive impulsivity using
the same rating scale as used in experiment 1, the NEO-PI-R
subscale deliberation acts as a substitute to the cognitive
reflectiveness scale.
MFFT is widely used to detect impulsivity in relation to mental
disorders such as attention deficit hyperactive disorder (ADHD) in
children [38] and substance-use problems [39]. However, it is still
controversial whether MFFT can detect impulsive personalities
[40–41].
The NEO-PI-R subscales of deliberation, self-consciousness,
and fantasy were related to persistence in making risky choices.
Persons who persisted in making risky choices would be deliberate,
less self- conscious, and less prone to fantasy. We speculate that the
repetition of risky choices is related to realistic logical thinking.
However, since we compared multiple items of NEO-PI-R
subscales by independent statistical tests, the finding should be
regarded as exploratory in nature. A more specific study on
personality traits related to risky choices would help to verify the
above speculation.
General Discussion
The experiments demonstrated that a self-rating of cognitive
reflectiveness or deliberation is related to persistence in making
high-risk/high-return choices. Moreover, these personality ten-
dencies were related to adherence to risk-taking choices after big
losses. However, the MFFT results showed that the persistence in
making risky choices was related to impulsiveness. Self-rating and
MFFT might thus detect different aspects of reflectiveness/
impulsivity. Self-rating is largely based on a person’s conscious
awareness of his or her own personality. On the other hand,
MFFT might detect an unconscious level of impulsivity because
study subjects were not informed that this test is used to assess
impulsivity. It could be that the IGT detects an unconscious level
of impulsivity. This notion is consistent with findings that the IGT
reflects the function of ‘‘somatic markers’’ that are primarily
autonomic bodily responses [9–10].
The next question is why unconsciously impulsive persons are
consciously deliberate. One possibility is that the logical thinking
leads to risky decision-making. A person may think that the loss is
so large that cautious card selection can not compensate the loss.
There is a report that might support this notion. In the IGT,
highly educated people ‘‘paradoxically’’ made impulsive choices
[42] and the choices made after a loss became riskier [43].
Another possibility is that experiencing a big monetary loss
inspires them about the possibility of subsequent big monetary
gain. For example, a previous study on video lottery terminals
showed that the possibility of a near win motivated people to
Figure 5. Subscales of NEO-PI-R that showed significant
differences between the lose-persistent and lose-resistant
subgroups. Compared with the participants in the lose-resistant
subgroup, those in the lose-persistent subgroup were more deliberate,
less self-conscious, and less fantasy prone (Student t-test, two-tailed).
doi:10.1371/journal.pone.0009368.g005
Figure 4. Scores of matching familiar figures test (MFFT) in the
lose-resistant and lose-persistent subgroups. The mean scores
and standard deviations are shown. The lose-persistent subgroup
tended to score higher than the lose-resistant subgroup.
doi:10.1371/journal.pone.0009368.g004
Big Losses
PLoS ONE | www.plosone.org4 February 2010 | Volume 5 | Issue 2 | e9368

Page 5

gamble despite the probability of monetary loss [44]. In our case,
the corresponding motivating behavior would be that participants
might speculate on the characteristics of the card decks and
imagine a big win.
In summary, it is thought that deliberate logical thinking
sometimes leads people to maintain risky decision-making
behaviors and proceed to addictive behaviors such as pathological
gambling in its final form. Further studies combining behavioral
and electrophysiological and/or biochemical measurements would
help to clarify the ‘‘paradoxical’’ correlation between unconscious
impulsivity and conscious deliberation.
Methods
Participants
Normal healthy volunteers participated in the experiments
(experiment 1: 57 college students: 23 males and 34 females;
experiment 2: 44 college students: 21 males and 23 females). They
had no history of alcohol or substance use and had been diagnosed
free from any kind of mental disease. They were told about the
ethical considerations before entering the study, and written
informed consent was obtained from each of them. This study was
conducted in accordance with the ethical code of the Japanese
Psychological Society.
Experimental Setting
The IGT developed by Bechara et al. (2000) was implemented
on a personal computer [10]. We developed a Japanese version of
the IGT, by converting $ to ¥ (Table S1). The number of trials
(100) was the same as in the original version of IGT.
Personality Assessment
In experiment 1, three kinds of personality traits were assessed:
cognitive reflexivity/impulsivity [22], sensation seeking [23–24],
and anxiety [25–26]. In experiment 2, the behavioral aspect of
reflexivity/impulsivity was assessed by means of MFFT [29]. We
used NMFFT, the more difficult version, for adults, in Japanese.
NEO-PI-R was used as a measure of comprehensive personality
assessment [27–28].
Procedure
All experiments and personality assessments were conducted
individually. Participants were invited to an experimental room
and explained the aim and ethical considerations of study, one
person at a time. They sat comfortably on a chair in the room and
were instructed on how to operate the computer version of the
IGT. Then, they were instructed to earn as much money as
possible. According to the standardized IGT procedure, 100 trials
were given. After completion of the IGT, personality assessments
were conducted.
Supporting Information
Figure S1
trials together with standard deviations in experiment 2. Total
number of selections from deck A’ and deck B’ decreased across
trials. The same tendency was apparent in experiment 1.
Found at: doi:10.1371/journal.pone.0009368.s001 (9.15 MB TIF)
Mean number of high-risk/high-return choices across
Figure S2
selecting from deck B’ and number of intervening trials before
selecting from the same deck after big loss from deck B’.
Participants tended to repeatedly select from deck B’ even as they
experienced big losses many times. The same tendency was
apparent in experiment 1.
Found at: doi:10.1371/journal.pone.0009368.s002 (2.88 MB TIF)
Relationship between number of big losses after
Figure S3
and B’ and score of fantasy scales (r=2.414, P,0.01)(A).
Relationship between sum of selections from deck A’ and B’ and
score of deliberation scales (r=.375, P,0.01)(B).
Found at: doi:10.1371/journal.pone.0009368.s003 (0.15 MB TIF)
Relationship between sum of selections from deck A’
Table S1
by converting $ to ¥ in Bachara et al., 2000.
Found at: doi:10.1371/journal.pone.0009368.s004 (1.13 MB TIF)
Net score of deck A’, B’, C’, and D’. These scores were
Acknowledgments
We are grateful to Dr. Kosuke Sawa (Senshu University), Dr. Seiji
Yamagami (Senshu University), and Dr. Shinsuke Shimojo (California
Institute of Technology) for their very valuable suggestions.
Author Contributions
Conceived and designed the experiments: YT NT DT NH. Performed the
experiments: YT DT. Analyzed the data: YT. Wrote the paper: YT NH.
Developed a Japanese version of the IGT: NT.
References
1. Hinson JM, Jameson TL, Whitney P (2003) Impulsive decision making and
working memory. J Exp Psychol Learn Mem Cogn 29: 298–306.
2. Crean JP, de Wit H, Richards JB (2000) Reward discounting as a measure of
impulsive behavior in a psychiatric outpatient population. Exp Clin Psycho-
pharmacol 8: 155–162.
3. Bickel WK, Odum AL, Madden GJ (1999) Impulsivity and cigarette smoking:
delay discounting in current, never, and ex-smokers. Psychopharmacology (Berl)
146: 447–454.
4. Richards JB, Zhang L, Mitchell SH, de Wit H (1999) Delay or probability
discounting in a model of impulsive behavior: effect of alcohol. J Exp Anal Behav
71: 121–143.
5. de Wit H (2009) Impulsivity as a determinant and consequence of drug use: a
review of underlying processes. Addict Biol 14: 22–31.
6. Kirby KN, Petry NM (2004) Heroin and cocaine abusers have higher discount
rates for delayed rewards than alcoholics or non-drug-using controls. Addiction
99: 461–471.
7. Petry NM (2002) Discounting of delayed rewards in substance abusers:
relationship to antisocial personality disorder. Psychopharmacology (Berl) 162:
425–432.
8. Monterosso J, Ehrman R, Napier KL, O’Brien CP, Childress AR (2001) Three
decision-making tasks in cocaine-dependent patients: do they measure the same
construct? Addiction 96: 1825–1837.
9. Bechara A, Damasio AR, Damasio H, Anderson SW (1994) Insensitivity to
future consequences following damage to prefrontal cortex. Cognition 50: 7–15.
10. Bechara A, Tranel D, Damasio H (2000) Characterisation of the decision-
making deficit of patients with ventromedial prefrontal cortex lesions. Brain 123:
2189–2202.
11. Fujiwara E, Schwartz ML, Gao F, Black SE, Levine B (2008) Ventral frontal
cortex functions and quantified MRI in traumatic brain injury. Neuropsycho-
logia 46: 461–474.
12. Clark L, Manes F, Antoun N, Sahakian BJ, Robbins TW (2003) The
contributions of lesion laterality and lesion volume to decision-making
impairment following frontal lobe damage. Neuropsychologia 41: 1474–1483.
13. Adida M, Clark L, Pomietto P, Kaladjian A, Besnier N, et al. (2008) Lack of
insight may predict impaired decision making in manic patients. Bipolar Disord
10: 829–837.
14. Smoski MJ, Lynch TR, Rosenthal MZ, Cheavens JS, Chapman AL, et al. (2008)
Decision-making and risk aversion among depressive adults. J Behav Ther Exp
Psychiatry 39: 567–576.
15. Haaland VØ, Landrø NI (2007) Decision making as measured with the Iowa
Gambling Task in patients with borderline personality disorder. J Int
Neuropsychol Soc 13: 699–703.
16. Shurman B, Horan WP, Nuechterlein KH (2005) Schizophrenia patients
demonstrate a distinctive pattern of decision-making impairment on the Iowa
Gambling Task. Schizophr Res 72: 215–224.
17. Schilt T, Goudriaan AE, Koeter MW, van den Brink W, Schmand B (2009)
Decision making as a predictor of first ecstasy use: a prospective study.
Psychopharmacology (Berl) 203: 519–527.
Big Losses
PLoS ONE | www.plosone.org5February 2010 | Volume 5 | Issue 2 | e9368