To Investigate Role of Impulsivity, Reward and Loss of Sensitivity in Decisions Making during Gambling Task: An Empirical Study

To Investigate Role of Impulsivity, Reward and Loss of

Sensitivity in Decisions Making during a Gambling Task:

An Empirical Study

GYAN PRAKASH (3570810095)

In partial fulfillment for the award of the degree

BACHELOR OF ENGINEERING

COMPUTER SCIENCE AND SOFTWARE ENGINEERING

Department of Humanities and Social Sciences,

Indian Institute of Technology Bombay



An Empirical Study

A PROJECT REPORT

Submitted by

GYAN PRAKASH (3570810095)

In partial fulfillment for the award of the degree

BACHELOR OF ENGINEERING

In


At

At

Prepared at

2012

JJJiiiiii

July 2012

Psychophysiology Lab,


Indian Institute of Technology Bombay




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BONAFIDE CERTIFICATE

Certified that this project report titled

Sensitivity in Decisions Making during a Gambling Task: An Empirical Study

bonafide work of Gyan Prakash

Engineering to the Vinayaka Missions University, Aarupadai Veedu Institute of Technology,

OMR Paiyanoor-603104, Kancheepuram, Distt(Tamilnadu) who carried out the project work

under my supervision.

Place: Mumbai

Date: 04/07/2012

BONAFIDE CERTIFICATE

Certified that this project report titled To Investigate Role of Impulsivity, Reward and Loss of

Decisions Making during a Gambling Task: An Empirical Study

bonafide work of Gyan Prakash ( Reg No. 3570810095) B.E, Computer Science & Software

to the Vinayaka Missions University, Aarupadai Veedu Institute of Technology,

603104, Kancheepuram, Distt(Tamilnadu) who carried out the project work

Dr. Azizuddin Khan

Project Supervisor

Assistant Professor



Indian Institute of Technology, Bombay,

Powai-400076, Mumbai

II


Decisions Making during a Gambling Task: An Empirical Study is the

B.E, Computer Science & Software

to the Vinayaka Missions University, Aarupadai Veedu Institute of Technology,

603104, Kancheepuram, Distt(Tamilnadu) who carried out the project work

Dr. Azizuddin Khan

Project Supervisor

Assistant Professor



Indian Institute of Technology, Bombay,

400076, Mumbai

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ACKNOWLEDGEMENT

Dedicating this project to the Almighty God whose abundant grace and mercies enabled

its successful completion, we would like to express our profound gratitude to The Dean

(Research & Development), Dr. Prof. Rangan Banerjee of Industrial Research and

Consultancy Center of Indian Institute of Technology Bombay who gave me an opportunity to

make this project a success.

It has been an honor for me to work under the extremely able guidance of Dr. Azizuddin

Khan, Assistant Professor. It goes beyond saying that his gregarious knowledge, guidance,

living interest, constructive criticism and kind consideration were instrumental during the entire

course of my project work and its successful completion.

Words fail to express my gratitude to our Project Mentor Miss Mohita Junnarkar, for

helping and supporting me with valuable suggestions and timely advices throughout the tenure of

our project work. In pursuit of this academic endeavor I feel that I have been especially fortunate

as she has been my inspiration and a proper guidance.

I am also very thankful to Miss Madhura Sohani Research assisstant for her unswerving

assistance and suggestions which helped me during my project and gives it a better finish.

I would like to take the opportunity to thank Mrs. Purnima Bajre for her constant

encouragement and support throughout, which always inspired me.

We would like to express my gratitude to our Principal Dr. N.R. ALAMELU for

providing me with all the required facilities without which the project would not have

been possible.

We wish to express our sincere thanks to our Head of Department, Prof. P.T.

SIVASANKAR for providing an opportunity to undertake this project & granting his

kind consents for carrying out our suggested project.

We extend our deep sense of gratitude to our Faculty Advisor Prof. R.

VISALATCHI Senior Lecturers of Computer Science and Engineering Department for

their valuable guidance as well as timely advice, which helped us a lot in completing the

project successfully.

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ABSTRACT

Objective: The aim of the current study is to understand impulsivity, reward and loss sensitivity

in decision making using Iowa Gambling Task and investigate how impulsivity affects decision-

making using BIS/BAS scale. We investigate how the personality trait determines decision

making using NEO-FFI scale. Method: We assessed 130 participants for conducting two types

of experiment (1) Choice behavior Test is conducted with the help of Iowa Gambling Task (IGT)

on the computer screen.(2) Personality Test is conducted with the help of Behavior Inhibition

system and Behavior Approach System (BIS/BAS), NEO-FFI( NEO-Five Factor Inventory)

scale and Rational Experiential Inventory (REI) .Results The result indicated that participants

who were low on impulsivity fared worst on IGT task compared to the participants who were

high on impulsivity. Similar results were demonstrated for personality traits and information

processing styles. The results imply that personality traits determine decision making process.

Similarly information processing styles evaluate preferences for information processing that

determine the decisions making and Impulsivity affects decision making.

Keywords- Decisions Making, Impulsivity, Iowa Gambling Task, Personality and Information

Processing Style.

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CHAPTER NO TABLE OF CONTENTS PAGE NO

TITLE I

BONAFIDE II

ACKNOWLEDGEMENT III

ABSTRACT IV

LIST OF FIGURES VI

LIST OF ABBREVIATIONS

1 INTRODUCTION 1

2 LITERATURE REVIEW 5

3 METHODLOGY 10

4 RESULT AND DISCUSSIONS 18

5 COCLUSIONS 26

6 REFFERENCES 27

7 APPENDIX

A. DESCRIPTIVE ANALYSIS WITH BLOCK WISE 29

B. DESCRIPTIVE ANALYSIS WITH DECK WISE 31

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LIST OF FIGURES PAGE NO.

Iowa Gambling Task Screenshot 13

Relation between BIS/BAS, NEO-V & REI Scale with Block Wise 22

Relation between BIS/BAS, NEO-V & REI Scale with Deck Wise 23

LIST OF TABLES PAGE NO.

Correlation Analysis 19

LIST OF ABBREVATIONS

IGT-Iowa Gambling Task

BIS-Behavior Inhibition System

BAS-Behavior Approach System

NEO-V –NEO-Five Factor Inventory Scale

REI-Rational Experiential Inventory Scale

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CHAPTER 1

INTRODUCTION

1.1 GENERAL:

Decision Making:

In day to day life, an individual has to decide between options that have immediate

consequences and delayed consequences. The decision to opt for immediate or delayed

reward is strongly related to professional success in life. For example; one student might

decide to go for a party on a given day, or stay at home to study for exam that is scheduled

next day. In order to function effectively, one has to postpone immediate, in favor of long

term positive outcomes in the future.

Decision making involves the outcome of cognitive processes leading to a choice between

alternative courses of action. Poor decision making has been described as “deciding against

one's best interests and inability to learn from previous mistakes, with repeated decisions

leading to negative consequences” (Bechara and Damasio, 2005).

Impulsivity and Decisions Making:

Impulsivity is a personality trait of an individual to initiate behavior without adequate

forethought and lack of foresightedness for momentary gains at a particular point of time.

Impulsivity tends to risk-taking, lack of planning, and making up one's mind quickly. There

are 3-factor model according to impulsivity Attentional ("getting easily bored"), motor

("going into action") and cognitive ("inability to plan") factors. Impulsive individuals have

increased reward sensitivity and reduced punishment sensitivity, reflected by their lowered

negativity during loss and enhanced positivity during win.

Impulsive decision-makers are those who operate on the far end of the decision-making

continuum. Impulsivity has been found to be related to a variety of antisocial behaviors,

delinquency, and a lack of social adjustment. High impulsivity shows weakness in learning of

reward and punishment association, in order to make appropriate decisions. This hyperactive ww

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BAS and hypoactive BIS may result into disadvantageous and risky decision making,

concentrating more on prospective rewards than punishments. .

The system mediates anxiety, and it is activated by goal conflicts of all kinds paradigmative

between approach and avoidance is re-offered as the Behavioral Inhibition System. BIS is the

conceptual substrate for sensitivity to secondary aversive stimuli, and is the proposed causal

basis of anxiety. It is sensitive to: (a) conditioned stimuli associated with punishment, and the

omission or termination of reward (frustrative non reward), (b) extreme novelty, (c) innate

fear stimuli (e.g. snakes, dead bodies, etc.), and (d) high-intensity stimuli.

The BIS mechanism is through as a comparator, continuously scans the environment. It

checks predicted events against actual events and is able to stop programmed motor activity

by other systems if they do not match. The BIS produce behavioral inhibition (i.e.

interruption of ongoing behavior) and an increase in level of arousal and attention. The

purpose of the BIS is to suppress behavior that is expected to lead to punishment. The system

also modulates the control of exploratory behavior by diversified attention toward threat or

novel stimulus.

Impulsivity has been variously defined as swift action without forethought or conscious

judgement (Hinslie, 1940) or behavior without adequate thought (Smith, 1952). Implicit in all

definitions of impulsivity are the two key features. First, impulsivity involves action. Second,

impulsivity involves lack of planning. The method of determining whether the action was

truly unplanned in two of the definitions above is to look at the outcome of the action, with

poor planning being associated with long-term losses in spite of short-term gains.

Personality and Decision Making:

Personality is commonly defined as “the sum total of all the behavioral and mental

characteristics by means of which an individual is rewarded as being unique”. Personality

type paradigm of the thinking (T) / and feeling (F) preference dichotomy has the most

significant influence on the decision making process. A preference for the thinking (T)

function constitutes an objective impersonal approach to decision making while a preference

for the feeling (F) function constitutes a subjective values driven approach. Sensing and

Thinking focus on past experience, and objective, tangible/ concrete data. The sensing (S)/

and intuition (N) preference dichotomy is the second factor that comes into play in the ww

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decision making process. Individuals with a preference for sensing (S) focus on past

experience and tangible / concrete criteria when confronted with decision making and

problem solving while those with a preference for intuition (N) focus on future possibilities

and broad, general issues. Personality types with a preference for intuition (N) and thinking

(T) utilize objective criteria while focusing on future directed broad concepts and

possibilities. Personality types with a preference intuition (N) and feeling (F)

utilize subjective criteria and focus on future directed broad concepts and possibilities.

Individuals with a preference for the perceiving (P) attitude want to continue to take in

information and defer decision making in an effort to acquire additional information. While

those with a preference for judging (J) want to take in data and come to closure as quickly as

possible. Individuals with a preference for judging (J) are more at ease once a decision has

been made.

Information Processing Style and Decision Making:

Decision making is a fundamental process in organizations and the quality of the decisions

that managers make influences their effectiveness as managers. The effectiveness of

managers, in turn, impacts the success or failure of the organization. Rational models of

decision-making often ignore individual decision-maker characteristics and assume

individuals process information and arrive at a decision in a similar manner (Hambrick,

1987). These models ignore the actual decision process and how individual differences affect

that process (Bourgeois and Eisenhardt, 1988; Rajagopalan, Rasheed and Datta, 1993).

Observation of actual decision making situations indicates that decision-making behavior is

characterized by differences in many areas, including the number of criteria used, the type of

information search which is undertaken, sources of information used, the use of heuristics

and the number of alternatives generated (Eisenhardt and Zbaracki, 1992). An individual

characteristic which is often linked to differences in decision making behavior is the way in

which individuals process information, also termed as cognitive style. Cognitive style

depends on the way people process and organize information and arrive at judgments or

conclusions based on their observations (Hunt, Krzystofiak,Meindl and Yousry, 1989). These

styles are viewed as relatively stable dispositions which lead to differences in behavior in the

decision-making process (Shipman and Shipman, 1985).

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1.2 OBJECTIVE

The aim of the current study is to understand impulsivity, reward and loss sensitivity in

decision making using Iowa Gambling Task and investigate how impulsivity affects decision-

making using BIS/BAS scale. We investigate how the personality trait determines decision

making using NEO-FFI scale.

1.3 SCOPE

This project aims to investigate the reward and loss sensitivity in decisions making which

will be helpful to persons who are in financial investment for different long and short term

gains. It can also be used for academic areas while introducing different educational

programs keeping in mind the progress of the country. This work will also be useful to

differentiate between the decisions making process of normal individual and individual with

some abnormalities.

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CHAPTER 2

LITERATURE VIEW

Decisions Making:

The Iowa gambling task is a psychological task thought to simulate real-life decision making.

The Iowa Gambling Task is widely used in research of cognition and emotion. IGT is an

experimental design which is used for measurement of decisions making. A key feature of

this task is that participant has to forgo short term benefit for long term profit. A correlation

has been found between successful IGT performance and development of somatic marker

signal in healthy control participants. The SMH purpose that somatic marker signal biasing

from the body represented and regulated in emotion circuitry of the brain. Role of SMH is the

process of decisions making which is measured by performance on the IGT. It provides a

descriptive, non critical account of resolution of SMH and support IGT. It examines the

psychological component of the SMH critical approaches the extent to which IGT data can

validate the SMH. It raises and evaluates some further conceptual concerns about novelty and

parsimony of SMH.

Impulsivity and Decision making:

Impulsivity is a personality trait (quality of person) which is characterized by the inclination

of an individual to initiate behavior without adequate forethought and resultant action is the

consequence of momentary decision. In the psychological literature authors have defined

impulsivity as “the tendency to act with less forethought than do most individuals of equal

ability and knowledge” (Dickman, 1993 & Goudriaan et al., 2005), ‘‘choice of a small, short

term gain at the expense of a large, long term loss’’ (Ainslie, 1974) or “a predisposition

towards rapid, unplanned reactions to internal or external stimuli without regard to the

negative consequences of these reactions to the impulsive individual or to others while

BIS/BAS is measurement scale which measures the impulsivity. Impulsivity tends to risk-

taking, lack of planning, and making up one's mind quickly while The BIS and BAS exerts

two effects that are facilitators(careful planning) and other antagonist(to work against). Some

researchers have proposed a 3-factor model according to impulsivity; attentional ("getting easily

bored”)factors. While BIS produces behavioral inhibition (i.e. interruption of ongoing

behavior) and an increase in level of attention. When person shows impulsive behavior they

perform Positive urgency and Negative urgency while BIS and BAS reflected on ww

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electrochemical responses elicited by positive and negative feedback signals during a

learning task. In impulsivity as a personality trait, impulsivity is part of normal behavior as it

contributes to adaptive functioning while BIS/BAS has been purposed for understanding how

behavior and regulation mechanisms relate to personality and psychological dysfunction.

Impulsive decision-makers are those who operate on the far end of this decision-making

continuum while BIS/BAS people perform more risk and safe decisions making. Impulsive

decisions maker perform inclination of individual to initiate behavior as without

consequences of their actions in acting moment while BIS/BAS perform impulsivity in

appetitive stimuli and anxiety in aversive stimuli. High impulsivity shows weakness in

learning of reward and punishment association in order to make appropriate decisions the

high BAS and low BIS group made the most risky decisions. High impulsive subject display

overall deflect in their decisions making compare than low impulsive subject while High

BAS/Low BIS display more risk decisions compare than Low BAS/High BIS. Several

theorists have argued that two general motivational systems underlie behavior. A behavioral

approach system (BAS) is believed to regulate appetitive motives, in which the goal is to

move toward something desired. A behavioral avoidance (or inhibition) system (BIS) is said

to regulate aversive motives, in which the goal is to move away from something unpleasant.

This system mediates fear is activated by threatening stimuli and that need not be faced but

can simply avoided and has been referred to as Fight Fligh Freeze System (FFFS).This

second System which is activated by appetitive stimuli, mediates the emotion of anticipatory

pleasure, is referred as Behavioral Approach System This general goal of the study is to

differentiate the functions of BIS and BAS in human term of their underlying Cognitive

electro cortical mechanisms. The BIS and BAS have the potential to influence punishment

mediated and reward mediated behavior. BIS and BAS sensitivity has facilates the validation

of RST derived hypothesis to study of human behavior. Thus general goal is to differentiate

between the function of BIS and BAS in humans in terms of their underlying cognitive and

electro cortical mechanisms. Mainly we sought to evaluate how individual difference in BIS

and BAS reflected on electrochemical responses elicited by positive and negative feedback

signals during a learning task. The function of BIS and BAS has been purposed within

neuropsychological framework for understanding how behavior and regulation mechanisms

relate to personality and psychological dysfunctions. The BIS and BAS exerts two effects that

are facilitators and antagonist. BAS facilates where as BIS antagonize the process of reward ww

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Stimuli. High BAS/LOW BIS individual should display the highest appetitive response and

positive emotions of these stimuli. Similarly BIS facilates BAS antagonize the process of

punishment Stimuli. High BIS /Low BAS individual should show the highest aversive

response and negative emotions to these stimuli. General factor of personality is Correlating

with measures of the behavioral Inhibition System (BIS), Behavioral Activation System

(BAS), generalized expectancies of reward and punishment.

Personality and Decisions Making:

Personality, defined as .the relatively stable behavioral patterns and attitudes of a given

individual (Costa and McCrae, 1985), is likely to play an important role in decision making.

While personality was briefly alluded to in Lazarus and Folkman’s (1984) transactional stress

model as a determinant of primary appraisal, more attention needs to be given to the types of

personality dispositions that make some people more vulnerable to certain stressors and

others less so. Personality is a wide-reaching concept and it is possible that only some

dimensions are likely to be relevant.

The Five Factor Model of personality (Costa and McCrae, 1987) describes personality as

containing five factors, defined as dimensions of individual differences that consistently show

themselves in actions, thoughts and emotions. The five factors are extroversion, neuroticism,

Openness to experience, conscientiousness and agreeableness. Extroversion is the tendency

towards positive feelings, excitement and friendliness. Neuroticism is another personality

factor and it is the tendency to experience negative emotions such as anxiety, emotional

stability and Impulse control.Research generally agrees that neuroticism has a negative

correlation with IQ scores (Furnham et al, 2007; Ackerman and Heggestad, 1997). Openness

to experience is the disposition to pay attention to beauty, abstract ideas, and liberalism.

Baker and Bichsel (2006) found that openness to experience correlates with intellectual

abilities at different stages of life. Other research has confirmed the positive relationship

between intellectual abilities and openness to experience (Furnham et al, 2007; Ackerman

and Heggestad, 1997). Conscientiousness involves self-discipline, achievement-striving, and

cautiousness. An extensive metanalysis showed that conscientiousness has no correlation

with measures of general intelligence, but that it does correlate negatively with measures of

math and general knowledge (Ackerman and Heggestad, 1997). Other researchers have found ww

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that non conscientious tend to do better in IQ tests (Furnham et al). Lastly, agreeableness

refers to qualities such as altruism, trust and compliance.

The meta analysis mentioned earlier found absolutely no correlation between agreeableness

and any measure of intellectual ability (Ackerman and Heggestad, 1997). In summary, it is

generally agreed that extroversion has an existing relationship with intellectual abilities, but

its direction seems to depend on the kind of test being used. Openness to experience is

generally positively correlated with intellectual abilities, while neuroticism is negatively

correlated with IQ. The relationship with conscientiousness is generally negative or non-

existing, and the relationship with agreeableness is non-existing. The review of articles shows

that there is an existing relationship between personality and intellectual abilities. Yet, no one

can tell which personality traits allow a person to behave more intelligently (or engage in

useful behavior) as opposed to score higher on IQ tests.

This study will examine the mediating or moderating effect of personality (particularly

conscientiousness, neuroticism and openness to experience) in the relationship between

intellectual abilities and intelligent behavior. Indeed, these scales have been used to show that

the Five-Factors are relatively enduring, evident in a wide range of behaviors, present across

age, gender, race, culture and language, and are possibly biologically and hereditarily based

(Costa and McCrae, 1992a). Further, support for the Big-Five has come from researchers of a

variety of theoretical orientations, and links have been established with major personality

instruments (Buss, 1996).

GFP occupies the apex of the hierarchy in a similar way as general factor of mental ability

occupies the apex in the organization of cognitive abilities. A GFP has now been extracted

from inter-scale correlations of several sets of the Big Five Inventory (BFI). It found high

score on GFP were related to self-esteem and positive effect and low score to negative effect.

BIS is the aversive motivational system that controls the experience of anxiety and negative

feelings such as Fear, Frustrations, and Sadness, and is sensitive to signals of punishment,

and novelty. BAS is the behavioral activation system causing movement towards goals and

result in feelings such as Hope, Elation and Happiness. GFP will correlate positively with

measures of BAS, self-esteem, positive affect and generalized expectancy of reward, and

correlate negatively with measures of BIS, negative effect, and generalized expectancy of ww

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punishment. The GFP was measured using the Big Five Inventory (BFI) is such as BIS/BAS

scale, Generalized Reward and Punishment Expectancy Scales, Single-Item Self-Esteem

Scale; Positive and Negative Affect Schedule (PANAS).

Information processing Style and Decisions Making:

A great deal of the Artificial Intelligence literature on autonomous artificial agents concerns

the representation and properties of several motivational states (e.g., goals, intentions and

commitments) and relate them to the agent’s overt behavior (Cohen and Levesque, 1990),

(Rao and Georgeff, 1991), (Singh, 1991), (Konolige and Pollack, 1993). However, the

mentioned literature doesn’t address the relationship between motivation and information

processing. This constitutes a serious drawback since agents built or defined within this

approach have no easy way of saying "That’s enough of processing!” If they have a large

body of cognitive structures relevant to some decision problem, they are committed to use

them all - they can’t escape.

The relationship between motivation and information processing has been one of the major

concerns in the literature on cognitive social psychology (Srull and Wyer, 1986),

(Pyszczynski and Greenberg, 1987), (Forgas, 1994), (Baumeister and Newman, 1994). It is

even becoming a central issue in neurology (Damásio, 1994). Nevertheless, this relationship

has not been explained with the computational level of detail required for Artificial

Intelligence purposes.

Hence, there is still a lot to be done along the integration of motivational factors within

cognitive models of information processing.. The extended model is called COMINT

(Cognition and Motivation Integration model of decision making). Traditionally, motivation

is viewed as a conscious and volitional process. COMINT represents an hypothesis regarding

possible automatic aspects of motivate

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CHAPTER 3

METHODLOGY

Participants:

Sample:

One hundred Thirty (130) participants visited the Psychophysiology Laboratory at IIT

Bombay individually to take part in the experiment. There were 101 males and 29 females

participants in this study. The mean age of male participants (Mean age=25.14 years,

SD=4.52 years) and female participants (Mean age=27.00 years, SD=6.87 years). The

participants educational level was three percent (5%) undergraduate (student had a high

school diploma or some college), thirty percent (33%) graduate (had a bachelor’s degree and

sixty seven percent (62%) post-graduate (had Master degree or pursing PhD).

Design:

5 (Block: Block1 (Trials 1-20) v/s Block2 (Trials 21-40) v/s Block3 (Trials 41-60) v/s Block4

(Trials 61-80) v/s Block5 (Trials 81-100)) X 2 (Impulsivity: High v/s Low) X 5 (Personality:

Neuroticism v/s Extroversion v/s Openness v/s Agreeableness v/s Conscientiousness) X 2

(Rational v/s Experiential)

Materials:

Iowa Gambling Task:

The Iowa Gambling Task (IGT) was originally developed as a card game by Bechara et al.

(1994). Here, we used a computerized version 1.00(1.00.029). There are four decks of cards

namely; A, B, C, and D. There were 100 trials in this task that lasted for 12 minutes. Here

two types of indicator bar such as green bar which indicates subject winning and losing

condition and red bar indicates borrow amount means how much money borrow subject for

performing task Subjects have to develop a long-term and profitable monetary scenario in a

situation of uncertainty and a conflict between the chance of encountering an immediate

reward. No information was given prior to the task on the task features, task duration or the

number of trials except for the task objective is win much more money as much possible and

avoid losing money.

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Performance on the IGT was operationalized in three ways: Advantageous deck,

Disadvantageous deck, and NET score. The advantageous deck was calculated by summation

of Deck A and B (A+B) in overall 100 trials and disadvantageous deck was calculate by

summation of Deck C and D (C+D) in overall 100 trials.

Net score was calculated as the difference between advantageous deck and disadvantageous

decks, with the latter being subtracted from the former. Net score can be thought of as a

measure of overall performance, integrating sensitivity to gains and losses. Thus, if a

participant were presented with advantageous decks (Decks C or D) on 20 trials during

Block1 and chose to play 3rd times Deck A, 4

th times Deck B , 8th times Deck C and 5th

Times Deck D , his or her Advantageous Deck play Score would be 13. If the same

participant were presented with the disadvantageous decks (Decks A or B) on 20 trials during

the same Block1 3rd times Deck A, 4

th times Deck B, 8th times Deck C and 5th Times Deck

D, his or her Advantageous Deck play Score would be 7. The net score for this participant

would be percentage Advantageous Deck plays (13), Disadvantageous Deck play (7),

yielding a net score of 6 for 20 trials in Block 1. The Net Score is calculate as [Deck(C+D)-

(A+B)]. The Net score was calculated for 20 trials for all five blocks as well.

Behavioral Inhibition System/Behavioral Approach System Scale (BIS/BAS):

Behavior Inhibition System/Behavioral Activation System Scale (Carver, C. and White, T.,

1994) is used for assess the individual differences in the sensitivity of these systems. A behavioral

avoidance (or inhibition) system (BIS) is said to regulate aversive motives, in which the goal is

to move away from something unpleasant. BIS/BAS Scale is 20-item questionnaire which

scales are classified in four type subscales such as BAS Drive, BAS Fun Seeking, BAS

Reward Responsiveness, and BIS or Punishment Sensitivity. Its Alpha coefficient (ά=0.67).

Each item of this questionnaire is a statement that a person may either agree with or disagree

with. For each item, the participants were requested to indicated how much you agree or

disagree with the item. It is a four point Likert type scale. The participants had to rate their

response from “very true for me =1” to “very false for me = 4”. It has potential influence

punishment mediated and reward mediated behavior. BAS is activated by appetitive stimuli

and mediates the emotion of anticipatory pleasure is referred as Behavioral Approach System

BAS is the conceptual substrate for sensitivity to secondary appetitive stimuli, and is the

proposed causal basis of impulsivity. It is sensitive to: (a) conditioned stimuli associated with ww

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reward, and (b) conditioned stimuli associated with the termination/omission of punishment.

The purpose of the BAS is to initiate exploratory, approach behavior that brings the organism

closer to final biological reinforces (e.g. food, sexual partners, etc.). Individuals with an

overactive BAS are more susceptible to impulsivity.

The BIS and BAS have the potential to influence punishment mediated and reward mediated

behavior. The BIS and BAS exert two effects that are facilitators and other antagonist. More

particular BAS facilates BIS antagonize the process of reward Stimuli. High BAS/LOW BIS

individual should display the highest appetitive response and positive emotions of these

stimuli. Similarly BIS facilates BAS antagonize the process of punishment Stimuli. High BIS

/Low BAS individual should show the highest aversive response and negative emotions to

these stimuli. Mainly we sought to evaluate how individual difference in BIS and BAS

reflected on electrochemical responses elicited by positive and negative feedback signals

during a learning task. Several theorists have argued that two general motivational systems

underlie behavior. A behavioral approach system (BAS) is believed to regulate appetitive

motives, in which the goal is to move toward something desired. A behavioral avoidance (or

inhibition) system (BIS) is said to regulate aversive motives, in which the goal is to move

away from something unpleasant. Several theorists have argued that two general motivational

systems underlie behavior. A behavioral approach system (BAS) is believed to regulate

appetitive motives, in which the goal is to move toward something desired. A behavioral

avoidance (or inhibition) system (BIS) is said to regulate aversive motives, in which the goal

is to move away from something unpleasant.

BAS subscale: there are three aspects of BAS that were tapped in this scale; namely BAS

Drive, BAS Fun Seeking and BAS Reward Responsiveness.

• BAS Drive Subscale: This scale includes 4 items that focus on the pursuit of desired

goals. Its Alpha coefficient (ά= 0.51). Statements such as “I go out of my way to get

things I want” and “When I go after something I use a "no holds barred" approach”

tapped this measure.

• BAS Fun Seeking: This scale has 4 items focusing on a desire for new rewards and a

willingness to approach a potentially rewarding event on the spur of the moment. Its

Alpha coefficient (ά= 0.34). Statements such as “I'm always willing to try something ww

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new if I think it will be fun” and “I crave excitement and new sensations” tapped this

measure.

• BAS Reward Responsiveness: This scale has 5 items pertaining to positive responses

to the anticipation or occurrence of reward. Its Alpha coefficient (ά= 0.63).

Statements such as “When I'm doing well at something I love to keep at it” and

“When I see an opportunity for something I like I get excited right away.” tapped this

measure.

BIS or Punishment Sensitivity Subscale: This scale has 7 items referencing reactions to the

anticipation of punishment. Its Alpha coefficient (ά= 0.42). Statements such as “Even if

something bad is about to happen to me, I rarely experience fear or nervousness” and “I feel

pretty worried or upset when I think or know somebody is angry at me” tapped this measure.

NEO-Five Factor Inventory (NEO-FFI) Scale:

NEO-Five Factor Inventory (NEO-FFI) scales (Costa, P. T., and McCrae, R. R., 1992) is a

self-report inventory scale. The NEO-FFI can help you understand an individual's basic

emotional, interpersonal, experiential, attitudinal, and motivational styles. It also can help you

quickly develop rapport with the examinee, provide meaningful feedback and insight that will

help your client develop a greater self-understanding, enable you to anticipate the course of

therapy, and help you select the optimal treatment based on his or her personality.

NEO-FFI Scale is 60- item questionnaire (ά=0.51) that has subscales such as Neuroticism,

Extroversion, Openness, Agreeableness, and Conscientiousness. The participants could agree

with or disagree with each statement. For each statement, the participants could indicate how

much they agreed or disagreed with statement on a 5 point Likert type scale. The participants

had to rate their response from “Strongly Agree =5” to “Strongly Disagree= 1”.

• Neuroticism Subscale (ά=0.70): This scale included 12-items that tapped the

negative affect and self-reproach. Statements such as “I am not a worrier.”, and “I

often feel tense and jittery.” tapped this measure

• Extraversion Subscale (ά=0.54): This scale has included 12-items which are

characterized by positive affect, sociability and activity. Statements such as “I laugh

easily.”, “I usually prefer to do things alone.” and “My life is fast-paced.” tapped this

measure. ww

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• Openness subscale (ά= 0.43): This scale has included 12-items which are

characterized by aesthetic interest, intellectual interest, unconventionality and

activity. It is referred to as Culture because of its emphasis on intellectualism, polish,

and independence of mind and Intellect because of its emphasis on intelligence,

sophistication, and reflection. Statements such as “Poetry has little or no effect on

me”, “I usually prefer to do things alone”, “I have a lot of intellectual curiosity”, “I

believe letting students hear controversial speakers can only confuse and mislead

them” and “I often try new and foreign foods” tapped this measure.

• Agreeableness Subscale (ά=0.58): This scale has included 12-items which are

characterized by nonantagonistic orientation and prosocial orientation. It can also be

seen as a combination of friendliness and compliance. Statements such as “I often get

into arguments with my family and co-workers” and “Most people I know like me”

tapped this measure.

• Conscientiousness subscale (ά=0.76): This scale has included 12-items which are

characterized by orderliness, responsibility, and dependability. Statements such as “I

keep my belongings clean and neat”, “I have a clear set of goals and work toward

them in an orderly fashion” and “Sometimes I’m not as dependable or reliable as I

should be” tapped this measure.

Rational Experiential Inventory (REI Scale)

REI Scale (Pacini, and Epstein, 1999) is a self-report inventory that assesses rational and

experiential thinking styles. The rational scale measures engagement in and favorability of

cognitive activities and corresponds to rational analytic thinking. The rational scale has been

found to be positively associated with openness, conscientiousness and favorable basic

beliefs, and negatively associated with neuroticism and conservatism (Pacini and Epstein,

1999). The experiential scale measures engagement in and favorability of intuitive activities

and corresponds to experiential-intuitive thinking. The Experiential Scale has been found to

be positively associated with extraversion, agreeableness and emotional expressivity, and

negatively associated with categorical thinking and intolerance.

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REI Scale is 24- item questionnaire that has two subscales namely; Rational Subscale and

Experiential Subscale. Its Alpha coefficient was (ά=0.50). Each item of this questionnaire is a

statement that a person may either agree or disagree with. For each item, the participants

indicated how much they agreed or disagreed with the item. The statements were rated on a 5

point Likert type rating scale with gradations of “Definitely False = 1” to “Definitely True =

5”. The two subscales are discussed in detail below:

• Rational Subscale (ά=0.47): This scale included 12-items that measures engagement

in and favorability of cognitive activities and corresponds to rational-analytic

thinking. The rational scale was found to be positively associated with openness,

conscientiousness and favorable basic beliefs, and negatively associated with

neuroticism and conservatism. Statements such as “I have a logical mind”, “I am not

very good at solving problems that require careful logical analysis” and “I try to avoid

situations that require thinking in depth about something” tapped this measure.

• Experiential Subscale (ά= 0.41): This scale included 12-items that measured

engagement in and favorability of intuitive activities and corresponds to experiential-

intuitive thinking. The experiential scale has been found to be positively associated

with extraversion, agreeableness and emotional expressivity, and negatively

associated with categorical thinking and intolerance. It is experiential processing is

affective, heuristic, and holistic. Statements such as “I often go by my instincts when

deciding on a course of action”, “I believe in trusting my hunches” and “I think there

are times when one should rely on one's intuition” tapped this measure.

Procedure:

The students from Indian Institute of Technology Bombay participated voluntarily in this

study. There were 130 student participants. The participants were tested individually in the

Psychophysiology laboratory. On arrival the participants were informed that the experiment

consisted of two parts namely a computerized test and a paper pencil test. The computerized

task consisted of Iowa Gambling Task and the paper pencil test consisted of the various

questionnaires namely, NEO-FFI, REI and BIS/BAS scales. The computerized and paper

pencil tasks were counterbalanced during administration.

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The participants were briefed about the nature of the experiment. The participants were

comfortably seated in front of the computer screen. The participants who were administered

the computerized task were instructed as “In front of you on the screen, there 4 decks of cards

A, B, C, and D. If you want to you select one card at a time, by clicking on the card, from

any deck you choose. Each time you select a card, the computer will tell you that you won

some money. I don’t know how much money you will win. You will find out as we go along.

Every time you win, the green bar gets bigger, every so often, however, when you click on

card, the computer tells you that you won some money, but then it says that you lost some

money too. I don’t know when you will lose, or how much you will lose. You will find out as

we go along. Every time you lose, the green bar gets smaller. You are absolutely free to

switch from one deck to the other at any time, and as often as you wish. The goal of the game

is to win as much money as possible, and if you can’t win avoid losing money as much as

possible. You won’t know when the game will end. You must keep on playing until the

computer stops. I am going to give you this $ 2000 credit, the green bar, to start the game.

The red bar here is a reminder of how much money you borrowed to play the game, and how

much money you have to pay back before we see how much you won or lost. It is important to

know that just like in real card game; the computer does not change the order of the cards

after the game starts. You may not be able to figure out exactly when you will lose money, but

the game is fair. The computer does not make you lose money at random, or make you lose

money based on the last card you picked. Also, each deck contains an equal number of cards

of each color, so the color of the reds does not tell you which decks are better in this game.

So you must not try to figure out what the computer is doing. All I can say is that some decks

are worse than the others. You may find all of them bad, but some are worse than the others.

No matter how much you find yourself losing, you can still win if you stay away from the

worst decks. Please treat the play money in this game as real money, and any decisions on

what to do with it should be made as if you were using your own money”. The participants

entered their demographic details on the computer screen and subsequently started with the

gambling task. The screenshot of IGT is shown in Fig. 1.

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Fig-1 Screenshot of Iowa Gambling Task

Followed by the gambling task, the participants rated the statements in various questionnaires

on NEO-FFI, REI and BIS/BAS. For the BIS/BAS scale they were instructed as “Each item

of this questionnaire is a statement that a person may either agree with or disagree with. For

each item, indicate how much you agree or disagree with what the item says. Please respond

to all the items; do not leave any blank. Choose only one response to each statement. Please

be as accurate and honest as you can be. Respond to each item as if it were the only item.

That is, don't worry about being "consistent" in your responses. Choose from the following

four response options: 1 = very true for me, 2 = somewhat true for me, 3 = somewhat false

for me and 4 = very false for me”, for NEO-FFI the participants were informed that “Here

are a number of characteristics that may or may not apply to you. For example, do you agree

that you are someone who likes to spend time with others? Please write a number next to

each statement to indicate the extent to which you agree or disagree with that statement.

5=Strongly Agree, 4=Agree, 3=Neutral, 2=Disagree, 1=Strongly Disagree” and for REI

they were instructed as “There are two primary ways in which people processes information

resulting in a decision that could be either made ‘analytically’ or based on a ‘gut feeling’.

Please answer the following questionnaire to better understand what your preferred way of

processing information. Please rate the following statements about your feelings, beliefs, and

behaviors using the scale below. Work rapidly as first impressions are as good as any”. After

completion of task, the participants were debriefed and were thanked for their valuable time.

The participants were finally asked to fill a post task questionnaire.

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CHAPTER 4

RESULT & DISCUSSIONS

Result:

The results focus on the role of impulsivity, Personality and information processing styles in

decision making. The result indicated that participants who were low on impulsivity fared

worst on IGT task compared to the participants who were high on impulsivity. Similar results

were demonstrated for personality traits and information processing styles. The results imply

that personality traits determine decision making process. Similarly information processing

styles evaluate preferences for information processing that determine the decisions making and

Impulsivity affects decision making.

Correlation Analysis:

As shown in Table 1, the model that best fit the data is the model that includes the interaction

between the Extroversion and Neuroticism scales (Pearson correlation r = -0.198, p < 0.05),

Agreeableness and Neuroticism scales (Pearson correlation r=-0.22, p<0.05) and

Conscientiousness and Neuroticism (Pearson correlation r=-0.201, p<0.05) and

Conscientiousness and Extroversion scale (Pearson correlation r=0.299, p<0.001) because

they are internally correlated to each others. This table shows the interaction between BAS

and Openness scale (Pearson correlation r=-0.201, p<0.05), BAS and Extroversion scale

(Pearson correlation r=-0.472, p<0.001). It happens as Extraversion primarily implies an

approach tendency towards BAS & Conscientiousness scales (Pearson correlation r=-0.190,

p<0.01) is negatively associated with BAS. This table shows interaction between BIS and

Neuroticism scale (Pearson correlation r=-0.445, p<0.001) which is negatively associated

with BIS. This table shows correlation between Rational and Extroversion scale (Pearson

correlation r=0.176, p<0.05), Rational and Conscientiousness scale (0.383, p<0.001) and

Rational and BAS scale (Pearson correlation r=-0.189, p<0.05) because the rational scale was

found to be positively associated with openness, conscientiousness and favorable basic

beliefs. This table shows the correlation between experiential and extroversion scale (Pearson

correlation r= 0.177, P<0.05) and Experiential and BAS scale(Pearson correlation r=-0.189,

p<0.05) because experiential scale has been found to be positively associated with ww

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extraversion .There were no correlation found between Impulsivity, Personality, and

Information Processing Styles with IGT Deck wise.

Table-1 Correlation Tables for showing correlation between NEO, BIS/BAS and REI.

NEO 1 NEO2 NEO3 NEO4 NEO5 BAS BIS REI-R REI-E

NEO 1 1

NEO2 -0.198* 1

NEO3 -0.075 0.044 1

NEO4 -0.222* 0.161 0.009 1

NEO5 -0.201* 0.299** -0.156 0.072 1

BAS 0.048 -0.472** 0.201* 0.106 -0.190* 1

BIS -

0.445** -0.007 -0.007 0.048 0.054 0.153 1

REIR -0.051 0.176* 0.162 -0.078 0.383** -0.189* 0.039 1

REIE 0.157 0.177* 0.143 0.124 0.015 -0.189* -0.029 0.122 1

NEO 1 = Neuroticism, NEO FFI 2= Extroversion,

NEO-FFI 3 = Openness NEO FFI 4= Agreeableness,

NEO-FFI 5= Conscientiousness BIS=Behavior Inhibition System

BAS=Behavior Approach System

REI-R=Rational Experiential Inventory-Rational

REI-E= Rational Experiential Inventory- Experiential

* P < .05, ** P < .001.

Repeated Measures:

There was main effects for Rational Experiential Inventory high/low (REI) and Bloch wise

Iowa Gambling Task (F (4,119) =3.065, P=0.01, Partial eta squared=0.093). The interaction

between Block wise IGT, Personality, Impulsivity and REI ((F (4,119) =2.9, P<0.01, partial

eta squared=0.089). The Mauchly's Test of Sphericity was significant for IGT Block wise

(Chi- Square=(x2 (9) =57.185,

Mauchly's W = 0.622, P<0.05).

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There was main effects for Behavior Inhibition System/ Behavior Approach System high/low

(BIS/BAS) and NEO-V high/Low with Deck wise Iowa Gambling Task (F (3,120) =2.727,

P<0.05, Partial eta squared=0.064). The Mauchly's Test of Sphericity was significant for

IGT Deck wise (Chi- Square=(x2 (5) =6.149,

Mauchly's W = 0.950, P<0.05).

Descriptive Statistical Analysis:

Descriptive statistical analysis was conducted to check the relation between Iowa Gambling

Task Block wise and high/low BIS/BAS, NEO-V and REI scales. Accordingly, in the two

versus, high and low, the statistical comparison in the BIS/BAS scale with Block1, the mean

for high was -1.91 in case of the BIS/BAS with Block1 the mean was; the mean obtained in

case of the low was -2.13. In next NEO-V scale with Block1, the mean obtained for the case

of high was -1.49; the mean obtained for the low was -2.64; in the last REI scale with Block1

the mean obtained for the case of high was –1.09; the mean obtained in the case of the low

was -2.91.Similarly the statistical comparison in the BIS/BAS scale with Block2, the mean

for high was 0.38 in case of the BIS/BAS with Block2 the mean was; the mean obtained in

case of the low was -1.22. In next NEO-V scale with Block2, the mean obtained for the case

of high was 0.82; the mean obtained for the low was 0.14. In the last REI scale with Block2

the mean obtained for the case of high was 1.56; the mean obtained in the case of the low was

-0.91. Similarly the statistical comparison in the BIS/BAS scale with Block3, the mean for

high was 1.56 in case of the BIS/BAS with Block3 the mean was; the mean obtained in case

of the low was 0.29. In next NEO-V scale with Block3, the mean obtained for the case of

high was 0.17; the mean obtained for the low was 1.9. In the last REI scale with Block3 the

mean obtained for the case of high was 0.94; the mean obtained in the case of the low was

0.97. Similarly the statistical comparison in the BIS/BAS scale with Block4, the mean for

high was 2.26 in case of the BIS/BAS with Block4 the mean was; the mean obtained in case

of the low was 1.00. In next NEO-V scale with Block4, the mean obtained for the case of

high was 0.37; the mean obtained for the low was 3.22. In the last REI scale with Block4 the

mean obtained for the case of high was 0.28; the mean obtained in the case of the low was

3.00. A descriptive statistical analysis was done in order to check the relation between IGT

Block wise and high/low BIS/BAS, NEO-V and REI scales. Similarly the statistical

comparison in the BIS/BAS scale with Block5, the mean for high was 1.24 in case of the

BIS/BAS with Block5 the mean was; the mean obtained in case of the low was 2.29. In next ww

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NEO-V scale with Block5, the mean obtained for the case of high was 1.24; the mean

obtained for the low was 2.34. In the last REI scale with Block4 the mean obtained for the

case of high was 0.22; the mean obtained in the case of the low was 3.21. A descriptive

statistical analysis was done in order to check the relation between IGT Block wise and

high/low BIS/BAS, NEO-V and REI scales. The type of IGT Descriptive statistical analysis

with Block wise was referred as (Table2 in appendix).

Descriptive statistical analysis was conducted to check the relation between Iowa Gambling

Task Deck wise and high/low BIS/BAS, NEO-V and REI scales. Accordingly, in the two

versus, high and low, the statistical comparison in the BIS/BAS scale with DeckA, the mean

for high was 20.69 in case of the BIS/BAS with DeckA the mean was; the mean obtained in

case of the low was 20.89. In next NEO-V scale with DeckA, the mean obtained for the case

of high was 21.27; the mean obtained for the low was 20.20. In the last REI scale with

DeckA the mean obtained for the case of high was 21.58; the mean obtained in the case of the

low was 20.02. Similarly the statistical comparison in the BIS/BAS scale with DeckB, the

mean for high was 27.57 in case of the BIS/BAS with DeckB the mean was; the mean

obtained in case of the low was 29.29. In next NEO-V scale with DeckB, the mean obtained

for the case of high was 29.31; the mean obtained for the low was 27.29. In the last REI scale

with DeckB the mean obtained for the case of high was 28.55; the mean obtained in the case

of the low was 28.24. Similarly the statistical comparison in the BIS/BAS scale with DeckC,

the mean for high was 25.40 in case of the BIS/BAS with DeckC the mean was; the mean

obtained in case of the low was 23.00. In next NEO-V scale with DeckC, the mean obtained


with DeckC the mean obtained for the case of high was 24.17; the mean obtained in the case

of the low was 24.43. Similarly the statistical comparison in the BIS/BAS scale with DeckD,

the mean for high was 26.49 in case of the BIS/BAS with DeckD the mean was; the mean

obtained in case of the low was 27.32. In next NEO-V scale with DeckD, the mean obtained


with DeckD the mean obtained for the case of high was 26.33; the mean obtained in the case

of the low was 27.42. A descriptive statistical analysis was done in order to check the

relation between IGT Deck wise and high/low BIS/BAS, NEO-V and REI scales. The type of

IGT Descriptive statistical analysis with Deck wise was referred as (Table3 in appendix).

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For each participant of the IGT, we counted the total number of card selections from the

disadvantageous decks and the advantageous decks. (Bechara et al., 2000b). Then, we

derived a net score for each block (the number from advantageous decks minus the number

from disadvantageous decks). Net score below zero indicates that the subjects were selecting

disadvantageously, whereas net score above zero indicates that subjects were selecting

advantageously.

The figure2 represents the IGT Block wise performance with BIS/BAS, NEO-V and REI

scale. The graph indicates block wise data values for each individual in each scale with low

and high values. The responses to the Block1, Bolck2, Bolck3, Block4, & Bolck5 indicated

that the person who had achieved high on BIS/BAS performed worst on IGT compared to

scores on low on BIS/BAS. The participants who scored high on NEO-V had lower

performance scores for IGT task whereas participants who scored low on NEO-V had higher

performance scores for IGT task. Similarly, for participants who scored high on REI

performed worst on IGT. The participant who scored low on REI performed well on IGT

task. The Fig. 2 depicts the participants’ performance on IGT task. The Fig 2 indicates that as

IGT trials proceeded, the participants’ performance on IGT task improved.

Fig-2 Relationship between, Impulsivity, Personality Traits, Information Processing Style and

Block wise IGT trials (100 trials).

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The figure3 represents the IGT Deck wise performance with BIS/BAS, NEO-V and REI

scale. The graph indicates block wise data values for each individual in each scale with low

and high values. The responses to the DeckA, DeckB, DeckC, DeckD, indicated that the

person who had achieved high on BIS/BAS performed worst on IGT compared to scores on

low on BIS/BAS. The participants who scored high on NEO-V had higher performance

scores for IGT task whereas participants who scored low on NEO-V had lower performance

scores for IGT task. Similarly, for participants who scored high on REI performed well on

IGT. The participant who scored low on REI performed worst on IGT task. The Fig. 2 depicts

the participants’ performance on IGT task. The Fig 3 indicates that as the participants’

Performance in IGT DeckA & DeckC on worst and DeckB and DeckD on well performance.

Fig-3 Relationship between, Impulsivity, Personality Traits, Information Processing Style and Deck

wise IGT trials (100 trials).

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Discussions:

We discussed about performance on the IGT was operationalised in three ways:

Advantageous deck, Disadvantageous deck, and NET score. The advantageous deck was

calculated by summation of Deck A and B (A+B) in overall 100 trials and disadvantageous

deck was calculate by summation of Deck C and D (C+D) in overall 100 trials.

In result we found relationship between IGT block wise and impulsivity, personality and

information processing style with the help of high/low. In both samples, the structure of the

BIS/BAS scales turned out to be four-dimensional: one dimension for the BIS scale and one

for each of the three BAS scales. These results were confirmed by differential relations of the

BIS scale and the three BAS scales with the Big- Five scales. Also Carver & White (1994),

Heubeck et al. (1998), Jorm et al. (1999), Leone et al. (2001) and Ross et al. (2002) found

that four dimensions are needed. The fact that we found the expected four-dimensional

structure for the translated BIS/BAS questionnaire also supports the validity of the

translation. Sometimes, BAS activity is measured as the sum of the three BAS scales (e.g.

Harmon- Jones, 2003, Gable et al., 2000, Gomez & Gomez, 2002, Gomez & McLaren, 1997,

O’Gorman & Baxter, 2002). This was confirmed by the differential relational pattern of the

BIS/BAS latent variables with the Big-Five personality dimensions. Several authors assume,

although sometimes implicitly, that BIS/BAS underlies part of the surface of personality as

described for example by the Big-Five (e.g. Corr, 2001; Gray, 1970; Matthews & Gilliland,

1999). However, the relation between Neuroticism and Extraversion of the BIS/BAS scale. In

accordance with our hypotheses and earlier findings, Neuroticism is highly positively related

with BIS and negatively with several BAS measures, but they can nevertheless shed light on

the meaning of the personality factor Neuroticism. In the literature Neuroticism is defined in

different ways: as emotional control (Fiske, 1949), negative emotionality, as negative affect

and as emotional (in) stability (Guilford, 1975; Hofstee, Raad, & Goldberg, 1992; Lorr,

1986).

In relation to information factor, the result shows that there was a significant relationship

between information and rational decision making style. Participants had higher field of

expertise, knowledge and decision-making skill. They believed in their judgment and relied

on their working experiences and intuition to make decision. Sometimes, respondents would

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and would deal with the complicated information. Similarly, risk factor had a significant

effect on intuitive decision-making style. The result of this study is aligned with the study of

Harteis and Gruber (2008); they stated that individuals with risk-taking readiness would tend

to use intuition to make decision. Finally, the findings show that there was no significant

relationship between uncertainty and time with intuitive decision-making style of academic

staffs. The two factors were not significantly affecting intuition decision making, therefore it

is urged to gather more and adequate data to support these two factors.

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CHAPTER 5

CONCLUSIONS

The results imply personality traits determine decision making process and information

processing styles evaluate preferences for information processing for determines the decisions

making. Impulsivity affects decision making. The responses to the Block1, Bolck2, Bolck3,

Block4, & Bolck5 indicated that the person who had achieved high on BIS/BAS performed

worst on IGT compared to scores on low on BIS/BAS. The participants who scored high on

NEO-V had lower performance scores for IGT task whereas participants who scored low on

NEO-V had higher performance scores for IGT task. Similarly, for participants who scored

high on REI performed worst on IGT. The participant who scored low on REI performed well

on IGT task. The result indicated that as IGT trials proceeded, the participants’ performance

on IGT task improved. The responses to the DeckA, DeckB, DeckC, DeckD, indicated that

the person who had achieved high on BIS/BAS performed worst on IGT compared to scores

on low on BIS/BAS. The participants who scored high on NEO-V had higher performance

scores for IGT task whereas participants who scored low on NEO-V had lower performance

scores for IGT task. Similarly, for participants who scored high on REI performed well on

IGT. The participant who scored low on REI performed worst on IGT task. The result

indicates that as the participants’ performance in IGT DeckA & DeckC on worst and DeckB

and DeckD on well performance.

We are used IGT For each participants, we counted the total number of card selections from

the disadvantageous decks, and the total number of card selections from the advantageous

decks for each block of 20 cards. Then, we derived a net score for each block (the number

from advantageous decks minus the number from disadvantageous decks); net scores below

zero indicate that the subjects were selecting disadvantageously, whereas net scores above

zero indicate that subjects were selecting advantage.

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APPENDIX A

Table-2 Descriptive Statistic Analysis with Block Wise

NEO BIS/BAS REI Scale Mean SD

N

BLock1(1-20) Trials HIGH HIGH HIGH .11 6.807 18

LOW -2.73 2.573 11

LOW HIGH -1.62 4.526 26

LOW -2.25 3.173 16

LOW HIGH HIGH -2.77 3.876 13

LOW -2.54 5.140 26

LOW HIGH .86 1.574 7

LOW -4.62 6.653 13

Total HIGH HIGH -1.10 5.861 31

LOW -2.59 4.494 37

LOW HIGH -1.09 4.186 33

LOW -3.31 5.079 29

Block2(21-40) Trials HIGH HIGH HIGH 1.2222 3.50723 18

LOW .0000 2.00000 11

LOW HIGH -1.0000 4.87442 26

LOW -3.3750 3.98121 16

LOW HIGH HIGH 1.6923 4.81983 13

LOW -.6923 4.07695 26

LOW HIGH -1.1429 3.80476 7

LOW .9231 5.86603 13

Total HIGH HIGH 1.4194 4.03959 31

LOW -.4865 3.57166 37

LOW HIGH -1.0303 4.61306 33

LOW -1.4483 5.28871 29

Block3(41-60) Trials HIGH HIGH HIGH 1.22 6.103 18

LOW -.18 3.027 11

LOW HIGH .69 6.195 26

LOW -1.62 4.272 16

LOW HIGH HIGH 1.23 4.658 13

LOW 2.69 6.424 26

LOW HIGH .57 3.599 7 ww

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LOW 1.69 6.725 13

Total HIGH HIGH 1.23 5.457 31

LOW 1.84 5.742 37

LOW HIGH .67 5.694 33

LOW -.14 5.655 29

Block4( 61-80) Trials HIGH HIGH HIGH .33 6.660 18

LOW .73 4.221 11

LOW HIGH .31 6.662 26

LOW .25 7.861 16

LOW .44 6.524 27

LOW HIGH HIGH .77 6.809 13

LOW 5.00 8.676 26

LOW HIGH -.86 6.914 7

LOW 4.31 8.400 13

Total HIGH HIGH .52 6.612 31

LOW 3.73 7.820 37

LOW HIGH .06 6.624 33

LOW 2.07 8.220 29

Block5 (81-100) Trials HIGH HIGH HIGH 2.56 6.609 18

LOW -1.64 4.178 11

LOW HIGH .08 6.560 26

LOW 3.63 5.071 16

LOW HIGH HIGH -2.31 4.750 13

LOW 3.31 8.997 26

LOW HIGH -.57 7.091 7

LOW 6.62 9.070 13

Total HIGH HIGH .52 6.303 31

LOW 1.84 8.143 37

LOW HIGH -.06 6.567 33

LOW 4.97 7.164 29

Total 2.29 7.251 62

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APPENDIX B

Table-3 Descriptive Statistic Analysis with Deck Wise

NEO BIS/BAS REI Mean Std. Deviation N

DeckA HIGH HIGH HIGH 22.06 8.356 18

LOW 19.46 5.027 13

LOW HIGH 20.77 5.616 26

LOW 27.29 12.486 7

LOW HIGH HIGH 22.36 4.802 11

LOW 19.65 5.403 26

LOW HIGH 20.44 4.912 16

LOW 18.23 8.238 13


LOW 19.59 5.215 39

LOW HIGH 20.64 5.300 42

LOW 21.40 10.570 20

DeckB HIGH HIGH HIGH 25.44 5.193 18

LOW 31.23 10.410 13

LOW HIGH 30.85 6.104 26

LOW 23.00 8.307 7

LOW HIGH HIGH 29.36 5.259 11

LOW 26.46 8.101 26

LOW HIGH 31.12 6.376 16

LOW 27.31 9.970 13


LOW 28.05 9.087 39

LOW HIGH 30.95 6.132 42

LOW 25.80 9.435 20

DeckC HIGH HIGH HIGH 26.22 8.822 18

LOW 24.38 6.640 13

LOW HIGH 22.69 6.117 26

LOW 24.00 3.916 7

LOW HIGH HIGH 22.82 3.868 11

LOW 26.42 9.786 26

LOW HIGH 20.81 4.608 16

LOW 25.77 8.438 13


LOW 25.74 8.825 39

LOW HIGH 21.98 5.607 42

LOW 25.15 7.110 20

Deck D HIGH HIGH HIGH 26.83 7.980 18 ww

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LOW 24.92 7.588 13

LOW HIGH 26.46 7.564 26

LOW 27.14 7.128 7

LOW HIGH HIGH 25.45 5.165 11

LOW 27.46 8.914 26

LOW HIGH 27.62 7.796 16

LOW 28.77 8.054 13


LOW 26.62 8.481 39

LOW HIGH 26.90 7.580 42

LOW 28.20 7.592 20

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Data & Analytics

To Investigate Role of Impulsivity, Reward and Loss of Sensitivity in Decisions Making during Gambling Task: An Empirical Study