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Running head: MEASURING IMPULSIVITY 1

Measuring Impulsivity: The Lightfoot Impulsive Inventory

Christy G. Coberly

Armstrong Atlantic State University

Author Note

Christy G. Coberly, Psychology Department, Armstrong Atlantic State University.

This research was made possible due to the help of Joshua Lightfoot and Trevor

Rawlinson. Also, a special thanks to our supervising professor, Dr. Vann B. Scott, Jr.

Correspondence concerning this article should be addressed to Christy Coberly,

Department of Psychology, Armstrong Atlantic State University, Savannah, GA 31419. E-mail:

[email protected]

MEASURING IMPULSIVITY 2

Abstract

Impulsivity has been highly correlated with risky behaviors including drug use. The correlation

between impulsivity and drug use is addressed in the Lightfoot Impulsive Inventory. Impulsivity

and drug use have been noted to have a bidirectional influence. However, it has also been

suggested that impulsivity may be affected by a third variable which should be further

investigating using longitudinal objective studies (De Bellis, 2002). However, The LII will

observe the more subjective analysis of impulsivity including the three factors which make up

the construct impulsivity: behavioral disinhibition, delay discounting, and inattention.

Keywords: impulsivity, delay discounting, behavioral disinhibition, inattention


Measuring Impulsivity: The Lightfoot Impulsive Inventory

Impulsivity can be seen in many risky or irrational behaviors such as drug abuse, binge

eating, gambling, unprotected sex, compulsive shopping, and a number of other disadvantageous

behaviors. Impulsivity was best defined by Perry & Carroll (2008) as “the inability to stop a

behavior that has negative consequences, preference for immediate over delayed gratification,

tendency to engage in risky behaviors, heightened novelty seeking, behaving without forethought

or consideration of outcomes, being impatient when asked to wait, having a short attention span,

and difficulty persisting at a particular activity.”

It has been noted that impulsivity may lay its mark somewhere in the genes, therefore,

under scrupulous analysis, one may be able to predict an individual’s chance of becoming

involved with drugs from a young age (De Bellis, 2002). If an individual has a predisposition for

impulsivity, their chance of becoming an addict is significantly increased. However, if an

individual partakes in experimentation with drugs, their level of impulsivity will be heightened

further (Perry & Carroll, 2008). The increase of impulsivity following chronic drug use is due to

a dysfunction of cognition in the frontal cortex (Jentsch and Taylor, 1999). Therefore, an

individual who has a predisposition for impulsivity and experiments with drugs is more likely to

have fewer periods of drug abstinence, if any. These individuals will have less success in

treatment programs, and will have a greater chance of relapse (Perry & Carroll, 2008).

Accordingly, if psychologists are capable of determining trait impulsivity in children, it may be

possible to proactively implement a plan to avoid drug use before it occurs.

There are three dimensions of impulsivity that have been observed including delay

discounting, behavioral disinhibition, and inattention. Delay discounting had been defined as a

“preference for smaller, more immediate rewards over larger, more delayed rewards” (de Wit,


2008). This phenomenon can be observed in experimental settings using discounting tasks. Delay

discounting experiments are typically performed using monetary values as the reward. Although

everyone will at some point partake in delay discounting, more impulsive individuals are more

likely to take a sooner, smaller amount of money opposed to a later, larger amount of money.

Drug abuse itself may also be seen as a form of delay discounting such that taking a drug and

becoming high is a more immediate reward opposed to the later reward of health.

A second well known aspect of impulsivity is behavioral disinhibition. Disinhibition is

the inability to withhold a proponent response. Lack of inhibition may be most commonly

observed in alcoholics and can be demonstrated in experimental settings using stop tasks (Logan,

Cowan, & Davis, 1984) or go/no-go tasks (Newman, Widom, & Nathan, 1985). In a stop task,

the participant is asked to respond to some stimuli. Once the participant has already initiated

their response, they are told to stop responding. The participant’s reaction time is noted and those

with slower reaction times are considered to be, potentially, more impulsive. In a go/no-go task,

a participant is asked to initiate a task or to stop a task dependent of responding to only specific

stimuli even though many stimuli may be presented. More impulsive individuals are expected to

make a greater number of errors on this task.

The most recent dimension of impulsivity being observed is inattention. Inattention can

be defined as the inability to maintain concentration on a particular thought or task for an

extended period of time. The ability to maintain focus when an addict is attempting to sustain

from drug use is crucial. Therefore, a more impulsive individual may be more inattentive and

find it more difficult to sustain from abusing drugs. This phenomenon occurs because a great

amount of attention is required in order to avoid drug related cues. However, attention has been

highly correlated with both stress and sleep deprivation. In other words, if a recovering drug


addict becomes sleep deprived or find one’s self in a stressful situation, their chance for relapse

is significantly increased. Even among healthy non-addicted individuals, distress and sleep

deprivation can result in a need for immediate gratification and lapses of attention which will

result in more risky behaviors. It should be noted, however, that these issues do not appear to

effect delay discounting or behavior inhibition (Acheson & de Wit, 2008).

The Lightfoot Impulsive Inventory (LII) focuses on the three factors of the impulsive

construct. These factors include delay discounting, behavioral disinhibition, and inattention

which have been addressed in order to develop a reliable self-inventory for trait impulsivity

which should be used as the first step in a proactive plan to prevent disadvantageous behaviors.

Method

Overview

We ran two studies using online questionnaires that measured impulsivity. Study one

contained 30 likert scale questions which covered three subscales. Study two was reduced to 16

items which were drawn from the first study and the three subscales were retained. We

hypothesized that the second study would be capable of determining trait impulsivity and would

achieve predictive validity which may determine future impulsive decision making that may be

measured using objective behavioral measures.

Participants

Using the Armstrong Atlantic State University SONA system, we had 117 Armstrong

students sign-up and complete study one of the LII and each participant was granted half an hour

of credit. Study two obtained another 108 Armstrong student participants, however, for the

second study, each participant was granted a full hour worth of credit. No demographics were

obtained.


Materials

In order to conduct our research, we placed an ad on Armstrong’s SONA system. When

participants signed up for our study, they were required to accept an informed consent before

proceeding to the questionnaire. The participants were made aware of their right to withdraw

their answers from the database at any time prior to completing all parts of the questionnaire. For

study one, we used 10 questions for each subscale of impulsivity totaling 30 questions. Study

one also contained a social desirability scale known as the Social Desirability Scale-17 (SDS-17)

(Stöber, J. 2001). Study two consisted of 16 questions which were pulled from the 30 questions

measuring impulsivity in study one. Study two also contained the SDS-17, the Barratt

Impulsiveness Scale-11 (BIS-11) (Patton, Stanford, & Barratt, 1995), the Sensation Seeking

Scale (SSS), (Zuckerman, Kolin, Price & Zoob, 1964), the Alcohol and Substance Abuse

Questionnaire (ASAQ) created by the health center of the University of Maryland, and an altered

form of the Rapid Alcohol Problem Screen (RAPS) (Cherpitel, 2000) which contained drug

questions as well as alcohol questions (Brown, Leonard, Saunders, & Papasouliotis, 2001).

Design

In this study, we developed a questionnaire which subjectively identifies trait impulsivity

and is capable of establishing known groups. After completing the 16 questions of the LII and a

social desirability scale, we were capable of assessing high or low impulsivity in participants.

Procedure

We placed an ad for participants to sign up for our research on Armstrong Atlantic State

University’s SONA system. Following the acceptance of an informed consent, students were

then able to take the online questionnaire through SONA. For study one, the participants

completed questions from three subfields of the construct impulsivity. These sub-constructs were


delay discounting, behavioral disinhibition, and inattention which contained 10 questions each

for a total of 30 questions. The participants were also asked to complete the SSS due to the

socially unaccepted nature of the questions contained in the LII.

Following study one we ran an exploratory factor analysis until we achieved simple

structure resulting in a loss of 14 questions on the LII. We then placed a separate ad on

Armstrong Atlantic State University’s SONA system and participants, again, were required to

accept an informed consent prior to completing the questionnaire. For the second study,

participants were required to complete the 16 questions of the LII, the SDS-17, the BIS-11, the

RAPS, the SSS, and the ASAQ.

Results

Study one

After obtaining 117 participants for study one of the LII (M = 40.11, SD = 9.81), we

conducted an exploratory factor analysis with varimax rotation and a method of maximum

likelihood extraction until all parts of the inventory achieved simple structure (items loading >

0.40 on only one factor). After discarding 14 questions which did not load properly, we were left

with 16 questions loading on 3 factors. For the three sub factors, delay discounting (M = 10.92,

SD = 4.10) properly loaded five questions, behavioral disinhibition (M = 4.96, SD = 2.23) loaded

three questions, and inattention (M = 24.23, SD = 6.50) loaded eight questions (see Table 1). It

should be noted that our third factor, behavioral disinhibition, loaded with a percent variance

slightly below 10 percent. However, we still included this section in our inventory as it is an

important aspect of measuring impulsivity. Overall, the LII was found to be highly reliable in the

first study (16 items; α = .84). The Cronbach’s alpha for the five delay discounting items, three


behavioral disinhibition items, and eight inattention items were .72, .67, and .85, respectively

(see Table 2).

Study two

After obtaining 108 Armstrong student participants for study two of the LII (M =43.17,

SD = 9.43), we ran a confirmatory factor analysis. We were able to retain all three factors which

were delay discounting (M = 12.13, SD = 3.98), behavioral disinhibition (M =5.81, SD = 2.42),

and inattention (M = 25.22, SD = 6.11) with Cronbach’s alphas of .75, .65, and .85, respectively.

The Cronbach’s alpha for the LII was .83 (see Table 2).

We also ran bivariate correlations to show validity of the LII when compared to other

scales. In order to obtain convergent validity, our participants took the BIS, and those results

were compared to the LII. The BIS showed a strong correlation of .68 compared to the LII. In

order to obtain discriminate validity, our participants took the SSS. The SSS displayed a weak

correlation of .35 compared to the LII (see Table 3).

Taking data obtained from study two, we were also able to show predicative validity in

our scale. Using an independent-samples median test and independent samples Mann-Whitney U

test, we were capable of demonstrating predictive validity for drug use. Relationships were found

between history of substance abuse and the LII with a correlation of .25 and also between

number of drugs experimented and the LII. If individuals had experimented with more than two

drugs, they were put into a high drug use known group. If an individual has experimented with

less than two drugs, they were put into a low drug use known group. With these known groups,

we established a .33 correlation with the LII (see Table 4).


Discussion

The LII was capable of showing reliability as well as criterion and construct validity. The

LII demonstrated strong correlations with the BIS which established convergent validity. The LII

also demonstrated weak correlations with the SSS which established discriminate validity of our

scale. However, it should be recognized that the subscale of behavioral disinhibition was

relatively weak in the LII and could potentially use some adjustments for better reliability.

Reliability may be increased by including more questions loading on the behavioral disinhibition

sub factor.

In order to retain reliability, a social desirability scale should always be given alongside

the LII to ensure accurate reporting. The LII is strongly susceptible to social desirability due to

the nature of the questions and, therefore, may result in socially desirable answering of

participants and, ultimately, skewed results.

In the future, operational longitudinal research may be a more appropriate study of

understanding impulsivity and its relationship to drug use. It is important to note that there is not

always much consistency between operational behavior tasks and self-reports of behavior (de

Wit, Crean, &, Richards, 2000). However, this may be the result of individual inability to

accurately report one’s own behavior and the cause of those behaviors (Goldiamond, 1965;

Hefferline, Kennan, & Harford, 1958; Svartdal, 1991). Therefore, it would be important to

include an operational behavior task following the LII inventory for greater validity. However,

the inventory may be used as a predicative measure for impulsivity which may be the

cornerstone for further investigation into the true nature of impulsivity.


References

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behavior in healthy volunteers. Experimental Clinical Psychopharmacology, 16, 113-123.

Brown, R. L., Leonard, T., Saunders, L. A., & Papasouliotis, O. (2001). A two–item conjoint

screen for alcohol and other drug problems. Journal of the American Board Family

Medicine, 14, 95–106.

Cherpitel, C. J. (2000). A brief screening instrument for problem drinking in the emergency

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Logan, G. D., Cowan, W. B., & Davis, K. A. (1984). On the ability to inhibit simple and choice

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Table 1Factor loadings for the Lightfoot Impulsive Inventory

Principal factor

ITEM Behavioral Delay Disinhibition Discounting Inattentiveness

1. I avoid taking illegal drugs and narcotics.*

0.82(0.67)

0.06 0.08

2. I always follow the rules.* 0.79(0.50)

0.08 0.12

3. I would operate a motor vehicle under the influence of drugs or alcohol.

0.64(0.37)

0.32 -0.03

4. I often put off studying, even for tests that are worth a large percentage of my grade.

0.15 0.53(0.54)

0.36

5. I find it easy to ignore consequences of my actions that will occur in the future.

0.04 0.78(0.76)

0.08

6. I find it hard to plan for my future. 0.00 0.73(0.63)

0.07

7. The future consequences of my actions often guide my decision making process.*

0.13 0.63(0.59)

0.05

8. I find it easy to stick to a schedule.* 0.26 0.65(0.48)

0.15

9. I have trouble paying attention. 0.04 0.24 0.78(0.65)

10. I find it easy to concentrate on a task for long periods of time.*

0.27 0.26 0.61(0.76)

11. I quickly jump from task to task. -0.10 0.15 0.50(0.32)

12. I become restless if I am forced to sit for long periods of time.

0.00 0.00 0.72(0.66)

13. I require constant stimulation or I quickly lose interest.

-0.02 -0.00 0.75(0.70)

14. I can easily pay attention to long lectures.*

0.06 0.02 0.79(0.85)

15. I rarely become distracted when I am working on a project.

0.18 0.02 0.63(0.51)

16. I find it easy to stick to a schedule.* 0.13 0.29 0.67(0.57)

Note: First row of factor loadings are from the exploratory factor analysis. The factor loadings in parentheses are from the confirmatory factor analysis. Items that are marked with an asterisk (*) were reverse coded.


Table 2Means, standard deviations, intercorrelations, a reliability scores for the Lightfoot Impulsive Inventory and its subscales

Study 1 Impulsivity 40.11 9.81 (.84) __ __ __ Behavioral Disinhibition 4.96 2.23 .50** (.67) __ __ Delay Discounting 10.92 4.10 .74** .32** (.72) __ Inattentiveness 24.23 6.50 .87** .21* .38** (.85)

Study 2 Impulsivity 43.17 9.43 (.83) __ __ __ Behavioral Disinhibition 5.81 2.42 .56** (.65) __ __ Delay Discounting 12.13 3.98 .73** .35** (.75) __ Inattentiveness 25.22 6.11 .85** .24* .33** (.85)

Note: Cronbach’s alpha is located in parenthesis. *p < 0.05; **p < 0.01

M SD LII BDI DD IA


Table 3Correlations between various surveys and the Lightfoot Impulsivity Inventory

Novel Scale& Subscales Established Scales

BIS(.79)

SSS(.85)

RAPS(.81)

ASAQ(.82)

SDS(.76)

LII .68** .35** .49** .44** -.40** BDI .36** .50** .61** .42** -.15 DD .49** .21* .442* .39** -.40** IA .58** .20* .23* .24* -.31**

Note: Cronbach’s alpha located in parenthesis.*p < 0.05; **p < 0.01


Table 4 Correlations between the Lightfoot Impulsivity Inventory and the questions used to determine predictive validity LII

.25**

.14

.33**

Median Test

(.050)

(.340)

(.004)

Mann-Whitney U

(.034)

(.180)

(.001)

Note: *p < 0.05; **p < 0.01

History of Substance Abuse

Relatives with History of S.A.

Drug Experimentation

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