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THE NEUROPSYCHOLOGICAL CORRELATES OF SEVERE ACADEMIC
PROCRASTINATION
BY

DAVID AARON STONE .

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Counseling Psychology

1 999

ABSTRACT
NEUROPSYCHOLOGICAL'CORRELATES OF SEVERE ACADEMIC
PROCRASTINATION
By

David Aaron Stone

Procrastination is a problem that is prevalent in academic settings. There has
been a proliferation of research into this disabling behavior over the last 15 years in
particular. The research has run the gamut from studies of a plethora of cognitive,
affective, and behavioral correlates. To date, no investigation has considered the possible
contribution of neuropsychological variables in procrastination. One problem has been
an over reliance on samples of convenience. As a result, the information on
procrastination describes typical but not severe procrastinators. Severe procrastinators
are those individuals who suffer signiﬁcant consequences as a result of their
procrastination. The present study was designed to be the ﬁrst to identify a sample of
severe procrastinators and then to compare their performance to a control group on
variety of measures of neuropsychological functioning.

The subjects were 63 community college students. Thirty-three were on academic
probation, and 30 were psychology students in good academic standing. Each subject
completed a brief neuropsychological assessment primarily focused on executive
functioning abilities. Subjects also completed additional instruments that assessed

procrastination, intelligence, depression, and Attention Deﬁcit Disorder.

A signiﬁcant mean difference was obtained on the procrastination scale
conﬁrming that the students on academic probation experience severe academic
procrastination. Further comparisons of means as well as correlational analyses failed to
support a relationship between executive functioning and proCrastination. The only
signiﬁcant difference on a neuropsychological measure was on the Ruff Figural Fluency
Test with the severe procrastinators performing much poorer. These results are discussed
in the context of the difficulties in assessing executive functioning ability and sampling

bias. Implications and suggestions for future research are discussed.

DEDICATION

To my daughter, Natalie, without whom this project surely would not have come to
completion. It is my hope someday she will understand the importance of this

accomplishment and know that for her as well, anything is possible.

iv

ACKNOWLEDGEMENTS

The author expresses sincere appreciation to Dr. Nancy Crewe for not only paving
the way for my entry into the program but for her patience and support throughout the
arduous process. Thanks to Joni Smith for being my conduit to the program when I was
so far away. A special thanks goes out to Dr. Robert Johnstone and Christy Wells for
their input and patience. There are also numerous people for whom I am eternally
grateful to for their encouragement, patience, and never ending belief that I could ﬁnish
despite my own doubts. So I say thank you from the bottom of my heart to Dr. Bernie
Schwartz, Mark Gordon, Dr. Lauren Harris, Dr. Matthew Keene, Dr. Leslie Dana-Kirby,

Jennifer Thomas, Dr. Lisa Crandell, Harry Stone, and the gorilla.

TABLE OF CONTENTS

LIST OF TABLES .................................................................................... viii

CHAPTER 1

INTRODUCTION ........................................................................ 1

CHAPTER 2 ‘

LITERATURE REVIEW ............................................................... 5
Procrastination ........................................................................ 5

Deﬁned ........................................................................... 5
Prevalence ......................................................................... 8
Types of procrastination ........................................................ 12
Consequences of academic procrastination ................................. 33
Experimental studies ............................................................ 35
Summary/critique ............................................................... 37
Executive functioning .............................................................. 42
Deﬁned ............................................................................ 42
Executive functioning and the frontal lobes ............................... 46
Behavioral disturbances associated with frontal lobe damage ............. 47
Neurological variability in a normal population ............................. 50
Summary/research questions . ...................................................... 54

CHAPTER 3 .

METHOD ................................................................................ 56
Subjects ............................................................................... 56
Instruments ........................................................................... 57

Procrastination Questionnaire .................................................. 57
Vocabulary Subtest .............................................................. 58
Block Design Subtest ............................................................ 59
The Tinkertoy Test .............................................................. 60
Controlled Oral Word Association Test ...................................... 62
Ruff Figural Fluency Test ...................................................... 63
Beck Depression Inventory ..................................................... 65
Wender Utah Rating Scale ..................................................... 65
Procedure ............................................................................. 66
Design ........................................................................... 66
Data Collection .................................................................. 66

CHAPTER 4

RESULTS ................................................................................. 68
Description of sample ............................................................... 68
Preliminary analyses ...................... . ........................................ '. 69
Demographic group comparisons .................................................. 70
Group differences in procrastination ............................................. 72
Group differences on control variables ........................................... 72
Group differences on measures of executive functioning ...................... 74
Relationship between procrastination and executive functioning ............ 74
Post Hoc comparisons ............................................................... 78

CHAPTER 5

DISCUSSION ........................................................................... 81

APPENDIX
A. RECRUITMENT LETTER .................................................... 93
B. CLIENT INFORMATION SHEET ........................................... 95
C. CONSENT FORM .............................................................. 97
D. TIME-USE QUESTIONNAIRE ............................................. 98
E. TIT SCORING PROTOCOL ................................................. 99
F. THE TINKERTOY TEST SUMMARY OF SCORES ..................... 101
G. BECK DEPRESSION INVENTORY ........................................ 102
H. WENDER UTAH RATING SCALE ......................................... 106

REFERENCES ........................................................................... 107

vii

LIST OF TABLES

Table Page

1. Mean Comparisons on Demographic Variables for Academic

Probation and Control Groups ........................................... 71
2. Mean Comparisons on Control Variables for Academic

Probation and Control Groups .......................................... 73
3. Mean Comparisons on Executive Functioning Measures for

Academic Probation and Control Groups .............................. 75
4. Intercorrelations between the Time Use Questionnaire (TU Q) and

Measures of Executive Functioning .................................... 76

5. Mean Comparisons on Control Variables and Executive Functioning
Measures for High and Low Procrastinators ........................... 79

viii

CHAPTER I

INTRODUCTION

Procrastination, the act of putting off until tomorrow what could be done today, is
‘ familiar to all of us. The subject of incalculable self-effacing jokes, it is impossible to
estimate the total human cost of procrastination in terms of lack of productivity and
suffering. A cursory search of the Internet yields 3,280 websites that contain some
reference to procrastination. Universities have posted self-help quizzes to help students
recognize whether or not a procrastination problem exists in addition to advice on
overcoming the problem. Business consulting ﬁrms have posted a myriad of information
about the enormous cost of wasting a business’s most valuable commodity — their
employee’s productivity. The most frequently appearing type of website has been posted
by students who have constructed a home page apparently to avoid what they
acknowledged they should be doing.

For years in the popular literature, various self-help books have appeared in
bookstores across the country (Porat, 1980; Knaus, 1979; Lakein, 1973; Ellis & Knaus,
1977) addressing procrastination. The authors, usually clinicians, offer various non-
empirical explanations for procrastination as well as numerous approaches to remediate
it. In academic settings it is estimated that the percent of college students who
procrastinate range from as low as 22% - 33% (Ely & Hamptom, 1973; Rosati, 1975) to
as high as 95% (Ellis and Knaus, 1977). Given this prevalence of procrastination, it is
surprising that procrastination has moved out of the popular psychology literature and
begun receiving serious empirical attention only over the last 20 years.

I

To date, the predominant empirical approach to investigating procrastination has
focused on correlating this often crippling behavior with a myriad of psychological,
cognitive, and personality factors including self-regulation (Senecal, Koestner, and
Vallerand, 1995), perfectionism (Ferrari, 1992, Flett et al., 1992), low self-esteem (Effert
& Ferrari, 1989), fear of failure ( Solomon & Rothblum, 1984), learned helplessness
(McKean, 1994a), low self-efﬁcacy (Haycock et al., 1998), irrational beliefs (Bridges and
Roig, 1997) among others. There is also a growing clinical literature that posit various
psychodynarnic explanations of procrastination including death anxiety (Donovan, 1995),
fear of success (Rorer, 1983), and being in an impasse during psychodynarnic treatment
A (Giovacchini, 1975).

To date, no investigation has considered the potential role of neuropsychological
variables in procrastination. It has long been an implicit bias of the social sciences to
seek. psychological explanations (e. g., low self-esteem) for the phenomena they study e. g.
depression. This bias is also covertly expressed in clinical practice. How often do
clinical or counseling psychologists require a full physical examination for their new
clients? It may not even occur to them to request one. The assumption is either that the
biological system is intact or that such variables are not very relevant to psychological
treatment. This is in contrast to the physical sciences, which historically seek tangible or
material explanations for the phenomena they study. While each discipline's assumptions
regarding causality have merit, Wicker (1985) reminds us that the human tendency to
think recurring thoughts limits our theories and research.

Over the last 10 to 15 years the social sciences have expanded their view of the
individual to conCeptualize them and their problems from a biopsychosocial perspective.

2

Ferrari, Johnson, and McCown (1995) in their book on procrastination and task
avoidance state, “to date, almost nothing is known about the neuropsychology of
procrastination. Theoretically, it is possible that severe chronic procrastinators exhibit
subtle neuropsychological deﬁcits related to executive functioning, but currently this
remains simply an interesting speculation” (p. 45).

It is the primary purpose of this exploratory study to investigate the
neuropsychology of procrastination in an attempt to shed light on whether deﬁcits in
executive functioning are related to severe procrastination. From a review of the
relevant procrastination literature as well as the literature on executive functioning-
ability, the question regarding the role of neuropsychological variables in procrastination
becomes reasonable. The current study had two objectives. The ﬁrst objective is to
identify a group of “clinical” academic procrastinators. As will be seen, the issues of
chronicity and severity have not been given serious consideration when investigating
procrastination. There seems to be an implicit bias that procrastination is not a “clinical”
condition. The second objective is to determine the relationship, if any, between
academic procrastination and several measures of executive functioning. Wicker (1985)
encourages researchers to consider alternative, even greatly divergent, perspectives to
explain what we believe we already understand. The consideration of
neuropsychological variables in procrastination is one such conceptual stretch. '

It is felt that an understanding of the relationship between academic
procrastination and neuropsychological variables will have signiﬁcance for counselors,
teachers, and researchers. A clearer understanding of neuropsychological variables in
procrastination can potentially lead to a process of identifying and intervening with a

3

large number of students who are currently undetected and who are failing to complete
their community college degrees. With the high prevalence of procrastination among
college students (cited earlier), it is imperative that counseling psychologists have a better

understanding of this disabling behavior.

CHAPTER II

LITERATURE REVIEW

Procrastination

 

2:ﬁ.n_ed

Procrastination is not a modern problem associated exclusively with industrial
societies and their emphasis on schedule adherence, punctuality, and efﬁciency. Nor has
the term always had an implicit negative moral quality about it as typiﬁed by such

adjectives for procrastinators as unproductive and lazy. According to American Heritage

 

Dictionary (1977), the word “procrastinate” comes from the Latin word procrastinare,
which means “to put forward until tomorrow.” It is further deﬁned as “putting off
something (especially unpleasant or burdensome) until a future time; especially to
postpone such actions habitually.” The negative connotation of this deﬁnition has not
always been the way procrastination has been perceived. Historically, in countries where
technology was not yet developed and adherence to was less important, the term
procrastination was not associated with descriptions such as lazy, indolent, or
unambitious. In an achievement-oriented society, however, such terms are routinely
used. ' Ferrari, Johnson, and McGown (1995) suggest that the Romans used the term to
express the notion that “deferring judgement may be necessary and wise, such as when it
is best to wait the enemy out and demonstrate patience in military conﬂict” (p.4).

Phillip Stanhope, the Earl of Chesterﬁeld, in 1749 offered an opinion about
procrastination that echoes modern society’s attitude toward procrastination. He stated
“no idleness, no laziness, no procrastination; never put off till tomorrow what you can do

5

today” (Stanhope, 1749 in Bartlett’s Quotations, 1968). Contemporary writers concur in
spirit with the notion that procrastination is undesirable. Solomon and Rothblum (1984)
deﬁned procrastination as the act of needlessly delaying tasks to the point of experiencing
discomfort. Lay (1986) deﬁned it as an irrational tendency to delay tasks that should be
completed. In our society, productivity and accomplishing are highly valued norms.
According to Haycock, McCarthy, and Skay (1998), procrastinators violate these societal
norms by failing- to get things done (responsibilities, tasks, or decisions) in a timely
manner. They agree with Solomon and Rothblum (1984) that procrastination involves
internal, subjective discomfort usually thought to be anxiety. It is this internal discomfort
that differentiates procrastination from simply deciding to do an activity later.

Milgram, Gehrman, and Keinan (1992) criticized the deﬁnition of procrastination
as requiring both behavioral delay and emotional upset on empirical as well as logical
grounds. They investigated whether students were performing daily life tasks (chores,
appointments) on time and they found only a weak relationship (.13) between behavioral
delay and emotional upset. They also found that students who. scored high on both
behavioral delay and emotional upset reported higher trait anxiety and were more
sensitive to negative events than students scoring low on behavioral delay but high on
emotional upset. They concluded, “procrastination is in the mind of the performer, not in
the eye of the beholder” (p. 198). Milgram (1991) offered his own deﬁnition of
procrastination, which emphasized four components as necessary for a behavior to be
considered procrastination: (1) postponing a behavior; (2) this postponement results in
substandard performance; (3) the task is considered by the procrastinator as being
important to perform; and (4) there is an experience of some level of emotional upset.

6

On logical grounds this multidimensional deﬁnition of procrastination certainly applies to
a large percentage of procrastinators but its generalizability~ is questionable.
Procrastination does not always lead to substandard performance. For many individuals
delaying a task is a deliberate motivational strategy. For others, “functional
procrastination” (Ferrari and Olivette, 1994) is not self-defeating but rather is in one’s
own best interest. For example, it may make sense to avoid paying income tax for as
long as possible to allow for maximum return on investment for the funds. As Milgram
et a1. (1992) just pointed out, not all procrastinators experience signiﬁcant levels of
distress from their dilatory behavior. So it Would appear that two years after offering his
multidimensional deﬁnition, he began to modify it appropriately. It is this writer’s
opinion that Milgram, Weizrnan, and Amiran’s (1991) deﬁnition is extremely accurate
for individuals whose behavior could be considered to have reached “clinical”
proportions. As will be discussed later in this literature review, the issue of severity and
chronicity has been sorely missing from the procrastination research.

Another approach to deﬁning procrastination in the literature is the use of
operational defmitions. This type of deﬁnition typically involves behavioral indices or
psychometric classiﬁcations. A variety of different behavioral measures have been used
to deﬁne academic procrastination including when assignments are turned in, when a
questionnaire is returned, number of self-paced quizzes completed during the last couple
of weeks of the semester (Solomon and Rothblum, 1984; Lay, 1986; Miller, Weaver, and
Semb, 1974). The second and most common way of operationally deﬁning
procrastination is through the use of self-report inventories. Several good inventories
have been developed that assess academic procrastination including the Procrastination

7

‘ Assessment Scale-Students (PASS) (Rothblum, 1984) and the Aitken Procrastination
Inventory (API) (Aitken, 1982); decisional procrastination including the Adult Inventory
of Procrastination (AIP) (McCown and Johnson, 1989); and procrastination of daily tasks
including the General Procrastination Scale (GP) (Lay, 1986). Thetypical procedure is
to administer the inventory and determine “high vs. low” procrastinators using quartile or
mean splits. Ferrari, Johnson, and McGown (1995) point out that an advantage of this
procedure is that it groups the data, which makes them amendable to hypothesis testing
with analysis of variance (ANOVA). A major disadvantage of these self-report
inventories is the extremely limited normative samples. Virtually every respectable
inventory reviewed by Ferrari et a1. (1995) was normed on undergraduate university
students. In addition, not a single inventory of academic procrastination contains any
normative information about the severity of procrastination. As a result these arbitrary
methods of deﬁning procrastination are at best a “stopgap measure” until better
instruments are developed. In summary, although there is some disagreement whether
experiencing emotional upset is necessary for avoidant behavior to be considered
procrastination, there is consensus that procrastination always involves avoidant behavior

that typically results in substandard performance.

Prevalence

Someone once said that only two things in life are certain: death and taxes. The
evidence suggests that there is at least one more --- procrastination. Aitken (1982),
however, observes that if everyone procrastinates at least occasionally, is it even a
problem that warrants investigation? The answer, of course, is “yes.” The universality of

a condition does in no way diminish its need for investigation. Rather one could argue
8

that conditions that affect the largest number of people warrant the most investigation.
Although Aitken’s question clearly was rhetorical, the logic implicit in it would lead us to
ignore, for example, tooth decay simply because it is so common. For those individuals
who procrastinate only some of the time and in limited areas of their lives,
procrastination is most likely not problematic. However, for those individuals who
“habitually” procrastinate, especially on important issues or tasks, procrastination can be
a severe, chronic, and debilitating problem.

To accurately estimate the prevalence of procrastination, it is useful to separate
procrastination rates among student and non-student populations. Most procrastination -
research has focused on students. They offer very convenient samples of research
subjects as well as the functional signiﬁcance of and consequences of procrastinating on
academic tasks (e.g., failing to graduate). As noted earlier, estimates of the percent of
college students who procrastinate range from as low as 22%-33% (Ely and Hampton,
1973; Rosati, 1975) to as high as 95% (Ellis and Knaus, 1977). In one of the early
surveys of student procrastination, Hill, Hill, Chabot, and Barrall (1978) asked 500
students from ﬁve different colleges to rate their procrastination on a ﬁve-point scale.
Their results showed that 27% of the students rated themselves as procrastinating
“usually and frequently.” Another 23% rated their procrastination as occurring “about
half the time” yielding a total frequency of 50%. Another interesting ﬁnding from this
study was the frequency of procrastination increased from freshman to senior year.

To study the personality proﬁles of student procrastinators, Aitken (1982),
developed her own self-report procrastination questionnaire. After administering her
questionnaire to 120 undergraduate students she found reported frequency of

9

procrastination similar to what Hill, Hill, Chabot and Barrall (1978) found in their study.
Twenty-six percent of her sample reported they frequently procrastinated with an
additional 27% procrastinating about half the time.

Solomon and Rothblum (1984) were interested in the frequency of students’
procrastination on academic tasks. They surveyed 342 undergraduates on a variety of
academic tasks including writing a term paper, studying for exams, and reading weekly
assignments. Results indicated that 46% of the subjects reported nearly always
procrastinating on writing a term paper, 27% on studying for exams, and 30%
procrastinate in keeping up with weekly reading assignments. When the students were
asked the degree to which they felt procrastination was a problem for them, 23% reported
it was almost always a problem when writing a term paper, 21% when studying for an
exam, and 23% when doing reading assignments. An additional important ﬁnding of this
study was that there were no signiﬁcant sex differences with regards to the ﬁequency of
reported procrastination. This ﬁnding is consistent with other ﬁndings (Ferrari, 1993;
Flett, Blankstein, Hewitt, and Koledin, 1992; Ferrari, 1991; Ferrari, 1992). Rothblum,
Solomon, and Murakami (1986), extending the work of Solomon and Rothblum (1984),
surveyed 379 university students to investigate cognitive, affective, or behavioral
differences between high and low procrastinators. They found that 40% of their subjects
reported that they nearly always or always procrastinate on exams to the point of
experiencing signiﬁcant anxiety.

Compared to the numerous studies of the frequency of academic procrastination, .
only a few studies report the prevalence of procrastination in the general non-student
population (Ferrari, Johnson, and McGown, 1995). McGown and Johnson (1989), in

10

their study validating an inventory for general procrastination tendencies, found that 25%
of the 146 adults surveyed reported that procrastination was a “signiﬁcant problem” in
their lives.

Harriot and Ferrari (1996) had 212 adults complete measures of decisional and
avoidant procrastination to assess the prevalence of procrastination in the general
community. Decisional procrastination (Effert and Ferrari, 1989) is the purposive delay
in making decisions within a speciﬁed period of time. Avoidant procrastination refers to
the delay in completing important activities of daily living e. g. paying bills, scheduling
appointments. In this study the overall prevalence of procrastination was 20%. An
additional ﬁnding, consistent with the research on academic procrastination, was the
absence of sex differences. The authors suggested that procrastination might decrease
with age since the obtained prevalence rates for older non-student samples are lower than
for students. In support of this hypothesis, McCown and Roberts (1994) found from their
telephone survey that procrastination did tend to decrease across the lifespan for both
sexes with an abrupt increase as individuals entered their sixties.

In summary, the literature consistently found that the prevalence of academic
procrastination is estimated to be somewhere between 30% to 50% of college
undergraduates. There is also no evidence that sex differences exist with regards to its
prevalence. There is also evidence to suggest that ethnicity does not affect the prevalence
of academic procrastination. Clark and Oliver (1994) examined academic procrastination
with African-American students using the Procrastination Assessment Scale-Students
(PASS). Thirty percent of the African-American students reported that they nearly
always or always procrastinate on writing a term paper, 28% when studying for exams,

ll

and 35% when keeping up with reading assignments. These percentages are consistent
with the ones reported earlier by Solomon and Rothblum (1984) using an exclusively
Caucasian sample. The African-American students reported a higher percentage than the
Caucasian students with regards to whether procrastination is always or nearly always a
problem for them. While procrastination among the general population appears to be,
somewhat less than for students, the total percentage of individuals who struggle with this
problem is staggering. For this reason alone it is surprising that the research has only
begun to proliferate in the last 10 years.

Types of Procrastination

 

The predominant methodology in procrastination research to date has been to
choose a type of procrastination (e.g., academic, decisional), administer various self-
report inventories, and then report a variety of correlates of procrastination including
psychological, cognitive, and personality factors. Such descriptive ﬁeld approaches to
procrastination (Heppner, Kivlighan, & Wampold, 1992) have not been fruitless. The
procrastination literature provides clear evidence that these factors are integrally involved
for the majority of procrastinators. The following literature review will ﬁrst address a
representative sample of research on decisional procrastination and general
procrastination of daily living. This will be followed by a more exhaustive review on the
more heuristically rich area of academic procrastination. Finally a critique of the
literature will be presented, setting the stage for the issues addressed in this study.

Procrastination of Daily LlViﬂ. In contrast to academic procrastination, which

 

deals with exclusively academic behaviors, procrastination of daily living (PDL) is less
speciﬁc and pertains virtually to all tasks that are involved in obtaining personal and

l2

professional goals. The questionnaires that assess the individuals propensity for PDL
will inquire about tasks such as paying bills, doing the dishes, punctuality, setting
appointments, and returning phone calls, to name just a few. PDL is also referred to in
the literature as procrastination of everyday life (Milgram, Sroloff, and Rosenbaum,l988)
and procrastination of daily routines (Milgram, Gehrman, and Keinan, 1992).

In a study in which he developed the General Procrastination Scale (GP), Lay
(1986) was interested in examining the “individual and situational correlates of
procrastinatory behavior.” In addition to completing the GP, students completed scales
assessing neurotic disorganization, organization, energy level, self-esteem, achievement,
and desirability. The author also included a behavioral measure that involved the
subjects mailing a questionnaire back to the investigator aﬁer completing it. Using a
median split procedure, high procrastinators tended to score high on neurotic
disorganization scale and low on the organization scale. Procrastination scores were
unrelated to academic achievement, energy level, and self-esteem.

Milgram, Sroloff, and Rosenbaum (1988) also investigated the procrastination of
everyday life. The authors argue that deﬁning exactly what is considered procrastination
with routine life tasks is inherently more difficult than deﬁning academic procrastination.
Milgram et a1. conceptualize procrastination of daily tasks to a trait rather than a state
characteristic. Subjects completed a procrastination questionnaire and several personality
measures assessing self-regulation, Type A behavior, and life satisfaction. Consistent
with other research (Solomon & Rothblum, 1984), procrastination was greater on tasks
regarded as unpleasant or impositions. Procrastination was also negatively related to
self-regulation, Type A behavior, and life satisfaction.

13

Milgram, Gehrman, and Keinan (1992), continuing with their programmatic
research, investigated the relationship between procrastination and emotional upset. As
discussed earlier, there are varying opinions about whether emotional upset is required
for a behavior to be considered procrastination rather than just waiting until a later time
to perform a task. Subjects in Milgram et al’s study were divided into 4 groups along two
dimensions: high vs. low procrastinators and high vs. low manifest emotional upset. Two
additional personality variables, repressor/sensitizer (W8) and pessimism, were also
assessed because they were hypothesized to be antecedents to procrastination. The R/S
variable refers to one’s perceptual threshold for a threatening event as well as the degree
of approach/avoidance to the event. Sensitizers who are characterized by low threshold
for and avoidance of a threatening event are thought to be more likely to procrastinate
regarding routines of daily living. Pessimism refers to a cognitive-affective expectancy
that things will turn out badly, which in turn leads to avoidant behavior. Level of
emotional upset was obtained by having the subjects report how upset they believe they
would get over procrastinating on 19 activities of daily living. The authors hoped to
develop a typology that delineates the relationship between procrastination and manifest
emotional upset. Manifest emotional upset and procrastination of daily events were only
mildly correlated while procrastination was unrelated to pessimism and S/R. This
supports the argument that not all procrastinators experience high level of emotional
upset about their behavior. A factor analysis divided the subjects into 4 different proﬁles
combining the two primary variables in this study (high vs. low procrastination, high vs.
low manifest emotional upset). These groups differ in their personality traits. The most
interesting ﬁnding is that the largest group from the factor analysis consisted of subjects

14

who were low in procrastination and high in manifest emotional upset. These “prompt”
individuals’ level of emotional upset seems to stir them on to avoid procrastination rather
than bog them down into behavioral delay. The next largest group of subjects fell into

the high level of procrastination and low level of emotional upset further establishing that
emotional upset does not appear to be a necessary condition for deﬁning what is
considered to be procrastination. These ﬁndings indicate that conCem about behavioral
delay is associated with poorer psychological adjustment in procrastinators and better
psychological adjustment in low procrastinators. One obvious problem with this study is V
that it used subjects who were imagining procrastinatory behavior rather than those
individuals who were struggling with this behavior.

Milgram and Naaman (1996) attempted to replicate the ﬁndings from the study
just reviewed, which had suggested a weak relationship between procrastination of daily
tasks and emotional upset or concern. They were also interested in determining whether
the same relationship between procrastination and emotional upset applied to academic
procrastination. Results indicated that delay and upset about delay were unrelated for
both daily life and academic procrastination. As before, the students were assigned to
one of four subgroups using median split procedure according to their respective levels of
delay and concern. The relationship between expressed emotional upset and
procrastination status was replicated with concerned procrastinators reporting poorer
adjustment and low procrastinators showing better adjustment. Procrastinators showing
low levels of emotional concern were described as having lower levels of aspiration

compared to concerned procrastinators.

15

Ferrari (1992) hypothesizes that perfectionistic tendencies play a moderating role
in procrastinatory behavior. Others have also identiﬁed perfectionism as being positively
related to procrastination (Frost, Marten, Lahart, and Rosenblate, 1990; Ashby, Mangine,
and Slaney, 1995; Flett, Blankstein, Hewitt, and Koledin, 1992). Ferrari was primarily
interested in whether perfectionistic tendencies were 1) associated with procrastination of
daily tasks and 2) whether procrastinators compared to non-procrastinators engaged in
perfectionistic tendencies for different reasons. As predicted, procrastinators reported
signiﬁcantly more perfectionism than non-procrastinators. Secondly, procrastinators do
appear to engage in perfectionistic behavior for different purposes than non-
procrastinators. For procrastinators the motive for “perfect behavior” is aimed at
impressing others, which is consistent with a “protective” self-presentation style. By this
it is meant that their “perfeCt behavior” is motivated by anxiety over what others think
about their performance. In contrast, non-procrastinators’ perfectionism appears to be
motivated by a desire to produce a “ﬂawless product” rather than by external social
factors such as approval. The ﬁndings of this study are consistent with other research
(Ferrari, 1991), which demonstrates that procrastinators attempt to avoid’negative
feedback about self.

Donovan (1995) takes quite a different approach to exploring procrastination of
everyday life. He points out that while anthropologists frequently apply psychological
theories to their investigations, they are reluctant to incorporate psychological assessment
instruments to help quantify their ﬁndings. The author proposed a relationship between
death anxiety and general procrastination. He predicted that individuals preoccupied with
their own mortality (high death anxiety) would exhibit a lack of motivation for competing

l6

tasks of daily living. This lack of motivation could manifest itself behaviorally as
“chronic procrastination.” While “chronic” was not deﬁned, he did argue that there is
literature to support the notion that on a broad level both death anxiety and O
procrastination involve altered perceptions of time. Procrastinators tend to underestimate
the amount of time a task will take (Lay, 1986), and individuals with death anxiety
experience a sense of time shortening. Donovan used two self-report inventories to test
his hypothesis that procrastination is a proxy for death anxiety. Results indicate a very
weak, but signiﬁcant, positive correlation between procrastination and death anxiety.
Those individuals experiencing high death anxiety tended to be procrastinators. The
author astutely points out that perhaps the small correlation is because procrastination is
not simply a motivational deﬁcit but a more complex construct.

Decisional Procrastination. In contrast to academic procrastination and

 

procrastination of daily living, which have been labeled in the literature as behavioral
forms of delay (Effert & Ferrari, 1989), decisional procrastination in considered a
cognitive type of delay. Also called “neurotic indecision,” it has been deﬁned as the
intentional delay in making decisions within some speciﬁed timeframe. Like other forms
of procrastination, the individual typically experiences some form of discomfort because
of the delay.

Janis and Mann (1977) argue that decisional procrastination is an antecedent of
behavioral delays, which typically represent a pattern used to avoid dealing with
situations perceived as stressful. They suggest that putting off a decision until either time
runs out or the decision is made for the procrastinator allow failure to be attributed to
factors outside the individual thereby protecting a fragile self-esteem. As will be seen in

17

this review, decisional procrastination has been related to a variety of cognitive, affective,
and personality variables.

Effert and Ferrari (1989) were interested in the personality correlates of decisional
procrastination - the tendency to avoid making decisions within a speciﬁc time frame. In
a correlational study subjects completed several personality inventories. The authors
found that decisional procrastinators reported low self—esteem, a propensity for cognitive
distortions (e.g., forgetfulness), and a tendency to misj udge the time needed to complete a
task. More speciﬁcally, these procrastinators underestimate the time needed to
complete a task by failing to think about all aspects of the decision. This results in the
person needing to work faster to complete the task. This will often lead to poor
performance, Which reduces self-esteem.

Ferrari (1992) studied female "compulsive procrastinators" with an interest in
identifying self-reported personality characteristics. Measures administered included
scales of both decisional and behavioral (daily tasks) procrastination, self-esteem, self-
consciousness, self-handicapping, intelligence, and identity style. Compulsive
procrastination was deﬁned as those subjects scoring one standard deviation above the
sample mean on two procrastination inventories. Results indicated that when compared
with nonprocrastinators, procrastinators claimed lower self-esteem, greater public self-
consciousness, greater social anxiety, and more self-handicapping tendencies.
Procrastinators also were less information oriented, had a stronger tendency toward a
difﬁrse identity style, and showed no difference in verbal or abstract intelligence.

Ferrari (1991) continued his investigation into the various ways that
procrastinators avoid not only tasks, including decisions, but in doing so avoid obtaining

18

feedback about their own abilities or lack there of. Ferrari conducted two studies. The
ﬁrst presented correlational data regarding personality variables. The second was an
experimental study that looked at whether procrastinators would choose a performance
task that would allow them to avoid any self-relevant information about their ability. As
expected, the correlational data showed that decisional procrastination was related to a
variety of dysfunctional decision making styles including defensive avoidance (ignoring
important information), rationalization (making excuses for avoiding information), and
buck passing (reliance on others to make the decision). Procrastination was also related
to diffuse-identity orientation and overconcern for social appropriateness.

In the experimental part of the study subjects were identiﬁed as either high or
non- procrastinators using a median split procedure and then randomly assigned to one of
two conditions. In the ﬁrst condition, Group A, students were told that they would be
given information about their performance on a cognitive task of their choosing (either an
easy or difficult task). The subjects in the second condition, Group B, were told that their
scores would be combined with everyone else’s scores, so that no personal information
about performance would be given. Results indicated that both procrastinators and non-
procrastinators prefer to choose easy tasks, however, only the procrastinators avoided any
information about performance regardless of task difﬁculty level. Ferrari concluded that
the stronger the tendency to procrastinate, the stronger the tendency to both avoid making
decisions as well as obtaining diagnostic information about oneself. He argued that this
supports Burka and Yuen’s (1983) popular theory that procrastinators go to any length to

protect their fragile self-esteem.

l9

Ferrari and McCown (1994) investigated the relationship between Obsessive
Compulsive Disorder (OCD) and procrastination tendencies. Citing Burka and Yen
(1983), who argue that anxiety and fear of failure are primary motives for chronic
procrastination in that they protect a fragile self-esteem, the authors wondered if the fear
and anxiety that individuals with OCD experience would be related to the fear and
anxiety individuals experience who struggle with decisional and/or behavioral
procrastination. Results indicate that obsessional thoughts are related to decisional but
not behavioral procrastination whereas compulsive acts were related to both types of
procrastination.

In addition to the prevalence of procrastination among the general adult
population, Harriot and Ferrari (1996) were particularly interested in avoidant, arousal,
and decisional procrastination. Avoidant procrastination is similar to general behavioral
delay also referred to as procrastination of daily life. Arousal procrastination seldom
appears in the literature and refers more to a reason for, rather than a distinct categbry of,
procrastination. Arousal procrastination has to do with putting things off as a way to
avoid boredom. These individuals put off tasks until the last moment to create a self-
irnposed time pressure that heightens their arousal and the “rush” of ﬁnishing just under
the deadline. These individuals have also been referred to as a sort of thrill seeker
(Ferrari & Emmons, 1995).

A battery of procrastination inventories and demographic information was
solicited ﬁ'om adults from varying career ﬁelds who attended a free lecture on
procrastination. In this study by Harriot and Ferrari (1996), 20% of the respondents
claimed to procrastinate to a signiﬁcant degree. When compared to the earlier reported

20

rate for college students the results suggest that perhaps procrastination tends to decrease
with age. However, to some degree this may be comparing apples and oranges because
the prevalence rates for college students are-based upon delaying completion of academic
tasks, not on the more general procrastination assessed with this study’s sample. They
also found some demographic differences in their sample. Higher rates of decisional
procrastination were reported by non-college educated individuals. In addition, higher
rates of procrastination were reported by individuals who had been married but are were
no longer, either due to divorce, death, or separation.

The developmental roots of “dysfunctional” procrastination in college age women
were the topic of investigation for Ferrari and Olivette (1994). These authors coined the
term “dysfunctional” to refer to decisional and avoidant forms of procrastination. A
“dysfunctional” procrastination score was obtained by summing the decisional and
avoidant scores. Using Baurmind’s (1971) typology of parenting styles, Ferrari and
Olivette were interested in whether procrastination tendencies were formulated as a result
of the type of parenting an individual was exposed to while growing up. Baurmind
identiﬁed 3 parental authority styles. A permissive parental authority style is
characterized as warm and less apt to use punishment. Children of this parenting style
tend to lack self-reliance and inquisitiveness. Authoritarian parenting styles control their
children through harsh punishment and tend to produce children who are unhappy,
withdrawn, and distrustful. The ideal parenting authority style is referred to as
authoritative and can be characterized as exerting a high degree of control but also
encouraging autonomy in appropriate areas. Children raised with an authoritative
parenting style tend to be self-reliant, self-controlled, and inquisitive.

21

The authors were interested in whether these different parental authority styles

. were correlated with decisional procrastination (putting off decisions) and avoidant
procrastination (putting off tasks). They hypothesized that authoritarian parenting styles
would promote higher levels of decisional and avoidant procrastination. They argued
that such procrastination would be a safe indirect way to rebel against the controlling
demands of the parent. Both mothers and fathers participated in this investigation.
Results conﬁrm that the home environment is a major source for the development of
chronic procrastination tendencies. Authoritarian and authoritative fathers were positively
and negatively associated with procrastination in their daughters respectively. The
author’s used a median split procedure to group the subjects into 2 groups: dysfunctional
procrastinators and nonprocrastinators. The dysfunctional procrastinators had mothers
who were reported to be decisional procrastinators themselves. Finally, dysfunctional
procrastinators reported higher levels of anger and anger suppression supporting the
notion that the procrastination may be a passive—aggressive reaction to an authoritarian
parenting style.

Ferrari and Emmons (1995) examined whether decisional and/or behavioral
procrastination was related to self-control and frequency of self-reinforcement. Self-
control refers to an individual’s ability to delay gratiﬁcation. It is reasoned that
individuals with high levels of self-control or restraint will be better able to endure
unpleasant tasks and may procrastinate less. Self-reinforcement is the process of an
individual rewarding themself for engaging in desired behaviors. Self-reinforcement can
take the form of positive statements made to oneself (e.g., I did a great job) or it can take
the form of allowing oneself to engage in a certain behavior (e.g., shopping). It was

22

hypothesized that procrastinators would show a tendency for less frequentself-
reinforcement. In this study college students completed several inventories with analysis
indicating a negative relationship between both kinds of procrastination and both self-
control and self-reinforcement. These results suggest that students will procrastinate
because of diﬁ'rculty deferring more immediate gratiﬁcation.

Academic Procrastination. From even a brief perusal of the literature, one can see

 

that the overwhelming majority of investigations address academic procrastination. It has
been my observation that less than 10% of all investigations of procrastination, regardless
of its type (e.g., decisional), have used non-students for their samples. Since virtually all
empirical work has been on college samples with an approximate mean age of 20-22
years old, one could argue that all procrastination research has been research on the
young academic procrastinator. Common sense tells us that academic procrastination
refers to putting off doing tasks directly related to successfully completing educational
goals. These delays can cover a wide range of tasks including (1) postponing the time
one intends to begin studying, (2) postponing the moment one actually begins to study,
(3) doing things other than studying, (4) turning in assignments past deadline, and (5)
producing less than optimal quality work.

There has been much fanfare in the literature on the issue of trait vs. state
procrastination. Academic procrastination has typically been regarded as a task-speciﬁc
behavior rather than a generalized trait (Ferrari et al., 1995). Consequently, most of the
early research focused on identifying the skills that needed remediation e.g. time
management or study habits. The state/trait distinction in the procrastination literature is
ambiguous. Part of that may be due to the nature of procrastination and part may be due

23

to the subjects that have been studied. For those who treat procrastination as a stable
personality trait, the question is how stable are personality traits in very young adults? If
trait procrastination is to be considered a “habit” that is manifest across different
situations and over time (Senecal, Lavoie, & Koestner, 1997), then it is my opinion that
virtually all academic procrastinators are trait procrastinators. Perhaps in time the
state/trait distinction will become a useful one. But until research samples become more
representative of adults in general or our theories of procrastination are better articulated,
the distinction will continue to be arbitrary.

As will be seen in the following section, academic procrastination has been
conceptualized in a variety of ways. The diversity of the research into academic
procrastination clearly suggests that it is a much more complex phenomenon than simply
a situation speciﬁc skill deﬁcit. There are cognitive, affective, and behavioral factors
involved in all forms of procrastination including those that are academic in nature.

Multiple Factor Studies. Solomon and Rothblum (1984) examined self-reported

 

academic procrastinators in an attempt to establish procrastination as more than simply a
deﬁcit in study skills and time management. Introductory psychology students were
asked to complete a battery of questionnaires measuring self-esteem, anxiety, study
habits, assertion, procrastination, depression, and irrational cognitions. The researchers
also included a behavioral task (self-paced quizzes) to provide a further measure of
procrastination. The self-report measure of primary interest in this study was the
Procrastination Assessment Scale - Students (PASS). It consists of two sections. The

ﬁrst section assesses the prevalence of procrastination in six academic areas (e.g. writing

24

an essay, studying for an exam). The second section presents scenarios and asks subjects
to identify possible reasons for procrastinating on the task presented in the scenario.

Factor analysis of subjects’ reasons for procrastinating identiﬁed two factors, fear
of failure and task aversiveness, accounting for the largest variance in their sample. The
investigators tabulated frequency of endorsement of reasons for procrastination and were
able to identify two distinct sub-groups of procrastinators. The fear of failure group
reported more depression, more irrational cognitions, more anxiety, low self-esteem, and
lack of assertion. The task aversiveness group was a larger and more heterogeneous
group. Individuals who procrastinated because of task aversiveness can be distinguished
from those who procrastinate because of fear of failure by'the absence of high trait
anxiety and low self-esteem.

McKean (1994) offered an intriguing explanation for academic procrastination.
Extrapolating from Seligman’s (1975) learned helplessness model, McKean suggested
that procrastination could be .a behavioral manifestation of “academic helplessness.” By
this he refers to a “self-defeating pattern involving a rather passive, maladaptive response
to a negative event.” (p.456). According to Seligman’s learned helplessness model,
people seek to explain to themselves the positive and negative outcomes they experience.
The explanations that people develop are based on 3 dimensions. A person will explain
an outcome by attributing it to causes that are (a) internal or external, (b) global or
speciﬁc, and (c) stable or unstable. Individuals will tend to develop characteristic ways
of explaining events along these 3 dimensions. Students who believe that academic
setbacks are caused by factors inside themselves (internal), that will affect many of their
academic activities (global), and which are long lasting (stable) will give up when faced

25

with future setbacks. A student developing academic helplessness in reaction to failing to
study effectively would typically engage in self-talk as follows: “I was not able to do it
because I lack ability, this will affect all my classes, and it’s always going to be this
way.” McKean believes that this type of attributional style leads to style of passive non-
responsiveness. One particularly damaging form this passive style can take is
procrastination. Among these'students, procrastination does not simply result from poor
time management skills, or lack of appreciation of the demands involved in completing
the task. Rather it is the “embodiment of their helpless non-responsiveness, borne of the
belief that the task itself is beyond their efforts. to control or complete it.” (p. 458).

McKean (1993) investigated the hypothesis that students at risk for academic
helplessness would procrastinate more than low risk students. One hundred seventy-eight
undergraduates completed scales that identiﬁed them as either high or low risk for
academic helplessness. As predicted the high-risk group reported signiﬁcantly higher
rates of academic procrastination, offering support that procrastination may be a
behavioral manifestation of academic helplessness.

In this next study the authors investigated the relationship among self-efﬁcacy,
anxiety, and academic procrastination. Haycock, McCarthy, and Skay (1998) argue that
self-efﬁcacy plays a role in whether people initiate and are persistent in completing
behaviors. The link between anxiety and self-efﬁcacy is intuitively clear in that one
would expect a person with weak efficacy expectations either about their own ability or
the likelihood of a desired outcome to experience a signiﬁcant level of anxiety. As
hypothesized, procrastination scores were signiﬁcantly related to self-efﬁcacy and
anxiety. Procrastination was negatively correlated with self-efﬁcacy and positively

26

related to anxiety. Multiple regression analysis was conducted to evaluate the unique
Contributions of variance that self-efficacy and anxiety contributes to procrastination in
this study. As expected, self-efﬁcacy was a signiﬁcant contributor to the variance in
procrastination, but unexpectedly, after the variance due to self-efﬁcacy was controlled
for, anxiety did not contribute signiﬁcantly to the variance in procrastination. The
authors hypothesize that anxiety affects self-efﬁcacy, which in turn affects
procrastination. A strength of this investigation is that it offers a concrete approach based
on self-efﬁcacy theory to treating academic procrastination.

Cognitive Factors. Ferrari, Wolfe, Wesley, Schoff and Beck (1995) investigated

 

the relationship between Ego-identity status and academic procrastination. Ego-identity
status refers to the way individuals process self-relevant information and make personal
decisions. Originally proposed by Berozonsky (1990), this social-cognitive model
identiﬁes two distinct orientation or identity styles: information-oriented and
diffuse/avoidant. While information-oriented individuals purposely seek self-relevant
information, diffuse/avoidant individuals take a more defensive approach to information
seeking. Diffuse/avoidant individuals are reluctant to deal with problems and decisions,
ultimately necessitating them to be more spontaneous rather than planful. These authors
were interested in whether identity styles were associated with procrastination. They
hypothesized that a diffuse/avoidant style would be positively associated with academic
procrastination. Results conﬁrmed the people with a diffuse-avoidant identity style are
more likely to engage in academic procrastination than an information-oriented identity
style. The information-oriented individuals also reported levels of procrastination higher
than the investigators expected. They attempt to explain that the motivation for the

27

procrastination among information-oriented individuals is different from that of the
diffuse/avoidant individuals. They reason that the information-oriented individuals wait
to complete tasks until the last minute in order to experience the “rush or thrill” or
working against a time limit. In other words the information-oriented individuals
procrastinate “on purpose” in order to motivate themselves and increase the sense of
accomplishment.

Like Solomon and Rothblum (1984), Ferrari, Parker, and Ware (1992) believe
that academic procrastination is not just a behavioral tendency to delay or mismanage
school-related tasks but rather “encompasses cognitive and affective components” (p.
496). In this study the authors attempted to determine if such factors could be identiﬁed
that could predict academic procrastination. The Myers-Briggs Type Indicator (MBTI) is
a popular personality inventory used extensively in academic settings for such tasks as
academic advising, career development, psychological counseling, and learning styles
(Provost & Anchors, 1987). In addition to the MBTI, this study assessed the relationship
between academic procrastination and two other cognitive variables, self-efﬁcacy and
locus of control. Students enrolled in an Associate of Arts program volunteered to
complete several inventories as part of their freshman orientation seminar. Results from
this “non-clinical” sample indicate that academic procrastination may not be predicted
ﬁom the personality factors identiﬁed by the MBTI. Additionally, scores on the
procrastination inventory were not correlated with academic locus of control. However,
scores were negatively correlated with general self-efﬁcacy suggesting that
procrastinators believe that they have little mastery over their own behavior and that they
are ineffective at mastering general life events.

28

Vodanovich and Seib (1997) were interested in the relationship between academic
procrastination and the ability for individuals to structure their time. A large sample of
undergraduate students completed a Time Structure questionnaire and a procrastination
inventory. Results show a signiﬁcant negative relationship between procrastination and
scores on the time structure questionnaire. The time structure questionnaire yields 5
subscales related to Sense of Purpose, structure routine, present orientation, effective
organization, and persistence. The subscale with the highest negative correlation with
procrastination was the effective organization scale. Stepwise multiple regression
indicated that the effective organization subscale was the best predictor of
procrastination. The effective organization subscale assess one’s “activity, organization,
and motivation” (p. 214). The fact that this subscale best predicts procrastination is not
surprising if it is placed within the context of being suggestive of relatively poor
executive functioning.

Several authors have proposed a link between academic procrastination and
irrational beliefs (Ferrari & Emmons, 1994, Solomon & Rothblum, 1984, Beswick,
Roghtblu, & Mann, 1988) however, these studies have suggested that the link is weak or
non-existent. Bridges and Roig (1997) re-exarnined the link between irrational thinking
and academic procrastination because “context effects” potentially contaminated the
earlier ﬁndings. They cite research (Council, 1993) that suggests that when multiple self-
report inventories are given at the same time, the subjects infer a relationship among
them and adjust their responses accordingly. Administering the inventories one at a time
at different points in time can eliminate these context effects. Bridges and Roig (1997)
administered the Procrastination Assesment Scale - Students and the Irrational Beliefs

29

Inventory (IBI) (Koopmans, Sanderrnan, Timmerrnan, and Emmelkamp, 1994) at
separate times with separate investigators. Results found a small but signiﬁcant positive
correlation between self-reported procrastination and the global IBI score. A stronger
positive correlation was found between procrastination and the problem avoidance
subscale of the IBI. Surprisingly, the IBI worrying subscale was not related to
procrastination, a ﬁnding for which the authors had no explanation.

F lett, Blankstein, Hewitt, and Koledin (1992) examined the potential signiﬁcance
of perfectionism as a model for procrastination. They posit that some of the
inconsistency with earlier research into perfectionism had to do with treating the
construct as unidirnensional in nature. Was perfectionism referring to an individual
having extremely high expectations for themself (self-oriented)? Did it refer to person
expecting ﬂawless performance from others (other-oriented)? Or did it refer to others
expectation for superior performance from us (socially prescribed)? F lett et al. (1992)
note the development of new multidimensional measures of perfectionism which will
allow for better clariﬁcation of the relationship between procrastination and
perfectionism. Using one of those new measures, they examined the relationship
between perfectionism, general procrastination, and academic procrastination. As
expected, socially prescribed perfectionism was positively related to both general and
academic procrastination. A frequently cited explanation for procrastination, fear of
failure, was also positively correlated with socially prescribed perfectionism.

Affective Factors. Milgram and Sadeh (1994) were interested in the relationships

 

between 5 aspects of academic procrastination: behavioral delay, personal upset about the
delay, how aversive the task is perceived, how capable one feels about doing the task, and

30

the desire to reduce behavioral delay in the future. In their sample of Israeli high school
students they found that how much students delayed on a task was only weakly related to
how upset they were about delaying. Students delayed more on academic tasks that were
labeled unpleasant regardless of how capable they felt in accomplishing them. The
participants were much more willing to admit to procrastinating for reasons that was least
threatening to their self-esteem (e. g. problems in time management) than to reasons that
was more threatening (e.g. lack of ability). Finally, the single strongest predictor of
desire to change delaying behavior was feeling a sufﬁcient degree of personal upset about
procrastinating. While this study established that not all procrastinators are bothered by
their behavior, the authors did not explain why this was so. One possible explanation is
that these students did not represent a sample of students’ self-reporting procrastination
problems but rather were responding to hypothetical academic tasks.

Lay (1994) was also interested in the emotional experiences of procrastinators.
The two emotions he was most interested in are anxiety (agitation) and depression
(dejection). The rule of thumb has been to assume that procrastinators generally
experience anxiety while delaying the completion of a task and dejection after the fact
when reﬂecting upon their dilatory behavior. Lay was interested in clarifying the anxiety
before and depression after procrastination hypothesis. Seventy-eight undergraduates
completed a variety of inventories before and after a writing assignment that required
them to write down thoughts and feelings about past study habits. Unexpectedly,
multiple regression analysis suggested that the agitation/dejection relationship is
reversed. In this sample, dejection is the principle affective reaction when contemplating
upcoming tasks and agitation appears more prominent in retrospection. I did not ﬁnd this

31

result too surprising. Given that academic procrastinators develop lower efficacy
expectations about their performance abilities (Haycock, McCarthy & Skay, 1998), one
would expect dysphoric feelings about beginning future tasks. In addition, it has been
established that procrastinators are overly concerned with appearing competent even to
the point of choosing easy tasks that do not build self-conﬁdence. As a result it is
reasonable to expect procrastinators to experience anxiety when disclosing prior incidents
of signiﬁcant task delays thereby exposing their “dirty secret.”

Lay’s ﬁnding do not establish deﬁnitively that anxiety is not a precursor to task
avoidance and delay. Rothblum, Solomon, and Murakami (1986) evaluated students at
three different times during the course of a semester to assess cognitive, behavioral, and
affective characteristics of procrastinators. Self-reported procrastinators were found to
report higher levels of test anxiety, weekly state anxiety, and anxiety related physical
symptoms. What Lay’s frndings do is suggest that the affective experiences of
procrastinators are more complex than ﬁrst thought.

Typological Approaches. McCown and Johnson (1991) attempted to classify

 

procrastinators into different types based upon personality variables. These authors used
the typology for academic procrastinators developed by McCown, Johnson, and Pretzel,
(1989), which is drawn from Eyesenck’s personality factors of psychoticism,
extraversion, and neuroticism. The Type I procrastinator, which is related to the
Eysenckian factor of psychoticism (P), is characteristically impulsive and anti-

. authoritarian and tends to resist deadlines imposed by. others. Type 11 individuals are
characterized by extraversion (E) and neuroticism (N), tend to be overly conﬁdent in their
ability to perform expected tasks in the allotted time, and ﬁnd themselves running out of

32

time. Type III procrastinators are characterized by high N, low E, and show low self-
conﬁdence in their abilities and are prone to negative affect such as depression. The
current study looked at these factors and their relationship to measures of study behavior
in university students during ﬁnal exams week. A strong point of this study is that the
authors attempted to operationally deﬁne “chronic procrastination” in their sample. They
deﬁned chronic procrastinators as those students who at the time of ﬁnals week were well
behind in obtaining experimental credits for the psychology class. Additionally, only
students who scored in the top quartile on a self-report procrastination inventory were
included in this study.

This attempt to objectively deﬁne the chronicity of procrastination is sadly
missing in the literature in general. However, it is not clear that McGown and Johnson’s
(1991) operational deﬁnition adequately addresses the issue of chronicity. Rationally,
their inclusion criteria address more directly the issue of severity, which is also
conspicuous by its absence in the literature. The author’s inclusion criteria do not address
how long, in a general sense, these students procrastinate to this level of severity. Results
were obtained in the expected directions. In this group of identiﬁed procrastinators, the
Eysenckian factors of N, P, and E were associated with actual study behaviors in the
direction that the factors would predict. For example, N was associated with higher
levels of anxiety regarding exams and a lack of conﬁdence in preparation consistent with
the Type III procrastinator.

Consequences of Academic Procrastination.

 

Roig and DeTommaso (1995) investigated the possible link between
procrastination and academic dishonesty (plagiarism and cheating). Their subjects, from

33

a private 4-year university, demonstrated a small but positive correlation between
cheating, plagiarism, and procrastination. Subjects’ scores on all inventories were
divided into three groups using the method of extreme groups in an attempt to compare
“high vs. low procrastinators.” This was done by dividing the distribution of
procrastination scores into thirds and then comparing the top versus bottom third.
Separate 2x2 analyses of variances of the cheating and plagiarism scores yielded no
signiﬁcant effects for cheating. The analysis was signiﬁcant for plagiarism with a main
effect for high vs. low procrastinators but not for sex. The authors cautiously conclude
that procrastination may play a role in academic dishonesty.

Tice and Baumeister (1997) investigated the potential costs and beneﬁts of
procrastination to health, stress, and performance, using a longitudinal approach to the
study of academic procrastination. By incorporating behavioral measures (when a term
paper was turned in) in addition to self-report inventories, the authors were able to obtain
a more detailed look at this disabling behavior. Results from this group of 44
undergraduate students indicated that there was a strong positive correlation between
scores on the procrastination inventory and the date when the term paper was turned in.

As expected, procrastinators turned in their papers later than non-procrastinators.
A median split procedure was used to identify procrastinators and non-procrastinators.
Procrastinators also received signiﬁcantly lower grades on the term paper and on two
exams. An additional ﬁnding was that procrastinators reported signiﬁcantly less stress
and fewer physical ailments early in the semester compared to non-procrastinators.
However, this trend reversed by the end of the semester. By that time procrastinators
were reporting signiﬁcantly more physical symptoms, stress complaints, and visits to the

34

student health center. The authors suggest that this study shed light on the beneﬁts and
costs of academic procrastination. Despite the apparent short-term beneﬁts of
procrastination, the long-term costs far outweigh these beneﬁts. They conclude that
procrastination “cannot be regarded as either adaptive or innocuous. Procrastinators end
up suffering more and performing worse than other people” (p.458).

Experimental Studies.

 

As noted earlier in this literature review, virtually all studies of procrastination
have used non-experimental correlational research designs. Also relatively rare in this
area of research is the use of behavioral measures of procrastination. The typical study
employs self-report measures for assessing both procrastination and the various other
variables researchers have been interested in. There are some notable exceptions where
the investigators used objective measures to evaluate procrastination, such as tracking the
number of lessons completed in a self-paced course is an example of a behavioral
measure. Others have asked subjects to mail back an envelope by a designated date as
their objective measure. Over the past 8 years, there have begun to appear experimental
investigations into procrastination that incorporate objective measures to back up the self-
report inventories, thus potentially improving the construct validity of programmatic
procrastination research. I

Milgram, Weizrnan, and Raviv (1991) examined the relationship between a new
behavioral measure of academic procrastination and three personality traits (self—control,
passive-aggressiveness, and test anxiety). The authors selected these three traits because
they have been theoretically and empirically implicated in procrastination. Female
college students were randomly assigned to one of eight experimental conditions during

35

which they were instructed to complete a task over four consecutive nights. In addition,
they completed a small battery of personality tests. Unlike any study reviewed to this
point, no self-report measure of academic procrastination was utilized. Instead,
procrastination was deﬁned as the “cumulative delay of students in complying with the
instructions to complete a test battery consisting of performance tasks at a scheduled time
over a number of sessions” (p.125). In others words, students were timed each night to
quantify how long they delayed in starting and completing the experimental tasks.

As predicted, students with low self-regulation ability and high test anxiety
showed longer delays on the behavioral procrastination measure. The correlation
between the behavioral procrastination measure and passive-aggressiveness was not
signiﬁcant. Passive-aggressiveness was correlated with test anxiety but not with self-
control. Analysis of Variance indicated several interactions among the three personality
variables providing evidence that both personal trait as well as situational factors effect
academic procrastination.

Continuing with this type of investigation, Senecal, Lavoie, and Koestner (1997)
used an experimental design including a behavioral measure to look at personal and
situational factors in procrastination. They speciﬁcally were interested in how
procrastinators would manage their time in a laboratory analogue of a real-world
situation. Rather. than looking at self-control, test anxiety, and passive-aggressiveness,
they wanted to establish what effect performance evaluation and frame of reference had
on procrastination. They hypothesized that students would procrastinate more when they
expected to be evaluated and when the frame of reference was focused on skills rather
than interests. The subjects were randomly assigned to one of four conditions in a 2

36

(anticipated vs. not anticipated evaluation) X2 (interest vs. performance-based frame of
reference) factorial design. Procrastination was behaviorally deﬁned as the latency to
begin the most aversive task as well as the total time to complete the four tasks.

As expected, students. who described themselves as trait procrastinators on the
self-report inventory, took more time overall to complete the task and also took the
longest time to start the most aversive task. This was particularly true when they were
expecting their performance to be evaluated. In contrast, being evaluated did not
negatively inﬂuence low-trait procrastinators. The authors suggest that their ﬁndings
support the popular “fear of failure” explanation of procrastination. They further argue
that procrastination is so widespread in academic settings because performance feedback
is so frequent. Finally, because no main effects, only interaction effects were found,
Milgram, Dangour, and Raviv’s (1991) statement that procrastination is mediated by
both state and trait factors is supported.

Summary/Critique.

 

The procrastination literature has been heuristically rich as evidenced by the.
proliferation of investigations over the last 15 years. Research on the various correlates
of different types of procrastination has yielded important ﬁndings but it also reveals
signiﬁcant disorganization that is present in this area of investigation. Staats (1991) notes
that fragmentation and diversity in methodology, theoretical language, and perspectives
are indigenous to sciences early on their pathways to uniﬁcation.

Three issues that are important to the objectives of this dissertation are

symptomatic of the fragmented approach currently employed to studying procrastination.

37

1. Object of Study. From a review of the literature a dichotomy emerges

 

regarding the "object" of investigation. Various studies (Effert & Ferrari, 1989; Solomon
& Rothblum, 1984; Milgram, Sroloff, & Rosenbaum, 1988; Milgram, Dangour, & Raviv,
1991) focus on investigating speciﬁc types of procrastination (e.g., academic, decisional,
routine life tasks), while others (Ferrari, 1991; McCown & Johnson, 1991; Muszynski &
Akamatsu, 1991; Flett, Blankstein, Hewitt, & Koledin, 1992) focus on the types of
procrastinator (e. g., neurotic, perfectionistic, pessimistic). This tendency to separate the
person from the behavior contributes greatly to the fragmentation of the literature.

2. Do procrastinators differ in important ways depending on the chronicity and

 

severity of their procrastination? Despite the rapid growth of procrastination research,

 

the issues of chronicity and severity are rarely operationalized in the literature. In
psychological research, chronicity typically refers to the duration while severity connotes
the intensity. It is my opinion that chronicity and severity represent two distinct
dimensions, which are relevant to any discussion regarding the etiology or treatment of
procrastination. The most frequent approach to the issue of severity in the literature
involves separating the subjects into “high vs. low” procrastinators. The most popular
method of dividing procrastinators into these categories is by median split (Ferrari, 1991;
Ferrari & Olivette, 1994). Median split refers to labeling all subjects scoring above the
median on a procrastination measures as procrastinators and all those falling below the
median as “non” or “low” procrastinators. It is important to note that this arbitrary
division does not necessarily have any clinical signiﬁcance. Subjects that are labeled as
“high” may not be reporting levels of procrastination that would be considered
problematic by either self-report or negative consequences (poor grades). The beneﬁt of

38

the procedure is primarily statistical as it allows data to be categorized making them
amenable to methods of analysis of variance.

In their study of the relationship between Eysenck's personality factors of
neuroticism, extraversion, and psychoticism to procrastination, McCown and Johnson
(1991) identify their sample as being university students suffering from "chronic"
procrastination. These students were identiﬁed as being "chronic" even though the term
was undeﬁned. From reviewing the article it appeared that they authors were actually
interested in the severity not chronicity of procrastination.

Confusion between chronicity and severity is also-evident elsewhere in the
literature. McCown and Johnson (1989) in their abstract describe their sample as
consisting of “227 chronic academic procrastinators.” In this study procrastinators were
operationally deﬁned as those subjects who (I) scored in the top quartile of norms for the
two administered procrastination inventories, (2) had obtained less than one half of
needed experimental credits for a class by the last month of that class, (3) signed up for
an experimental session during the last 3 weeks of the class. While these authors are to
be commended for their attempt to objectively deﬁne procrastination, it is unclear as to
what dimension they were attempting to deﬁne. The ﬁrst criterion is an apparent
reference to severity while the following two are more suggestive as to the duration of the
procrastinatory behavior

Another good attempt to address the issue of severity was made by Ferrari (1991),
who deﬁned "compulsive" procrastinators as those subjects in his study scoring one
standard deviation above the sample mean on two procrastination inventories. Milgram,
Gehrman, and Keinan (1992) used the construct of manifest emotional upset to attempt to

39

differentiate between types of procrastinators. Emotional upset refers to the presence and
degree of negative affect as the result of engaging in procrastinatory behavior. The
authors felt that the use of emotional upset as a variable might be useful in establishing a
typology of procrastinators. The use of emotional upset is at least a rough reference to the
issue of severity.

3. What are the consequences of severe procrastination? It is my clinical

 

experience that there are individuals who suffer distressing consequences (e.g., academic
probation, job loss) as a result of their procrastination. Conspicuous by its relative
absence in the literature is discussion of the actual costs or consequences of
procrastination. There has been ample reference to the possible beneﬁts of
procrastination, for example, in terms of protecting a fragile self-esteem. Typically,
reference to consequences involves academic performance e.g. grade point average,
which has yielded contradictory ﬁndings. Solomon and Rothblum (1988) found a
negative correlation between procrastination and academic performance while other
studies (Solomon & Rothblum, 1984; Lay, 1986) found no effect on academic
performance. There have been two relatively recent studies that have taken different but
interesting approaches to looking at the costs of procrastinating. In a longitudinal study,
Tice and Baumeister (1997) found that procrastinators showed early beneﬁts but greater
long term costs compared to non-procrastinators in terms of higher levels of stress, lower
grades, and more frequent physical illnesses. Roig and DeTammaso (1995) explored the
relationship between procrastination and academic dishonesty (cheating and plagiarism).

They discovered a positive relationship between procrastination and academic dishonesty

40

suggesting one possible consequence of procrastination is resorting to extreme potentially
disastrous behavior,

A possible explanation for not addressing the issues of severity, chronicity, and
consequences of procrastination may be found in subject selection. The typical sample in
the procrastination literature has been recruited from undergraduate psychology courses.
Such samples are not likely to be representative of procrastinators in general or even of
all student procrastinators. They may differ in important ways, for example, from
procrastinators who voluntarily seek treatment because of their procrastination or from
students who have already suffered real consequences like academic probation as a result
of task avoidance. I have not come across a single procrastination study that used self-
referred procrastinators for their sample. This suggests that the student procrastinators
sampled in the literature to date largely represent "non-clinical" samples of convenience
that are likely very different from a more severe "clinical" group of procrastinators. A.
reasonable interpretation of the typical procrastination sample is that these students ﬁnd
their procrastination annoying but hardly incapacitating. These are students who by the
very fact that they are university students have been able to attain goals despite their self-
reported procrastination. A critical consequence of omitting issues such as chronicity
and severity is a truncating of the variance in studying procrastinatory behavior. By
focusing exclusively on non-clinical samples of procrastinators, a great deal of
information is lost regarding our understanding of procrastination. For the purposes of
my research, the issues of type of procrastinator/procrastination, the clinical/non-clinical
continuum, and consequences of procrastination are all central to investigating the
contribution of neuropsychological factors to procrastination.

41

 

From this review of the procrastination literature it is clear that even though
research in this area is proliferating, this literature remains plagued by fragmentation.
The research seems to be struggling for a direction and is not systematically moving
towards addressing such important issues as theory and treatment of procrastination.
Unfortunately this current research project will do little to directly address these issues.
Its purpose is not to “defrag” the procrastination literature. Rather, it attempts to throw
another iron into the ﬁre by raising the possible role of neuropsychological variables.
The sections that follow review literature pertinent to neuropsychological factors in
procrastination. After deﬁning executive functioning ability and presenting evidence
that it is primarily served by the frontal lobes of the brain, behavioral disturbances
associated with frontal lobe injury will be reviewed. Following that, neurological
variability in a "normal" populations will be explored with the intention of demonstrating
that executive functioning ability is not fully developed in all young adults, suggesting
the possibility that executive functioning deﬁcits exist in a "normal" population. Finally,
it will be suggested that procrastination is a possible behavioral manifestation of deﬁcient
executive functioning.

Executive Functioning

 

Executive functioning refers to those abilities that allow an individual to
successfully perform independent, goal-directed and self-serving behavior (Lezak, 1983).
Sohlberg and Mateer (1989) argue that executive functioning ability is fundamental to
competency in everyday functioning. It is important to distinguish executive functioning
ability from other cognitive abilities such as memory, language, attention, and perception.

42

Executive functioning refers to higher order abilities that enable a person to effectively
use all available cognitive skills in goal directed behavior. Another way to conceptualize
the distinction is to consider cognitive skills as the “what” we know and executive
functioning abilities as representing the “how” effectively we use what we know.

Lezak (1983) parsimoniously deﬁnes executive ﬁrnctioning as having four
components: (1) goal formation, (2) planning, (3) implementation of goal-directed plans,
and (4) effective performance. Each of these components has a distinct set of behaviors
and all are necessary for "appropriate, socially responsible, and effectively self-serving
adult conduct" (p. 507). Lezak suggests that executive functions are so central to
effective functioning that even mild deﬁcits in these abilities can lead to a serious
compromise of an individual’s ability to be effective in daily activities. “So long as the
executive functions are intact, a person can sustain considerable cognitive loss and still
continue to be independent, constructively self-serving, and productive” (p. 42).

Pennington (1991) suggests that executive functions refer to the processes such as
planning, organizational skills, optimal set maintenance, selective attention, and
inhibitory control. He more generally deﬁnes executive functioning as the “ability to
maintain an appropriate problem solving set for the attainment of a future goal” (p. 13).
Perecman (1987) defrned executive functioning as a supraordinate ability that is
fundamental to achieve a speciﬁc goal. Very similar to Lezak’s conceptualization, she
identiﬁes anticipation, goal selection, and monitoring as central to executive functioning.
She identiﬁes the process as follows: a goal must ﬁrst be anticipated and established, then

planning is necessary. Once the behavior has been initiated, the actions must be carried

43

out in a proper order and the results along the way must be monitored and behavior
adjusted accordingly.

If one looks critically at the procrastination literature, there are several instances
where the researchers seem to be implicating executive type functions as contributing to
procrastination. Lay (1986), in his validation study for a procrastination inventory,
included scales of neurotic disorganization, organization, energy level, self-esteem, and
academic achievement. Procrastinators scored high on neurotic disorganization and low
on the organization scales. Inconsistent with the studies reported earlier, self-esteem was
not correlated with procrastination. High scores on the neurotic disorganization scale
describe someone who "ﬁnds it difficult to focus his attention on the details of everyday
activity; is absent-minded, easily distracted and poorly organized; has trouble
accomplishing things on time and is very forgetful." There are interesting similarities
between individuals scoring high on neurotic disorganization and what one would expect
from persons with deﬁcient executive functioning. Ferrari, Wolfe, Wesley, Schoff, and
Beck (1995) described a “lack of planfulness” by procrastinators secondary to a
diffuse/avoidant identity style. If an individual procrastinates long enough, then
circumstances rather than preparation eventually determine the outcome. Such a lack of
preparation and difﬁculty with planning maybe an expression of identity style however
other explanations are plausible.

In outlining their intervention for treating procrastination, Haycock, McCarthy,
and Skay (1998) identify “getting started” on a speciﬁc task as a common problem for
procrastinators. They suggest that the skills necessary for initiating a task need to be
“isolated and broken down into small attainable steps” (p 321). They suggest that low

44

self-efﬁcacy leads to less initiation and persistence on a task which ultimately leads to
avoidance behavior. The ability to independently break a task into steps and form a plan
to accomplish those steps clearly falls within the domain of executive functioning. While
Haycock et al. (1998) were discussing procrastination as a function of low self-efficacy,
they did not offer a possible explanation for the possible genesis of low self-efﬁcacy
other than poor past performances. Could those past poor performances on academic
tasks and the accompanying difficulties with initiation and planning be related to
executive functioning?

Another study that is potentially suggestive of the relationship between executive
functioning and procrastination is by McKean (1994), who looked at the relationship
between yet another variable, learned helplessness, and procrastination. The author
posits that students can develop academic helplessness in the face of repeated academic
failures in which the student comes to believe that the outcome of his/her work is
unrelated to the effort exerted. Students are particularly vulnerable because college is
New World requiring new and different strategies to be successful. The ability to meet
such new demands tasks the strength of a student’s executive functioning abilities.
McKean addresses the behavioral, cognitive, and affective consequences of academic
helplessness, however, he fails to hypothesize possible etiological reasons for the
behavior.

In summary, executive functioning is central to a person’s ability to engage in
independent and successful goal oriented behavior. If an individual has relatively weak
executive functioning abilities, such as difﬁculties with goal formation, planning, or
implementation of plans, then procrastination could be an expression of these difﬁculties.

45

The very same procrastination that is currently being attributed to cognitive and affective
variables such as task aversiveness, fear of failure, laziness, low self-efﬁcacy, and diffuse
identity style may indeed be a deﬁcit in executive functioning ability.

Executive Functioning and the Frontal Lobes.

 

It is widely accepted that executive functioning is neuroanatomically localized
primarily in the frontal lobes of the cerebral cortex (Pennington, 1991) anterior to the
central sulcus and superior to the Rolandic ﬁssure (Mattson & Levin, 1990). More
speciﬁcally, executive type functions are localized in what is known as the pre-frontal
lobe referring to areas of the cerebral cortex just anterior to the frontal lobes. In the
literature the terms frontal and pre-frontal are essentially used interchangeably with
regards to executive functioning. Not possessing speciﬁc sensory or motor ﬁinctions, its
abilities are considered supra-modal and the frontal cortex is considered to be primarily
association cortex meaning it is responsible for higher order integrative processes. The
frontal lobes regulate the state of the organism, control the essential elements of the
subject's intentions, program complex forms of activity, and constantly monitor all
aspects of activity (Hecaen & Albert, 1975). Perecman (1987) states that the frontal
lobes of the brain are involved in the highest level of goal directed acts including
complex sequencing and the creation of long and short-tenn plans.

While there is a consensus in the literature that executive functions are mediated
by the prefrontal areas of the cortex, a taxonomy. of how and speciﬁcally where the
various executive functions are located within the prefrontal areas has not been developed
(Pennington, 1991). There have been many theories of pre-frontal functioning
(Goldman-Rakic, 1988; Fuster, 1985). Shallice (1988) proposed a model of ﬁ'ontal

46

 

functioning that distinguishes between routine and non-routine actions. He proposed that
non-frontal areas of cortex handle routine actions while non-routine or novel actions
require the activation of preﬁontal executive areas. Using a planning task (the Tower of
Hanoi), Shallice found some evidence that patients with frontal lesions were impaired on
non-routine tasks compared to patients with more posterior lesions. Perecman (1987)
concurs that different brain areas mediate routine vs. non-routine acts. She argues further
that when a novel act becomes routinized through practice, posterior brain areas are
sufﬁcient to maintain it. She cites a study by Mazziotta, Phelps, Carson, andlKuhl (1982)
that used positron emission tomography to show non-frontal activation for thoroughly
learned motor acts and frontal lobe activation for newly acquired motor acts. Even
though our understanding of the frontal lobes is less well developed than our
understanding of the ﬁrnctions of other areas such as the temporal and parietal lobes, the
limbic system, or sub-cortical structures, it is widely accepted that the frontal/pre-frontal
areas of cortex represent the home of executive functioning abilities.

Behavioral Disturbances associated with frontal lobe damage.

 

There is an extensive clinical literature on the effects of brain lesions in the frontal
lobes in general and executive functioning in particular (Duncan, 1986; Kamath,
Wallesch, & Zimmerrnann, 1991; Petrides & Milner, 1982; Damasio, 1979; Hecaen &
Albert, 1978). Basic sensory, motor, and speech functions remain intact with prefrontal
damage while complex goal directed behavior deteriorates. In fact, prefrontal lesions can
be associated with impairment in control of all functions, both cognitive and emotional,
because of the massive number of afferent and efferent connections between the
prefrontal cortex and almost every other brain area. (Kaczmarek, 1987). Deﬁcits in

47

executive functioning can also result from damage in sub-cortical regions that subserve
the frontal lobes.

It is important to note that a person can suffer substantial losses to their cognitive
abilities and may still be able maintain an effective and independent lifestyle. However,
even mild damage to executive functioning ability can render a person with intact
cognitive abilities essentially disabled (Lezak, 1995). The behavioral consequences of
ﬁ'ontal damage can be profound regardless of whether the injury was incurred during
adulthood or childhood (Grattan & Eslinger, 1992; Williams & Mateer, 1992).

Walsh (1991) describes changes in executive functioning that are typically
associated with injury to the frontal lobes (referred to as the frontal syndrome). These
changes are (1) poor abstract ability, (2) lack of ﬂexibility in changing cognitive set, (3)
deﬁcient adaptive problem solving, and (4) decreased planning capacity. Zeigarnick
(1949) noted that soldiers who had suffered damage to their frontal lobes lacked, among
other things, initiative. These soldiers needed external sources of stimulus to guide their
behavior. Lezak (1983) classiﬁes behavioral disturbances associated with frontal lobe
damage into ﬁve general categories. The category relevant to this study is referred to as
"problems with starting" (p.81). An individual with "problems of starting" will
demonstrate decreases in productivity, initiative, and ambition. These qualities are
especially prevalent when attempting novel tasks. This individual will perform
satisfactorily on routine tasks of daily living. To others he/she will appear lazy or
apathetic. They can "talk a good game" about plans and intentions, but they are virtually

unable to transform the words into deeds.

48

Shallice and Burgess (1991) investigated deﬁcits in planning abilities associated
with frontal lobe damage. Subjects were required to carry out 8 tasks that were written
on a card. Six of the tasks were simple such as buying a loaf of bread. The seventh task
was to be at a certain place in 15 minutes and the eighth task was to ﬁnd out certain
information about 4 things such as the price of a loaf of bread. They were also given
certain rules, which further increased the complexity of the tasks. These subjects were
forced to develop a strategy for accomplishing these tasks. Compared to control subjects,
the subjects with frontal lobe damage tended to break the rules and have more difficulty
completing the tasks. Similar difﬁculties with following rules and planning have been
replicated with a route ﬁnding task using mazes (Canavan, 1983). An interesting ﬁnding
is that these types of subjects can recite the very rules they are unsuccessful at
implementing.

Stuss, Benson, Kaplan, Weir, Naeser, and Lieberman (1983) argue that the
deﬁcits of the frontal lobes are illuminated when the individual attempts to transform
knowledge into action. When presented with a task, which requires the sequencing of
multiple steps or that requires organizing complex responses, the individual's
performance immediately. Baddeley (1986) coined the phrase “dysexecutive syndrome”
to refer to the disorganization of behavior that accompanies damage to the frontal/pre-
frontal areas.

While adequate executive functioning ability is integral to independent
functioning, it is particularly central when attempting unstructured tasks. People vary on
the amount of structure (external assistance) needed to effectively accomplish tasks
(Lezak, 1983). As noted earlier, individuals with compromised executive functioning

49

ability can perform routine tasks with relative case. It is when attempting novel and/or
difficult tasks particularly with time constraints that problems with executive functioning
ability are illuminated. It is very interesting to note that most interventions for
remediating procrastination teach individuals to plan and execute more effectively (Lay,
1990; Lamwers & Jazwinski, 1989; Roberts, Fulton & Semb, 1988). In essence these
approaches externally impose the structure that individuals have difﬁculty imposing for
themselves internally.

Only one study has been located that explicitly cites procrastination as a direct
sequela of brain injury. Strub (1989) documents the case of a 60-year-old man with a
frontal lobe syndrome following a cerebral hemorrhage. The reported residuals of his
injury include apathy, social withdrawal, and decreased motivation. Intelligence
remained within normal limits. This man was described as knowing what is required of
him at work yet he chronically procrastinated and left details unattended. This case is
suggestive of the connection between neuropsychological factors and procrastination.

It has been the intention of this review so far to establish that executive
functioning is integrally involved with the successful execution of goal-directed behavior.
Furthermore, damage to the parts of the brain that serve executive functioning ability
result in a cluster of behavioral deﬁcits that can include procrastination-like behavior.

Neurolochal Variability in a "Normal" Porﬂation.

 

To this point it has been suggested that some individuals procrastinate because of
deﬁcient executive functioning abilities which makes managing the complex demands of

an unstructured academic environment very difﬁcult. The likelihood of ﬁnding a

50

neurological basis to procrastination is increased if there is some developmental
evidence, which could support the type of deﬁciency or delay suggested above.

The frontal lobes are the most recent phylogenetic region of the brain. The pre-
frontal regions are virtually non-existent in the rodent brain and occupy 3.1% of the neo-
cortex of the cat, 13% in apes, and 24% in man (Perecman, 1987). The development of
prefrontal areas and the development of their functions have traditionally been seen as
occurring quite late in the course of normal brain development. Others have argued that
the ﬁrst emergence of many prefrontal functions, e. g. selective attention and inhibition,
are observable during the second half of the ﬁrst year of life (Pennington, 1991). Despite
this, Pennigton (1991), argues that executive functions do have a very protracted course
of development.

The axons within and leaving the prefrontal cortex begin to myelinate during the
sixth month after birth and are the last part of the cortex to complete myelination.
Yakolov and Lecours (1967) indicate that the completion of the myelination process of
the frontal lobes does not occur until the third decade of life. The later development of
this areas supports the notion that higher, later maturing functions are involved (Spreen,
1983).

Luria (1973) proposed a developmental timefrarne for different “functional
systems” in the brain. A functional system refers to the process whereby several brain
regions simultaneously mediate a behavior. One of his proposed functional systems is
referred to the output/planning unit. It consists primarily of the frontal lobes and
represents the highest functional level of the brain, responsible for planning and carrying
out behavior. Luria proposed that the output/planning unit developed between the ages of

51

l2 and 24, which he believes corresponds to the developmental tirneframe of the frontal
cortex. It is interesting that the developmental timeframes believed to be operating with
the frontal cortex correspond to the typical age for college students. It therefore seems
plausible that many individuals may experience functional deﬁcits secondary to possible
developmental delays in executive ﬁrnctioning.

Cognitive psychologists have also established that there is considerable variability
in adults' abstract thinking ability. Approximately 40% of normal adults do not attain
formal operational thinking deﬁned as the ability to "construct totally hypothetical mental
representations and then to perform various complex cognitive operations on those
representations" (Shute & Huertas, 1990, p 2). Pennington (1991) concurs that there is a
rough correspondence between the development of executive functions and the different
Piagetian stages of cognitive development. He suggests that these stages of cognitive
development can be “reconceptualized as changes in the nature and complexity of the
executive strategies or mental representations that can be held online in working memory
to guide behavior” (p. 16).

Relevant to the purposes of this study is whether similar variability is present with
regards to executive functioning. Shute and Huertas (1990) were intrigued by the
proposition tha "variability in cognitive development reﬂects variability in frontal lobe
function." (p. 3). More speciﬁcally, they were interested in developmental variability in
frontal lobe functioning of normal college undergraduates. They wanted to compare

performance on measures of frontal lobe functioning with measures of formal operational
thinking ability. They supposed that sufficient frontal lobe development is required for
the attainment of formal operational thinking. They administered an abbreviated

52

neuropsychological test battery (Booklet Category Test, Wisconsin Card Sorting Test,
Trails A & B, and Digit Symbol), a clinical interview (Piagetian Shadows Task) to
determine level of cognitive development, and 4 cognitive tasks to 58 college
undergraduates with no history of neurological illness or trauma. Results indicate a
"strong relationships betvlreen the cognitive development measure and measures of frontal
lobe dysfunction” (p. 8). Those subjects who successfully negotiated the abstract
reasoning demands of the classical Piagetian Shadows Task were also those who scored
highest on the measures of frontal lobe dysfunction. These ﬁndings suggest that the
ability for the highest levels of abstract reasoning require adequate frontal lobe
development. Those subjects who performed best on the frontal lobe measures, which are
also considered to be measures of executive functioning, were the same subjects who '
attained the highest levels of cognitive deve10pment. It was also found that the mean
score of their sample on the measure of cognitive development was 3.6, which falls
below the cutoff score for the attaimnent of abstract reasoning ability. This study
provides evidence that in a "normal" sample 1) there is signiﬁcant variability in frontal
lobe functioning, 2) measures of cognitive development and frontal lobe functioning are
correlated, and 3) adequate frontal lobe development is necessary to attain abstract
reasoning abilities. Formal operational thought (abstract reasoning) and executive
functioning ability are very similar. Although Shute and Huertas (1990) provide
evidence of variability in frontal lobe functioning, various behavioral expressions of such
variability were not addressed. From an evolutionary perspective, executive funCtion
skills should be subject to more variation than many other areas of brain function because
of both the relative and absolute size of the prefrontal cortex has increased dramatically

53

in recent evolution. Thus like the language area of the brain, the frontal lobes should be
particularly vulnerable to developmental pathologies (Pennington, 1991).

Summary/Research Questions

 

It has been the objective of this entire review to establish various points including:
1. Procrastination is a serious problem that afflicts a large number of individuals.

2. Collectively, the procrastination research has clearly established a plethora of various
cognitive, personality, affective, psychological, and behavioral factors associated with
procrastination.

3. The procrastination literature has made virtually no reference to the possible
contribution of neuropsychological variables to explaining this behavior.

4. The executive functioning and developmental variability literature suggests the
possibility of the role of neuropsychological factors in procrastination.

The purpose of the current study was to investigate the role of neuropsychological
factors in severe academic procrastination. Academic procrastination was selected rather
than other types of procrastination (e. g., daily tasks) because an academic environment is
full of demanding, novel, and unstructured tasks. It is such tasks that can bring to the
forefront potential deﬁcits in executive functioning.

More speciﬁcally, the following question was raised: Will severe or "clinical"
procrastinators demonstrate deﬁcits in executive functioning ability on reliable and valid
measures of executive functioning? My predictions are:

1. A "clinical" group of community college students participating in an

academic monitoring program or on academic probation will report

54

signiﬁcantly higher levels of academic procrastination than a control
group of community college students not on academic probation.

There will be a negative relationship between academic procrastination
and performance on three measures of executive functioning ability. As
academic procrastination increases, performance on measures of executive
functioning ability will decrease.

For clinical procrastinators, scores on measures of executive functioning
ability will account for a signiﬁcant amount of variance in academic
procrastination above and beyond the variance explained by other
independent or control variables.

Executive functioning ability, depression, ADHD status, and general
intellectual ability will combine to predict group membership (i.e.,

procrastinators vs. controls).

It is important to clarify that the goal of this study is not toestablish the presence

of "brain damage" in clinical procrastinators. If performance deﬁcits are found, they

would be not be indicative of brain damage. Rather such results may be suggestive of a

developmental delay or a non-pathological dysfunction of the same order as Dyslexia,

Attention Deﬁcit Disorder, or Developmental Arithmetic Disorder (American Psychiatric

Association, 1996). The question is not one of "damage" but rather of "dysfunction."

This potential dysfunction has yet to be adequately diagnosed and treated. With the high

incidence of procrastination among college students (cited earlier), it is imperative that

counseling psychologists have a better understanding of this disabling behavior.

55

CHAPTER III
METHOD

Two groups of subjects were recruited from Lansing Community College (LCC)
in Lansing, Michigan and Glendale Community College (GCC) in Glendale, Arizona.
Both colleges have similar number of students and serve cities of similar size
(approximately 100,000). A group of students on academic probation and a control group
were recruited from LCC and GCC. The director of counseling services at LCC provided
permission to recruit students from their Academic Monitoring Program (AMP).
Students who participate in the AMP do so because they have been dismissed from
school because of poor academic performance and have essentially been placed on
academic probation. These students sign a contract that binds them to work to improve
their academic performance and to regularly meet with an academic counselor. In
exchange they are permitted to continue enrollment at LCC.

I sent a letter on LCC letterhead and signed by the Director of the Counseling
Center to students in AMP soliciting their participation in a research project (See
Appendix H). The letter informed the students about the study and said that they would
be reimbursed $10 for their hour of participation. At GCC the same recruitment letter
was approved by the Registrar and was mailed to all students on academic probation for
Spring semester of 1998. For both LCC and GCC the recruitment letter produced a
response between 5 to 10 % of the letters mailed. The recruitment letters produced a total
of 59 responses. I experienced signiﬁcant difﬁculties getting the probation students to
follow through with participation. Over 60% of the students on academic probation did

56

not return phone calls or show up for their scheduled appointment. In order to recruit
additional subjects, ﬂyers were posted in classrooms at GCC advertising $10 to students
on academic probation that were interested in participating in a research project. This
produced the additional subjects necessary to complete this study.

The control group, which consisted of community college students who have
never been on academic probation, were recruited through Introduction to Psychology
classes at GCC. The control subjects were told that students were needed. for a research
study of factors that interfere with students completing community college in a timely
manner. They were told that their participation entered them into a lottery for 3 cash
prizes of $100, $50, and $25.

Instruments

Pertinent subject information was obtained using a Client Information sheet (see
Appendix B). Information requested was age, sex, ethnic background (optional), number
of semesters spent at community college to date, credits completed to date, declared
college major, grade point average, whether on academic probation and, if yes, how
many times, whether they have documented learning disability, whether they had ever
received special education services, where they had ever experienced seizures or a
serious head injury, and whether they feel as if they have experienced problems in school
because of procrastination.

Procrastination Questionnaire. The dependent variable in this study,

 

procrastination, was assessed by using the Time Use Questionnaire (TUQ) (See'
Appendix D) which consists of 19 self-report items (Aitken, 1982). Each item is ranked
on a 5 point Likert Scale from 1 = True to 5 = False. Scores are summed across the 19

57

items with 8 of the items scored in the reverse direction because they are worded in the
negative direction. The scores on the TUQ can range between 19 and 95. The PQ has an
internal consistency coefﬁcient alpha of .85. With regards to construct validity, the TUQ
signiﬁcantly correlates ( .37 - .48) with several behavioral indicators of academic
procrastination including test studying behavior and beginning/completion of term
papers. Aitken (1982) stated that the TUQ appears to be a “reliable, useful instrument to
use in assessing procrastination among college students.” When compared to other
existing self-report procrastination questionnaires like the Procrastination Assessment
Scale — Students (PASS) (Solomon and Rothblum, 1984), the TUQ has better internal
consistency, higher correlations with objective behavioral measures of academic
procrastination, and more items allowing for more variability in responding.

Neuropsychological functioning was assessed by a short battery consisting of two
subtests from the Wechsler Adult Intelligence Scale-Revised (Wechsler, 1981), The
Tinkertoy Test (Lezak, 1983), the Controlled Oral Word Association Test (Benton,
Hamsher, Vamey, & Spreen, 1983), and the Ruff Figural Fluency Test (Ruff, Light, &
Evans, 1987). Together these tests are designed to provide information regarding a
variety of neuropsychological and cognitive functions including (a) executive
functioning, (b) general intellectual ability, (c) visuospatial conceptualization, (d)
visuomotor coordination and constructional ability, (e) verbal ﬂuency, (f) nonverbal
ﬂuency, (g) divergent thinking, (h) cognitive ﬂexibility.

Vocabulary Subtest. The Vocabulary subtest of the Wechsler Adult Intelligence

 

Scale - Revised (WAIS-R) (Wechsler, 1981) was used in conjunction with the Block
Design subtest of the WAIS-R) to give a reliable and valid estimate of general intellectual

58

ability (Silverstein, 1982). This subtest measures a variety of functions including
language ability and fund of information. It isthe single best measure on the WAIS-R of
verbal and general mental ability. The Vocabulary subtest also involves memory,
concept formation, and reasoning ability. The subtest requires the subject to verbally
give deﬁnitions to a list of 35 words of increasing difﬁculty level. The deﬁnitions given
by the subject reﬂect the nature of a person's thought processes, its depth, extent of
analysis, and more subtle nuances of emotions and values. The Spearrnan—Brown
corrected split-half reliability coefﬁcients range from .94 to .96 across nine age groups
from age 16 to -74, with an average reliability coefficient of .95 (Wechsler, 1981). The
two-subtest short form (Vocabulary and Block Design) has a correlation of .90 with Full
scale IQ and a reliability of .94 (Silverstein, 1982).

Block Design Subtest. The Block Design subtest of the Wechsler Adult

 

Intelligence Scale - Revised (WAIS-R) (Wechsler, 1981) was used to assess visuomotor
c00rdination and visuospatial conceptualization. It was also used in conjunction with the
Vocabulary subtest to give a valid and reliable estimate of general intellectual ability.
The subject is asked to use red and white blocks to construct replicas of stimulus patterns
printed on a smaller scale. This subtest is timed and can reveal a great deal about the
subject's thinking processes, problem solving style, and temperament. The Spearman-
Brown corrected split-half reliability coefﬁcients range from .83 to .89 across nine age
groups from age 16 to 74, with an average reliability coefficient of .86 (Wechsler, 1981).
The two-subtest short form (Vocabulary and Block Design) has a correlation of .90 with

Full Scale IQ and a reliability of .94 (Silverstein, 1982).

59

The Tinkertoy Test. The Tinkertoy Test (TTI‘) (Lezak, 1983) is a simple and

 

straightforward test devised to assess executive functioning ability. The subject was
given ﬁfty Tinkertoy pieces and asked to "make whatever you want." The subject was
told that he/she would have at least ﬁve minutes to work on it. Tinkertoys are a childrens
construction toy consisting of plastic objects of various sizes and shapes (e. g. dowels,
spools). Unlike most mainstream measures of executive functioning ability like the
Wisconsin Card Sorting Test or the Category Test, the TTT provides less structure for the
subject. Typically, the testing environments combined with the standardized tests provide
a great deal of external structure, which makes it difﬁcult to observe the subject’s ability
to impose the structure him or herself. The TIT allows the subject to initiate, plan, and
structure a potentially complex activity. The open-ended nature of the TTT better reﬂects
independent goal oriented behavior, which is the heart of executive functioning ability.
The TIT also provides " a more comprehensive assessment of goal-oriented behavior
than do other tests: from formulating a goal, to planning and organizing the steps, to
sequencing of the motor plan and self-correction” (Malcom, 1993, p. 3). These core
functions of goal formation, planning, carrying out, and regulation of performance are
"absolutely essential to the maintenance of social independence in a complex society”
(Lezak, 1983, p. 513).

Lezak (1983) developed a scoring system for the TI‘T (See Appendix E). The
constructions are scored by the total number of Tinkertoy pieces used (TTTr_rp) in the
construction as well as a complexity of the construction (mm). The complexity
score consists of seven subscores for variables such as symmetry, three dimensionality,
mobility, and whether the name of the construction ﬁts its appearance. In her initial

60

study, Lezak (1982) found signiﬁcant differences on TITnp and TITmp scores
between subjects with known brain injuries who were either able to live independently
without supervision and a group of subjects who were dependent for assistance with their
daily functioning. The dependent group scored lower on both TTT scores. The
independent group also had lower scores than healthy control subjects. Cicerone and
DeLuca (1990) used the TIT along with the Trailmaking Test (another test of executive
functioning ability) and other measures of verbal ability, perceptual organization, and
attention to predict ratings of activities of daily living (ADL). The executive functioning
factor represented by the scores on the TTT and Trailmaking Test was the most
signiﬁcant predictor of ADL ratings for outpatients with a history of traumatic head
injury. Bayless, Vamey, and Roberts (1989) found that unemployed subjects with a
closed head injury performed signiﬁcantly more poorly on the WM than the
employed subjects with a history of closed head injury.

Malcolm (1993) developed two new scoring systems for the TTT which extends
Lezak's (1982) standard scoring system by focusing on the process of construction rather
just on the end product. These experimental scales were developed as part of a larger
study that, in addition to developing a new scoring system, offered further reliability and
validity information regarding the standard scoring system. Malcolm administered the
TIT as well as a full neuropsychological battery including traditional measures of
executive functioning. Additionally two behavior-rating scales were completed for each
subject. Subjects were individuals with a history of closed head injury living’in a long-
term inpatient rehabilitation facility. A comparison group of healthy control subjects
were also utilized in the study. The ﬁrst important ﬁnding of this study was the two new

61

 

:-

 

 

experimental scoring systems were no better than Lezak's (1982) standard scoring system
(TITnp and TITganp). Concerning construct validity, the TIT standard scores
correlate well with other tests of executive functioning (Wisconsin Cart Sorting Test, .62
for categories achieved; Ruff Figural Fluency Test, .53 for the number of unique designs)
With regards to ecological validity, the TIT was able to successfully predict "behavioral
rating scale scores after the variance accounted for by other neuropsychological
measures" were taken into account. (Malcolm, 1993, p.52). Interrater reliability of TIT
scores ranged from .76 to .97 for TITr_1p and TITc_oprp_ respectively. Test-retest
reliability coefﬁcients were .46 for WM and .66 for TTTr_rp. While both test-retest
reliabilities were statistically signiﬁcant, they are strongly suggestive that the
motivational state of the subject is important.

Controlled Oral Word Association Test: The Controlled Oral Word Association

 

Test (COWAT) (Benton & Hamsher, 1976) is a test of verbal ﬂuency that is also known
as the Word Fluency Test and the FAS Test. Subjects are asked to say as many words
that they can think of that begin with a certain letter (F ,A,S). Proper nouns, numbers, and
words with the same preﬁx but a different sufﬁx are excluded (e.g. run, runs). The
subject is given one minute for each letter. Word ﬂuency is strongly associated with both
age and education so total raw scores are adjusted yielding corrected percentiles (Benton
& Hamsher, 1976). Test-retest reliability for adults has been reported as .88 and .70 in
older adults (Snow et al., 1988).

Word ﬂuency tasks provide an "excellent means of ﬁnding out whether and how
well the subject organizes his thinking" (Estes, in Lezak, 1983, p. 330). While there are
various types of verbal ﬂuency tests (i.e. naming items in a category), the COWAT

62

provides the least amount of structure by only providing the ﬁrst letter and in doing so
makes it a difﬁcult task for subjects who have trouble developing strategies for
themselves.

Word ﬂuency, as measured by the COWAT, "has proven to be a sensitive
indicator of brain dysfunction" (Lezak, 1983, p. 331). Crockett et al. (1986) reports that
the COWAT is the best discriminator between groups with known frontal lesions and
those with non-frontal lesions. Frontal lobe lesions regardless of their side typically
depress scores on the COWAT with lesions on the left producing lower word production
than right side lesions (Perret, 1974). Bilateral frontal lesions reduce verbal ﬂuency even
more than left frontal lesions (Benton, 1968).

Ruff Figural Fluency Test: The Ruff Figural Fluency Test (RFF T) (Ruff, Light, &

 

Evans, 1987) is a test of nonverbal ﬂuency analogous to the verbal ﬂuency tests such as
the COWAT (Ruff, 1988). The RFF T consists of ﬁve sections, each of which includes a
short practice section followed by a one-minute trial. In each section, a pattern of dots is
arrayed in a circular pattern within a square area. Over successive sections, the arrays of
dots are either presented in a random pattern or are accompanied by visual distracters.
Both of these modiﬁcations of the-ﬁrst section make the task progressively more difficult.
The subject's task is to make as many different designs possible within the time limit by
connecting two or more dots with straight lines. Each design has to be different in some
way from all the others.

Two scores are derived for the RF F T: the total number of Unique Designs a
subject makes across all ﬁve sections, and an Error Ratio which is calculated by dividing
the total number of design perseverations by the total number of unique designs

63

generated. The Error Ratio is an "index of planning efﬁciency" (Ruff, 1988, p. 9). These
two raw scores are adjusted for age and education and then converted to percentiles. A
qualitative evaluation of the subject's performance is also recommended by Ruff to
determine the type of strategies, if any, employed by the subject. Test-retest reliabilities
for the number of Unique Designs for the normative group ranged from .58 to .69 for
sections one through ﬁve and .76 for total number of Unique Designs. With regards to
discriminant validity, the RF F T is not signiﬁcantly correlated with motor speed, aphasia,
verbal ﬂuency, or memory. Factor analyses of the RFF T demonstrate that the RFFT
"assesses planning, initiation, and divergent reasoning in both clinical and nonclinical
groups" (Ruff, 1988, p 21).

Jones-Gotman and Milner (1977) have found that right frontal groups produce
more perseverative errors and less novel output than subjects with lesions located in other
areas of the brain. Furthermore, there is a double dissociation between verbal and non-
verbal ﬂuency whereby a right frontal lesion group was more impaired on a design
ﬂuency task while a leﬁ ﬁ'ontal lesion group was signiﬁcantly more impaired on a word
ﬂuency task. Ruff, Evans, & Marshall (1986) when comparing head’injured patients with
controls found that the RF FT is also sensitive to the severity of injury. They found that
_ ﬁgural ﬂuency to be more impaired for both Unique Designs and Error Ratio in the
severe compared to moderate head injury group.

The neuropsychological tests just disCussed form a brief test battery that taps the
frontal lobes in general and executive ﬁmctioning speciﬁcally. In addition, this test

battery allows for an accurate estimate of a very important potential confounding

variable; intellectual functioning. In order to control for two other feasible confounding
variables, depression and Attention Deﬁcit Disorder, two other tests were administered.

The Beck Depression Inventory (BDI) (Beck, Steer, & Garbin, 1988) was used as

 

a measure of depression (See Appendix G). It is important to control for the presence of
depression and ensure that it is not suppressing performance on the neuropsychological
measures. The BDI is a widely used research and clinical instrument. Reliability ratings
(i.e., test-retest, internal consistency), have ranged from .86 to .93 (Reynolds & Gould,
1981; Beck, 1970). Concurrent validity with other self-report depression scales such as
the lung Self-Rating Depression Scale (Zung, 1969 and the MMPI D-Scale (Beck, 1970)
are good.

The Wender Utah Rating Scale (WURS) (Ward, Wender, & Reimherr, 1993) is a

 

twenty-ﬁve item self-report inventory that was used to identify the possible presence of
Attention Deﬁcit Hyperactivity Disorder (ADHD). Subjects reported on a Likert-type
scale whether they demonstrated certain behaviors as a child (See Appendix H). Using a
cutoff score of 46, the WURS correctly classiﬁed 86% of the adults' with attention deﬁcit
hyperactivity disorder, 99% of the normal control adults, and 81% of adults with unipolar
depression (Ward et al., 1993). Split-half reliability comparing the odd/even items for the
normal comparison group was .90. With regards to validity, a Pearson correlation
coefﬁcient of .41 was obtained when correlating scores on the WURS with the Parents
Rating Scale. The Parents Rating Scale is a heavily used and psychometrically sound
instrument that identiﬁes the presence of ADHD in children. Higher scores on the

WURS were also correlated with a better response to a pharmacological intervention for ‘

65

ADHD for patients who participated in a placebo study (Wender, Reimherr, Wood, &
Ward, 1985).
Procedure

M. Because this research is the ﬁrst investigation to look at
neur0psychological variables and procrastination, a passive or correlational ﬁeld design
was utilized. According to Heppner, Kivlighan, and Wampold (1992), this type of design
is very helpful especially in the early stages of an investigation: "A researcher can
quickly and relatively easily describe possible relationships among variables" (p. 215).
Because a correlational design is low on internal validity (no random selection or
assignment), no cause-effect conclusions could be drawn from this study. However, it
can be particularly helpful in disconﬁrming hypotheses (e.g., when no signiﬁcant
relationship is found between key variables). A strength of this design is its external
validity, which Gelso (1980) argues is critical for counseling research. Since this study
took place on college campuses and used subjects with genuine concerns (no induction of
procrastination occurred), generalizability was facilitated.

Data Collection. All subjects initially completed a consent form and a Client

 

Information sheet (See Appendix A & B). On top of the consent form was a number that
would identify the subject for the remainder of the study. The consent form was then
separated from the test packets thus protecting the conﬁdentiality of the subjects. The
primary investigator individually tested all but 3 of the subjects. All subjects were either
tested in a private room located on the respective campuses or at the subject’s home if
transportation was a problem. F orty-ﬁve of the 63 subjects were tested on campus. The
average testing time was between 45 and 60 minutes. (The primary investigator scored all

66

test protocols. To permit the establishment of inter-rater reliability, a Ph.D. level

psychologist also scored the I I'I constructions. The instruments were presented in the

following orders:

1.

2.

8.

9.

Client Information Sheet

2. Time-Use Questionnaire (TU Q)

Wender Utah Rating Scale (WURS)

Beck Depression Inventory (BDI)

Vocabulary Subtest of the WAIS-R ’

Block Design Subtest of the WAIS-R

Controlled Oral Word Association Test (COWAT)
Tinkertoy Test (TIT)

Ruff Figural Fluency Test (RFF T)

Upon completion of the testing the subjects were debriefed about the nature of the study.

Questions were answered at that time "and the subjects were asked not to talk with others

about their participation. They were also informed that if they desired information about

the results, to leave their addresses and a summary would be mailed to them at a later

time. Each subject in the AP group was then given $10 cash. The professor for the

Introduction to Psychology course was given the money for the lottery for the control

subjects, which he administered after all students who wished to participate had done so.

67

CHAPTER IV
RESULTS

Description of Sample.

 

The subjects in this study were 65 community college students who had not yet
completed their two-year degree. One subject, however, needed to be excused for a
personal emergency during the middle of testing and never consented to completing the
testing. A second subject also discontinued participation during the middle of testing
when their parent asked me to leave because strangers were not permitted in the house.
Evidently the student had not received permission for me to come to the home. This
student was unwilling to complete participation at a later time.

Of the remaining 63 subjects, 30 (47.6%) were in the control group (CG) and 33
(52.4%) were in the Academic Probation (AP) group. Sixty-six percent of the subjects
were female'and 34 % were male. Based on ethnicity, 64% were Caucasian, 18% were
Hispanic, 11% were African-American, 6% were Asian, and 1% responded as “Other”.
The mean age for the sample as a whole was 24.1 years (SD = 6.7) with a range ﬁ'om 17
to 46 years of age. The mean number of credits completed by the subjects was 24.8
credits with a range from zero to 65 credits. Sixty credits are required to obtain an
Associate of Arts degree. The mean grade point average was 2.49 on a 4.0 scale with a
Standard Deviation of 1.1. Looking at the combined sample, 7.9% reported having a
diagnosed learning disability, 9.5% reported previously receiving special education
services, 3.2% reported having a history of seizures, and 6.3% reported sustaining a head
injury. All 5 of the subjects who reported having a learning disability were in the
academic probation group, as were 5 of the 6 who had special education, and 3 of the 4

68

who had head injuries. One question on the Information Sheet (See Appendix B) asked
whether they had experienced problems in school because of procrastination. Fifty
percent of the subjects responded that it had been a problem and 50% reported that
procrastination had not been a problem in school.

Preliminary Analyses.

 

For the semesters during which data was collected, Lansing Community College
(LCC) had an enrollment of 17,152 and Glendale Community College (GCC) had 18,088
students enrolled. For LCC, 54.7% were female and 45.3% were male. For GCC, 55.2%
were female and 44.8% were male. For LCC, the ethnic breakdown was as follows:
73.7% Caucasian, 8.5% Hispanic, 8% African-American, 2.7% Asian, and 7.1% other.
For GCC, the ethnic breakdown was as follows: 69.8% Caucasian, 15.5% Hispanic, 4.1%
Aﬁican-American, 4.1% Asian, 1.8% Native American, and 4.7% other.

For the semesters during which data was collected, 3.7% of LCC students were on
academic probation while 2.5% of GCC students were on probation. For LCC 56.1%
were male and 43.9% were female. For GCC, 54.2% were male and 45.8% were female.
The ethnic breakdown for students on probation at GCC were as follows: 60% Caucasian,
18.4% Hispanic, 8.7% African-American, 4.6% Asian, and 9.3% other. Information
regarding ethnicity for students on probation at LCC was not available.

The academic probation sample obtained for this study was 57% female and
43% male. The control group of students in good academic standing was 71% female
and 29% male. With regards to ethnicity, 76.7% of the control group were Caucasian

compared to 51.5% for the academic probation group. The control group was 10%

69

Hispanic and 6.7% African-American, while the academic probation group was 24.2%
Hispanic and 15.2% African-American.

To evaluate the reliability of the subject’s scores on the TTT, a second rater was
recruited who also scored all 63 constructions. The second rater and I independently
scored the constructions generating two scores; one for total number of pieces utilized
and the other being the complexity score. The inter-rater reliability was r = .862. There
was perfect agreement between the raters for 61.9% of the subjects, raters differed by one
point for an additional 27% of the subjects, differed by two points for 11.1% of the
subjects. The two raters never disagreed by more than two points

The remaining statistical analyses done in this exploratory study consisted
primarily of t-tests and correlations. The t-tests for the executive functioning variables
were one tailed with an alpha leVel of .05. All other t-tests were two tailed. Because
multiple t-tests were conducted thereby increasing the probability of ﬁnding signiﬁcant
differences due to chance, the Bon Ferroni adjustment was used, which adjusted the alpha
for each t-test to .004.

Demographic Group Comparisons.

 

Table 1 lists the means, standard deviations, and t-values for the AP and the
control group for the demographic variables included in this study. There were no
signiﬁcant differences between the groups in the number of semesters completed and the
number of credits completed. However, there was a signiﬁcant difference between the
groups in grade point average. The average grade point average (GPA) for the control
group was 2.84 and for the AP group was 2.09 (t = 2.65, p < .01). I A signiﬁcant
correlation was found between GPA and scores on the Time Use Questionnaire (r = -.39,

70

Table 1

Mean Comparisons on Demographic Variables for the
Academic Probation and Control Groups

 

 

 

 

 

Academic Control
Probation Group
Variables M S_D M S_D t: p
value
Age , 25.2 7.8 22.9 5.3 1.34 ns
Credits 22.3 17.2 27.4 19.4 1.07 ns
Semester 4.3 2.5 3.6 2.5 0.97 ns
GPA 2.1 0.86 2.8 1.1 2.65 <.01
N=33 N=30

GPA = Grade Point Average

71

p < .01) for the entire sample in this study. As procrastination scores increase GPA
decreases. This relationship was true for both the AP and control groups. There were
also differences between the control group and the AP group on ethnicity. Seventy-six
percent of the control group was Caucasian, compared to only 51% of the AP group.
Conversely, the control group was 10% Hispanic and 7 % Aﬁican American, while the
AP group was 24% Hispanic and 15% Aﬁican-American.

Group Differences in Procrastination.

 

The ﬁrst prediction, that subjects in the Academic Monitoring Program or on
academic probation (AP) would report signiﬁcantly higher levels of academic
procrastination than a control group, was supported. The AP group had a mean score of
55 on the Time Use Questionnaire compared to a score of 44.7 for the control group (t =
3.25, p < .001). There were also signiﬁcant differences in reported procrastination levels
between the groups. Sixty-four percent of the AP group reported that procrastination was
a problem compared to only 36% of the control group (X2 = 4.57, p<.05).

Group Differences on Control Variables.

 

As indicated in the methods section, several variables were included to control for
their potential relationships with executive functioning performance. The three variables
are depression (BDI), Attention-Deﬁcit Disorder (WURS), and intellectual functioning
(IQ). Table 2 contains the means, standard deviations, and t values for the two groups for
these three variables. The AP group scored signiﬁcantly higher on depression with a
mean score of 11.6 on the BDI while the control group had a mean of 6.1 (t=3.26, p<
.001). There were no signiﬁcant differences on the Wender Utah Rating Scale between
the two groups (t = 1.09, p < .28). An additional important ﬁnding was that there was no

72

Table 2

Mean Comparisons of Control Variables for the
Academic Probation and Control Groups

 

 

 

 

 

Academic Control
Probation Group
Variables M . §I_) M 52 t; 2
value
BDI 11.6 7.5 6.2 5.6 3.26
<.001
WURS 28.6 16.5 24.4 13.7 1.09 ns
FSIQ 96.9 0.44 98.1 11.9 0.44 ns
N=33 N=30

Note: BDI - Beck Depression Inventory
WURS - Wendor Utah Rating Scale
FSIQ - Wechsler Adult Intelligence Scale Full Scale IQ

73

signiﬁcant mean difference on IQ. The AP group had an estimated Full Scale IQ of 96.9
while the control group had a Full Scale IQ of 98.1 (t = .44, p < .66).

Group Differences on Measures of Executive Functioning.

 

Table 3 lists the means, standard deviations, and t-values for the AP group and the
control group on the 3 measures of executive functioning. No signiﬁcant differences
were found between the two groups on the COWAT and the TTT. On the RFFT total
number of constructions, the AP group performed signiﬁcantly worse (Raw score = 67.2)
than the control group (Raw score = 85.1)(t=3.l2, p< .001). There was no signiﬁcant
difference between the two groups on the Error Ratio score, which is an indication of
perseveration, of the RFFT.

Relationship between Procrastination and Executive Functioning Measures.

 

The second prediction, that academic procrastination and performance on three
measures of executive functioning would be signiﬁcantly inversely related, was not
supported. The correlation matrix in Table 4 reports the relationships between the
executive ﬁinctioning measures and procrastination, and between all the executive
functioning measures. Procrastination scores on the Time Use Questionnaire (TUQ)
were not correlated with verbal ﬂuency on the COWAT(r = .112), non-verbal ﬂuency on
the RF FT (r = -.126), and general executive functioning ability on the TIT complexity
index (-.002). Both the TIT and the RFF T contain additional scales that were also
included in the analysis. It was found that the error ratio score on the RFF T was not
signiﬁcantly correlated to the TUQ (r = -.177). Neither of the additional
TIT scales, total number of pieces and total elapsed time for the construction, were
signiﬁcantly related to procrastination scores (r = -.002, r = .176 respectively)

74

Table 3

Mean Comparisons of Executive Functioning
Measures for the Academic Probation & Control Groups

 

Academic Control

 

Probation Group
Variables M S_D M M)_ t_-_ p
value
TUQ 55 13.2 44.7 11.7 3.25 <.001
COWAT 36.6 9.5 37.4 7.6 0.38 ns
RFFT 67.2 23.3 85.1 22.3 3.12 <.001
RFFT c_, 44.2 9.1 43.9 8.9 0.14 ns
I 1'] 92 26.2 12.8 25.2 11.9 0.32 ns
1'” m2 7 1.5 7 1.6 0.01 ns
1 I l t;_mc_ 240.5 122.7 253.7 139.4 0.40 ns
N = 33 N = 30

Note: TUQ = Time Use Questionnaire
COWAT = Controlled Oral Word Association Test
RF FT = Ruff Figural Fluency Test
RFFTE. Ruff Figural Fluency Test Error Ratio Score

TTTQE = Tinkerytoy Test Total number of pieces
mm: Tinkertoy Test Complexity Score
mm = Tinkertoy Test Total Time to complete construction

75

Table 4

Intercorrelations between the Time Use Questionnaire (TUQ)
and Measures of Executive Functioning

 

 

 

Variables 1 2 3 4 5 6 7
1. TUQ --

2. COWAT 0.11 --

3. RFFT -0.13 0.36* --

4. RFFT g -0.18 -0.02 0.16 ~-

5. TIT 92 -0.00 0.24 0.24 0.02 --

6. TIT 2292 0.04 0.17 0.39* -0.05 064* --

7. TIT 92.5 0.18 0.15 0.21 0.02 0.45* 0.44* --
N = 63 * p < .01

76

Among the measures of executive functioning, several signiﬁcant relationships were
found. Verbal ﬂuency (COWAT) did signiﬁcantly correlate with non-verbal ﬂuency
(RFFT) (r = .355, p < .01). The RFFT was also correlated with the complexity score on
the TIT (r = .391, p < .01). The remaining signiﬁcant relationships were between the 3
different TTT scores: total number of pieces used in the construction (TTTr_rp), total time
taken to complete construction (TIT m), and the complexity of the construction (TTT
comp). All three of the TIT scores produced large positive intercorrelations ranging
from r = .441 between TTTM and TTTti_mg to r = .641 between TITr_rp and mm
(all p < .01).

A step wise linear regression was run to test the third prediction that the executive
functioning variables would explain a signiﬁcant amount of variance in the
procrastination scores after accounting for the potential control variables of depression,
intelligence, and ADHD status. All control variables are continuously scaled and were
entered into the regression in step one. The three measures of executive functioning are
also continuous variables and were aggregated to produce one overall executive
functioning score for each subject. Results of the step-wise multiple regression were
non-signiﬁcant. Step one, which consisted of the three control variables, produced a R2 =
.055, F(3,58) = 1.13, p = .346. Step two, which incorporated the aggregate measure of
executive functioning, was also non-signiﬁcant with a R2 = .059, F-to-change (3,55) =
.084. Based upon the results of the analysis conducted so far, the proposed discriminant
function analysis to test prediction four was not done. Since the correlation matrix and
the step-wise multiple regression showed a non-signiﬁcant relationship between the
independent and control variables and procrastination scores, the analysis became moot.

77

Post Hoc Comparisons.

 

Because of the unexpected ﬁndings of this study, ftuther post hoc analyses were
conducted in an attempt to further clarify a possible relationship between procrastination
and executive functioning. All subjects who self-reported procrastination in this study
(N =32) were divided into either a high or low procrastination group through the use of a
median split and then subjected to t-tests. Table 5 presents the means, t-scores, and p-
values for the 3 control variables and 5 executive ﬁrnctioning measures. From a review
of Table 5, no signiﬁcant mean differences were found between the high and low
procrastination group. Furthermore, the means were not consistently elevated in the
expected direction. Based upon the predictions of this study, it would be expected that
the low procrastinators compared to high procrastinators would perform better on the
executive functioning measures. However, the high procrastinators produced higher
scores on the COWAT, TITr_rp_, and mm. The only measure that the two groups
performed as expected was the RF FT total score where the high procrastinators produced
fewer unique designs than the low procrastinators.

The last post hoc analysis conducted revisited prediction 2 that there would be a
negative correlation between scores on academic procrastination and performance on
measures of executive functioning. As reported earlier, no signiﬁcant correlation was
found in this study. In that analysis the scores for the entire sample (N =63) were utilized
to test the hypothesis. While that sample size increased the power of the analysis making
lower correlation coefﬁcients statistically signiﬁcant; it also included all of the control
subjects for whom no relationship between procrastination and executive functioning was
expected a priori. In order to explore the relationship between the clinical procrastinators

78

Table 5

Mean Comparisons of Control Variables and Executive
Functioning Measures for High and Low Procrastinators

 

 

 

 

PROCRASTINATION

High Low

Variables M M t_- p
value

BDI 12.5 9.0 1.30 ns
WURS 30.3 26.1 0.71 ns
WAIS-F S 98.8 95.9 0.71 ns
COWAT 38.8 36.1 0.79 ns
RFFT I 35.6* 37.6* 0.54 ns
TTT g, 42.6 45.8 0.96 ns
TTT 22 29.6 24.5 1.05 ns
TTT m 7.4 6.8 1.27 ns

N = 16 N = 16
" T -Scores

79

and executive functioning, correlations were computed between the measures of
executive functioning and the TUQ for the Academic Probation (AP) group. Based on
the AP sample size of 33, a correlation of at least .35 is required for statistical
signiﬁcance. Consistent with the earlier ﬁnding, none of the correlations between the
TUQ and executive functioning were signiﬁcant. The only correlation that exceeded r =

.20 was between TUQ and the I l 1% (r= .21).

80

CHAPTER V
DISCUSSION

This exploratory study had two goals. The ﬁrst goal was to successfully identify
and investigate a group of “clinical” procrastinators whom do not represent the “samples
of convenience” that predominates the procrastination literature. The second goal was to
explore the relationship between academic procrastination and executive functioning
ability. As mentioned earlier, the procrastination literature has inadequately addre$sed
the issues of chronicity and severity of procrastination in their samples. The typical
approach to deﬁning the severe and chronic procrastinators has been to take students
from undergraduate psychology courses and divide them into high and low
procrastination groups by using a median split procedure based upon questionnaire
scores.

In the current study, the attempt to identify and investigate a group of “clinical”
procrastinators proved successful. It was predicted that students who were on academic
probation or who were being monitored for poor academic performance would produce
higher scores on a reliable and valid measure of procrastination. This prediction was
strongly supported with the academic probation group producing a signiﬁcantly higher
mean score than a control group of psychology students.

Further evidence that the academic probation group in this study represents a
group with severe and chronic procrastination can be found by looking at Aitken’s (1982)
original sample from which she developed the procrastination questionnaire used in the
current study. In her validation study, Aitken administered the procrastination
questionnaire to 120 freshman and sophomore university students (62% women, 38%

81

men). The mean total procrastination score was 46.4 (SD = 12.0), virtually identical to
the mean of 44.7 (SD = 11.7) obtained for the control group in the current study. It is
also interesting that the sex breakdown in the current study (66.7% women, 33.3% men)
is remarkably similar to Aitken’s sample. Both Aitken’s mean of 46.4 and the mean of
44.7 obtained in this current study are far below the mean of 55.0 (SD = 13.1) obtained in
this study for the academic probation group. The control samples from the current study
and the Aitken study are typical of subjects of whom most of our understanding of
procrastination has been founded. Signiﬁcantly less is known about the cognitive,
affective, and behavioral correlates of severe and chronic procrastinators such as those
identiﬁed in this study.

For the procrastinators in this study, their behavior has had deleterious
consequences including signiﬁcantly lower grade point averages as well as statistically
signiﬁcantly higher levels of reported depression when compared to the control group.
This study has demonstrated an effective way of identifying those individuals for whom
procrastination is potentially debilitating. It is imperative that future research into
procrastination takes the issue of sampling seriously if the ﬁeld hopes to help those
individuals who are most adversely affected by this condition.

While the goal of identifying and investigating a group of clinical procrastinators
was met, the same cannot be said for the second and primary goal of this investigation,
namely, to establish the presence of executive functioning deﬁcits in those individuals
with chronic and severe procrastination. The discussion about sample selection provides
some reasonable assurance that the procrastinators in this study were not garden-variety
procrastinators for whom the behavior is simply annoying or inconvenient. Rather they

82

represented a group of individuals who were falling behind and having difﬁculty
completing college classes as indicated by their presence in either the academic
monitoring program or being placed on academic probation. The difficulties the
procrastination group is experiencing cannot be attributed to differences in other
variables such as intelligence or the presence of a learning disability for there were 'no
signiﬁcant differences between the procrastinators and the control group on these
variables. It was hypothesized that these community college students struggled with
relatively weaker executive functioning abilities, which made it difficult for them to
manage the demands of the college environment

The failure to ﬁnd a signiﬁcant relationship between procrastination and several
measures of executive functioning was unexpected. As addressed in the literature review,
there was reasonable justiﬁcation for expecting an important relationship between
procrastination and executive functioning ability. Additionally, the most proliﬁc writers
in the ﬁeld of procrastination (Ferrari, Johnson, & McCown, 1995) suggest the feasibility
of such a relationship. The current ﬁndings suggest three plausible explanations: 1)
There is no relationship among the variables, 2) the current sample was too small to
provide the power to detect the relationships, or 3) the measures of executive functioning
that were selected were inadequate in measuring the abilities under investigation. With
regards to the ﬁrst explanation, as is reﬂected in Table 4, none of the 6 indices of
executive functioning was signiﬁcantly correlated with scores on the procrastination
questionnaire (Time Use Questionnaire). The only signiﬁcant relationship in Table 4 was
among the measures of executive functioning. The COWAT and RF F T were positively
correlated, which is consistent with other research (Demakis and Harrison, 1997) which

83

found a positive relationship, in their sample of 134 college students, between these same
measures of verbal and non-verbal ﬂuency. The RF F T was also positively correlated
with the TTTgomgscore, which is consistent with Malcolm’s (1993) results. Also
consistent with this current study is the Malcolm’s ﬁnding of no signiﬁcant relationship
between TIT_cg_rr_rp scores and scores in verbal ﬂuency (COWAT). Since the TIT is a
non-verbal constructional task that is conceptually closer to the RFFT than the COWAT,
it is not surprising that the TTTco_mp would not be signiﬁcantly related to the COWAT.

The only ﬁnding potentially suggestive of a relationship between executive
functioning and procrastination was a mean difference on the RFF T with the academic
probation group performing signiﬁcantly more poorly than the control group. Since it
was established that the academic probation group does represent a group of severe
procrastinators (prediction 1), it can be suggested that the severe procrastinators
performed signiﬁcantly more poorly on a task of executive functioning than the control
group.

This group difference on the RFFT is not only statistically but clinically
signiﬁcant as well. The mean score of 67.2 designs for the AP group (SD = 23.2)
corresponds to a T-score of 34.2 which falls in the low average range. The control
group’s mean of 85.1 unique designs (SD = 22.1) falls into the average range. The
performance of the control group is remarkably similar to the mean score of 86.9 unique
designs (SD = 21.9) obtained by Demakis and Harrison (1997). In their study, they
administered the RFFT to 134 college students to investigate the correlation between the
same verbal and non-verbal ﬂuency measures utilized in the current investigation. The
similarity in performance by the Damkis and Harrison sample and the control group in

84

this current study further establish a real difference in non-verbal ﬂuency between
clinical procrastinators and control subjects. What speciﬁc ability these two groups differ
in is still unclear based on the results of the current study. The RFF T provides
information about divergent drinking, cognitive ﬂexibility, and the ability to use planning
strategies. The lack of support for prediction 2 makes it impossible at this point to argue
for which speciﬁc executive functioning ability, if any, is responsible for the large
performance difference.

Two other analyses supported the ﬁrst explanation that no relationship exists
between procrastination and executive functioning ability. Means were also compared by
dividing the entire study sample into procrastinators and non-procrastinators regardless of
whether they were on academic probation. The assignment to each group was based on
the subject’s response on the demographic sheet (See Appendix A) to the question “do
you feel like you have experienced problems in school because of procrastination?”
When comparing these two groups, there was no signiﬁcant difference on any of the
executive functioning measures. One last comparison was done which involved dividing
the just mentioned procrastination group into a high and a low group using a median split
procedure. When the high and low procrastination groups were compared on the
COWAT, RFF T, RFF T error ratio, TITgp, and TITcomp no signiﬁcant mean
differences were found.

The second potential explanation for ﬁnding no signiﬁcant relationship between
procrastination and executive functioning involves the possibility of having committed a
Type 11 error. It is conceivable that the sample size employed in this exploratory study
was too small, lacked power, and that the hypothesized relationship between executive

85

functioning and procrastination exists but is not being detected. From visually inspecting
the correlations in Table 4 it can be seen that several of the executive ﬁrnctioning
measures had correlations above .10 suggesting a weak but non-signiﬁcant relationship.
If the sample size had been increased and the size of the relationships remained
unchanged, then there would have been statistical signiﬁcance but questionable practical
signiﬁcance of the ﬁndings.

Since there was no prior research in this area of investigation to provide a
guideline as to an expected effect size, Cohen’s rule of thumb approach for classifying
effect size was used. With an alpha = .05, power = .80, and an estimated effect size of .5
standard deviations, the sample size obtained in this study exceeds the recommended
sample size of 25 subjects per group. Given the size of the correlation coefficients
obtained in addition to the results of the post-hoc analysis, the likelihood of a Type 11
error seems very remote.

The third potential explanation for the lack of ﬁndings between executive
functioning and procrastination touches on a fundamental assumption of this study. The
results of this study are predicated on the assumption that the selected measures of
executive functioning and procrastination are reliable and valid instruments. Of
particular importance to this study is the construct validity of the measures of executive
functioning. Ferrari, Johnson, and McCown (1995) reviewed Aitken’s (1982) Time Use
Questionnaire and reported it to be a psychometrically sound measure of academic
procrastination for college students. As a result, there is little reason to suspect that

procrastination has been poorly measured in this study. However, the issue of how to

86

effectively assess executive functioning has a long history of debate, the details of which
are relevant to the ﬁndings of this study.

As reviewed earlier, executive functioning has been deﬁned as having several
components including the capacities for formulating goals, planning how to perform
those goals, and carrying the goals out in an effective manner. These capacities are
crucial for independent, creative, and socially constructive behavior (Lezak, 1982).
Equally crucial is the ability to accurately measure those abilities that are critical to
independent functioning. The effective assessment of executive functioning should help
to identify which of the executive ﬁrnctioning components identiﬁed above may be
dysfunctional.

Unfortunately, a paradox exists when trying to assess executive functioning
ability (Lezak, 1995). There is a great deal of structure inherent in the typical
psychological testing situation. The examiner determines what activity the subject will
do and with what materials. The structure is not problematic in cognitive assessment,
which seeks to determine how much knowledge, skill, or intellectual ability one has.
Accordingly, psychology has a plethora of tools for identifying and making ﬁne
discriminations of cognitive functions such as memory, attention, or intelligence. In
contrast, testing structure directly impedes the ability to measure executive functioning
and to answer such questions as how a person goes about doing a task or whether it is
done at all. Lezak (1982) poignantly puts it this way:

Questions dealing with executive functions ask how well a patient maintains a

performance rate, how consistently and effectively he self-corrects, how

87

responsive is he to changes in the demands of the task, or does he start and stop

activities by himself and if so, how apprOpriately, and so on (p. 282).

Obtaining the answers to these questions is not conducive to the typical
assessment setting because while the examiner wants to be able to observe these abilities
of executive functioning, the examination setting itself places the subject within a
structured setting in which the examiner dictates what the subject is to do. Unfortunately,
the executive functioning measures selected for this study are not immune from the
paradox of trying to evaluate how participants structure themselves in a situation that is
already structured for them. This dilemma was considered when selecting the COWAT,
RFFT, and the TTT for this study. I attempted to select from the available measures
those that seemed the least structured in addition. to those that have been found to
primarily represent pre-frontal cortex.

Another possible more productive approach to measure selection would have
been to select one reputable test that corresponds to each of the 4 components of
executive functioning. That would not have necessarily led to entirely different measures '
as the ﬂuency measures used in this study are considered to be mainstream
neuropsychological tests. However, the Tinkertoy Test is considered a relatively new
measure of executive functioning, which has not been extensively used either clinically
or in research. ’

i In addition to the difficulty of evaluating executive functioning ability, the issues
of response bias and sex differences may have contributed to the unexpected ﬁndings of
this study. When recruiting for the academic probation group, there was only a 5-10%

response to the recruitment letters. In addition, 60% of the subjects who did respond
88

failed to complete participation for a variety of reasons, e.g. not showing up at arranged
time, not returning phone calls. As a result, the sample obtained likely represents the
“best” of those on academic probation. It can be argued that the obtained sample is the
higher functioning individuals of the entire academic probation population. It is
reasonable to question whether the 90% who did not respond to the recruitment letter are
different in important ways including executive functioning. Did they choose not to
participate because they were not interested or was it possibly because they were too
disorganized to ﬁt anything else into their days. The non-participants may have reported '
similar levels of procrastination as the sample obtained, however, they may do so for the
reasons predicted in this study. Future research would be best served by expending the
time and effort to capture a larger percentage of students on academic probation.

There was also some potentially important sex differences in the academic
probation group. Women appear to be slightly over-represented in the academic
probation group. In the current study, women represented 57% of the subjects on
academic probation, which is higher than the 43.9% and 45.8% reported by LCC and
GCC respectively. This ﬁnding suggests that women were more willing than men to
participate in the current study. The reasons for this difference can only be speculated.
Perhaps this volunteer bias could indicate that women, in general, are more willing to be
helpful to others in need. It could also suggest that the women were more concerned
about their probation status and believed that participation would somehow be beneﬁcial
to them. This explanation becomes more feasible when recalling that the stated purpose
of the study was to “investigate factors that interfered with the timely completion of
community college.” Women were also over-represented in the control group, as only

89

29% of the control group were male. The issues of response bias and sex differences are
important sampling considerations for future research.

The results obtained in this research were surprising, particularly when considered
in the light of the anecdotal information obtained during data collection. Time was spent
debrieﬁng subjects after their participation was completed. When asked to explain why
they were having difficulty managing the demands of college they would consistently
comment that they were at a loss to speciﬁcally explain what happened. Some subjects
stated that they felt like they knew what they had to do but would have difficulty getting
things “organized to do it. Others stated that there was simply too much for them to keep
up with and that going to college was much harder than they expected. A smaller group
of subjects said they had no idea of what the problem was and that they weren’t sure why
they were going to college.

On a behavioral level, the tremendous difficulties (i.e. no shows, late arrivers) that
this researcher had in getting the subjects to follow through with participation also
seemed to be suggestive of the kind of disorganization that seemed to be of epidemic
proportions with the subjects on academic probation. However, each of these individuals
who were struggling to the point of being on probation and who were verbalizing
problems that seemed to be of an executive functioning nature, were able to sit down in
the structured test situation and perform satisfactorily. Lezak (1982) suggests that
evaluating executive capacities by means of interviews, observation, improvised
assessment techniques, and standardized test will usually "bring to light executive
dysfunctions that may not have become evident in the usual clinical examination.” (p.
285)

90

Nevertheless, what conclusions are to be drawn from this study? Results strongly
suggest that the severe procrastinators in this study do not as a group suffer from
deﬁcient executive functioning ability. What then accounts for the signiﬁcantly higher
levels of procrastination that the AP group evidenced? Unfortunately, this study offers
little direction as to the possible reasons for their procrastination. From this study we do
know that the 2 groups have comparable intellectual abilities. We also know that the AP
group does not represent a group of individuals who are more clinically depressed or
have a higher incidence of learning disabilities. An educated guess would be that the
severe and chronic procrastinators in the AP group are very heterogeneous and are likely
to share the same cognitive, affective, and behavioral correlates identiﬁed in the review
of the procrastination literature. In truth, this is an empirical question because the
procrastinators in this study were selected very differently than the prototypical
procrastination sample. It may be that severe procrastinators have similar but more
extreme proﬁles of cognitive, affective, and behavioral factors established in the
literature. It may also be that entirely different variables are leading to clinical levels of
procrastination.

It would be short sighted to conclude, from the results of this exploratory study,
that neuropsychological variables are not involved in procrastination." Given the small
sample size employed as well as the difﬁculties inherent in measuring executive
functioning, further research in this area is needed. It my opinion that the lack of power
inherent in this study is not responsible for the unexpected results. Rather, ﬁrrther
thought needs to be invested in ﬁnding better instruments or more effective methods for
evaluating a person’s ability to formulate goals, establish plans for meeting goals, and

91

executing those plans. The executive functioning measures selected for this study was
selected because performance on those measures is primarily subserved by the frontal
lobes of the brain. The rationale was to choose measures that were clearly frontal lobe
measures and to choose measures that evaluated both left and right frontal cortex.
Perhaps a more effective approach would have been to select instruments that
corresponded to each of the 4 components of executive functioning described by Lezak
(1983). For example, one component of executive frmctioning is planning ability. This
ability can be evaluated by Such measures as the Tower of London or Porteus Mazes.
Organizational ability could be evaluated by copying a complex ﬁgure such as the one
used in the Rey Complex Figure. It was my intention to more speciﬁCally explore which
speciﬁc executive functioning abilities may be compromised for severe procrastinators if
this exploratory study suggested a relationship between the two.

In summary, an attempt was made in this study to identify a viable research
problem and develop testable questions and a set of hypotheses. An attempt was also
made to establish a methodology that provided a reasonable chance of identifying those
individuals who suffer from severe procrastination without contaminating the sample as
to the true purpose of this study. A theoretical rationale for investigating
neuropsychological factors in procrastination was presented along with its relevance to
the ﬁeld of counseling psychology. It is hoped that this study was successful in
answering the questions posed as well as triggering further empirical interest to more

deﬁnitively clarify neuropsychological variables in procrastination.

92

APPENDIX A

 

Recruitment Letter

Date:

Return address:

Dear ,

 

I am writing to you about a special opportunity that I thought you may be
interested in. Michigan State University has contacted me about a research study that
they will be conducting. The purpose of the study is to learn about factors that interfere
with students ﬁnishing community college in a timely manner. Your participation in this
study involves you completing a few brief questionnaires and a short test battery of your
thinking skills. You can complete your participation in 50 to 60 minutes. For your
participation you will be paid $10 at the end of the hour.

Your participation is completely voluntary. You are free to withdraw ﬁom the
study at any time. Your participation in this study will be treated with strict conﬁdence
and you will not be personally identiﬁed in any of the results or test materials. Your
academic counselor or myself will not have access to your test results or any of your
questionnaire responses. In fact, I won’t even know if you chose to participate. The
results of this study and any additional information that you would like to know will be
made available to you at you request. If you are interested in participating or have any

other questions, please call David Stone at (517) 371-8530.

Sincerely,

93

Dr. John Cansﬁeld

Director, Counseling Center

Note: This was the letter used for Lansing Community College. The same letter was
used to recruit from Glendale Community College. The only changes were my phone
number and the name of the Director of the counseling center. - APPENDIX A

94

APPENDIX B

Client Information Sheet

1) Subject Number:

 

2) Sex: 3) Age:

 

3) Ethnic Background e.g. Caucasian, Aﬁican-American:

 

4) Length of time (Number of semesters) spent at Community College so far:

 

6) Credits completed to date:

 

7) Major:

 

8) Grade point average:

 

9) Are you or have you been on Academic Probation?

 

If yes, how many times?

 

10) Do you have a documented learning disability and if so what type?

 

 

11) Have you ever received special education services?

 

12) Have you ever had seizures?

 

13) Have you ever had a serious head injury?

 

95

APPENDIX B cont.

14) Do you feel as if you experience problems in school because of procrastination?

 

If yes, please explain in your own words how long it has been a problem and how
severe you think it is?

96

' APPENDIX C
Consent Form

The purpose of this study is to learn more about factors that interfere with students
completing community college in a timely manner. I understand and agree to the
following conditions: -

1. I freely consent to participate in this study being conducted by David Stone, a
graduate student in Counseling Psychology, under the supervision of Nancy
Crewe, Ph.D., Professor of Psychology at Michigan State University. I
understand that my participation is completely voluntary.

2. I understand that my participation will involve completing some questionnaires
and a short battery of tests that will assess my thinking skills. These tests will ask
me to answer questions, complete some paper and pencil tasks, and to assemble
some objects. The total time to complete my participation is between 50 to 60
minutes.

3. I also understand that a photograph may be taken of an object that I assemble.
The only identifying information in the photograph is an ID. number.

4. I understand that my name (ﬁrst name only) will only be known by David Stone
and that it will be held in strict conﬁdence. I further understand that my name
will not appear on any questionnaires or test materials. In addition, I understand I
will remain anonymous in any report of the research ﬁndings.

5.° I understand that I may choose not to participate or choose to withdraw my
participation at any time without penalty. Your academic counselor will not
have access to your test results or any of your questionnaire responses.

6. I understand that I will receive a $10 stipend as a result of my participation in this
study.
7. I understand that if I have any questions or concerns that arise as a result of my

participation in this study, I can contact David Stone at (517) 646-8007.

Signature Date

 

97

APPENDIX D

TIME-USE QUESTIONNAIRE
Directions: This questionnaire will give information about your use of time and study behavior. There are
no correct answers so please answer honestly. Please use the following scale to answer the statements
below. Write the letter from the scale below in the space provided at the end of each statement.
A=True B=Mostly C=Cannot =Mostly E=False
True Say False
l. l delay starting things until the last possible minute.
2. I am careful to return library books on time.
3. I often don’t ﬁnish tasks on time.
4. I usually meet my own self-set deadlines.
5. Even when I know that a job needs to be done, I never want to start it right away. _
6. 1 keep my assignments up to date by doing my work regularly from day to day. _
7. If I have a number of jobs that need to be done by the end of the day, 1 usually get them done.
8. If there were a workshop offered that would help me learn not to put off starting my work, I would go.
9. 1 don’t seem to know when I need to start a job to be able to get it done on time. _
10. 1 am often late for appointments and meetings.
1 l. I use the vacant hours between classes to get a head start on my evening’s work.
12. I delay starting things so long that I sometimes don’t get them done by the deadline.
13. 1 overestimate the amount of work that 1 can do in a given amount of time.
14. I don’t delay when 1 know that I really need to get ajob done.
15. If I have an important project to do, I get started as soon as possible.
16. When I have a test scheduled soon, I often ﬁnd myself working on other jobs instead of studying for
the test.
17. I often ﬁnish my work well before it is due.
18. I get right to work at jobs that need to be done.

19. If I have an appointment, 1 make certain that the clothes 1 want to wear are ready the day before.

98

APPENDIX E
I I I Scoring Protocol (Taken from Malcolm, 1993):

Two sets of scores are derived from the subjet's construction: number of pieces uses
( I I I pp) and the total for the complexity score (I I Icomp).

1) TITnp for the ﬁnal construction can have a maximum value of ﬁfty. It it is
unclear to the examiner whether certain combination of pieces are inteded to be part of
the ﬁnished construction, the subject should be asked about it. In general, any
combination of pieces should be included in the ﬁnal T'ITgp score.

2) The I I Icomp score represents eight variables (see scoring sheet) with the
higest possible score being 12 and the lowest possible score being a -1.

a) gig: Does the subject combine any pieces in the course of the construction (i.e.
versus aimlessly manipulating pieces without putting any together)?

b) r_rp: Identical to I I I r_rp with an ordinal scale.
c) name: Does the subject name the ﬁnal construction?

d) mov: Does the ﬁnal construction have freely moving parts; does it have
mobility, i.e., functionally rolling wheels?

e) gym: Does the ﬁnal construction have parllelism of design, i.e., eithe two
facing sides corresponding in the arrangement of pieces (symmetry x 2), or two
pairs of mathcing sides (symmetry x 4), although each pair can represent a
different design.

f) Q: Is the ﬁnal construction three-dimensional (i.e., versus piesceslying ﬂat on
the surface of the table)?

g) stand: Is the entire ﬁnal construction free-standing (i.e., versus pieces needing
to be held up by hand or propped up by means of support other tlm by the
construction itself)?

99

APPENDIX E cont.

h) error: As described above, this sCore refers to whether there were errors of
misﬁt pieces, incomplete connections, or pieces that are dropped and not picked

up.

100

APPENDIX F

 

THE TINKERTOY TEST
SUMMARY OF SCORES

Subject Number:
Date of Testing:

 

 

SCORES:

1. Number of pieces (TTTrrp) =

 

2. Complexity Score (TITcomp) =

 

M_c_ score either lor 0

Np score as follows: np less than or equal to 20 = lpts, np from 21 to 30 = 2 pts,
np from 31 to 40 = 3pts, 41 to 50 = 4 pts.

PM. score 1 or 0

We soore 1 or 0 for mobility and l or 0 for moving parts. Max score = 2.
.3131. score 0, 1 for symmetry X2, 2 for symmetry X4 Max score =2

M score 1 or 0

s_taid score 1 or 0

CI'I'OI' score -l for one 01' more errors.

101

APPENDIX G

BECK DEPRESSION INVENTORY

This questionnaire consists of 21 groups of statements. After reading each group of
statements carefully, circle the number (0,1,2,3) next to the one statement in each group
which best describes the way you have been feeling the past week, including today. If
several statements within a group seem to apply equally well, circle each one. Be sure to
read all the statements in each group before making your choice. .

1. 0 I do not feel sad.
1 I feel sad.
2 I am sad all the time and I can't snap out of it.
3 I am so sad or unhappy that I can't stand it.
2. 0 I am not particularly discouraged about the future.
1 I feel discouraged about the future.
2 . I feel I have nothing to look forward to.
3 I feel that the future is hopeless and that things cannot improve.
3. 0 I do not feel like a failure.
1 I feel I have failed more than the average person.
2 As i look back on my life, all I can see is a lot of failure.
3 I feel I am a complete failure as a person.
4. 0 I get as much satisfaction out of things as I used to.
1 1 don't enjoy things the way I used to.
2 I don't get real satisfaction out of anything anymore.
3 I am dissatisﬁed or bored with everything.
5. 0 I don't feel particularly guilty.
1 I feel guilty a good part of the time.
2 I feel quite guilty most of the time.
3 I feel guilty all of the time.

102

10.

11.

12.

MNHO WNt-‘O MNHO MN—‘O DON—‘0 “NF-‘0

WN—‘O

APPENDIX G cont.

1 don't feel I am being punished.
I feel I am being punished.

I expect to be punished.

I feel I am being punished.

I don't feel disappointed in myself.
I am disappointed in myself.

I am disgusted in myself.

I hate myself.

I don't feel I am any worse than anybody else.

I am critical of myself for my weaknesses or mistakes.
I blame myself all the time for my faults.

I blame myself for everything bad that happens.

I don't have any thoughts of killing myself.

I have thoughts of killing myself, but I would not carry them out.
I would like to kill myself.

I would kill myself if I had the chance.

I don't cry any more than usual.
I cry more now than I used to.

I cry all the time now.

I used to be able to cry, but now I can't cry even though I want to.

I am no more irritated by things than I ever am.

I am slightly more irritated now than usual.

I am quite annoyed or irritated a good deal of the time.
I feel irritated all the time now.

I have not lost interest in other people.

I am less interested in other people than I used to be.
I have lost most of my interest in other people.

I have lost all of my interest in other people.

103

13.

’14.

15.

16.

17.

18.

19.

WNv-‘O WN—‘O WNI-‘O WN—‘O Nt-‘O WN—‘C

WNr-‘O

APPENDIX G cont.

1 make decisions about as well as I ever could.

I put off making decisions more than I used to.

I have greater difficulty in making decisions than before.
I can't make decisions anymore.

I don't feel that i look any worse than I used to.

I am worried that I am looking old or unattractive.

I feel that there are permanent changes in my appearance that make me
look unattractive.

I believe that I look ugly.

I can work about as well as before.

It takes an extra effort to get started at doing something.
I have to push myself very hard to do anything.

I can't do any work at all.

I can sleep as well as usual.

I don't sleep as well as I used to.

I wake up 1-2 hours earlier than usual and ﬁnd it hard to get back to sleep.
I wake up several hours earlier than I used to and cannot get back to sleep.

I don't get more tired than usual.

I get tired more easily than I used to.

I get tired from doing almost anything.
I am too tired to do anything.

My appetite is no worse than usual.

My appetite is not as good as it used to be.
My appetite is much worse now.

I have no appetite at all anymore.

I haven't lost much Weight, if any, lately.
I have lost more than ﬁve pounds.

I have lost more than ten pounds.

I have lost more than ﬁfteen pounds

104

20. 0
l
2
3
21. 0
1
2
3

APPENDIX G cont.

I am no more worried about my health than usual.

I am worried about physical problems such as aches and pains, or upset
stomach, or constipation.

I am very worried about physical problems and it's hard to think of much
else.

I am so wonied about my physical problems that I cannot think about

anything else.

I have not noticed any recent changes in my interest in sex.
I am less interested in sex than I used to be.

I am much less interested in sex now.

I have lost interest in sex completely.

Interpreting the Beck Depression Inventory

 

Add up the score for each of the twenty-one questions and obtain the total. Scores will
range from zero to sixty-three.

Total Score

1-10
11-16
17-20
21-30
31-40
over 40

Levels of Depression

 

Normal ups and downs

Mild mood disturbance .
Borderline clinical depression
Moderate depression

Severe depression

Extreme depression

105

APPENDIX H

WENDER UTAH RATING SCALE

 

AS A CHILD I WAS (OR HAD)

Not at all or
very slightly

Mildly

Moderately

Quite

gm

Much

 

1. Concentration problems. easily distracted

 

. Anxious. wonying

 

Nervous. tidgety

 

. lnattentive, daydreaming

 

. Hot or short'tempered. low boiling point

 

030145908)

. Temper outbursts

 

7. Trouble with stick-to-it-iveness. not following
through. failing to finish things started.

 

8. Stubborn, strong willed

 

9. Sad or blue, depressed. unhappy

 

10. Disobedient with parents. rebellious, sassy

 

11. Low opinion of myself

 

12. Irritable

 

13. Moody. haves ups and downs

 

14. Angry

 

15. Acting without thinking. impulsive

 

16. Tendency to be immature

 

17. Guilty feelings, regretful

 

18. Losing control of myself

 

19. Tenwncy to be or act irrational

 

20. Unpopular with other children. didn't keep
friends for long.

 

21. Trouble seeing things from someone else's
view

 

22. Trouble with school. visits to principals
ofﬁce

 

23. Overall a poor student, slow learner

 

24. Trouble with mathematics or numbers

 

25. Did not achieve up to potential

 

 

x0

 

 

x1

 

x2

 

x3

 

'x4

 

106

 

REFERENCES

Aitken, M. (1982). A personality proﬁle of the college student procrastinator.
Unpublished doctoral dissertation, University of Pittsburgh.

 

American Psychiatric Association. (1994). Diagnostic and Statistical Manual of Mental
Disorders IV. Washington DC: American Psychiatric Association.

 

 

Ashby, J .S., Mangine, J. D., Slaney, RB. (1995) An investigation of perfectionism in a
University sample of adult children of alcoholics. Journal of College Student
Development. M6), 452-456.

 

 

Baddeley, A. (1986). Working Memory. Oxford: Clarendon Press.

 

Bailey, J. & Coppen, A. (1976). A comparison between the Hamilton Rating Scale and
the Beck Depression Inventory in the measurement of depression. British Journal
of Psychiatry, 1_2§, 486-489.

 

 

Baurmind, C. (1971). Current patterns of parental authority. Developmental Psychology
Monographs, 4, 2.

 

 

Bayless, J .D., Vamey, N.R., & Roberts, R.J. (1989). Tinkertoy performance and
vocational outcome in patients with closed head injuries. Journal of Experimental
Neuropsychology, 11(6), 913-917.

 

 

Beck, A.T., Steer, R.A., & Garbin, MG. (1988). Psychometric properties of the Beck
Depression Inventory: Twenty-ﬁve years of evaluation. Clinical Psycholtgy
Review, 8, 7-10.

 

Benton, AL. (1968). Differential behavioral effects in frontal lobe disease.
Neuropsychologia, 6, 53-60.

 

Benton, A.L. & Hamsher, K. (1976). Multilingual Aphasia Examination. Iowa City:
University of Iowa Press.

 

Benton, A.L., Hamsher, K., Vamey, N.R., & Spreen, O. (1983) Contributions in
neuropsychological assessment. New York: Oxford University Press.

 

 

Berzonsky,M.D. (1990). Self-construction over the life-span: A process perspective on
identity formation. In G. J. Neimeyer & R.A. Neimeyer (Eds.), Advances in
personal construct theory ( pp. 155-186). Greenwich, CT: JAI Press.

 

Beswick, G., Roghtblu, ED. & Mann, L. (1988). Psychological antecedents of student
procrastination. Australian Psychologist, 23, 207-217.

 

107

Bridges, K.R., & Roig, M. (1997) Academic Procrastination and irrational thinking: a re-
examination with context-controlled. Personality and Individual Differences.
22(6), 941-944.

 

 

Burka, J .B. & Yuen, L.M. (1983). Procrastination: Why you do it, and what to do about
11. Reading, MA: Addison-Wesley. .

Canavan, AG. (1983). Stylus-maze performance in patients with frontal-lobe lesions:
Effects of signal valency and relationship to verbal and spatial abilities.
Neuropsycholoﬂr, 2_1_(4), 375-3 82.

 

Cicerone, K.D., & DeLuca, J .(1990). Neuropsychological predictors of rehabilitation
outcome. Journal of Clinical and Experimental Neuropsychology, _12, 92-98.

 

Clark, J .L., & Oliver, W.H. Jr.; (1994) Academic Procrastination among Aﬁican-
American college students. Psychological Reports. _7_5, 931-936.

 

Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York.
Academic Press.

 

Council, J .R. (1993). Context effects in personality research. Current Directions in
Psychological Science. 2, 31-33.

 

 

Crockett, D., Belsker, D., Hurwitz, T., & Kozak, J. (1986). Clinical utility of three
measures of frontal lobe dysfunction in neuropsychiatric samples. International
Journal of Neuroscience, M, 241-248.

 

 

Damasio, A.R. The Frontal Lobes. In K.M. Heilman & E. Valenstein (Eds), Clinical
neuropsychology. New York: Oxford University Press, 1979.

 

Demakis, G.J., & Harrison, D.W. (1997). Relationships between verbal and nonverbal
ﬂuency measures: Implications for assessment of executive functioning.
Psychological Reports. 81, 443-448.

 

Donovan, J .M. (1995) Relating psychological measures to anthropological observations:
Procrastination as a ﬁeld proxy for death anxiety. Journal of Social Behavior and
Personality. 10(2), 465-472.

 

Duncan, J. (1986). Disorganization of behavior after frontal lobe damage. Cognitive
Neuropsychology, 3, 271-290.

 

Effert, B.R. & Ferrari, J .R. (1989). Decisional procrastination: Examining personality
correlates. Journal of Social Behavior and Personality, 4(1), 151-156.

 

108

Ellis A. & Knaus, W. .(1977). Overcoming Procrastination. New York: Institute for
Rational LiVing.

 

Ely, D., & Hampton, J. (1973). Prediction of procrastination in a self-pacing
instructional system. ERIC Documentation Service, No. Ed 075501.

 

Estes, W.K. (1974). Learning theory and intelligence. American Psychologist. 2_9_, 740-
749.

 

Ferrari, J .R. (1991) Procrastination and Project Creation: Choosing easy, nondiagnostic,
items to avoid self-relevant information. Journal of Social Behaviour and
Personlaigy. 6(3), 619-628.

 

Ferrari, J .R. (1992). Compulsive procrastination: Some self-reported characteristics.
Psychological Reports, M, 455-458.

 

Ferrari, J .R. (1993) Christmas and procrastination: explaining lack of diligence at a
“real-world” task deadline. Personality and Individual Differences, M, 25-33.

 

Ferrari, J .R., & McCown, W. (1994) Procrastination tendencies among obsessive-
compulsives and their relatives. Journal of Clinical Psychology. 511(2), 162-167.

 

Ferrari, J .R., & Emmons, RA. (1994). Procrastination as revenge: Do people report
using delays as a strategy for vengeance? Personality and Individual Differences.
17, 539-544.

 

Ferrari, J .R., & Olivette, M.J. (1994). Parental Authority and the development of female
dysfunctional procrastination. Journal of Research in Personality. §, 87-100.

 

Ferrari, J .R., & Emmons, RA. (1995). Methods of procrastination and their relation to
self-control and self-reinforcement. Journal of Social Behavior and Personality.
MU), 135-142.

Ferrari, J .R., Johnson, J .L. & McGown, W. G. (1995) Procrastination and Task
avoidance. Plenum Press, New York.

 

Ferrari, J .R., Parker, J .T., & Ware, CB. (1992). Academic procrastination: Personality

correlates with Myers-Briggs types, self-efficacy, and academic locus of control.
Journal of Social Behavior and Personality, 2(3), 495-502.

 

Ferrari, J.R., Wolfe, RN, Wesley, J .C., Schoff, L.A.& Beck, BL. (1995). Ego-Identity
and academic procrastination among college students. Journal of College Student
Deve10pment. 16(4), 361-367.

 

 

109

Flett, G.L., Blankstein, K.R., Hewitt, P.L. & Koledin, S. (1992). Components of
perfectionism and procrastination in college students.

Frost, R.O., Marten, P., Lahart, C., & Rosenblate, R. (1990) The Dimensions of
Perfectionsirn. Cognitive Therapy and Research. M6), 449-468.

 

Fuster, J .M. (1997). The Prefrontal Cortext. New York: Lippincott-Raven Publishing.

 

Gelso, C.J. (1980). Research in counseling: Methodological and professional issues. ﬁg
Counseling Psychologg, 8, 7-35.

 

Giovacchini, PL. (1975). Productive procrastination: Technical factors in the treatment
of the adolescent. Adolescent Psychiatry, 4, 352-270.

 

Goldman-Rakic, RS. (1988). Topography of cognition: Parallel distributed networks in
primate association cortex. Annual Review of Neuroscience, _l_l, 17-156.

 

Grattan, L.M. & Eslinger, P.J. (1992). Long-term psychological consequences of
childhood frontal lobe lesion in patient dt. Brain and Cognition, M, 185-195.

 

Green, L. (1982). Minority students' self-control of procrastination. Journal of
Counseling Psychology, 29(6), 636-644.

 

Harriott, J ., & Ferrari, J .R. (1996). Prevalence of procrastination among samples of
adults. Psychological Reports. 7_8, 611-616.

 

Haycock, L.A., McCarthy, P. & Skay, CL. (1998). Procrastination in college students:
The role of self-efficacy and anxiety. Journal of Counselirg and Development.
16, 317-324.

 

Heaton, R.K. (1981). A Manual for the Wisconsin Card Sorting Test. Odessa, Fla.:
Psychological Assessment Resources

 

 

Hecaen, H. & Albert, ML. (1975). Human Neuropsychology. New York: John Wiley &
Sons, '

Heppner, P.P., Kivlighan, D.M., & Wampold, BE. (1992). Research Design in
Counseling. Paciﬁc Grove: Brooks/Cole Publishing.

 

Herson, M. & Bellack, AS. (1988). Dictionary of Behavioral Assessment Techniques.
New York, N.Y.: Pergamon Press.

 

Hill,M., Hill,D., Chaot, A., & Barrall, J. (1978). A survey of college faculty and student
procrastination. College Student Personnel Journal. 12, 256-262.

 

110

Janis, I.L., & Mann, L. (1977). Decision Making: A psychological analysis of conﬂict,
choice, and commitment. New York: Free Press.

 

 

Jones-Gotrnan, M. & Milner, B. (1977). Design ﬂuency: The invention of nonsense
drawings after focal cortical lesions. Neuropsychologia, 1;, 653-674.

 

Kaczmarek, B.L.J. (1987). Regulatory function of the frontal lobes. In E. Perecman
(Ed.), The Frontal Lobes Revisited. New York: IRBN.

 

Kamath, H.O., Wallesch, C.W. & Zimmermann, P. (1991). Mental planning and
anticipatory processes with acute and chronic frontal lobe lesions: a comparison

of maze performance in routine and non-routine situations. Neuropsychologig, Q.
271 -290.

 

Knaus, W. (1979). Do It Now. Englewood Cliffs, New Jersey: Prentice Hall.

Koopmans, P.C., Sanderrnan, R., Tirnmerrnan, I. & Emmelkamp, P.M.G. (1994). The
Irrational Beliefs Inventory: Development and psychometric evaluation.
European Journal of Psychologigal Assessment, 19, 15-27.

 

Lakein, A. (1973). How To Get Control Of Your Time and Life. New York: The New
American Library.

 

Lamwers, L.L. & Jazwinski, CH. (1989). A comparison of three strategies to reduce
student procrastination in PSI. Teaching of Psychology, 1_6_(1), 8-12.

 

Lay, CH. (1986). At last, my research article on procrastination. Journal of Research in
Personaligy, _2_0, 474-495.

 

Lay, C11. (1988). The relationship of procrastination and optimism to judgments of time
to complete an essay and anticipation of setbacks. Journal of Social Behavior and

Personaligy, _3_(3), 201-214.

 

Lay, CH. (1990). Working to schedule on personal projects: An assessment of person-
project characteristics and trait procrastination. Journal of Social Behavior and

Personaligy, 5(3), 91-103.

 

Lay, CH. (1994). Trait procrastination and affective experiences: Describing past study
behavior and its relation to agitation and dej ection. Motivation and Emotion,
1_8_(3), 269-284.

 

Lezak, MD. (1982). The problem of assessing executive functions. International Journal
of Psychology. M, 281-297.

 

 

lll

Lezak, MD. (1983). Neuropsychological Assessment. New York: Oxford University
Press. '

 

Lezak, MD. (1995). Neuropsychological Assessment New York: Oxford University
Press.

 

Luria, AR. (1973). The Working Brain: An Introduction to Neuropsychology. New
York: Basic Books.

 

Malcolm, CD. (1993)., Lezak’s tinkertoy test: Validity and reliability of an executive
functioning measure. Unpublished doctoral dissertation, Boston University.

 

 

Mattson, A.J. & Levin, HS. (1990). Frontal lobe dysﬁrnction following closed head
injury. The Journal of Nervous and Mental Disease, 178(5), 282-291.

 

Mazziota, J .D., Phelps, M.E., Carson,R.E., & Kuhl, DE. (1982). Tomographic mapping
of human cerebral metabolism: Auditory stimulation. Neurology, 3_2_, 921-937.

McCown, W., & Johnson, J. (1989) Nonstudent validation of an adult inventory of
procrastination. Paper presented at the American Psychological Association, New
Orleans, LA. -

McCown, W. & Johnson, J. (1991). Personality and chronic procrastination by university
students during an academic examination period. Personality and Individual
Differences, 12(5), 413-415.

 

McCown, W., & Roberts, R. (1994). A study of academic and work-related
dysfunctioning relevant to the college version of an indirect measure of impulsive
behavior. Integra Technical paper 94-28, Radnor, PA: Integra, Inc.

 

McCown, W., Johnson, J ., & Petzel, T. (1989). Procrastination, a principal component
analysis. Personality and Individual Differences, M0), 197-202.

 

McKean, K.J. (1993). Using multiple risk factors to assess the behavioral, cognitive, and
affective effects of learned helplessness. The Journal of Psychology. 128(2), 177-
183. ' .

 

McKean, K.J. (1994). Academic helplessness: Appling learned helplessness theory to
undergraduates who give up when faced with academic setbacks. College Student
Journal. 3, 456-462.

 

Milgram, N., & Naaman, N. (1996) Typology in Procrastination. Personality and
Individual Differences. 29(6), 679-683.

 

 

112

Milgram, N.A. & Sadeh, S.M.C. (1994). Correlates of academic procrastination:
‘ Discomfort, task aversiveness, and task capability. The Journal of Psychology,
1_22(2), 145-155.

 

Milgram, N.A., Sroloff, B., & Rosenbaum, M. (1988). The procrastination of everyday
life. Journal of Research in Personality, 2, 197-212.

 

Milgram, N.A., Weizrnan, 1)., & Amiran, a (1991). Situational and personal
determinants of academic procrastination. The Journal of General Psychology;

119(2)z 123-133.

Milgram, N.A., Gehrman,T. & Keinan,G. (1992). Procrastination and emotional upset: a
typological model. Personality and Individual Differences, M02). 1307-1313.

 

Milgram, N.A., Weizrnan, D., & Raviv, A. (1992). Situational and personal determinants
of academic procrastination. Journal of General Psychology, 119(2), 123-133.

 

Miller,L.K., Weaver, F .H., & Semb, G. (1974). A procedure for maintaining student

progress in a personalized university course. Journal of Applied Behavioral
Analyses, 2, 25-28.

Muszynski, S.Y. & Akamatsu, T.J. (1991). Delay in completion of doctoral dissertations

in clinical psychology. Professional Psychology: Research and Practice, 2(2),
1 19-123.

 

Passingham, R. (1993) The Frontal Lobes and Voluntary Action. New York: Oxford
University Press. -

 

Pennington, BR (1991). Diagnosing Learning Disorders: A Neuropsychological
Framework. London: Guilford Press.

 

Perecman, E. (1987). The Frontal Lobes Revisited. New York: The IRBN Press. ,

 

Perret, E. (1974). The left frontal lobe of man and the suppression of habitual responses
in verbal categorical behavior. Neuropsychologia, M, 323-330.

 

Petrides, M. & Milner,B. (1982). Deﬁcits on subject-ordered task after frontal lobe
lesions in man. Neuropsychologia, 20, 249-262.

 

Porat, F. (1980). Creative Procrastination. San Francisco: Harper & Row.

 

Provost, T.A. & Anchors, S. (1987). Applications of the Myers-Briggs Type Indicator in
Higher Education. Palo Alto, CA: Consulting Psychological Press.

 

 

113

Reynolds, W.M. & Gould, J .W. (1981). A psychometric investigation of the standard
and short form Beck Depression Inventory. Journal of Consulting and Clinical
Psychology, 42(2), 306-307.

 

Roberts, S.M., Fulton, M., & Semb, G. (1988). Self-pacing in a personalized psychology
course: Letting students set the deadlines. Teaching of Psychology, 1_5(2), 89-92.

 

Roig, M. & DeTommoso, L. (1995). Are college cheating and plagiarism related to
academic procrastination. Psychological Reports, 7_7(2), 691-698.

 

Rorer, LG. (1983). “Deep” RET: A reformulation of some psychodynarnic explanations
of procrastination. Cognitive Therapy and Research, 1(1), 1-9.

 

Rosati, RA. (1975). Procrastinators prefer PSI. Educational Research and Methods, 8,
17-19.

 

Rothblum, E.D., Solomon, L.J., & Murakami, J. (1986). Affective, cognitive, and
behavioral differences between high and low procrastinators. Journal of
Counseling Psychology, 22(4), 387-394.

 

Ruff, R.M., Evans, R., & Marshall, L.M. (1986). Impaired verbal and ﬁgural ﬂuency
after head injury. Archives of Clinical neuropsychology, 1, 87-101.

 

Ruff, R.M., Light, R.H. & Evans, R. (1987). The Ruff ﬁgural ﬂuency test: a normative
study with adults. Developmental Neuropsychology, 2(1), 37-51.

 

Ruff, RM. (1988). Ruff Figural Fluency Test adminstration manual. San Francisco, CA:
Neuropsychological Resources.

 

Seligman, M.E.P. (1975). Helplessness: On Depression, Development, and Death. San
Francisco, CA: W.H. Freeman.

Senecal, C., Koestner,R., & Vallerand, R.J. (1995). Self-Regulation and academic
procrastination. The Journal of Social Psychology. 135(5), 607-619.

 

Senecal, C., Lavoie, K., & Koestner, R. (1997). Trait and situational factors in
v procrastination. Journal of Social Behavior and Personality. 12(4), 889-903.

 

Shallice, T. (1988). Information processing models of consciousness: possibilities and
problems. In A.J. Marcel & E. Biasiach (Eds.), (pp. 305-333), Oxford: Clarendon
Press.

Shallice,T. & Burgess, P. (1991). Higher-order cognitive impairments and frontal IObe
lesions in man. In H.S. Levin, H.M. Eisenberg, & A.L. Benton (Eds.), Frontal
Lobe Function and Dysfunction. New York: Oxford University Press.

114

Shute, G.E. & Huertas, V. (1990). Developmental variability in frontal lobe function.
Developmental Neuropsychology, 6(1), 1-11.

 

Silverstein, AB. (1982). Two and four subtest short forms of the Wechsler adult
intelligence scale-revised. Journal of Consulting and Clinical Psychology, 5_0_(3),
41 5-418.

Snow, W. G. ,Tiemey, M. C., Zorzitto, M. L., et al. (1988). One-year test-retest reliability
of selected neuropsychological tests in older adults. Journal of Clinical and
Experimental Neuropsychology, _1_0, 60.

 

 

Sohlberg, M.M. & Mateer, CA. (1989). Introduction to Cognitive Rehabilitation:
Theory and Practice. New York: Guilford Press.

 

 

Solomon, L.J. & Rothblum, ED. (1984). Academic procrastination: Frequency and .
cognitive-behavioral correlates. Journal of Counseling Psychology, 3_1 (4), 503-
509.

 

Solomon, L.J, & Rothblum, ED. (1986). Affective, cognitive, and behavioral differences
between high and low procrastinators. Journal of Counseling Psychology, 2(4),
387-394.

 

Spreen.O. (1983). Psychometric properties of dichotic word tests. Journal of Clinical
Neuropsychology, 5(2), 169-179.

 

 

Spreen, O., Tupper,D., Risser, A., Tuokko, H., & Edgell, D. (1984). Human
Developmental Neuropsychology. New York: Oxford University Press.

 

Staats, A.W. (1991). Uniﬁed positivism and uniﬁcation psychology: Fad or new ﬁeld?
American Psychologg, 4_6(9), 899-912.

 

Stanhope, P. D. [Lord Chesterﬁeld]. Letters. December 26,1749. Cited 1n _B__artlett’ s
Familiar Quotations (14th ed..) Boston: Little, Brown and Company, 1968,
p. 719.

 

 

Strub, R.L. (1989). Frontal lobe syndrome in a patient with bilateral globus pallidus
lesions. Archives of Neurology, 431024-1027.

 

Stuss, D.T., Benson, D.F., Kaplan, E.F., Weir, W.S., Naeser, M.A., & Lieberman, 1.
(1983). The involvement of orbitofrontal cerebrum in cognitive tasks.
Neuropsychologia, 21, 235-248.

 

115

 

Tice, D.M. & Baumeister, RF. (1997). Longitudinal study of procrastination,
performance, stress, and health: The costs and beneﬁts of dawdling.
Psychological Science, 8(6), 454-458.

 

Tuckman, B.W. (1991). The development and concurrent validity of the procrastination
scale. Educational and Psychological Measurement, 5_1_, 473-480.

 

Vodanovich, S.J. & Seib, HM. (1997). Relationship between time structure and
procrastination. Psychological Reports, @(1), 211-215.

 

 

Walsh, KW. (1991). Understanding Brain Damage. New York: Churchill Livingstone.

Ward, M.F., Wender, P.H., & Reimherr, F.W. (1993). The Wender Utah Rating Scale:
an aid in the retrospective diagnosis of childhood attention deﬁcit hyperactivity
disorder. American Journal of Psychiatry, 150, 885-890.

Wechsler, D. (1981). WAIS-R Manual. New York: The Psychological Corporation.

 

Wender, P.H., Reimherr, F.W., Wood, D., & Ward, M. (1985). A controlled study of
methylphenidate in the treatment of attention deﬁcit disorder, residual type, in
adults. American Journal of Psychiatry, 142, 547-552. '

 

Wicker, A.W. (1985). Getting out of our conceptual ruts. American Psychologist,
4_0(10), 1094-1103.

 

Williams, D. & Mateer, CA. (1992). Developmental impact of frontal lobe injury in
middle childhood. Brain and Cognition, 20, 196-204.

 

Yakovlev, P.I. & Lecours, AR. (1967). The myelogenetic cycles of regional maturation

of the brain. In A. Minkowski (Ed.), Regional Development of he Brain in Ear1y
LE, (pp. 3-70). Blackwell: Oxford.

 

Zeigarnick, B.V. (1949). Loss of spontaneity due to combat injury to the frontal lobes.
Soviet Psychology, MU), 60-71.

 

Zung, W.W.K. (1965). A self-rating depression scale. Archives of General Psychiay,
12, 63-70.

 

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