MAXED OUT: THE RELATIONSHIP BETWEEN CREDIT CARD DEBT,
CREDIT CARD DISTRESS AND GRADE POINT AVERAGES
FOR COLLEGE STUDENTS
By
Temple Day Smith

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Sociology
2011

ABSTRACT
MAXED OUT: THE RELATIONSHIP BETWEEN CREDIT CARD DEBT,
CREDIT CARD DISTRESS AND GRADE POINT AVERAGES
FOR COLLEGE STUDENTS
By
Temple Day Smith
Few students leave college with a plan for paying off their debt. Starting a career
inundated with student loans and credit card debt burdens is a reality many college students face
today. In the wake of graduation coming to terms with the consequences of credit card debt is
stressful for many students. This dissertation observes the relationship between distress, credit
card debt, and grade point averages for college students.
Evidence suggests that there is a debt culture among college students that varies by
income. Debt culture refers to the tolerance levels students have regarding credit card debt.
Among economically advantaged college students, this study demonstrates that status
consumption encourages purchases to gain peer recognition and social prestige. While
disadvantaged college students illustrate patterns of survival borrowing. Borrowing from credit
cards to meet basic needs such as clothing and textbooks.
Findings from this study illustrate that having credit card accounts in collection increases
distress and negatively affects grade point averages. Secondly, that family income is a significant
predictor for grade point averages and financial literacy. Students who have higher family
incomes report higher grade point averages, and are less likely to have accounts in collection.

ACKNOWLEDGEMENTS
Everyone reads the dissertators acknowledgements. For this reason and for those who
have helped me—I wanted to write acknowledgements that captured (well) how grateful I was
for the gracious support I received from so many. Faculty, family, and friends have helped me
complete this dissertation. I am also indebted to the National Institute of Mental Health and the
American Sociological Association for the opportunities and funding support I received as a
Mental Health Fellow in the Minority Fellowship Program.
The faculty of this department has provided me a most excellent graduate education.
They have set the bar high for me as a new social scientist. The superlative examples of my
committee have taught me how to think like a sociologist, develop capacity for sociological
research, and translate the uniqueness of my ideas into clear scientific writing. I am grateful for
everything they taught me and everything I learned by watching. They are all well deserving of
special recognition.
Dr. Broman has been a good advisor to me throughout my entire graduate school career. I
wandered in his office as an 19 year old undergraduate seeking an independent study, and had no
idea that over a decade later I would continue to visit his office as a graduate student. Under his
mentorship I learned how to design rigorous college level courses, and voice with clarity my
academic voice. He has been a world class advisor, drill sergeant, coach, mentor—and now a
friend. The purplest of prose could not describe how grateful I am to have had the opportunity to
work with such a brilliant scholar. He has been a cheer leader of my abilities when initially I
wasn‘t sure that I was smart enough to pursue a doctorate degree. At 19 he saw potential and
today the world sees a doctor. I am glad that he encouraged me to apply to graduate school and
more importantly that he mentored me.

iii

Dr. Gold has to be the most articulate, and fascinating professor I have ever met. Dr.
Gold is fun to listen to, his academic insights are always relevant, smart, and fresh. Dr. Gold has
given me great advice and assistance whenever I talked with him, especially regarding post
graduation life and my plans. He is administratively timely, warm, and kind. Dr. Gold‘s last
name suits him well, for truly he has a heart of Gold.
Dr. Zhang is the kind of Professor you pray will say ―yes‖ to being on your committee.
She is bionically brilliant and organized. Dr. Zhang is a quantitative genius and modeled a good
example of the type of skill set I hope to possess one day. In the short time that Dr. Zhang
mentored me she has had an enormous impact on not only the quality of this dissertation but the
way I approach research in the social sciences. I am grateful that she was apart of my
committee.
Dr. Canady has been an invaluable source of support and guidance for me personally and
professionally. I have her to thank exclusively for being such a refuge in stormy hours when you
feel like giving up. She helped me overcome many stressors germane to writing a dissertation. I
appreciate her so much for spending time with me and for opening up her home to me on so
many occasions. Her sound thinking, excellent cooking, and good advice have meant so much to
me. Dr. Canady has been so helpful during many crucial decision-points in my life. I thank God
for her spiritual gravity and Christian example. She has shown me how to have an
uncompromised ethical back bone. Proverbs 31:10 says who can find a virtuous woman? It is too
bad the writer didn‘t know Dr. Candy.
My sister Kim has been amazing through this entire process. Kim is a wonderful
example of grace and good humor. I hope one day in the future I can be for her, what she has
always been for me. She has been an ideal big sister, everyone should be as fortunate to have a

iv

sister like Kim. I am so grateful for her—without her support, I may have never finished this
dissertation.
I owe my brother Aaron big. He has made countless breakfasts, dinners, and went above
and beyond to ensure that while in college his financially disadvantaged little sister, could afford
a few extras. Many have brothers – that is just a male sibling. But not everyone has a big brother
(that is something special) especially the one that I have.
Valerie and Jerri Nilson have literally been there from start to finish. To my very first
week of college until my doctoral graduation day. Val quite possibly will never know how
intense an impact she has made on my life, partly because I am not sure how I could ever put that
into words. She has taught me poise, tact, and what thoughtfulness really means. She has shown
me that big things happen when you do the little things right. When J.M. Barrie wrote, ―Always
try to be a little kinder than is necessary,‖ he undoubtedly had been studying Val.
I have always told Cindy Humes that she deserves an award. My graduate career is filled
with memories of all the sweet and thoughtful things she has done for me. Whether it was
bringing a plate of food covered in aluminum foil to the library in the middle of the night,
listening to my endless rants about graduate school, or offering a good word at the right time,
and a big hug. Her love and support has made a profound difference in my life and I am grateful
to be her spiritual daughter.
My friends LaToya Brown-Evans, Tamira Cason-Chapman, Doris Reynolds, LaToya
Murphy, Tonisha Lane, and Geneva Thomas provided countless hours of comic relief, listening
ears for venting, interest in my work, and were there when I needed them most.

v

For keeping your promises, for your loving kindness, for being a present help in the time
of trouble—for all this and so much more I give you praise and thanks, Jesus Christ, my Lord
and Savior.
English writer Thomas Paine once wrote,‖ the harder the conflict, the greater the
triumph.‖ This quote aptly captures the excitement, exhaustion, frustration, and joy this project
has brought me. I have finally triumphed! Indeed.

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TABLE OF CONTENTS

LIST OF TABLES ......................................................................................................................... ix
LIST OF FIGURES ....................................................................................................................... xi
CHAPTER 1
INTRODUCTION .......................................................................................................................... 1
Statement of the Problem .................................................................................................... 6
Significance of the Study .................................................................................................... 7
CHAPTER 2
LITERATURE REVIEW ............................................................................................................... 8
Credit Card Exposure for College Students ...................................................................... 10
Status Consumption .......................................................................................................... 13
Financial Literacy ............................................................................................................. 16
CHAPTER 3
METHODS ................................................................................................................................... 22
Recruitment: Use of Questionnaire ................................................................................... 22
Interview Sample Selection .............................................................................................. 23
Characteristics of the Sample............................................................................................ 25
Sources of Data ................................................................................................................. 27
Questionnaires....................................................................................................... 27
Measures and Reliability....................................................................................... 29
Scale reliability and items used in each scale ........................................... 29
Financial literacy........................................................................... 29
Credit card distress. ....................................................................... 30
Credit card debt. ............................................................................ 31
Interviews .............................................................................................................. 32
Data Analysis .................................................................................................................... 33
CHAPTER 4
RESULTS ..................................................................................................................................... 34
Qualitative Findings .......................................................................................................... 50
Theme 1: Low Levels of Financial Literacy ......................................................... 51
Theme 2: Status Consumption: Students Reported That Spending on
Large Ticket Clothing Items to Gain Peer Recognition Is Important ................... 53
Theme 3: Anticipatory Spending: Students Reported Using Loan Refunds
to Repay Accumulated Credit Debt Incurred During the Semester ...................... 55

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CHAPTER 5
CONCLUSION ............................................................................................................................. 58
Discussion ......................................................................................................................... 60
Limitations ........................................................................................................................ 64
Future Research ................................................................................................................ 67
APPENDIX ................................................................................................................................... 70
REFERENCES ............................................................................................................................. 84

viii

LIST OF TABLES

Table 1.

Descriptive Statistics for the Sample .............................................................. 26

Table 2.

Family Income ................................................................................................ 34

Table 3.

Credit Card Debt ............................................................................................. 35

Table 4.

Grade Point Averages ..................................................................................... 36

Table 5.

Credit Card Ownership ................................................................................... 36

Table 6.

Credit Card Balances ...................................................................................... 37

Table 7.

Father‘s Education .......................................................................................... 38

Table 8.

Mother‘s Education ......................................................................................... 39

Table 9.

Race................................................................................................................. 39

Table 10. Regression Analysis of Credit Card Debt and Credit Card Distress .............. 41
Table 11. Regression Analysis of Credit Card Debt, Family Income and Credit
Card Distress ................................................................................................... 42
Table 12. Regression Analysis of Credit Card Debt, Family Income and Credit
Card Distress ................................................................................................... 42
Table 13. Regression Analysis of Credit Card Debt, Family Income, Race,
Parent‘s Education, Credit Card Balances and Credit Card Distress.............. 43
Table 14. Regression Analysis of Credit Card Debt, Family Income, Race,
Parent‘s Education, and Grade Point Average ................................................ 44
Table 15. Regression Analysis of Family Income, Race, Parent‘s Education,
and Credit Card Balance ................................................................................. 45
Table 16. Regression Credit Card Debt, Family Income and Race ................................ 46
Table 17. Regression Analysis of Family Income, Race, Parent‘s Education,
and Credit Card Balance ................................................................................. 47
Table 18. Regression Analysis of Credit Card Debt, Family Income, Race,
Parent‘s Education, Interaction of Income and Credit Card Debt
and number of Credit Cards ............................................................................ 48

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Table 19. Regression Analysis of Credit Card Debt, Family Income, Race,
Parent‘s Education, Interaction of Income and Credit Card Debt,
Credit Card Balance and Credit Card Distress .............................................. 48
Table 20. Regression Analysis of Credit Card Debt, Family Income, Race,
Parent‘s Education, Interaction of Income and Credit Card Debt,
Number of Credit Cards and Credit Card Distress ......................................... 49
Table 21. Face-to-Face Interview Participants ............................................................... 57

x

LIST OF FIGURES

Figure 1. Collection consequences for missed credit card payments. ............................................ 9
Figure 2. Estimated point deductions from credit score given certain financial events. .............. 11
Figure 3. Relationship between financial literacy, income, credit debt, distress and grade
point averages. ............................................................................................................ 20
Figure 4. Credit card distress. ....................................................................................................... 40

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CHAPTER 1 INTRODUCTION
This dissertation examines credit card debt, credit card distress and grade point averages
for college students. In recent years, there has been a dramatic increase in credit card use among
college students (Lyons, 2004; Wells, 2007). Increased credit card use among college students
has generated concerns that student‘s credit card behavior is putting them at greater risk for high
debt levels and misuse and/or mismanagement of credit after graduation (Lyons, 2004; Hoffman,
McKenzie & Paris, 2008). The analysis of this dissertation examines how undergraduate college
students are handling debt accumulated through credit card usage, and how the strain of
collection efforts impacts both emotional well being and grade point averages.
It is necessary to clearly define the terms used in this study. Credit card debt refers to
money owed on credit cards that has not been paid. Credit card distress refers to the emotional
disturbance student borrowers feel when they cannot pay credit card bills (for example, ‗I have
cried about the bills I owe‘; ‗I spend a lot of time thinking about my credit card bills‘). Lastly,
this study examines the grade point averages of students with accounts in collection. Studying
the ways students handle credit card debt is important because improperly managed credit has
many negative outcomes for college students while in college and after graduation. There are
numerous reasons exploring the credit card debt of college students is crucial. A few reasons are
discussed here, while the literature review in chapter two goes into further detail.
Research on college student credit card debt is needed because credit card debt has
become a serious distraction impairing concentration needed to study (Hayhoe, Leach, Turner,
Bruin, & Lawrence, 2000). When a student has a delinquent account and creditors begin
collection practices, these practices (phone calls, payment letters, etc) hinder a student‘s ability
to give full attention and concentration to studies. Prolonged distractions caused from collection

1

efforts has also been linked to students working longer hours to pay off debt, missing classes,
and ultimately deciding to quit school, such behaviors and decisions affect college student
retention rates (Hayhoe et al.,2000; Joo, Durband, & Grable, 2008; Allen & Jover; 1997 as cited
in Lyons 2004). Improperly managed credit card debt also impacts credit scores, limiting a
student‘s hiring potential in certain fields effecting post graduation employment opportunities
(Wells, 2007; Manning, 2002). The accumulation of credit card debt is also affecting the
disposable income of college student‘s families (Lyons, 2004; Norviltis, Szablicki & Wilson;
Asinof & Chaker, 2002).
While literature has confirmed that the consequences of improperly managed credit are
dangerous for college students, literature has not offered sound explanations for why certain
students are more vulnerable to credit card debt than others. Overall, literature has offered only
surface level explanations cloaked in a language of personal responsibility to delineate why some
students incur unmanageable credit card debt loads while others do not. Implied in the literature
is a belief that credit card spending and the resulting debt are consequences of individual choices,
and credit card debt is the consequence of poor individual choices. Impulsivity (Roberts &
Jones, 2001; Davies & Lea, 1995; Norvilitis et al., 2003), over solicitation (Bianco & Bosco,
2002; Kessler, 1998; Souccar; 1998; Hoffman, McKenzie & Paris2008) and optimism about
ability to repay debt (Wells, 2007; Drentea, 2008; Norvilitis et al., 2003) are well documented in
literature as reasons students incur credit card debt. Such factors suggest that students can make
choices to eliminate accumulating credit card debt and simply need to make better choices. This
is not entirely true.
A study conducted by Lyons (2004) found that students from families with lower
incomes and Black and Hispanic college students were more likely to have unmanageable credit

2

card debt loads. Lyons‘s study confirmed that these students were more vulnerable to debt
because in addition to the difficulty of managing their credit card debt they were also having
financial difficulties in general because they were from families with lower incomes. The results
of Lyons‘s study indicated that students from poorer families were more likely to hold large
credit balances, have little or no financial support from parents, work more than 16-20 hours per
week and more likely to hold other types of debt and receive need-based financial aid. These
findings support concerns raised by Zhou and Su (2000) who indicate that students with lower
family incomes are likely to have higher student loan amounts and credit card debt than students
from families with higher incomes.
These studies suggest that college students from poorer families and minority college
students are more vulnerable to accumulate debt that they cannot repay, primarily because they
do not have other monetary resources available to help meet the expenses of college attendance.
Sharply reduced family financial contributions to college expenses, and declines in public
financing of higher education have shifted student economic strategies from savings, grants, and
part-time employment to reliance on federally subsidized loans and credit cards.
For disadvantaged college students credit cards offer a borrowing source to satisfy
college expenses from which their advantaged counter parts are insulated. Lower socioeconomic
status creates greater vulnerability for credit card debt. Thus, an over reliance on credit cards to
make ends meet or survive the economic demands of college could be viewed as hyper
consumption and irresponsible credit management instead of a survival tactic to cope with low
socioeconomic status. Literature has confirmed that structural inequality has created varying
access to resources that create pronounced advantages and disadvantages for individuals in the
realms of socioeconomic status, housing and education (Wilson, 2003, 1990; Robert, 1999;

3

Kessler et al., 1999, 2003, MacLeod, 2000; Mills, 2003; Link and Phelan 1995). Structural
inequality occurs when organizations, institutions, governments or social networks contain an
embedded bias, which provides advantages for some members and marginalizes or produces
disadvantages for other members. This can involve unequal access to health care, housing,
education and other physical or financial resources or opportunities (Jencks, 2003; Conley, 2003;
Wright, 2003).
One of the consequences of sustained structural inequality over time are disparities in a
society‘s resources primarily the distribution of wealth. Socioeconomic stratification is the
hierarchical arrangement of classes within a given society based upon wealth, power, and
prestige (Wright, 2003). One of the central beliefs of socioeconomic stratification results in
unequal distribution of desirable resources and rewards in society (Wright, 2008; Broman, 1996;
Ren, Amick, & Williams, 1999; Microwsky, & Ross, 1999; William, 1990; Oliver, & Shapiro,
1995). Unequal distribution of rewards and resources limit the capacity of the individual to
adequately cope and adapt in an environment.
Macro social structures are correlated to individual characteristics and behavior. This
perspective predicts that because social structures shape individual values, and behaviors, credit
card spending and debt then, could be attributed to conditions of life that derive from an
individual‘s structural position. While individuals can make choices regarding their individual
behaviors, those choices are situated within political, economic, historical, cultural, and family,
contexts.
The idea that everyone has the same opportunities and that individuals can ―choose their
way‖ into a socioeconomic status that confers resources to adequately compete in life is
uncritical and simplistic. Today the United States has suffered unprecedented declines in

4

employment. Recession woes complicate post graduation plans for many hopeful graduates, and
increases in tuition are becoming extortionate, these societal issues demonstrate that in these
financially turbulent times, even those who occupy higher socio economic classes are not
completely protected from a compromised economy. Social positioning among the rungs of the
lower class today, requires heightened agency and over access to resources to transcend classes
and level the playing field.
Unfortunately, the United States has been witnessing a steady decline in household
incomes since the mid-1990‘s, coupled with rising college education costs (Manning, 2002;
Baum, & O‘Malley as cited in Lyons, 2004). Black and Morgan (1999) found that families with
a wide range of economic characteristics are borrowing on credit cards to meet household
expenses. Simultaneously, credit card spending has increased from $243 billion in 1990 to $891
billion in 2000 (U.S. Bureau of the Census, 1999 as cited in Drentea, 2000).
Over the last two decades, households have been financing more of their expenditures
using credit (Getter, 2003). Greater household debt use, larger amounts of credit borrowed, and
broader distribution of consumer credit have generated concerns that households face greater
financial stress (Getter, 2003). Engaging in ―survival borrowing‖ borrowing from credit cards to
meet household expenses has led to growing household indebtedness in the United States that not
only introduces students to credit card reliance, but also desensitizes students to credit card debt.
Additionally, since more households face greater financial stress today, college students may not
be able to turn to family for financial support in the face of credit card misuse (Lyons, 2004).
Families becoming over extended financially may impair the transition to college and
adjustment to living away from home, particularly for first generation college students (Lareau,
2003; Lyons, 2004). The disadvantages created from a lack of parental support pose challenges

5

for many college students. Literature has indicated that both parental income and other parental
characteristics are critical in shaping life chances for children (Mayer, 2008; Wells, 2007;
Norvltis et al., 2003; Tokarczyk, 2004). Education has often been viewed as a very viable means
to achieve upward mobility and gain economic rewards (Lyons, 2004; Armstrong & Craven,
1993; Hayhoe, 2002; Hayhoe et al., 1999). However, the expensive price tag of a college
education requires financial resources that are not available for economically disadvantaged
college students.
Statement of the Problem
College students who have credit card debt that they cannot repay experience distress that
not only impacts well being but grade point averages. The consequences of credit card debt for
college students are a serious problem. Health penalties resulting from the strain of debt are
costly. Coping with chronic stress exhausts energy levels needed to combat strain. When the
stress is not alleviated, as in the case with unpaid credit card bills, a person repeatedly
responding to stressful events becomes vulnerable to emotional problems, accidental injuries,
physical distress (i.e. headaches, back aches, skin irritants), and behavioral disorders (i.e.
irritability, distractibility, chronic fatigue) (Pearlin, 1996; Mieach, Caspi, Moffit, and Wright et
al., 1999; Mirowsky, 1999; Williams, 1995).
Literature has confirmed that well being affects grade point averages for college students.
Students who reported dealing with chronic stress also reported increased absences in class
attendance (Dollinger, Matyja, and Huber, 2007), sleep deprivation, (Lund and Reider et. al
2010), and studying fewer hours outside of class (King and Bannon, 2002). For college students
insolvable credit card debt is not only a chronic stressor that impacts both grade point averages
and well being, it also influences student‘s decisions about working more hours to address debt.

6

Working more than 20 hours a week has been shown to hinder the academic performance of
college students (Klum and Sherna, 2006; Orzag and Whitmore, 2001;Austin & Phillips, 2001;
Norvilitis, Osberg, Young, 2006 et.al).
While this study examines the experiences of college students, it should be noted that the
strain of unresolved debt has consequences that can follow students into their adult lives. The
discussion chapter elaborates on the consequences of unresolved credit card debt for college
students transitioning into adulthood.
Significance of the Study
Credit card debt is difficult for young adults to manage Robert, 1998; Rogers, Hummer,
& Nan, 2000; Ross & Wu, 1995; Williams & Collins, 1995 as cited by Pampel & Rogers 2004;
Manning 2000). Young adults have come to age during unprecedented growth in materialism and
consumer culture. The enormous profitability of consumer credit cards, together with the crossmarketing strategies of financial services conglomerates in the mid- and late 1990s, have
produced competitive pressures to recruit new clients at an increasingly younger age.
This study is significant because it articulates credit debt as a stressor that impacts both
well being and grade point averages for college students. Additionally, unique to this study are
qualitative findings that divulge intimate details from college students about their credit card
spending. Findings from this study will advance the understanding of both credit debt as stressor
and identify how college students accumulate this kind of harmful credit card debt.

7

CHAPTER 2 LITERATURE REVIEW
Despite a strong tradition in the literature examining socioeconomic status and well-being
(Anderson & Armstead 1995; Mirowsky & Ross 1999) little is known about other financial
measures that impact well-being such credit card debt. Researchers examining health in
relationship to one’s level of financial distress and worry about financial matters have found
clear connections (Bagwell & Kim, 2003; Drentea & Lavrakas, 2000; Kim & Garman, 2003;
Kim, Garman, & Sorhaindo, 2003; O’Neill, Sorhaindo, Xiao, & Garman, 2005). Lacking from
the literature is a more specific understanding of the association between credit card debt and
well being. Previous work has found that prolonged financial stress, such as continuous credit
problems and unmet financial needs, are both associated with worse physical health and
ultimately poorer mental health outcomes (Drentea & Lavrakas 2000).
For example, financial strain has been associated with physical health problems
(Manning, 2000; Anchensel 1999; Kessler, 1999 & 2000), increased drinking problems (Pierce,
1996), decreased self esteem (Aldana & Lijenquist 1998), and depression (Kim, 2006). For
college students in particular, prolonged financial stress generated from credit card debt has been
proven to increase anxiety (Drentea, 2000; Roberts & Jones, 2001; Wells, 2007; Hoffman,
McKenzie, & Paris, 2008), school dropout (Manning, 2002; Jones, 2005; Hayhoe, Leach, Allen,
& Edwards, 2005; Joo, Durband, & Grable, 2008), working longer hours (Austin & Phillips,
2001; Norvilitis, Osberg, Young, 2006 et.al ) compulsive spending (Mowen & Spears, 1999;
Baumeister, 2002) suicide (Dossey, 2005; Johnson, 2005) bankruptcy and charge-offs
(Mannix,1999; McMutrie 1999; Roberts & Jones, 2001; Staten & Barron, 2002; Johnson, 2005).
Unlike debt that can be deferred, such as educational loan payments or large debt
amounts that can be resolved across a longer time period (e.g., a home mortgage), credit card

8

debt is different. Credit card debt is meant to be resolved more expediently than a mortgage and
cannot be deferred like student loan debt. For credit card debt, debtors are expected to pay
monthly minimum payments, at least, and there are stringent actions taken for failure to do so.
This is important to note because the stress generated from credit card debt can be additive. This
means there are several consequences linked to missing one payment. Figure 1 illustrates the
consequences that stem from missed credit card payments.

Figure 1. Collection consequences for missed credit card payments. For interpretation of the
references to color in this and all other figures, the reader is referred to the electronic version of
this dissertation.

The consequences of insolvable credit card debt are continuous. A person continues to
receive late notices, letters that demand payment, and calls from creditors and collection
agencies until payment obligations are satisfied and (Huygen, 1999; O‘Neil, Prawitz, 2006 et.al)
over time consequences worsen. For example, the longer the credit card bill is unpaid the longer

9

efforts will be made to obtain monies for payment. Moreover, until the bill is paid the debtor
undergoes the constant stress collection efforts, experiencing the chronicity of collection efforts
daily make credit card debt a stressor that affects well being. This can be particularly stressful if
resources to alleviate distress of collection efforts are unavailable. Additionally, over time a
cycle of missed payments can demolish a credit score. A credit score determined by Fair Issac
Credit Corporation ranges from a low of 350 to a high of 850. Relapsing on a scheduled credit
card payment can create a significant decrease in credit scoring. Exact calculations of
impairment can depend on a number or variables, varying in their impact on credit scoring. Fair
Issac Credit Corporation has developed general estimations for impairment resulting from
common credit behaviors.
Figure 2 highlights these behaviors as well as pursuant percentage damage relative to
credit scoring, behavior that ranges from utilizing all available credit to filing for bankruptcy.
Estimated point deductions subtracted from a credit score in relation to each financial event are
also illustrated.
Credit Card Exposure for College Students
Modern U.S. society has been described as a time in which ―we are active consumers,
motivated by self-expression rather than basic survival‖ (Drentea, 2000). The culture of the
credit card is not only propagated, but college students are exposed early and often to credit
offers. College students are invited to obtain credit across various advertising and solicitation
mediums that make avoiding credit offers practically impossible. For a college student securing a
line of credit is highly likely. The frequent exposure to offers is a likely reason as to why the
average college student has at least three or more credit cards (Manning, 2002). Credit card
vendors gain access to students through several avenues. Many pay fees to the institution to set

10

Figure 2. Estimated point deductions from credit score given certain financial events.
information contained in this chart was taken from the Fair Issac Credit Organization website:
www.myfico.com/creditEducation. Calculations are based on an average credit score of 650-680.

up booths to solicit students on campus. Some credit card vendors sponsor student organizations
to solicit other students. Purchases made in campus bookstores often contain solicitations for
credit cards inserted into the bag in which books are packed. Credit card companies also solicit
assistance from college and university development alumni offices. Many institutions promote
affinity cards with a picture of a campus landmark or mascot on the card to attract students.
Colleges and universities allow several common types of credit card solicitation to take place.
These solicitation methods include, but are not limited to, sales tables, bag inserts, give-a ways,
and posters.
The frequent exposure to credit offers of various types from various sources fuels credit
acceptance that can lead to debt. Nellie Mae (2001), found that 76% of undergraduates have at
least one credit card. The study also reported that the average credit card balance for

11

undergraduate students was $2,169. Fifty five percent of college students get their first card as
freshmen, and 25% first used credit cards in high school. College is a time of transition into
adult responsibilities, and using credit cards is one way that young people perceivably
demonstrate their maturity, as a result students are being lured into a spiral of spending beyond
their means seemingly unaware about the financial consequences.
A College student‘s decision to obtain credit that may lead to debt is also fueled by
knowing others around them who are/were in debt. A study conducted by Lea at al. (1993)
termed this ―culture indebtedness‖ this study found an important factor in predicting debt status,
was debtors knowing or being surrounded by other debtors. A community of debtors creates an
environment that reinforces a person‘s beliefs, attitudes, and personal norms that overspending
and excess buying is normal. Today‘s college students exhibit higher levels of consumption than
in past decades. There is a widespread view that attitudes about debt have changed dramatically
during the twentieth century, from a general abhorrence of debt to acceptance of credit as part of
a modern consumer society (Roberts and Jones 2001).
Overtime, social norms and attitudes may be modified to reflect this dysfunctional
orientation (Roberts and Jones 2001). In a college environment, students have encountered a
climate that endorses the use of frequent credit card use, and debt acceptance. As stated
previously, statistically 60% to 82% of college students are credit cardholders, with 14%
carrying balances over $3,000 and 20% having three or more cards. Credit card debt, owing
money, having high balances can all seem normal, especially if everyone surrounding an
individual has credit cards and carry debt. What becomes abnormal is using alternative methods
other than credit cards for purchases. Credit cards make retail transactions simpler, by removing
the immediate need for money. Studies have concluded that in retail settings, when exposed to a

12

credit card logo, college students are more likely to purchase quicker, and spend more money
than students who were exposed to the same products without the presence of a credit card logo
(McElroy, Kleck, Harrison & Smith, 1994; Mannix, 1999; McBride, 1997; Hayhoe, Leach, &
Turner, 2000; Roberts & Jones, 2001). Feinberg (1986) concluded that students have been
conditioned to associate credit cards and spending.
Credit card use stimulates spending and when compared to cash, credit cards leads to
greater imprudence. For example, the introduction of credit cards to the fast food industry
resulted in more sales and transactions that are 50% to 100% larger than cash transactions
(Ritzer, 1995). To many, the money involved in credit card transactions is abstract and unreal
(Roberts & Jones, 2001). The realization that one is actually spending ―borrowed‖ money that
has to be repaid is a reality that many college students do not grasp during transactions.
Consequently, credit can be confused with income or ―real money‖ from earnings
because using credit eliminates the visibility of cash being spent. Credit cards prompt many to
spend quickly and more impulsively than they would with cash. College students have been
raised in a credit card society, where excess credit card use is glamorized (Manning, 2002). This
means that college students are being socialized to perceive consumer credit as a generational
entitlement rather than an earned privilege. For most American students, credit card
―membership has its privileges‖ before commencing a full-time job and adhering to a financial
budget.
Status Consumption
Consumer research on compulsive buying began with work by Faber, O'Guinn, and
Krych (1987), and Valence, D'Astous, and Fortier (1988; as cited by Mowen & Spears, 1999).
Faber and O'Guinn (1988) defined compulsive consumers as "people who are impulsively driven

13

to consume, cannot control this behavior, and seem to buy in order to escape from other
problems". Edwards (1992) defined compulsive buying behavior as "a chronic, abnormal form of
shopping and spending characterized, in the extreme by, an over powering, uncontrollable, and
repetitive urge to buy, with disregard for the consequences (Mowen & Rowen, 1999). Although
compulsive buying gives an individual short-term positive reward, it results in long-term
negative consequences.
College students may be more prone to becoming compulsive spenders for a number of
reasons. Outside of being conditioned to spend and enticed by multiple credit card offers there
may be social pressures that prompt excessive spending behaviors. One mentioned earlier was
the culture of indebtedness. The other can be described as status consumption. Status
consumption is a form of power that consists of respect, consideration, and envy from others
generated by what a person owns. Today status is seen more through ownership of products than
personal, occupational, or family reputation (Eastman et al. 1997). To achieve a position of
social power or status one must exceed the existing community norm.
Moreover, being viewed as wealthy is socially desirable, being recognized as such might
require continual investment in costly items. This leads to a treadmill of consumption, where
spending habits may be difficult to support with the earnings of a college student budget. In a
college environment that is over solicited with credit card offers as well as retail advertisements
it is probable that there is more social pressure to spend in order to keeping up with peers. From
iPods, E-readers, Mac books, designer book bags and so on, college presents an environment that
promotes spending. Such spending can be justified especially on gadgets that can be viewed as
viable products to enhance scholastic productivity. The ownership of such products also
becomes unique identifiers affording social prestige and acceptance by both peers and fellow

14

students. Unfortunately, status consumption is a competitive and comparative process, which
requires consumers to continually increase their conspicuous signals of wealth (Bell 1998). Their
status gain leads to their financial loss.
On college campuses there are more opportunities to compare status signals with others
as many living (dormitories), dining (cafeterias), and work domains (libraries, lecture halls) are
public. Moreover, to achieve a position of social power or status, one must exceed the existing
norm. This often results in purchasing higher priced items and shopping more frequently. For
college students it becomes socially important to maintain a ―high profile look‖ even if this
means spending beyond means.
Additionally, Sociologists and social psychologists have suggested that debt-tolerant or
debt-inducing norms might be generated if a consumer adopts a reference group with more
economic resources than he or she has (Newcomb, 1943, as cited Wang & Xiao, 2009). The
result is that there is no end to wants, and little improvement in satisfaction, despite the increase
in accumulation of goods. Bell termed this the ―treadmill of consumption‖. Many college
students get stuck on this treadmill their entire college tenure, vulnerable to becoming
compulsive buyers.
Debt management being more difficult for young adults today can be attributed to their
expectations concerning salaries upon degree completion, and estimated length of repayment.
Studies concluded that students were overly optimistic about their abilities to retire debts quickly
(Perloff & Fetzer, 1989; Wicker et al. 2004). These studies concluded that students are likely to
be more optimistic about future events when events are further away in time, and they are less
optimistic, and presumably more accurate, when impending events are closer in time.
Incidentally, college students may be ―overly optimistic‖ about paying off debt. Many assume

15

that there will be both adequate means and time to repay debt. Expectations may readjust as
repayment time nears, and they are presented with a clearer picture of their debt load. This is
particularly true for upper class students, adjusting their expectations in the face of graduation. If
the assessment and appraisal of how credit card debt can be repaid is skewed, credit card debt
can become a significant stressor when a debtor begins to miss payments escalating collection
efforts.
Financial Literacy
For college students who may be new to both being a debtor and having an account in
collection, dealing with debt collectors is very stressful. Findings from several studies indicate
that the financial literacy of college students is a chief determinant of whether students
successfully manage credit lines, avoiding debt insolvency (Lyons, 2004; Hoffman, McKenzie,
& Paris, 2008; Dale, and Bevill, 2007). Unfortunately, studies have also concluded that financial
literacy rates among college students are very low (Davies, & Lea 1995; Roberts & Jones 2001).
Debt collection practices create a significant source of stress causing distress and impacting
academic performance. For this reason it is appropriate to discuss the collection practices of
creditors.
The stress of collection efforts and the new responsibility of handling bill collectors
becomes a source of ongoing stress that causes distress. For college students that lack financial
literacy and experience in dealing with collectors and being in debt (especially in delinquent
status) predisposes students to higher levels of anxiety, and prolonged stress. All firms that
extend credit to consumers establish procedures for the collection of overdue bills (Hill, 1994;
Sutton, 1991).

16

The methods designed to obtain payment from indebted consumers range from high cost
to low cost approaches, all directed towards prompting payment. High cost individualized
approaches are methods that cost the agency more money to implement such as mailing personal
individualized letters highlighting the consequences of nonpayment. Letters are usually sent to
new debtors who have a history of timely bill payment (Sutton, 1991). The rationale is that these
debtors have a history of repayment and are more likely to pay when gently reminded. Low cost
approaches included telephone calls. This is more cost effective for agencies and tends to be
effective for contacting consumers that have poorer repayment histories.
The goal of both methods is repayment fostered through negative reinforcement. This is
viewed as an effective strategy on the behalf of collection agencies, because debtors can only
escape this aversive onslaught by paying the bill. Letters highlight the consequences of non
payment, including the loss of privileges with the creditor, impairment of their credit ratings and
possible legal action. Telephone calls convey a sense of urgency that emotionally arouses
debtors, particularly when they are both ongoing and reoccurring. Bill collectors are trained to
recite scripts that coerce debtors to commit to bill repayment (Hill, 1994). Collectors are
socialized to convey urgency, or firmness. The belief is that both unpleasant news and stern
people are motivators for repayment. The tone collectors take entails arousal with a hint of
irritation or disapproval.
Collectors use phrases that prompt, ―promises to pay‖ or convey high importance.
Phrases like: ―It is imperative that you pay us today‖ or ―This account has reached a critical
stage.‖ Collectors are rewarded and punished for the outcomes of their work. Raises, promotions,
cash prizes, and gifts, are used to encourage collectors to obtain promises to pay, and dollars in
payments. Collectors have incentives for conveying intensity and collection, in many cases they

17

are paid partially in commissions. This literature highlights how receiving multiple calls from
aroused collectors can be intimidating (especially for new debtors) and highly stressful.
For college students who are more likely to be both new debtors (Staten & Barron, 2002;
Shenk, 1997; Hayhoe; 2002) and have low levels of financial literacy (Davies, & Lea 1995;
Roberts & Jones 200) the strain of collection predisposes them to greater levels of distress
(Allen, Edwards, & Hayhoe 2007). Debt collection can be a daily stressor. It is possible for a
debtor to receive multiple calls daily from a collection agency or agencies hoping to settle an
account to earn commission. College students may be extremely unprepared for the rigors of
debt collection practices. Being pursued by trained bill collectors in the face of having both
limited experience with handling collectors and insufficient funds to repay debt can become
taxing.
The financial literacy of college students has consequences for how they handle and
process both being in debt and handling the strain of collection efforts. For example, studies have
concluded that debt collection agencies rely on the obliviousness of consumers regarding both
financial literacy and the law when collecting debts For example, a bill collector in a study
stated: ―If people know the law, if people really knew the law, we would collect a lot less
money‖ (Hill, 1995).
In American educational systems financial literacy is not incorporated into formal
curricula or universally required for diploma or degree program completions. As a result, the
reality is a young person today is highly likely to be unfamiliar with handling credit as well as
troublesome debt and bill collectors. There are laws that benefit consumers in the ―rules of
engagement‖ with collectors, and offer boundaries to escape the strain of collection efforts. The

18

Fair Debt Collection Practices Act is an example of such laws instituted in each state. However,
it is left up to consumers to be knowledge of the laws.
For example, some provisions under this Act state:
Telephone calls to debtors can be made only between the hours of 8:00 a.m. and 9:00
p.m. occurring on Mondays through Sundays.
Direct contact with debtor‘s employers or any third party with respect to monies owed is
prohibited
Debtors have the right to request that collectors cease communication.
If consumers, especially college students, were familiar with the provisions of this act,
even if means to repay the debt in full were absent, options regarding communication or skillful
negotiation with collectors could be utilized to lessen the chronic burden of collection efforts.
For instance, if a consumer experienced emotional distress when dealing with collectors on the
telephone under the provisions of this act they could mail a cease and desist letter and telephone
calls to the debtor would be prohibited. While this does not eradicate the debt, it does alleviate
the stress of daily telephone calls from a creditor. This affords the debtor the ability to map out
debt solvency without the constant irritant and emotional arousal bill collectors evoke. For
college students financial literacy has several advantages. Figure 3 illustrates a relationship
between financial literacy, income, credit debt, distress and grade point averages.
A lack financial literacy affects credit card debt. Financially literate consumers are able to
convert the knowledge they possess about finances into informed decisions and behavior that
maintain financial well being. Consequently, income is linked to financial literacy. Individuals
with higher income tend to be more financially literate than persons who have lower incomes
(Brown, Taylor and Price, 2004).

19

Financial
Literacy
Credit card debt

Credit Card
Distress

Lowered
Grade Point
Average

Income

Figure 3. Relationship between financial literacy, income, credit debt, distress and grade point
averages.

On the other hand, a lack of financial literacy affects credit card debt adversely. A person
who is not financially illiterate is often uninformed about the responsibility of credit card
ownership, and more likely to engage in more behaviors that lead to debt insolvency. An
obvious impact that income has on credit card debt is the ability it lends to an individual to pay
or default on payments. Thus, individuals that have higher incomes are greater insulated from the
perils of unmanageable debt, avoiding vicious debt recovery practices from creditors.
Credit card distress arises when debt cannot be repaid and creditors pursue the borrower
often daily to collect money. The notices, telephone calls, the vocal aggression of collectors, and
other collections tactics all increase anxiety regarding the debt owed. These collection efforts
also remind the borrower that they do not have the money to pay the debt and will continue to be
20

pursued by creditors until money owed is paid. This can create high levels of distress that can
affect academic performance.
When the debtor is pursued daily, this becomes a daily hassle that the debtor must
emotionally navigate. Moreover, this strain is intensified by the absence of resources a debtor has
to combat collection efforts. Consequently, to deal with collection efforts many students who
have borrowed beyond their capacity to repay, engage in financial problem solving that
compromise the ability to academically perform. Students who are over extended financially
work longer hours (Austin & Phillips, 2001; Norvilitis, Osberg, Young, 2006 et.al), miss more
class periods (Jones, 2005; Hayhoe, Leach, Allen, & Edwards, 2005; Joo, Durband, & Grable,
2008), and get less sleep (Lund & Reider et. al 2010), taken together these problem solving
strategies could seriously impact scholastic functioning resulting in lowered grade point
averages. The inability of a college student to repay credit card debt, results in credit card
distress. Dealing with credit card distress is a stressor that impacts grade point average because it
becomes a distraction that hinders the ability of a student to concentrate and spend sufficient
time and energy studying.

21

CHAPTER 3 METHODS
This study has two sources of data, a questionnaire sample of 330 students and face-toface interviews conducted with 30 students selected from the questionnaires. The data collected
from the questionnaires are analyzed using quantitative methods, specifically regression analysis,
ANOVAs tables, and descriptive statistics. The interviews were qualitatively examined using a
phenomenological coding strategy to identify themes pertinent to the research agenda of this
study. This chapter describes recruitment, sampling, sources of data, measures, and descriptive
information about the sample, and each are detailed in turn.
Recruitment: Use of Questionnaire
To locate my sample, I contacted two different professors at Michigan State University. I
met with both professors to ask permission to administer my questionnaire during class. During
the meetings we reviewed the questionnaire, consent procedures, as well as the length of time the
questionnaire would take to distribute, complete and collect. I was granted permission by both
professors to administer my questionnaire. Finally a date was chosen when I would actually
administer the questionnaire. On the day I arrived to each course, I introduced myself to the
students, and reviewed my questionnaire and consent procedures. I then explained that their
decision to participate or decline would have no academic consequences. The two courses
selected were a four-credit Social Science course and a three-credit course in a different
department.
The reason that the social science course was selected is because it is a four-credit course
required for graduation regardless of academic major. Additionally, enrollment typically ranges
from 200 – 330 undergraduate students. The number of students enrolled in the course I sampled
was 210. Given the large enrollment, and general requirement status, I thought this class would

22

yield a broad diversity of respondents across majors and class standing that would ultimately
diversify the study‘s sample. Also, attendance was mandatory and recorded in this course,
therefore I could be fairly confident that on the day questionnaire would be administered I would
have a large number of students present to answer the questionnaire.
I chose the other course because of course content. This course was a personal finance
course. I thought this course would provide an increased opportunity to locate the students this
study focuses on: students who have credit card debt they are having difficulty paying. I also,
realized that students enrolled in this course might be taking proactive measures against financial
mismanagement. Course enrollment for this class was 160 students and attendance was
mandatory. Between the two courses 330 students total completed the questionnaire.
Interview Sample Selection
The 330 questionnaires were organized by academic class standing (freshmen,
sophomore, junior or senior). It is important to note that the questionnaires were used to locate
30 students to interview face-to-face. More about the interview selection process is discussed
later in this chapter. Briefly, it should be mentioned here that this study has a specific focus on
students who cannot pay their bills and are distressed by collection efforts. The questionnaires
helped identify these students. Only students who self reported experiencing distress because
they were having difficulty paying their credit card bills were interviewed. Using the
questionnaire to locate these students helped ensure that only students who met this specific
research focus were interviewed. Using the questionnaires to locate the target sample helped save
time and reserve incentives disbursed by locating students who met interview criteria and
eliminating those who did not.

23

Methodology research suggests a sample size of at least 30 to 32 is conventional to
guarantee that sample statistics do not vary much from the population parameters that they
estimate (Frankfort and Guerrero, 2006). Respondents who reported that they did not have any
credit cards and were not in credit card debt were removed from consideration. Attempts were
made to identify students that were financially at risk. For the purposes of this study, students are
identified as financially at risk if they had one or more of the following characteristics
1) Have one or more credit card accounts
2) Have credit card balances of $1,000 or more
3) Are delinquent on their credit card payments 30 days or more
5) Only pay off their credit card balances some of the time or never.
The measures of financial risk were constructed based on previous research that has
consistently identified credit misuse and/or mismanagement according to these characteristics
(Baum and O‘Malley 2003; The Educational Institute and The Institute for Higher Education
Policy 1998; U.S. General Accounting Office 2001; Lyons 2004). These measures identify
students who are having difficulty managing their credit and/or repaying their credit card
balances. Targeting students that are having difficulty managing credit is the first step to
exploring adequately the relationship between credit card debt, wellbeing, and academic
outcomes. Of the 330 questionnaires, 130 had completed the questionnaire completely, reported
having at least one credit card, owed a balance on the card, and met other financial risk eligibility
criteria previously mentioned. These are the respondents that I contacted from the questionnaires
to be interviewed. From the remaining 130 questionnaires eight questionnaires were randomly
drawn from each pile (freshmen, sophomore, junior and senior) for a total sample size of 32.
After all respondents were selected, using the contact information listed on the questionnaire,

24

they were contacted via email or telephone and asked to participate in a face-to-face interview.
Obtaining ethnographic accounts from students offer the opportunity to explore in depth the
academic consequences as well as the distress students reported experiencing as a result of credit
card debt, particularly when debt is insolvable.
Interviews were conducted in a reserved study room at the Michigan State University
library. A cash incentive of $25.00 was offered for participation. Incentives have been well
documented in the literature for bolstering response rates (Dillman 2003; Neuman 2006; Biemer
and Lyberg 2003). Creating an incentive that is likely to be equally appealing to everyone in the
sample of interest is important. For this reason cash incentives were chosen.
Characteristics of the Sample
The respondents in this study were undergraduate college students (n=330). Females
accounted for (51.5%) of the study‘s sample and males (46.7%). Six students in this sample
(1.8%) did not answer. The racial identification of the respondents are as follows: African
Americans (14.4%), Mexican American or Chicano (3.5%), Asian American (6.7%), Whites
(71.9%) and other (3.5%). More than half of the sample was underclassmen: freshmen (30.2%)
and sophomores (32.4%). Upper classmen sampled were juniors (14.9%) and seniors (22.5%).
The majority of the students (98.7%) were full-time students, with only (1.3 %) being part-time.
A little over Fifty-four percent (54.3%) of the students who reported owning a credit card
obtained the card at the age of 18. Surprisingly, (14.3%) of the sampled reported obtaining a
credit card as young as 16 and less than two-percent (1.4%) of students in this sample reported
obtaining a card at 21 years of age. Collectively, (62.5%) of the students owned credit cards.
Among those students with credit cards, the amount owed on these cards ranged from $500
(66.4%) to over $6,000 (2.2%). A table of descriptive statistics is provided below.

25

Table 1
Descriptive Statistics for the Sample
Variables
Gender
Male
Female
Race
African American
Mexican American or Chicano
Asian American
Whites
Other
Class Standing
Freshmen
Sophomore
Junior
Senior
Enrollment status
Part-time
Full-time
Credit card Ownership
Yes
No
Number of Credit Cards Owned
0
1
2
3
4
5
Balance owed on credit card(s)
500
$1,500 – $2,500
$3,000 – $6,000
Over $6,000
Family Income
<$10,000 - $39,999
$40,000 - $69,999
$70,000 - $89,999
Over $90,000

a

Frequency

Percentage

154
170
45
11
21
225
11

14.4%
3.5%
6.7%
71.9%
3.5%

95
102
47
71

30.2%
32.4%
14.9%
22.5%

311
4

1.3%
98.7%

200
120

62.5%
37.5%

115
133
44
12
5
2

37.0%
42.8%
14.1%
3.9%
1.6%
0.6%

89
37
5
3

66.4%
27.6%
3.7%
2.2%

41
47
51
140

26

47.5%
52.5%

14.7%
16.8%
18.3%
50.2%

Table 1 (continued)
Variables
Father‘s Education
Grade School
High School
College
Graduate School
Mother‘s Education
Grade School
High School
College
Graduate School

Frequency

Percentage

6
68
151
79

2.0%
22.4%
49.7%
26.0%

4
69
179
58

1.3%
22.3%
57.7%
18.7%

a

N= 330

Sources of Data
The sources for data collected in this study were obtained from 330 questionnaires
completed by students in class and 30 face to face interviews. Demographic data was also

collected from the questionnaire.
Questionnaires
The questionnaire in this study contained 71 questions. The questionnaire contained six
sections labeled A-F. Each section is outlined below. The complete questionnaire is listed in the
appendix.
A- Credit card ownership information
B- Financial Literacy
C- Credit Card Distress
D- Credit card spending
E- Scholastic behavior, credit card debt and grade point averages
F- Demographic information

27

The questionnaire took students on average 30 minutes to complete. The questions used
in each section were constructed and informed both by the research agenda for this study as well
as existing literature. I asked students questions that I thought would help explore the hypotheses
of this study. Here, I would like to briefly describe what existing literature was used to help
inform the design of the questions in each section. It is also important to note here that personal
experiences with debt collection practices and debt resolution also informed question creation
and selection.
Questions used in sections A and B: Credit Card Ownership and Financial Literacy were
informed using the Money beliefs and behaviors scale (MBBS) modified by Hayhoe (1999) and
the Attitude to Debt scale (Lea, 1995). Efforts in sections A & B were made to collect
information about the debt load students carried as well as knowledge students held in regard to
financial management, understanding of credit and other demographic information pertinent to
understanding debt vulnerability (i.e. age at time of applying for credit, credit card balance,
number of credit cards, etc).
Sections C and D: credit card distress and credit card spending were influenced using the
Student Financial Well- Being Scale (Norvilitis et. al, 2003) and Attitude toward debt and Future
Optimism scale (Wells, 2007). In sections C and D the goal was to ask students questions to help
understand both the impact credit card debt had on distress and what prompted credit card
spending.
Questions in sections E and F concerning grade point averages and demographic
information were informed by a number of items in scales previously referenced. The goal in
section E was to examine specific events or happenings that may impair scholastic functioning
related to the stress associated with credit card debt. Previous literature has identified that grade

28

point averages affect student mental health (Caldwell, 2010; Graham, 2006; Nielsen, 2002). This
is an important finding because in this study, I explore the effects credit card debt have on grade
point average, and the distress students undergo as a result of credit card debt. Section F collects
demographic information about the student‘s background (race, class standing, gender, etc).
Measures and Reliability
Three scales were created for this dissertation: financial literacy, credit card distress, and
credit card debt. The items used to create the scales were taken from the survey ―Maxed Out:
College students, grade point averages, distress, and credit card debt that I designed for this
dissertation project. Each scale will be discussed in regards to the items that make up each scale,
assessment of usefulness of the scale and the reliability of the scale. The reliability of the scales
is measured using Cronbach‘s alpha. The alpha is a measure of internal consistency, that is, it
measures how closely related a set of items are as a group. A "high" value of alpha is often used
(along with substantive arguments and possibly other statistical measures) as evidence that the
items measure an underlying (or latent) construct. Alpha scores range from negative values to 1.
Statistically reliable alpha scores are generally at least 0.60. Additionally, the distributions of all
the questions that make up the scale are provided.
Scale reliability and items used in each scale
Financial literacy. The alpha for the financial literacy scale is 75. This scale was coded
by taking the mean values for the questions for all respondents (no=0 and yes=1). The closer a
respondent‘s financial literacy score is to ―1‖ the more the respondent (presumably) is financially
knowledgeable regarding the questions asked. In relation to the survey the financial literacy
scale is composed of questions B3- B12. Specifically, the questions students answered as a
measure of financial literacy are:

29

B3. I know the APR on my card(s)
B4. In the past I have negotiated with creditors about a lower APR for my card(s)
B5. I am aware of the debt collection practices for my card(s)
B6. I know what factors influence my credit score.
B7. I am familiar with the provisions of the Fair Credit Reporting Act
B8. I know how to obtain a copy of my credit report.
B9. In the last 6 months I have obtained a copy of my credit report.
B10. I know how to read a credit report.
B11. If I wanted to learn more about handling money I would ask my parents.
B12. I have taken a personal finance course here at MSU.
B13. Managing credit is a problem for me.
This scale is useful for gaining a general knowledge about the financial literacy of
students in this sample. The questions in this scale address whether or not a student is familiar
with locating, interpreting, and understanding various financial documents (i.e. credit card
statements, credit reports, etc). Students were asked questions about credit reports; collection
practices, and about other items that could be found on their credit card statements. This is scale
is a helpful predictor to estimate the familiarity a student has with understanding, and
interpreting documents vital to financial health. For example, if a student does not know how to
order, or read a credit report how can he/she be knowledgeable of their credit score or credit
standing financially? The absence of this kind of knowledge might severely impair a students‘
ability to make sound financial decisions and affect the future borrowing potential of a student.
Credit card distress. The alpha for the credit card distress scale is .86. The scale is
composed of questions C1- C4, C6-C10. The answer choices to these questions were coded as

30

(never=0, hardly ever=1, some of the time=2, most of the time=3, always=4). The higher a
respondent‘s score is to ―4‖ the more distress they reported experiencing because of credit card
debt. Specifically, the questions students answered as a measure of distress in relation to credit
card debt are:
C1. I worry about being able to pay my credit card bills.
C2. I spend a lot of time thinking about my credit card bills.
C3. I get down when I think about the money I owe.
C4. I have cried about owing credit card bills.
C6. A phone call from a creditor ruins my day.
C7. When creditors call I do not answer.
C8. Creditors call my cell phone.
C9. It is hard to make arrangements with creditors
C10. I feel overwhelmed by my debt.
This scale is a useful measure to predict the distressing effects of credit card when the
debt is not repaid. The items in this scale ask specific questions regarding responses a person
might have in relation to dealing with stressful events caused by the inability to make credit card
payments or satisfy arrangements as detailed in credit card contracts. Answering positively
(sometimes, most of the times, or always) to questions suggest that the respondent is having
difficulty meeting payment obligations and is experiencing distress or emotional discomfort as a
result.
Credit card debt. This variable measures accounts that students have in collection status
for non-payment. The answer choices to this question were coded as (no=0, yes=1) Yes, they had

31

accounts in collection because they were past due on bill payments or not they were not. The
actual question is listed below. The entire questionnaire is listed in the appendix.
C5: Creditors call me because I am past due on my account.
Interviews
Thirty undergraduate students were interviewed for this study. The purpose of electing to
conduct interviews for this study was to gain a comprehensive understanding of ―what being in
debt is like for an undergraduate student.‖ How might this type of pressure be described and
what caused the debt in the first place. The interviews conducted for this study offered great
detail from students themselves about how they experience debt, what they know about money
and, more importantly, how they were taught financial literacy.
The average interview lasted for 1.5 hrs. In total 52 hours were spent completing
interviews with students. The face-to-face interview questions that I used during interviews are
listed below.
1. Growing up what did you learn about credit cards, managing money?
2. How old were you when you first applied for your credit card?
3. Why did you apply/ what made this offer appealing?
4. Where did you learn this?
5. When did you first realize your credit card debt was a problem?
6. What event made you realize this?
7. How did you respond? (What did you do?)
8. Does anyone know about your debt? (Who?)
9. Have you sought help or thought about seeking help?
10. How do you feel about owing the money you owe?

32

11. Are people you know, (or people around you) experiencing similar problems?
12. What causes you to spend money beyond what you intended while shopping?
13. How often does this happen?
14. Do you buy things that cannot be returned?
15. How has credit card debt affected your grades?
Data Analysis
Eight variables are used in this study. They are: family income, credit card debt, grade
point averages, credit card ownership, credit card balances, parent‘s education, race and credit
card distress. Using descriptive analysis frequency distributions are provided for each variable in
the beginning of the results chapter. The goal of the frequency distribution tables is to provide
the reader with a description of the variables used in analysis.
Finally, using SPSS, a variety of analyses were conducted using cross tabulations,
ANOVA, and multiple regressions to examine each hypothesis. The goal for the analysis of each
hypothesis was to explore and provide clarity regarding understanding the relationship between
credit card debt, distress and grade point averages. A series of different variables are inserted
into the regression models to further examine this relationship and reveal what variables help
predict credit card distress, and lower grade point averages.

33

CHAPTER 4 RESULTS
In this chapter both the qualitative data from the interviews and quantitative data from the
questionnaires are discussed. This chapter begins discussing the hypotheses for this study and
ends exploring the phenomenological themes gathered qualitatively from the interviews. Before
the hypotheses are discussed, frequency tables for all variables pertaining to the hypothesis are
presented. Following the frequency tables each hypothesis is explored in turn.
Eight variables are used in this study. They are: family income, credit card debt, grade
point averages, credit card ownership, credit card balances, parent‘s education, race and credit
card distress. In the following tables frequency distributions are provided.

Table 2
a

Family Income

Family Income
<$10,000 - $39,999

Frequency
41

%
14.7%

$40,000 - $69,999

47

16.8%

$70,000 - $89,999

51

18.3%

Over $90,000

140

50.2%

a

N = 279

Most of the students in this sample had family incomes that are in the higher ranges of
this income interval. Table 2 details the majority of students in this sample 68.5% had family
incomes of $70,000 to over $90,000. The remaining students in this sample have family incomes
that range from under $10,000 to $69,999.

34

Recall from chapter two that credit card debt was measured by asking students whether
they had accounts in collection for non-payment. Table 3 highlights that credit card debt is a
problem for 11% of students in this study who reported that creditors call them because they
have accounts in collection for non-payment.

Table 3
Credit Card Debt

a

Credit Card Debt

Frequency

%

YES

30

11%

NO

243

89%

a

N = 273

Table 4 highlights that 24.3% of students have above a 3.6 grade point average. Nearly
half (44.5%) of students in this sample reported grade point averages of 3.0 to 3. Most students
in this sample have at least a 3.0 grade point average. Students reporting grade point averages of
2.0 to 2.9 totaled 29.1% and 2.1% of students reported having grade point averages of 1.0 to 1.9.
More than half of the college students in this sample 62.5% have credit cards. Findings in
table 5 align well with literature regarding credit card ownership and utilization among college
students explored in chapter one. Researchers estimate that 60% to 82% of college students own
credit cards (Dunn 1993; Hayhoe et al. 2000; Roberts and Jones 2001). This study highlights
similar findings.
The distribution of credit card balances ranges from 66.4% of students reporting that they
owe at least $500.00 on their credit card to 27.6% reporting that they owe as much as $2,500.

35

Table 4
a

Grade Point Averages

Grade Point Average

Frequency

%

1.0 to 1.9

6

2.1%

2.0 to 2.9

85

29.1%

3.0 to 3.5

130

44.5%

3.6 or above

71

24.3%

a

N = 292

Table 5
a

Credit Card Ownership

Do you own a credit card?

Frequency

%

YES

200

62.5%

NO

120

37.5%

a

N = 320

36

Students carrying credit card balances from $3,000 to over $6,000 in table 6 totals 5.9%. It is
also interesting to note that this question (how much money do you owe on your credit card?)
was skipped most frequently with 196 students out of 330 electing not to answer this question in
particular. The students that skipped this question tended to be white (145), freshmen and
sophomore; they had little credit card debt, and reported not being financially literate. Students
that answered this question had more debt; reported more credit card distress, were financially
literate and tended to be upperclassmen.

Table 6
Credit Card Balances

a

How much money do you owe
on your credit card(s)?

Frequency

%

$500

89

66.4%

$1,500 - $2,500

37

27.6%

$3,000 - $6,000

5

3.7%

Over $6,000

3

2.2%

a

N = 134

Most 49.7% of the college students in this sample have fathers that attended college and
graduate school 26%. Only 22.4% of college students in this sample have fathers that only
attended high school and 2% attending only grade school. Table 7 shows that overall the fathers
of college students in this study are well educated.

37

Table 7
Father’s Education

a

Educational Level

Frequency

%

Grade School

6

2.0%

High School

68

22.4%

151

49.7%

79

26.0%

College
Graduate School
a

N = 304

Table 8 illustrates that 57.7% of college students in this study have mothers that attended
college and 18.7% reported that their mothers attended graduate school. Overall, table 8
highlights that college students in this study have fairly well educated mothers with only 1.3%
reporting that the highest level of education achieved by their mother was grade school and
22.3% reporting high school. Table 9 illustrates that the majority of students (71.9%) in this
study are white. This is reflective of the predominantly white Midwest University from which
the sample for this study was drawn.
Figure 4 illustrates students self-reported distress scores experienced from having credit
card debt (items in this scale are listed in chapter 2). In this figure the distress scores range from
0 – 4. The number ―0‖ corresponds to a student reporting that they are not under any financial
strain that would cause distress because of credit card debt. The number ―4‖ demonstrates that
the financial strain of having credit card debt is affecting the student‘s well being. While the
majority of students in this sample have distress scores that fall the between 0 – 1 ranges, the
remainder of students have scores that are spread throughout the interval ranges reflecting
38

Table 8
Mother’s Education

a

Educational Level

Frequency

%

Grade School

4

1.3%

High School

69

22.3%

179

57.7%

58

18.7%

College
Graduate School
a

N = 310

Table 9
a

Race

Race

Frequency

%

Black or African American

45

14.4%

Mexican American or Chicano

11

3.5%

Asian Americans

21

6.7%

225

71.9%

11

3.5%

White or Caucasian
Other
a

N = 313

39

Figure 4. Credit card distress.

diversity in regards to the impact that credit card debt has on well being. In the next section, the
hypotheses of this study are introduced and explored in depth.
This study has four hypotheses:
Hypothesis 1: College students that have accounts in collection are distressed than
college students who do not have accounts in collection.
Hypothesis 2: College students that have accounts in collection are more likely to have
lower grade point averages, than college students who do not have accounts in collection.

40

Hypothesis 3: Students from lower income families are more likely to obtain credit and
carry high balances compared to students from higher income families.
Hypothesis 4: Students from lower income families are more distressed than higher
income college students that have accounts in collection.
Hypothesis one inquired whether or not college students that had accounts in collection
were distressed. Hypothesis one was supported in analysis. College students that have accounts
in collection were distressed about their debt. The regression in table 10 illustrates a positive
linear relationship between credit card debt and credit card distress. The more credit debt a
college student in this study had, they reported experiencing greater levels of distress.

Table 10
Regression Analysis of Credit Card Debt and Credit Card Distress
Statistic
Credit Card Debt
R

2

p
1.42**
.417

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 273.
*p<.05, **p<.01

Table 2 details the family income distribution for students in this study. Almost half of
the students in this study reported family incomes over $90,000. Initially, it might appear that
family income could mediate the impact of credit card distress for college students. The
regression in table 11 demonstrates that income was not a significant predictor of credit card
distress for students. That is, family income did not impact whether a student was more or less
distressed about credit card debt. Hypothesis 4 explores this finding in more detail.

41

The regression in table 12 illustrates that credit card debt is the most significant predictor
of credit card distress for college students. Additionally, the regression in table 13 highlights
that the amount of money owed on the credit card is also a significant predictor of credit card
Table 11
Regression Analysis of Credit Card Debt, Family Income and Credit Card Distress
Statistic

p

Credit Card Debt

1.42**

Family Income

-.044

R

2

.417

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 240.
*p<.05, **p<.01

Table 12
Regression Analysis of Credit Card Debt, Family Income and Credit Card Distress
Statistic

p

Credit Card Debt

1.38**

Family Income

-.009

Race

.143

Father‘s Education

.006

Mother‘s Education

-.103

R

2

.427

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 231.
*p<.05, **p<.01

42

Table 13
Regression Analysis of Credit Card Debt, Family Income, Race, Parent’s Education, Credit
Card Balances and Credit Card Distress
Statistic

p

Credit Card Debt

1.31**

Family Income

.020

Race

.058

Father‘s Education

-.037

Mother‘s Education

-.122

R

2

.479

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 120.
*p<.05, **p<.01

distress. In short, hypothesis one then is supported in analysis and students that have accounts in
collection are distressed.
Hypothesis two inquired whether college students that have accounts in collection would
have lower grade point averages. Hypothesis two was supported in analysis. College students
that had accounts in collection had lower grade point averages. The regression in table 14
illustrates that as credit card debt decreases grade point average increases.
In chapter one, the rigors of debt collection practices were detailed. This finding is not
surprising, that having accounts in collection, affects grade point average. For undergraduate
students steady streams of telephone calls requiring payments from aggressive debt collectors
can be distracting. Time spent to manage daily phone calls, and deal with this kind of financial
strain could prohibit concentration ultimately impacting academic performance. Additionally,
table 14 shows a positive linear relationship between family income and grade point average.
Students that have higher family incomes, tend to have higher grade point averages. Income is

43

Table 14
Regression Analysis of Credit Card Debt, Family Income, Race, Parent’s Education, and Grade
Point Average
Statistic

p

Credit Card Debt

-.367*

Family Income

.113*

Race

-.061

Father‘s Education

.123

Mother‘s Education

-.002

R

2

.104

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 215.
*p<.05, **p<.01

inextricably linked with education. Typically, the more education an individual attains the more
likely they are to earn higher wages.
For college students, this means that being from a higher income family has resulted in
privileges that promote high academic functioning in college. For example, having college
educated parents to help navigate transitioning to college, attending elite schools, participation in
cultural refining activities (plays, museums, vacations etc) all transmit cultural capital that is
rewarded in higher education.
This s well documented in the literature (Bourdieu, 1977; Bowles and Gintis, 1976;
Foley, 1990; MacLeod, 1995). Consequently, it is not surprising then that students, who reported
higher family incomes, have higher grade point averages. In summary, analysis has illustrated
important findings supporting hypothesis two. College students that had accounts in collection
did have lower grade point averages; they were also more likely to have lower family incomes.

44

Hypothesis three inquired whether lower income college students would be more likely to
obtain credit and carry high balances. Hypothesis three was not supported in analysis. Lower
income college students did not carry higher credit card balances and obtain more credit. The
regression in table 15 highlights that family income is not a significant predictor for credit card
balances.

Table 15
Regression Analysis of Family Income, Race, Parent’s Education, and Credit Card Balance
Statistic

p

Family Income

.013

Race

-.300*

Father‘s Education

-.060

Mother‘s Education

.030

R

2

.047

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 121.
*p<.05, **p<.01

One way to interpret this finding is that the balance of a credit card depends upon
multiple factors (the credit limit offered, individual spending and consumption habits, etc) and
family income alone does not influence the balance of a credit card. Hypothesis three examines
lower income college students and their credit balances, a low-income status may limit the
amount that could be borrowed. Lower income college students would not necessarily carry
higher balances because they may not be eligible for high credit limits.
In table 15 race is a significant predictor of credit card balances. Recall, that race was
coded as 0= other and 1= African American. Table 15 reflects that credit card balances are lower

45

for African Americans. This finding is not surprising because as previously stated income
determines eligibility for credit card limits. Creditors extend higher limits to applicants with
higher incomes, and typically lower limits for applicants with lower incomes. While African
American students in this sample reported having lower credit balances, Table 16 shows that
African American students were more likely to have both accounts in collection for payment
relapse and lower family incomes.

Table 16
Regression Credit Card Debt, Family Income and Race
Statistic

p

Family Income

-.055**

Race

.254**

R

2

.084

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 240.
*p<.05, **p<.01

Table 17 further examines hypothesis three and illustrates that number of credit cards a
student has is not correlated with family income. Lower income college students did not carry
higher credit card balances or carry multiple credit cards. To this extent, family income is not a
predictor of whether or not a student will obtain credit or carry higher balances. Hypothesis three
was not supported by the data.
Finally hypothesis four inquired whether lower income college students that have
accounts in collection would be more distressed than higher income students with accounts in
collection. Hypothesis four was not supported in analysis. Lower income students with higher
credit card balances were not more distressed than higher income college students with high
46

Table 17
Regression Analysis of Family Income, Race, Parent’s Education, and Credit Card Balance
Statistic

p

Family Income

-.009

Race

.294

Father‘s Education

.057

Mother‘s Education

.039

R

2

.013

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 264.
*p<.05, **p<.01

credit card balances. The interaction variable created in regression 18 composed of credit card
debt and family income illustrates the complete opposite of what hypothesis 4 suggested. Higher
income students with high levels of debt were actually more distressed than lower income
college with high levels of debt.
The findings in this study indicated that higher family income was a predictor of financial
literacy. Given this finding, it is then not surprising that higher income students with high levels
of debt are more distressed than their lower income counter parts. This finding suggests that
perhaps being aware of the perils of credit card debt and the consequences might make being in
debt more stressful for higher income college students who are financially literate. Additionally,
large balances on credit cards not consented by parents may warrant an explanation. This may
deter high-income students from seeking financial assistance from parents. Thus, resulting in
higher levels of stress concealing purchases and combating the strain of being in debt.
There were other variables that were significant predictors of credit card distress besides
having accounts in collection. Table 19 illustrates that the balance owed on a credit card is a

47

Table 18
Regression Analysis of Credit Card Debt, Family Income, Race, Parent’s Education, Interaction
of Income and Credit Card Debt and number of Credit Cards
Statistic

p

Credit Card Debt

.886*

Family Income

-.035

Race

.172

Father‘s Education

.015

Mother‘s Education

-.106

Interaction: Income &
Credit Card Debt

.185*

R

2

.438

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 231.
*p<.05, **p<.01

Table 19
Regression Analysis of Credit Card Debt, Family Income, Race, Parent’s Education, Interaction
of Income and Credit Card Debt, Credit Card Balance and Credit Card Distress
Statistic

p

Credit Card Debt

.030

Family Income

-.022

Race

.089

Father‘s Education

.021

Mother‘s Education

-.132

Interaction: Income &
Credit Card Debt

.216

R

2

.493

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 118.
*p<.05, **p<.01

48

predictor of credit card distress. College students that carry balances that they can pay each
month (at least the minimum payment) report feeling less distressed over credit card balances.
Credit card balances become a stressor for students when they are unable to meet payment
obligations.
Additionally, table 20 reports that the number of credit cards owned, and mother‘s
education level are also a predictor of credit card distress. The number of credit cards a student
owns has implications for the amount of debt that can be utilized. Students who carry more than
one card have access to multiple credit lines, and therefore maybe at risk of creating balances
that they cannot maintain. Interestingly, table 20 also reports that as the educational level of the
mother increases, credit card distress decreases.

Table 20
Regression Analysis of Credit Card Debt, Family Income, Race, Parent’s Education, Interaction
of Income and Credit Card Debt, Number of Credit Cards and Credit Card Distress
Statistic

p

Credit Card Debt

.939*

Family Income

-.028

Race

.144

Father‘s Education

.000

Mother‘s Education

-.113*

Interaction: Income &
Credit Card Debt

.134

Number of Credit Cards

.166**

R

2

.485

Note. Dependent variable: credit card distress. Unstandardized coefficients reported. N = 229.
*p<.05, **p<.01

49

This finding is interesting for a number of reasons. One is that the education of the father
was insignificant. This might reflect the number of students in this study that do not have a father
present in the home, or skipped this question because they were uncertain about their father‘s
educational level. Additionally, this finding might reflect that more educated parents may parent
more skillfully, for example, possessing the ability to help comfort a college student that is
distressed regarding credit card debt. This finding requires deeper investigation, and should be
addressed in future studies, as parental education was not a variable directly examined in this
study.
In conclusion the data has helped elucidate several important findings. Family income is
a significant predictor for grade point average and credit card debt. That is students who have
higher family incomes report lower credit card debt and higher grade point averages, and are
less likely to have accounts in collection. Secondly, having accounts in collection increases
distress and negatively affects grade point averages.
Qualitative Findings
This study conducted 30 face-to-face interviews with college students. Almost half of the
participants were sophomores 14, juniors totaled 4, Seniors 8 and 6 freshmen. Approximately 14
students interviewed were male, and 16 were female. Each interview was 1 to 1.5 hours in
duration totaling 52 hours. The findings from those interviews are detailed in this chapter. There
are three reoccurring themes that persist throughout the qualitative interviews for this study.
Each theme will be discussed in turn. A table of interview participants is included at the end of
this chapter.
Respondents reported the following most often:

50

1. Students had low levels of financial literacy. Students reported that they learned
financial literacy through trial and error methods, not from parents or other
institutions
2. Status Consumption prompted majority of credit card purchases. Students reported
that spending on large ticket clothing items to gain peer recognition is important.
3. Anticipatory spending: students reported using loan refunds to repay accumulated
credit debt incurred during the semester.
Theme 1: Low Levels of Financial Literacy
Twenty-one respondents reported that they were told by family members or parents not to
obtain credit cards. However, they were not offered sound reasons or given clear explanations
about why obtaining credit cards could have serious negative financial consequences if credit is
managed improperly. The interviews reveal that weak explanations are given to accompany stern
warnings about securing credit cards. Consequently, despite stern warnings students interviewed
in this sample secured lines of credit some as many as three-four cards. While students are
encouraged not to use cards, the reality is 84% of college students own at least one card.
Tragically, what is not being shared with college students is how to use credit wisely and
how to become financially literate. When students arrive to college they are over solicited with
offers to apply for credit cards. These offers are particularly enticing if the student is faced with
financial dilemmas and lack of financial support. Sadly, without a solid understanding of the
perils of credit card offers many students forget about the warning they receive and apply for
credit offers.

51

Students were asked if they could recall what they were taught or learned about money
and credit cards when they were growing up? What stories advice or interactions they had with
their family and money. Repeatedly, students answered with responses such as:
― I really didn‘t know much. I was told not to get credit cards though.‖(Sophomore, male)
―I mean nobody really said anything in particular…I really was never sat down and
talked to about money.‖(junior, female)
―What I know, I taught myself, ain‘t nobody coach me or nothing….that‘s that TV kinda
family, that don‘t happen in real life.(senior, male)
―I never even saw my parents managing money.‖(freshmen, female)
These statements reflect how students maybe vulnerable to unwise financial choices,
because they lack financial literacy. Credit cards are not inherently ―bad‖ consequences of poor
credit management and lack of financial literacy cause adverse financial consequences.
Interviews revealed that students lacked financial literacy regarding selecting credit cards with
reasonable interest rates, interpreting statements, and understanding the terms and conditions
associated with credit card offers. Students in this sample were unaware of information that is
printed on statements. It is unclear whether students read statements carefully or at all. For
example, only 23% (75 students out of this study‘s sample of 330) of students in this study
reported knowing the APR for their current credit card(s). This information is printed and made
available on each monthly statement. It is unclear then why only 23% of the students in this
study reported knowing the APR for a card they carry. For the majority of students who reported
not knowing the APR for their credit card, this is an example, of not being sure whether students
are reading statements or lack financial literacy regarding interpretation.

52

This theme of students being cautioned against applying for credit is very noteworthy
because if students are only being ―cautioned‖ how are they being educated? Moreover, if
families, relatives, parents, or educational institutions do not educate students about effectively
handling personal finances, how do they learn? Who teaches them? Unfortunately, as one
respondent stated: “I am wiser about credit cards now. That is because I know everything about
credit card debt now that I am in it…I got debt now” (senior, male). Tragically, many college
students learn mastery of personal finances by dealing with the consequences of
mismanagement.
Theme 2: Status Consumption: Students Reported That Spending on Large Ticket
Clothing Items to Gain Peer Recognition Is Important
Status consumption expresses the idea that admiration, envy, recognition and/or respect is
earned on the basis of what an individual possesses. Moreover, the process of acquiring this kind
of recognition is competitive and continuous. It requires constant accumulation of ―things‖ and
chronic spending to stay at pace with trends. The recognition from peers based on the ownership
of possessions for many college students is very important. Certain clothing, electronics,
hairstyles and various other items are conspicuous signals and identifiers of wealth and prestige.
Desiring this form of admiration has been discussed repeatedly during the interviews. The
benefits of gaining this admiration result in increased dating opportunities, invitations to
premiere social events, and inclusion in elite friendship circles. While this type of behavior has
been associated with high school sub culture, notions of being awarded a social status of
―popular‖ or ―unpopular‖ based on appearance and possessions is very much a part of the college
student sub culture. Particularly for minority students whom are parts of smaller populated ethnic
circles. Freshmen and sophomore students report more commonly than juniors and seniors that

53

status and appearance are very important. The pursuit of inclusion and desire for recognition
encourages excess spending and status consumption driven purchases for many students. One
respondent stated:
―College is all about what you have. People think they have to buy an outfit for every
party they go to. You need a picture perfect image…yea. People are so judgmental.
What‘s hot true religion, 7‘s (referring to $168.00 jeans) When you are on campus 18, 19,
20---you care, 21, 22 not so much. (freshmen, female)
I feel like you only have so many times to keep telling people you can‘t go, before they
stop asking you to come out. Telling people you can‘t go repeatedly even if money is the
reason…means eventually they will quit inviting you.‖ (junior, female).
―I was like, I am not gone be the only one not going to spring break!‖ ―I cash advanced
my card and was out.‖ (sophomore, female)
These statements mirror how possessions or shared experiences generate respect and
inclusion from peers. For many college students acquiring costly items to gain respect prompts
excess spending. For others college affords the opportunity to make friends with many diverse
individuals. Becoming friends with individuals of varying social economic statuses may
necessitate spending beyond available means to foster friendships, particularly if friendships are
with individuals of higher SES. From spring break trips, sorority/fraternity membership dues,
excessive dinners, frequent movie outings, expensive clothing the high cost of inclusion can
create vulnerability to debt. Additionally, factors unaddressed in this study that surfaced during
interviews regarding how debt is accumulated were: owning a car, having a sibling in college at
the same time they are attending, and medical expenses. This is addressed in this study‘s
limitations.

54

Theme 3: Anticipatory Spending: Students Reported Using Loan Refunds to Repay
Accumulated Credit Debt Incurred During the Semester
Living from one loan refund period to another has become an economic survival strategy
for many college students. During interviews respondents reported reliance on excess monies
from loans awarded to help resolve debt accumulated throughout a semester. The anticipation of
loan refunds creates a dependence on borrowing to meet financial obligations that are often
created with the intention of being satisfied with ―left over aid.‖ Many students begin to borrow
educational loans that total cumulative amounts that can be compared to home mortgages. This is
an alarming trend because few students have a realistic plan for debt repayment of any kind. The
reality that a refund check is generated from ―borrowed money‖ that has to be repaid in the
future seemingly resonates with few students. The following statements illustrate attitudes about
borrowing and repayment.
―When we get money we think one thing: splurge. A refund check is the most money I
have ever —period. I splurged I was not taught any different.‖ (freshmen, female)
―It feels like free money. I know I have to repay it. When I graduate I will.‖ (freshmen,
female)
―I saw my credit report and I have $200,000 of private loan debt coupled with student
loan debt. I believe that I will get a job to help me pay back my loans.‖(junior, male)
Using anticipated loan refunds to cover debt accumulated throughout a semester is dangerous
because it creates a dependence on the receipt of excess funding. It encourages economic
frivolity that can be remedied by excess borrowing. However, glitches in financial aid, exceeded
maximums, and graduation create inability to financially problem solve by receiving excess
financial aid. This kind of financial problem solving is not sustainable. Additionally, such a

55

dependence on receiving access aid to help repay debt poses problems after a student graduates
and no longer receives refund checks from excess aid.
In conclusion, interviews with students raise a very important question: Who is
responsible for educating young adults to manage their finances? While it is clear that financial
illiteracy has disastrous consequences, it is not clear how students will become financial literate.
Traditionally, the expectation has been that parents are responsible for teaching pertinent ―life
skills‖ (i.e. managing finances) that help aid the transition of young adults for life in college and
beyond.
However, as these accounts from students illustrate, many are educating themselves,
through learning from a series of costly financial mistakes. Perhaps colleges and universities
should have a vested interest in ensuring that students become financially literate, especially
since many institutions directly market credit cards to college students in the form of affinity
cards or through lucrative contracts with third parties.
Moreover, college students translate a ―win‖ for the credit card industry, often depending
on their financial obliviousness, and misuse of credit for profit. College students are not only
―loosing‖, they face great disadvantages in playing the game altogether. College students do not
have an adequate grasp on the rules, as previously stated the financial literacy rates of college
students are low. As a result, many college students end up with low scores across the board, low
credit scores, low grade point averages and compromised well being.

56

Table 21
Face-to-Face Interview Participants
Name

Class Standing

Gender

1. Tisha
2. Emily
3. Gina
4. Keasha
5. Ellen
6. Christina
7. Kelly
8. Beth
9. Ebony
10. Janet
11. Riley
12. Kate
13. Rebecca
14. Dana
15. Margret
16. Julie
17. Derrick
18. Robert

freshmen
freshmen
freshmen
freshmen
freshmen
sophomore
sophomore
sophomore
sophomore
sophomore
sophomore
sophomore
junior
senior
senior
senior
freshmen
sophomore

female
female
female
female
female
female
female
female
female
female
female
female
female
female
female
female
male
male

19. Aaron
20. Kyle
21. Jamal
22. Brian
23. Jeff
24. Rueben
25. Seth
26. Kirk
27. Nathaniel
28. Charles
29. Curtis

sophomore
sophomore
sophomore
junior
junior
junior
senior
senior
senior
senior
senior

male
male
male
male
male
male
male
male
male
male
male

Note. For the confidentiality of participants, names have been changed.

57

CHAPTER 5 CONCLUSION
The results from this study provide evidence that credit debt for college students is not
only an issue, but has pernicious consequences for both distress levels and grade point averages.
In chapter three the hypotheses for this study were explored. In summation, the following results
were presented.
Hypotheses one demonstrated that college students suffer distress when they have
accounts in collection. While, this finding may seem obvious it is important.
It could have been the case that students having accounts in collection could have become
tolerant to both financial strain and collection efforts adopting a nihilistic attitude. Hypothesis
one confirms that college students are alarmed about debts that incur and suffer distress when
they are unable to resolve the debt.
Hypothesis two confirms one of the study‘s most important findings that credit card debt
negatively impacts grade point averages. In this study students who had accounts in collection
also had lower grade point averages. Arguably, the reasons for lower grade point averages can be
numerous (poor study habits, class truancy, illness etc) However, students in this study reported
that their grade point averages were affected by their credit card debt and subsequent time spent
managing bills instead of scholastic related activities.
Students in this study with higher grade point averages also reported that they had fewer
accounts in collection, higher levels of financial literacy more educated parents, and higher
family incomes. As previously stated, for college students, this means that being from a higher
income family has resulted in privileges that promote high academic functioning in college. For
example, having college educated parents to help navigate transitioning to college, attending elite

58

schools, participation in cultural refining activities (plays, museums, vacations, etc) all transmit
cultural capital that is rewarded in higher education and standardized tests.
This is well documented in the literature (Bourdieu, 1977; Bowles and Gintis, 1976;
Foley, 1990; MacLeod, 1995). Consequently, it is not surprising then that students, who reported
higher family incomes, have higher grade point averages.
Hypothesis three revealed that family income was not a determinant of credit card balances or
the number of credit cards a college student carries. While it may be difficult if not impossible to
conclude exhaustively what factors affect whether students will or will not accumulate debt.
However, this study has offered insight into what makes a college student vulnerable to debt
accumulation. This study has highlighted anticipatory spending, knowing others whom are
indebted, status consumption, over solicitation of credit offers and lack of financial literacy, are
all factors that increase vulnerability to debt.
Finally, hypothesis four found that higher income students with accounts in collection
reported experiencing more distress than lower income students with accounts in collection.
Initially, this finding was surprising given the assumption that higher income students
presumably have access to funds to resolve credit debt. While this may be true, there are other
stressors that describe why higher income students report being more distressed regarding credit
card debt.
One reason is because they are higher income. Higher income students may lack
exposure and a point of reference for dealing with debt. Additionally, their families or
communities may contain few people who are indebted, creating embarrassment or reluctance to
seek help. Previously mentioned, was also how debt a student incurred may not have been

59

consented by a parent, and therefore the student does not seek parental assistance in resolving the
debt.
Finally, another reason higher income students with accounts in collection may have
reported experiencing higher distress levels than lower income students with accounts in
collection, is that higher income students reported higher financial literacy levels. An awareness
of the severity of consequences for financial mismanagement may be more stressful for
financially literate college students. This is due to their ability to assess accurately how much
damage they have caused for example, and what repair efforts are necessary to address
mismanagement.
Discussion
The rising costs of education and deceiving job markets have gained increased popularity
in both literature and media. College students are an important sector of American society and
these young consumers are acquiring student loans and are heavily solicited by marketers of
credit cards. Today college students are urged to create debt at a time in life when they have the
least income (Wells, 2007). It is not surprising then, many college students have developed a
dysfunctional orientation regarding credit card spending, resulting in debt loads that are difficult
to manage. There is a debt culture for the millennial college student generation. The millennial
college students have grown up during an era that has presented debt and credit as normative
responsibilities of adulthood.
Media and digital platforms such as face book, twitter, blogs, and online photo albums
also present unprecedented pressures to manage appearance and compete with peers through the
ownership of expensive clothing and electronic gadgets. Technology has allowed young adults
the opportunity to create a diverse population of friends that may have greater economical

60

privilege. Unlike young adults decades ago, that were limited to establishing friendships with
others in close proximity that may have been economically similar. Young adults today with the
use of technology maintain friendships with a wide variety of others that attend different schools,
live in different neighborhoods and occupy different income levels. Consequently, ―keeping up
with the Jones‖ today could mean attempting to compete with more advantaged peers.
Competition with advantaged peers could create consumption habits that supersede income
levels creating unmanageable credit card debt.
Status consumption is not the only culprit inciting debt vulnerability for college students.
Not all college students use credit cards for luxury items. Disadvantaged college students coming
from families that have lower incomes, use credit cards as a borrowing source for necessities.
Survival borrowing for many disadvantaged college students is the only option for instrumental
support needed during college. The expenses of textbooks, healthcare, cell phone plans, and
other day-to day expenses (transportation, grooming, toiletries, etc) create ongoing costs for
disadvantaged college students, who lack financial support from parents. Thus, credit cards
create immediate access to funds that temporarily solve financial dilemmas. However, as
purchases and balances increase disadvantaged college students are at risk for payment relapse.
For many college graduates the prospect of beginning a career in debt is not only a
serious concern but also a reality. The extent of debt that students are carrying upon graduation
has become a crucial predictor of their career choices and salary expectations (Davies and Lea,
1995). What types of consequences do young adults face upon graduation, leaving with not only
their degrees but also student loan and credit debts?
Literature has shown that anxiety is more common among young adults, in part due to
economic hardship experienced in young adulthood (Mirowsky & Ross, 1999; Drentea, 2000).

61

The early adult years of the life cycle are a challenging time in which most men and women have
many job and family responsibilities and economic transitions (Drentea, 2000; Pearlin & Skaff,
1996). Young adults typically have not reached their full earning potential, which further
aggravates financial stress.
Additionally, financial stressors often affect workplace performance. (Kim, Sorhaindo, &
Garman, 2006). Garman et. al (1996) concluded that 15% of workers in the United States are
experiencing reduced work productivity affected by their financial stress. Studies have shown the
financial distress is also a predictor of work place absenteeism (Jacobson, 1996; Kim & Garman,
2006). Financial distress has also been documented in literature as a predictor of pay level
satisfaction, and organizational commitment both of which influence absenteeism (Kim &
Garman, 2006).
In addition to absences from work, employees under financial distress often report to
their jobs but are unable to carry out duties (Cox, Stanley, & Kessler, 1996; Kim and Garman,
2006), or spend time working on personal finances (Kim, 2000). This literature reflects a
behavioral pattern for young adults whom experienced difficulty focusing on academics in
college because of financial distress. In the face of the same financial strain they endured in
college, these students could experience similar distraction and distress at work as they try to
channel efforts into workplace productivity.
Moreover, the demands of life especially during the early years of transition from college
to post graduation and family development could heighten financial strains as expenses become
both more costly and unpredictable. Financial instability and unexpected expenses worsens the
ability of an individual to eradicate financial pressures (Wells, 2007). For young adults the early
years of career building and family formation can be trying.

62

An attempt to control solicitation of college students from credit card companies has not
been successful. In an attempt to legislate ethical behavior of credit card companies the
Consumer Federation of America released a three-year study highlighting the hazards for college
students falling behind on credit card payments. The organization and others attempted to use the
study to lobby Congress for legislation that would limit card issuer‘s ability to extend credit to
students under 21 years old. However, Legislative efforts failed to pass, therefore, credit card
issuers are legally allowed to solicit and issue cards to college students, even those younger than
21 years old (Bianco and Bosco, 2002). In response to these groups, credit card companies are
now offering pseudo ―financial education‖ programs along with credit applications. Solicitation
still continues unabated. Furthermore, it is not realistic or the responsibility of credit card
companies to financially educate consumers whose financial obliviousness grossly fattens their
profit margins.
While financial literacy is key to ensuring proper credit management, it is undecided
where the responsibility or burden for financial education rests for college students and other
consumers. Whose responsibility is it to teach financial literacy? Arguably, parents have a huge
role in positioning children for such healthy financial decision-making regarding credit.
Unfortunately, not all parents are financially literate. Many parents expose their children to
unhealthy financial practices or do not teach their children fiscal responsibility. Financial literacy
for college students is often learned through trial and error.
Moreover, what role should colleges and universities take to address the financial literacy
of their students? While many colleges offer personal finance courses as an elective should such
courses be mandated as a requirement? Such efforts, might equip colleges and universities with
solutions to address the growing problem of college student credit card debt. Financial literacy

63

for college students is vital for the transition into adulthood. While some colleges have banned
credit card marketers from their campuses (Lazarony, 1999;Wells 2007) and others have the
reduced access of credit card marketers to campuses (Rugen, 2004;) such efforts are largely
ineffective to address student credit debt. These efforts do not educate college students about
debt management. These actions might protect some students from applying for credit cards, but
they do not provide a means for students to become financially literate. Educators, parents, and
financial service professionals need to prepare students for the financial decisions they will have
to make.
Limitations
When research is exploratory as in this study, there are limitations and opportunities for
future research. This research has limitations and opportunities in the areas of survey
development, sample selection, and generalizability. In the area of survey development,
exploring additional questions in the questionnaire may have provided deeper insight into credit
card utilization for college students. During the face-to-face interviews three areas continued to
reappear as persistent reasons for student‘s credit card debt. Unfortunately, because they were
not asked in the questionnaire, this study was unable to ascertain the impact possible for the
broader sample population. These questions were:
1. What is the limit on your credit card? While the questionnaire did ask students how
much money they owed, knowing the credit available would have been useful to
determine how much money lower income and higher income student typically get
approved for, and who is actually closer to reaching or ―maxing out‖ the limit
available on the credit card.

64

2. Do you have siblings? Do you have siblings currently in college? During the
interviews many students indicated that they relied on credit cards heavily because
their parents were also supporting siblings either at home or who were also in college.
The need for financial independence was heightened by the unavailability of parental
funds being expended to support other siblings. For some college students in this
sample, securing credit cards or working more hours was a means to supply funds
needed for college expenses, and reduce monetary neediness from parents.
3. Do you have a car, here at school? During interviews many students reported using
credit cards to satisfy debts incurred from parking violations and having their cars
towed. The ability to explore car ownership as a dependent variable in a linear
regression model with credit card debt, and how much money do you owe might have
been an insightful method to gauge spending habits of college students and credit
card debt.
The second limitation is the sensitivity of this topic. Owing money, being in debt, and not
having means of repayment are sensitive areas to disclose personal information about to another.
Ultimately this may cause embarrassment that tampers with the ability of a respondent to report
truthfully. Some participants fail to report accurately about sensitive experiences, particularly if
experiences are current or recent (Catania, 1999; Desimone and LeFloch 2004).
Finally, the use of a convenience sample while highly useful and effective for this topic
resulted in an uneven distribution of students based on classifications of race, class standing, and
family income. The bias of convenience samples has been documented in literature as an issue,
specifically with college student populations (Lynn 2008; Dillman 2003; Neuman 2006; Biemer

65

and Lyberg 2003). While this study will used a convenience sample, the results are somewhat
more generalizable for the following reasons:
1. The subject matter is relevant to the sample.
2. The sample demographically matches desired characteristics.
3. Face-to-face interviews with students helped explore in greater detail debt, and well
being outcomes providing greater detail about the issue.
The information gathered from interviews offers valuable insight into the problem
through the lenses of student experiences. The information gathered may or may not be
generalizable to the entire population, but it offers an excellent starting point for future research
considerations. Two of the major critiques of convenience sampling has been one that results are
difficult to generalize because the questions being asked are ill suited for the sample creating a
bias. For example, asking freshmen students questions about retirement options may be ill suited
for a population that has just begun schooling. While accessibility to freshmen students may not
be difficult obtain, asking this group about retirement may render data of questionable quality.
For this study literature does confirm that college students are over solicited for credit offers and
are likely to have 3-4 credit cards (Wells 2007; Hayhoe, Hayhoe 1999; Turner, Bruin 2000;
Rugen 2004; Lyons 2004; Roberts and Jones 2001; Allen, Edwards, and leach 2007). This
finding suggests that the issue of credit card debt for college students is widespread and highly
relevant. This study asked a sample of college students‘ questions about an issue that literature
confirms is highly relevant for them.
Second, a critique of convenience sampling has been because the sample is gathered
based on the convenience of the researcher the sample demographically may not match desired
characteristics. For example, gathering grade point average information for high school students

66

who are currently serving detention for low grades. This would be a convenient sample, but
results would be difficult to generalize. This study uses a sample that is easily accessible, but the
questionnaire is designed to filter respondents to meet the characteristics desired to study
(college students who have credit card debt).
In conclusion, an extension of this research would be a longitudinal study to determine
what struggles did college students report experiencing regarding their debt immediately
following graduation? What might they have done differently regarding credit choices and
consumption behavior? Research should focus on newly graduated students 1 – 5 years out of
undergraduate programs.
Going to college is often perceived as a way to increase economic rewards in the job
market. The current trends of student loan borrowing and credit card dependence suggests that
attending college is expensive and often difficult to navigate financially. Research is slightly
silent regarding what has prompted the soaring costs of college education and what can be done
to combat expenses to ensure that attending college is financially equitable for college students.
Perhaps the rising expenses and relative benefits of college has fueled the indecision of some
young people about attending college. Future research should examine this. A greater of
understanding of this could create the rewarding experience college is expected to be, and
produce the societal benefits of having well educated individuals within our communities.
Future Research
Financial literacy has been identified as the solution to the problem of credit card abuse
on campuses (Roberts and Jones, 2001; Norvilitis, Szablicki, and Wilson 2003). However, little
research has been done to test this relationship. Longitudinal studies that examine money
attitudes and consumption behaviors after intervention (i.e. financial literacy) are needed.

67

Additionally, perceived financial well-being appears to be related to psychological well-being, a
more internal locus of control, and lower levels of dysfunctional impulsivity (Norvilitis et al,
2003). For college students future research should explore self-reports of perceived financial
well being.
Finally, longstanding concerns for colleges and universities nation wide are retention
rates. Grade point averages, mental health and financial concerns have been documented in
literature as determinants that cause students to terminate enrollment and affect college retention
rates (Hill, 2002; Graham, 2006; Caldwell, 2010). This study has shown that credit card debt
affects both grade point averages and well-being. Examining retention rates were beyond the
scope of this dissertation, however the correlations that credit card debt has with both well-being
and grade point average merit consideration regarding college student retention rates for future
research efforts.

68

APPENDIX

69

Appendix: Survey Instruments
Consent Statement for Face-to-Face Interviews
Dear Student:
Thank you for agreeing to participate in this face- to -face interview. I am conducting a research
study. The purpose of this research is to examine the attitudes and behaviors among college
students regarding credit. In this face- to- face interview I will ask you questions about credit
cards, debt, mental health and academic performance. The average time to complete the
interview is about an hour. Participation is voluntary, you may choose not to participate at all,
and you may refuse to answer certain questions, or discontinue participation at any time without
consequence. As a way to thank you for your participation, you will receive $25.00 cash. You
will receive payment even if you choose not to answer every question, or you decide to terminate
the interview.
There are no serious risks involved in this survey. However, you may feel distress as you answer
questions related to credit card debt and small risk of breach of confidentiality if any details of
debt are disclosed outside of research. You will not directly benefit from your participation.
However, your participation in this study may contribute to the understanding of how college
students acquire credit card debt, and subsequent impacts on mental health and academic
performance.
All records will be kept for a minimum of three years following the closure of this study. Files
will be kept under lock and key, in a locked file cabinet. The Institutional Review Board as well
as the researchers listed on this consent form are the only individuals who will have access to
records obtained in this study. Your confidentiality will be protected to the maximum extent
allowable by law.
If you have concerns or questions about this study, such as scientific issues, how to do any part
of it, or to report an injury, please contact the researcher at:
Temple Smith
P.O. Box 1432
East Lansing, MI 48826
Telephone: 517 214-2852
Email: smithtem@msu.edu
You may also contact my advisor at:
Dr. Clifford Broman
Department of Sociology at Michigan State University
Office: (517) 355-1761
Email: broman@msu.edu

70

If you have questions or concerns about your role and rights as a research participant, would like
to obtain information or offer input, or would like to register a complaint about this study, you
may contact, anonymously if you wish, the Michigan State University‘s Human Research
Protection Program at 517-355-2180, Fax 517-432-4503, or e-mail irb@msu.edu or regular mail
at 202 Olds Hall, MSU, East Lansing, MI 48824.
Confidentiality will be protected to the maximum allowable extent under law. If you agree to
participate please sign below and I will give you a copy for your records.
I voluntarily agree to participate in this study
Signature:__________________________________ Date:_____________________

71

Face to Face Interview Questions
1. How old were you when you first applied for your credit card?
2. Why did you apply/ what made this offer appealing?
3. Growing up what did you learn about credit cards, managing money?
4. Where did you learn this?
5. When did you first realize your credit card debt was a problem?
6. What events made you realize this?
7. How did you respond? (what did you do?)
8. Does anyone know about your debt? (who?)
9. Have you sought help or thought about seeking help?
10. How do you feel about owing the money you owe?
11. Are people you know, (or people around you) experiencing similar problems?
12. What causes you to spend money beyond what you intended ?
13. How often does this happen?
14. Do you buy things that cannot be returned?
15. How has credit card debt affected your grades?

72

Consent Statement for questionnaire
Dear Student:
Thank you for taking the time to read this letter. I am conducting a research study. The purpose
of this research is to examine the attitudes and behaviors among college students regarding
credit. What you have before you is a survey about college students and debt that we ask you to
complete. The survey should take you about 20 minutes to complete. After you have completed
the survey, I will collect it. There are no serious risks involved in this survey. However, you may
feel distress as you answer questions related to credit card debt and how you feel about debt. You
will not directly benefit from your participation. However, your participation in this study may
contribute to the understanding of how college students acquire credit card debt, and subsequent
impacts on mental health and academic performance.
You may be wondering how we selected you to participate in the study. I elected to come into
classrooms on campus, and simply ask for your participation. If you choose to participate,
remember: All responses are completely confidential, and your participation in the study is
completely voluntary. You may choose not to participate at all, and you may refuse to answer
certain questions, or discontinue participation at any time without consequence. Choosing not to
participate will not affect your grade in this course. Your confidentiality will be protected to the
maximum extent allowable by law. All records will be kept for a minimum of three years
following the closure of this study. Files will be kept under lock and key, in a locked file cabinet.
The Institutional Review Board as well as the researchers listed on this consent form are the only
individuals who will have access to records obtained in this study.
A small subset of students will be contacted and asked to participate in a face to face interview
discussing personal financial behaviors. If you are contacted you will receive more information
regarding the interview at that time, further participation after learning about the interview, will
be totally voluntary. However, if you are selected and choose to participate you will receive
$25.00 in cash. If you have questions or concerns about your role and rights as a research
participant, would like to obtain information or offer input, or would like to register a complaint
about this study, you may contact, anonymously if you wish, the Michigan State University‘s
Human Research Protection Program at 517-355-2180, Fax 517-432-4503, or e-mail
irb@msu.edu or regular mail at 202 Olds Hall, MSU, East Lansing, MI 48824.
If you have concerns or questions about this study, such as scientific issues, or to report an
injury, please contact the researcher at:
Temple Smith
P.O. Box 1432
East Lansing, MI 48826
Telephone: 517 214-2852
Email: smithtem@msu.edu
You may also contact my advisor at:

73

Dr. Clifford Broman
Department of Sociology at Michigan State University
Office: (517) 355-1761
Email: broman@msu.edu
IRB#09-722
You indicate your voluntary agreement to participate in this study by completing and returning
this questionnaire.
Thank you so much for taking the time to complete this survey.
This survey will ask you questions about credit cards, debt and mental health. Please circle the
appropriate answer choice to each question.
*****************************
SECTION A
1. Do you own a credit card?
Yes

No

2. How many credit cards do you have (do not include debit card(s)?
0
1
2
3
4
5
6
more than 6

3. How old were you when you obtained your first credit card?
16
17
18
19
20
21
over 21

4. How much money do you owe on your credit card(s)?
$500

$1,500-$2,500 $3,000 - $6000

over $6,000

*****************************
SECTION B
1. I pay my credit cards off every month.
Yes

No

2. I have difficulty paying the minimum balance.
Yes

No

3. I know the APR on my card(s)
Yes

No

4. In the past I have negotiated with creditors about a lower APR for my card(s)
Yes

No

74

5. I am aware of the debt collection practices for my card(s)
Yes

No

6. I know what factors influence my credit score.
Yes

No

7. I am familiar with the provisions of the Fair Credit Reporting Act.
Yes

No

8. I know how to obtain a copy of my credit report.
Yes

No

9. In the last 6 months I have obtained a copy of my credit report.
Yes

No

10. I know how to read a credit report.
Yes

No

11. If I wanted to learn more about handling money I would ask my parents.
Yes

No

12. I have taken a personal finance course here at MSU.
Yes

No

13. Managing credit cards is a problem for me.
Yes

No

*****************************
SECTION C
1. I worry about being able to pay my credit card bills.
Never

Hardly Ever

Some of the time

Most of the time

Always

2. I spend a lot of time thinking about my credit card bills.
Never

Hardly Ever

Some of the time

Most of the time

Always

Most of the time

Always

3. I get down when I think about the money I owe.
Never

Hardly Ever

Some of the time

75

4. I have cried about owing credit card bills.
Never

Hardly Ever

Some of the time

Most of the time

Always

5. Creditors call me because I am past due on my account(s)
Never

Hardly Ever

Some of the time

Most of the time

Always

6. A phone call from a creditor ruins my day.
Never

Hardly Ever

Some of the time

Most of the time

Always

Most of the time

Always

Most of the time

Always

Most of the time

Always

Most of the time

Always

7. When creditors call I do not answer.
Never

Hardly Ever

Some of the time

8. Creditors call my cell phone.
Never

Hardly Ever

Some of the time

9. It is hard to make arrangements with creditors
Never

Hardly Ever

Some of the time

10. I feel overwhelmed by my debt
Never

Hardly Ever

Some of the time

***************************** For the following questions please answer yes or no.
11. I have considered getting another job to help me pay debt.
Yes

No

12. I am embarrassed about the money I owe on credit cards.
Yes

No

13. I have talked to someone about my debt.
Yes

No

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14. Regardless of my debt I still treat myself to things.
Yes

No

15. I have trouble enjoying myself because of debt.
Yes

No

16. I regret applying for credit cards
Yes

No

17. When I get upset about my credit card debt, I consider drinking.
Yes

No

*****************************
SECTION D
1. My friends encourage me to apply for credit cards
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

2. I am attempted to apply for credit cards in the mall
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

3. I usually throw away credit card offers I get in the mail
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

Almost Never
Once in a while
Sometimes
Frequently
6. I use my credit card to reward myself for hard work

Almost Always

Almost Never

Almost Always

4. I see posters for credit cards up around campus
Almost Never

Once in a while

Sometimes

5. I charge treats for myself on my credit card

Once in a while

Sometimes

77

Frequently

7. I use my credit card to put gas in my car
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

Frequently

Almost Always

Frequently

Almost Always

8. I use my credit card to buy groceries
Almost Never

Once in a while

Sometimes

9. I use my credit card to buy books
Almost Never

Once in a while

Sometimes

10. I use my credit card to eat at restaurants
Almost Never

Once in a while

Sometimes

11. I take cash advances on my credit card when I run out of money
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

12. I mostly use my credit card to buy clothes
Almost Never

Once in a while

Sometimes

13. I would not have money to cover my expenses without my credit card.
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

Frequently

Almost Always

Frequently

Almost Always

14. I use my credit card to buy alcohol
Almost Never

Once in a while

Sometimes

15. I use my credit card to buy cigarettes
Almost Never

Once in a while

Sometimes

16. I use my credit card(s) to treat friends to dinner
Almost Never

Once in a while

Sometimes

*****************************

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SECTION E
1. I have missed class because I was making calls to get my bills in order
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

2. I have been late to class paying bills
Almost Never

Once in a while

Sometimes

3. A phone call from a creditor upset me so much, I stayed home from class
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

4. I have trouble concentrating because of my debt
Almost Never

Once in a while

Sometimes

5. I feel like my GPA would be better if I didn’t have credit card bills to pay
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

6. I find that working so much limits me from studying like I could
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

7. I have sought professional help about my bills
Almost Never

Once in a while

Sometimes

8. I have had to drop a class because I was working too much
Almost Never

Once in a while

Sometimes

Frequently

Almost Always

Frequently

Almost Always

9. I work to pay down my credit card bills
Almost Never

Once in a while

Sometimes

10. Overall, I feel I would be a better student if I did not owe on my credit card
Almost Never

Once in a while

Sometimes

*****************************

79

Frequently

Almost Always

SECTION F
1. What is your current Class standing?
Freshmen

Sophomore

Junior

2. How do you describe yourself?
1. Native American
2. Black or African American
3. Mexican American or Chicano
4. Puerto Rican or Latin American
5. Oriental or Asian American
6. White or Caucasian
7. Other (please specify ___________)
3. What is your current grade point average?
1. Below 1.0
2. 1.0 to 1.9
3. 2.0 to 2.9
4. 3.0 to 3.5
5. 3.6 or above
.What was your grade point average during high school?
1. Below 1.0
2. 1.0 to 1.9
3. 2.0 to 2.9
4. 3.0 to 3.5
5. 3.6 or above

80

Senior

4. What is the highest level of schooling completed by your father? (circle one)
Grade School
1 2 3 4 56 7 8

High School
9 10 11 12

College
13 14 15 16

Graduate School
17 18 19 20 21 22

5. What is the highest level of schooling completed by your mother? (circle one)
Grade School
1 2 3 4 56 7 8

High School
9 10 11 12

College
13 14 15 16

Graduate School
17 18 19 20 21 22

6. What was your family’s total annual income while you were in high school? (Please
circle one)
1. Under $10,000

6. $50,000 to $59,999

2. $10,000 to $19,999

7. $60,000 to $69,999

3. $20,000 to $29,999

8. $70,000 to $79,999

4. $30,000 to $39,999

9. $80,000 to $89,999

5. $40,000 to $49,999

10. $90,000 and above

7. What is YOUR current total monthly income (from working, if you are employed)?
(Please circle one)
1. Under $100

5. $700 to $899

2. $100 to $299

6. $900 to $1,199

3. $300 to $499

7. $1,200 to $1,499

4. $500 to $699

8. $1,500 or more

8. Are you a full time student?
Yes

No

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9. Have you ever received an academic honor, award, scholarship because of
outstanding G.P.A and/or test scores?
Yes

No

10. What kind of place best describes where you currently live?

______________________________

For my research study, I would like to follow up with a face-to-face interview for a small
number of you. If you would be willing, please put your contact info here:
Name_______________________________
Phone______________________________Email______________________________

Thank you for taking the time to complete this survey. We appreciate your input!

82

REFERENCES

83

REFERENCES
Aguirre, Adalberto & Turner, Jonathan. 2007. ―American Ethnicity: The Dynamics and
Consequences of Discrimination.‖ New York, New York. McGraw-Hill Companies.
Allen, Judy & Jover, Margaret. 1997. ―Credit Card Behavior of University Students: Ethnic
Differences. Consumer Interest Annual. Pg. 162-170.
American Psychological Association. (2009). Publication Manual of the American Psychological
Association. Washington, DC: American Psychological Association.
Asinof, Lynn & Chaker, Marie. 2002. ―College Planning: Families Scramble to Pay Tuition;
Colleges Begin Offering New Aid. The Wall Street Journal, July 18.
Avery, R.B., Bostic, R.W., Calem, P.S. & Canner, G.B., 2003. ―An overview of consumer data
and credit reporting‖. Federal Reserve Bulletin 89, pp. 47–73.
Baum, S. & O‘Malley, M. 2003. College on Credit: How borrowers perceive their Education
Debt. Retrieved December 17, 2004, from http://www.nelliemae.com/library/
nasls_2002.pdf
Baumeister, Roy. 2002. ―Yielding to Temptation: Self Control Failure, Impulsive Purchasing and
Consumer Behavior.‖ The Journal of Consumer Research. Pgs. 670-676.
Bianco, Candy & Bosco Susan. Ethical Issues in Credit Card Solicitation of College StudentsThe Responsibility of Credit Card Issuers, Higher Education and Students.
Bonilla-Silva, Eduardo. 2006. ―Racism without Racist.‖ Lanham, Maryland. Rowman &
Littlefield Publishers, Inc.
Broman, Clifford. 2001. ―Work Stress in the Family Life of African Americans.‖ Journal of
Black Studies. Pg. 835-846.
Broman, Clifford, Hamilton, Lee, & Hoffman, William. 2001. ―Stress and Distress Among the
Unemployed: Hard Times and Vulnerable People.‖ New York, New York. Kluwer
Academic/Plenum Publishers
Conley, Dalton. 1999. ― Being Black, Living in the Red: Race, Wealth, and Social Policy in
th
America, 10 Edition.‖ Berkley California. University of California Press.
Clark & Oswald. 1994. ―Unhappiness and Unemployment‖. Economic Journal. Pg. 648–659.
Davies, Emma & Lea, Stephen. 1995. "Student Attitudes to Student Debt. Journal of Economic
Psychology. pg. 663-679.

84

Drentea, Patricia & Lavrakas, Paul. 2000. ―Over the Limit: The Association Among Health,
Race and Debt.‖ Social Science & Medicine. Pages 517-529.
Feinstein, J.S., 1993. ―The Relationship Between Socio-economic Status and Health: A Review
of the Literature‖. Milbank Memorial Fund Quarterly pp. 279–322.
Grable, John, & Joo, So-Hyun. 2006. ―Student Racial Differences in Credit Card Debt, Financial
Behaviors, and Stress.‖ College Student Journal. pg. 400-408.
Hayhoe, Celia, & Turner Pamela. 1999. ―Discriminating the Number of Credit Cards held By
College Students using Credit and Money Attitudes. Journal of Economic Psychology.
pg. 643-656.
Hayhoe, Celia, Leach, Lauren, Turner, Pamela, Bruin, Mary, & Lawrence, Frances. 2000.
―Differences in Spending Habits and Credit Use of College Students.‖ The Journal of
Consumer Affairs. Pg. 113-133.
Hayhoe, Celia. 2002. ―Comparison of Affective Credit Attitude Scores and Credit Use of
College Students at Two Points in Time. Journal of Family and Consumer Sciences. Pg.
71-77.
Hayhoe, Celia, Leach, Lauren, Allen, Myria, & Edwards Renee. 2005.―Credit Cards held by
College Students.‖ Financial Counseling and Planning. Pg. 1-5.
Hoffman, Michael, McKenzie, Karen, & Paris, Susan. 2008. ―Paper or Plastic.‖ The CPA
Journal. Pg. 16-20.
Hunt, R.M., 2008. ―The development and regulation of consumer credit reporting in America‖.
Federal Reserve Bank of Philadelphia, Working Paper 02-21.
Inglehart, Ronald & Baker, Wayne. 2000. ―Modernization, Cultural Change, and Persistence of
Traditional Values.‖ American Sociological Review. Pg. 19-51.
Jekot, Wayne. 2005. ―Over the Limit: The Case for Increased Regulation of Credit Cards for
College Students.‖ Connecticut Public Interest Law Journal.
Joo, Sohyun & Grable, John. ―The Academic Impact of Financial Stress on College Students.
2008. Journal of College Student Retention‖. Pg. 287-305.
Kessler, A. 1998. ―College Students: A Market Worth Pursuing.‖ Bank Marketing Journal. Pg.
14-17.
Kidwell, B. & Turrisi, R. 2000. A cognitive analysis of credit acquisition and college student
financial development. Journal of College Student Development, 41, 589-598.

85

Kim, Jinhee, Sorhaindo, Benoit, & Garman, Thomas. 2006. ―Relationship between Financial
Stress and Workplace Absenteeism of Credit Counseling Clients.‖ Journal of Family
Economic Issues. Pg. 216-225.
Lareau, Annette, & Conley, Dalton. ―Social Class: How does it work?‖ 2008. New York, New
York. Russell Sage Foundation Publications.
Leach, Karen & Hayhoe, Celia. 1998. ―Exploring College Students‘ Awareness of and Use of
Credit‖. The Journal of Consumer Education. Pg. 7–12
Lyons, Angela. 2008. ― Risky Credit Card Behavior of College Students.‖ Handbook of
Consumer Finance Research. Book Chapter pg. 185-207.
Lyons, Angela. 2003. Credit practices and financial education needs of Midwest College
Students. A report to Midwest College Administrators, University of Illinois at UrbanaChampaign, 62 pp., 2003.
Lyons, A., Scherpf, K., & Neelakantan, U. 2006. ―Intergenerational Transfer of Financial
Behaviors From Parents to Children.‖ (Working Paper). Indianapolis, IN: Networks
Financial Institute, Indiana State University.
Lynch, J.W., Kaplan, G.A., Salonen, J.T. 1997. ―Why do Poor People Behave Poorly? Variation
in Adult Health Behaviors and Psychological Characteristics by the Stages of the
Socioeconomic Life Course.‖ Social Science and Medicine. Pg. 809-819.
Manning, Robert. 2000. ―Credit Card Nation‖, Basic Books, New York , p.169 citing a study
conducted by marketing research firm Claritas, Inc.
Manning, Robert. 2000. ―Credit Card Nation: The Consequences of America‘s Addiction to
Credit.‖ Basic Books, New York.
Manning, Robert. 1999. ―The Social Consequences of Student Debt.‖ Consumer Federation of
America, Washington, D.C.
Mattson, L., Sahlhoff, K., Blackstone, J., Peden, B., & Nahm, A.Y. 2004. ―Variables Influencing
Credit Card Balances of Students at a Midwestern University. Journal of Student
Financial Aid. Pg. 7-18.
McGuigan, F.J. 1999. ―Encyclopedia of Stress.‖ Boston: Allyn & Bacon.
Miech, Richard, Moffitt, Bradley, Wright, Entner, Silva, Phil. 1999. ―Low Socioeconomic Status
and Mental Disorders: A Longitudinal Study of Selection Versus Causation During
Young Adulthood.‖ American Journal of Sociology. Pg. 1096-1131.

86

Mirowsky, John & Ross, Catherine. 1999.‖Economic Hardship Across the Life Course.‖
American Sociological Review. pg.548-569. Roberts, James & Jones, Eli. 2001. ―Money
Attitudes, Credit Card Use, and Compulsive Buying among American College Students.‖
Journal of Consumer Affairs.
Mowen, John & Spears, Nancy. 1999. ―Understanding Compulsive Buying Among College
Students: A Hierarchical Approach‖. Journal of Consumer Psychology. Pg. 407-430.
Munro, J., & Hirt, J. 1998. ―Credit Cards and College Students: Who Pays, Who Benefits?‖
Journal of College Student Development. Pg. 55-65.
Murphy, Angela. 2005. ―Money, Money, Money: An Exploratory Study on the Financial
Literacy of Black College Students.‖ College Student Journal. pg. 478.
Nellie Mae. 2002. Undergraduate students and credit cards: An analysis of usage rates and
trends. Retrieved from http://www.nelliemae.com/library/ccstudy_2001.pdf
Norvilitis, J.M., & Wilson, P.B. 2003. ―Factors Influencing Levels of Credit Card Debt in
College Students.‖ Journal of Applied Social Psychology. Pg. 935-947.
Norvilitis, J.M., Merwin, M.M., Osberg, T.M., Roehling, P.V., Young, P., & Kams, M.M. 2006.
―Personality Factors, Money Attitudes, Financial Knowledge, and Credit Card Debt in
College Students.‖ Journal of Applied Social Psychology. Pg. 1395-1413.
Pinto, Mary, Parente, Diane, & Palmer, Todd. 2002. ―College Student‘s Credit Card Debt and
the Role of Parental Involvement: Implications for Public Policy.‖ Journal of Policy and
Marketing. Pg. 105-113.
Roberts, James, & Jones, Eli. 2001. ―Money Attitudes, Credit Card Use, and Compulsive Buying
Among American College Students.‖ The Journal of Consumer Affairs, Pg. 213-240.
Royce, Edward. 2008. ― Poverty and Power: A Structural Perspective on American Inequality.‖
Lanham, Maryland. Rowman & Littlefield Publishers, Inc.
Sechrist, G.B., & Stangor, C. 2001. ―Perceived Consensus Influences Intergroup Behavior and
Stereotype Accessibility. Journal of Personality and Social Psychology. Pg. 645-654.
SPSS. 2001. SPSS for Windows. Rel. 11.0.1 Chicago: SPSS Inc.
Souccar, Kreinin. 1999. ―Card Marketers Initiating a Soft Sell on Campus‖. American Banker.
Pg. 170.
Souccar, Kreinin . 1998, ‗The New 3 R‘s on College Campuses: Reading, Riting, and Revolving
Debt‘.‖ American Banker. Pg.171.

87

Sullivan, T.A., Warren, E., & Westbrook, J.L. 2000. ―The Fragile Middle Class: Americans in
Debt.‖ New Haven, CT: Yale University Press.
Wang, Jeff, & Xiao, Jing. 2008. ―Buying Behavior, Social Support, and Credit Card
Indebtedness of College Students.‖ International Journal of Consumer Studies. pg. 2-10.
Warwick, Jacquelyn, & Mansfield. 2000. ―Credit Card Consumers: College Student‘s Attitude
and Knowledge.‖ Journal of Consumer Marketing. pg. 617-626.
Wells, Cassandra. 2007. ―Optimism, Intertemporal Choice, And College Student Debt.‖ Journal
of Personal Finance. Pg. 44-66.
Yang, B. & Lester, D. 2001. Predicting the number of credit cards held by college students.
Psychological Reports. Pg. 667-668.
Zhou, Li & Hung-Jen Su. 2000. ―Predicting College Student Debt: An Exploratory Study on
Sociodemographic Economic, Attitudinal, and Behavioral Determinants. Proceedings of
the Association for Financial Counseling and Planning Education, 133-140.

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