Identification With MDD

Running head: SELF-IDENTIFICATION WITH MAJOR DEPRESSIVE DISORDER IN
UNDERGRADUATE COLLEGE STUDENTS: A STUDY ON THE EFFECTS OF SELF-
DIAGNOSIS AND THE INTEGRATION OF PRIMARY CARE AND MENTAL HEALTH
Self-Identification with Major Depressive Disorder in Undergraduate College Students: A Study
on the effects of Self-Diagnosis and the Integration of Primary Care and Mental Health
Brynn J. Lipira
Stetson University

SELF-IDENTIFICATION WITH MDD 2
Abstract
The aim of this study is to form a better understanding about the way individuals relate to Major
Depressive Disorder (MDD) from a perspective of self-diagnosis. This study presented
participants with a form containing a list of diagnostic criteria for MDD taken from the DSM-5,
an emotionality scale (NEO-PI-R), extraversion scale (NEO-PI-R), vulnerability scale (NEO-PI-
R), depression scales (NEO-PI-R and CES-D), questions about self-identification with MDD,
and questions about the use of internet for information-seeking behaviors. There were three
forms: one contained an account of a patient who has been clinically diagnosed with MDD, the
second contained an account of a patient who displayed some depression symptoms but had been
clinically proven not to have MDD, and a control without a patient account. The findings of this
study support the hypothesis that individuals who are exposed to a list of diagnostic criteria and
an account of a clinically diagnosed patient were more likely to claim the probability of
themselves having MDD than individuals who were exposed to a list of diagnostic criteria and an
account of a patient with some depression symptoms who had not been diagnosed with MDD, or
a control in which no supplemental information regarding MDD was given.

Self-Identification with Major Depressive Disorder in Undergraduate College Students: A Study
on the effects of Self-Diagnosis and the Integration of Primary Care and Mental Health
According to the U.S. census (2011) 89.9% of Americans who have attained a
bachelor’s degree or higher level of education have Internet access in their home. The use of
Internet by all Americans is on the rise as home Internet access has more than doubled in the past
fourteen years. Google Trends (2013) reports the search query “symptoms” as the most
frequently searched term in the United States in the category of health. Searches for doctors are
included in the health category but aren’t on the list of the most popular search queries—
depression is. Depression is the ninth most commonly searched term in the health category on
Google. The number of searches preformed on “Major Depression” is at an all-time high, with
“Major Depression Symptoms” in a breakout phase which means that the search term has
experienced a change in growth greater than 5000%.
These facts indicate that Americans are using the Internet more frequently than ever in
relation to their concern for mental health and diagnosis. A recent study demonstrated one of the
many ways young Americans are using the Internet in relation to mental health, specifically
Depression. In the study performed by Moreno et al. (2012) several Facebook profiles were
monitored for indicators of depression. It was found that 33% of participants displayed
depression symptoms on Facebook, a commonly used social networking site. These findings are
in accordance with a previous study which found that 33% of college students reported
symptoms of depression (Wells, Klerman, & Deykin, 1987).
Depression is known to be prevalent in young populations with 30% of college students
reporting feeling so depressed in the last 12 months that it was difficult for them to function

(American College Health Association, 2009). The rate at which college students are being
diagnosed with depression is also on the rise. The number of college students diagnosed with
depression grew 56% from 2006-2012. Major Depressive Disorder (MDD) has a yearly
incidence of almost 8% in this age group (Hunt & Eisenberg, 2010). An astounding 22% of
adolescents and young adults also suffer from depressive symptoms at the sub-diagnostic level—
these individuals suffer from many of the symptoms of MDD, but don’t have a severe enough
case to be diagnosed. Although so many individuals, particularly of this age group, are affected
by depression only about 10% of college students report seeking any type of mental health care
in the past year (Rosenthal & Wilson, 2008).
The idea that so few people affected by depression are seeking help should be alarming.
The mentality that finding adequate help is not necessary, however, is reinforced by society.
Results from a study conducted in 2003 suggest that 9% of all adults will experience MDD in
any given year and approximately 16% of American adults will experience MDD in their
lifetime (Kessler, et al., 2003). Less than one third of Americans currently taking antidepressants
have seen a mental health professional in the last year (Pratt, Brody, & GU, 2011). There is a
certain stigma attached to having a mental illness which could have an effect on diagnosis and
help-seeking behaviors. Patients often wish to be treated outside the realm of personality
disorders because these diagnoses often have fewer stigmas associated with them than ‘severe’
mental illness (Kernberg & Yeomans, 2013). This calls into question the understanding of the
general public about mental illness.
Mental illness is a very complex topic. The exact cause of mental disorders is largely
unknown to the psychological community although several theories have been developed in an
attempt to explain what mental disorders are and why they occur (Uher, 2013). Some of the most

current theories include the exploration of genealogy. The relatively vague understanding of the
cause of mental illness makes accurate diagnosis and treatment all the more difficult.
The Diagnostic and Statistical Manual of Mental Disorders (DSM) is one of the most
commonly used guides for diagnosis (Clegg, 2012). The DSM is published by the American
Psychiatric Association (APA) and has been in existence since 1952. The DSM is a product of
almost one hundred years of transformations beginning in 1918 when the first standardized
classification manual, Statistical Manual for the Use of Institutions for the Insane, was published
(National Committee for Mental Hygiene, 1918). This manual persisted as the primary method
of diagnosis until 1946 when Medical 203 was published (Office of the Surgeon General, Army
Service Forces, 2000).
The DSM as we know it did not develop until 1952 and was used alongside other
manuals such as Medical 203 until further development and publication of the DSM-II
(American Psychiatric Association, 1968). From that point forward the DSM has been revised
and rewritten five times to reflect more modern and perhaps more accurate interpretations of
symptomology in relation to clinical diagnosis (Clegg, 2012). The most current issue of the
DSM, the DSM-5 (American Psychiatric Association, 2013), is in accordance with the most
recent theories and findings about psychiatric disorders.
The complexity and difficulty of diagnosis is highlighted in the DSM. There are sections
following each possible diagnosis pertaining to similar diagnoses which should be considered
and ruled out before any official diagnoses are made. Many mental illnesses, depression in
particular, have a high level of comorbidity (the circumstance in which two or more disorders
exist in an individual simultaneously) which contributes to the overall complexity of diagnosis
(Widdowson, 2011). In a previous study that examined the diagnostic complexities of

depression, 46.3% of participants who had MDD had comorbidity with personality disorders or
mental retardation (Morrison, Bradley, & Westen, 2003). The study also identified that 76.9% of
participants had comorbidity with characterological issues which are mental illnesses outside the
realm of personality disorders or mental retardation.
Diagnosis is a crucial aspect of the mental health profession for numerous reasons
(Dennis & Lederman, 2013). Namely, diagnosis aids in patient education, provides a common
understanding of a condition, aids in treatment planning and medical management, is
fundamental to record keeping, and is necessary for reimbursement by insurance companies.
Achieving optimal mental health is the goal of the mental health profession. Many treatment
plans are contingent upon diagnoses which may take several visits with the most qualified
professional to obtain. While some disorders, or disorders of certain severity, are well-served
utilizing only traditional therapeutic methods, more severe degrees of mental illness are more
readily helped in combination with medication.
Only two professions are qualified to prescribe medications for the mentally ill—medical
doctors such as primary care physicians, and psychiatrists. This fact conflicts with the notion that
mental health professionals are the most qualified individuals to accurately identify and diagnose
mental illness. Psychiatrists are by all means qualified to aid the mentally ill but the
qualifications of primary care physicians should be called into question.
Psychiatrists are required to complete coursework in psychology, biology, chemistry, and
pharmaceutical study as well as completing residencies in order to obtain licensure. Primary care
physicians are not as well versed in the field of psychology and tend to have relatively little
understanding about mental illness. These types of doctors typically have years of training and
experience regarding physical ailments such as the flu, and minor aches and pains. In the

integration of primary care and mental health, there tends to be a gap of communication between
mental health professionals and primary care physicians (Fischer, Heinrich, Davis, Peek, &
Lucas, 1997).
The problematic nature of primary care physicians prescribing medications for the
mentally ill is intensified by current insurance debacles. Many insurance providers do not cover
mental health visits, therapy or testing so the financial burden of obtaining treatment by the
proper professional often rests fully on the shoulders of the patient (Uebelacker, Smith, Lewis,
Sasaki, & Miller, 2009). It is important to understand that visits to primary care physicians are
covered by most insurance companies and those without insurance can often visit primary care
physicians at a reduced rate under provisions of hospitals or other large medical networks.
Commonly covered primary care visits may include concerns of mental health as there are often
physical symptoms of mental illness.
Even if an insurance provider does not cover mental health visits by a primary care
physician, most visits are covered such as annual wellness visits. As previously mentioned,
physical symptoms of mental illness are common and can therefore lead to a visit to a primary
care physician for mental health concerns (Uebelacker, Smith, Lewis, Sasaki, & Miller, 2009). In
the circumstance that the appointment with a primary care physician is not the result of a
physical symptom of mental illness, mental health concerns may still be discussed and treated by
the primary care physician. In turn of either circumstance, issues of mental health are being
covered by insurance companies because the visit is not being coded as a mental health visit,
rather as a wellness visit (Fischer, Heinrich, Davis, Peek, & Lucas, 1997).
Given that less than one third of Americans currently taking antidepressants have been
seen by a mental health professional in the past year (Pratt, Brody, & GU, 2011), it must be

inferred that someone other than a mental health professional (psychiatrist) is maintaining
prescriptions for these patients. This should be a rather disconcerting realization and understood
as a major disservice to the mentally ill. Through such easy access to mental health medications,
many problems arise (deGruy, 1997). It implies that there is a ‘quick fix’ for such illnesses and
that long-term commitment to treatment is unnecessary. In fact, a large part of the reason many
patients prefer to be diagnosed with non-personality disorders is because acute treatment plans
are often based on pharmacological interventions rather than long-standing combinations of
pharmacology and therapy (Kernberg & Yeomans, 2013).
Mental illnesses such as MDD require long-standing therapy and monitoring of progress.
Morrison et al. (2003) identified the first noticeable signs of clinical change in depressed patients
in the twentieth therapy session, and did not identify relatively permanent change until the
fiftieth session. A study conducted by Kopta, Howard, Lowry, and Beutler (1994) identified that
104 sessions were necessary for 50% of a given population of depressed patients to overcome
characterological symptoms. The remaining 50% of the participants needed more than 104
sessions. These findings, as well as expert testimony, indicate that severe mental disorders
require a long-standing commitment to therapy.
By removing mental health professionals from the process of prescribing mental health
medication, there is also a significant chance of misdiagnosis and incorrectly medicating
patients. Medications used to treat mental illnesses can have life-threatening physical and mental
side-effects when not administered and monitored properly or carefully (Strejilevich, et al.,
2011). Even patients who are properly diagnosed and medicated can experience a significant
negative impact on emotional health, behavior, cognitive and physical functioning as side-effects
of such medications. Adverse reactions to mental health medications are common, especially in

the mentally ill who already have impaired cognitive functioning, and can cause additional
traumas which can be detrimental and irreversible. A common side-effect of antidepressant use
is increased risk of suicide.
Misdiagnosis is common in patients with bi-polar disorder, which includes depressive
symptoms, and is often diagnosed with MDD (American Psychiatric Association, 2013). This
often leads to inadequate or inappropriate treatment (Soloman, et al., 2006). Under-diagnosis of
depression occurs in 44.3% of patients coming into primary care (Gabarron, et al., 2002). The
effects of misdiagnosis and mis-medication effect the prognosis of many mental illnesses
including MDD. There are many sub-types of depression which may be diagnosable under MDD
but have very different ideal treatment plans and pharmacological recommendations (Kernberg
& Yeomans, 2013). Approximately 30% of patients with MDD develop chronic refractory
depression which is the persistent reoccurrence of depressive episodes over the course of many
years, and can further enhance the need for adequate care and accurate diagnosis (McGrath &
Miller, 2008).
The belief that mental illnesses are uncomplicated and can easily attain diagnosis should
be avoided at all costs. The model set forth by primary health care is influencing the general
public’s understanding of mental health. Primary care physicians often make official diagnoses
in as little as ten minutes (Kates & Craven, 1998). This is highly discouraged as diagnostic
questions around bipolar illness, major depressive episodes, Attention Deficit/Hyperactivity
Disorder, and severe personality disorders are extremely important for clinicians to make
appropriate treatment recommendations (Kernberg & Yeomans, 2013). If mental health
professionals are not present, such critical questions may not be asked and may not be assessed
accurately.

There has been a reciprocal effect between the commonality of MDD diagnosis, easily
available medication, and commercialism and advertising. A recent study measured the effects of
exposure to a Cymbalta (antidepressant) television commercial on how much information
participants learned, and self-reported likelihood of seeking an antidepressant medication
(Callaghan, Laraway, Snycerski, & McGee, 2013). It was found that participants who were
exposed to the commercial had a significantly greater level of drug knowledge than the control
group. Although the control group and the group exposed to the commercial showed no
significant difference in their desire to seek pharmacological treatment, drug-knowledge scores
and drug-seeking scores were negatively correlated. This indicates that the more information a
person knows about a disorder, the more likely they will be to seek pharmacological treatment. A
depression inventory was also completed by participants and those with higher depression scores
were more likely to report a desire to seek pharmacological aid.
Commercials and advertisements such as the one used in the 2013 study by Callaghan et
al. often instruct people to discuss pharmacological options with their doctor if they think they
may be suffering from a mental illness such as depression. This advice and information may also
lead one to perform additional Internet research on the disorder they are concerned about having.
This would explain the tremendous growth of the number of Google searches preformed on
“Major Depressive Symptoms”. Upon performing this Google search, many resources such as
WebMD and MayoClinic return results. These resources can often be ambiguous and non-
specific regarding the actual requirements of clinical diagnosis.
As of November 11th
, 2013 WebMD’s depression guide lists eleven primary symptoms of
depression (WebMD, 2013). The guide warns that depression can be severe and life-threatening
if not diagnosed and treated properly. The guide also gives two shocking statistics—that

approximately half of the people who experience symptoms never get diagnosed or treated for
their illnesses and that more than one out of every ten people battling depression commit suicide.
These statements are not cited and their credibility is unknown, but they seem very serious. The
website explicitly warns that medical help should be sought out if any of the listed symptoms are
keeping a person from leading a normal, active life. The list of symptoms are not discriminatory,
do not warn about the possibility of the symptoms being attributed to a disorder outside of the
one listed on the guide, and the symptoms do not line up with the symptoms found in the DSM.
As similar information appears not only in television commercials for drugs , but also on
Internet resources, the number of people exposed to such ambiguous information regarding
mental illness is steadily increasing. Current statistics and health care circumstances indicate that
people are more frequently receiving pharmacological depression treatment from primary care
physicians than from mental health professionals (deGruy, 1997). All of these factors call into
question whether or not diagnosis can be influenced in the patients mind—can we influence how
likely people are to self-diagnose based on the information they are being given? The idea of
self-diagnosis has been long thought of in regard to medical students and the phenomenon has
been given the name “Medical Student Syndrome.”
For purely hypothetical purposes, say a person saw a drug commercial for an
antidepressant and could relate to some of the symptoms mentioned. This person then looks up
information online and realizes that they can relate to quite a few of these symptoms, which are
rather ambiguous in nature, and end up questioning whether or not they have the disorder. After
a few days of dwelling on the idea, the person becomes convinced they have said disorder. At
this point, the person decides to make an appointment with their primary care physician to
discuss pharmacological options, or brings the topic to discussion in their existing appointment.

They claim that they have been doing some research on depression and are fairly certain they are
suffering from the disorder and desire the relief described in the commercial they saw. The
doctor will likely conduct a brief questionnaire about depression and elicit a diagnosis, as
previously cited in ten minutes or less, and prescribe a medication.
The outcome of this highly probable hypothetical situation was completely based on
commercial influence and self-diagnosis. It is hypothesized that individuals who are exposed to a
list of diagnostic criteria and an account of a clinically diagnosed patient will be more likely to
claim the probability of themselves having MDD than individuals who are exposed to a list of
diagnostic criteria and an account of a patient with some depression symptoms who has not been
diagnosed with MDD, or a control in which no supplemental information regarding MDD is
given.
Method
Participants
Nineteen undergraduate males and 36 undergraduate females of various majors from
Stetson University participated in the study. Participants ranged in age from eighteen to twenty
three years old.
Materials and Procedure
A list of diagnostic criteria for MDD was taken from the DSM-5 (American Psychiatric
Association, 2013). Emotionality, extraversion, vulnerability, and depression scales were taken
from the NEO-PI-R (Costa & McCrae, 1992). Scale questions were randomized in order to
prevent participants from responding to similar questions consecutively. Participants were asked
to rate each scale item using a five point Likert scale where one represented “Never like me”,
two represented “Almost never like me”, three represented “Sometimes like me”, four

represented “Almost always like me”, and five represented “Always like me”. Negatively keyed
items were translated and the totals of individual tests were calculated by adding item scores.
The CESD Short Scale was also used (Andresen, Malmgren, Carter, & Patrick, 1994).
Subjects responded to the CESD by rating each given item in terms of the frequency that each
mood or symptom had occurred during the past week on a four point scale, ranging from zero
(“none of the time”) to three (“most of the time”). A score was assigned by translating negatively
keyed items and totaling all item scores.
Questions about the use of internet for information-seeking behaviors were developed
(Appendix A). Some questions about information-seeking behaviors were multiple choice and
others were statements rated using a five point Likert scale where one represented “definitely
would not”, two represented “probably would not”, three represented “maybe”, four represented
“probably would”, and five represented “definitely would”.
Questions about self-identification with MDD were also developed (Appendix B,
Appendix C). Items were rated using a five point Likert scale where one represented “Not at all
likely”, two represented “Not very likely”, three represented “Somewhat likely”, four
represented “likely”, and five represented “very likely”.
Additionally, two variations of a one-paragraph description of a patient were created. The
first was a synopsis of a patient who had been clinically diagnosed with MDD (Appendix D) and
the second was a synopsis of a patient suffering from some symptoms of depression, but not
suffering from MDD (Appendix E). Participants were also asked to identify their age group by
circling a set of numbers that best described their current age (18-20, 21-23, 24-26, 27-29, 30+)
and their gender by circling male or female.

Participants registered via public bulletin located in an academic hall on campus.
Participants received one of three forms at random: the control, the diagnosed condition, or the
undiagnosed condition. Participants receiving the diagnosed and undiagnosed conditions were
first asked to read a full list of diagnostic criteria for Major Depressive Disorder taken from the
DSM-5 (American Psychiatric Association, 2013). Participants were not informed of the source
of the diagnostic criteria. Upon completion of reading the excerpt participants were given the
questionnaire portion of the survey.
Participants receiving the diagnosed form received a synopsis of a patient who had been
clinically diagnosed with MDD (Appendix D), and questions about self-identification with MDD
(Appendix B). Participants receiving the undiagnosed form received a synopsis of a patient
suffering from some symptoms of depression, but not suffering from MDD (Appendix E), and
questions about self-identification with MDD (Appendix B). Participants receiving the control
form received questions about self-identification with MDD (Appendix C) and no client
synopsis.
All participants were presented with a questionnaire containing the following: an
emotionality scale (Costa & McCrae, 1992), extraversion scale (Costa & McCrae, 1992),
vulnerability scale (Costa & McCrae, 1992), depression scales (Costa & McCrae, 1992)
(Andresen, Malmgren, Carter, & Patrick, 1994), and questions about the use of internet for
information-seeking behaviors (Appendix F).
Once participants completed answering all questions, they handed in their surveys, were
debriefed, and released. Debriefing was consistent among all participants and included
reassuring participants that no information about their identity could be known from any
information provided on the survey and that no information regarding their identity had been

retained from the sign-up period of the study. Participants were also informed that none of the
information gathered in the study was sufficient for diagnosis. The participants were told which
personality traits were being measured (depression, vulnerability, emotionality, and extraversion)
and they were informed of the source of all scales and questions on the survey. Finally,
participants were explained that there were three forms of the survey they had taken—a control
with no supplemental information regarding MDD, an undiagnosed form which contained a
symptom list of MDD taken from the DSM 5 and a synopsis of a client with depressive
symptoms that was not suffering from MDD, and a diagnosed form which contained a symptom
list of MDD taken from the DSM 5 and a synopsis of a client suffering from MDD. Participants
were welcomed to ask questions about the research.
Results
A univariate ANOVA found a significant Form Difference on ratings for the statement “I
think I am currently suffering from Major Depressive Disorder.” The Form Difference was
F(2,49)=3.007, p=0.059 and shows that there was a significant difference in the way participants
rated the statement dependent on which form of the survey they had been given. The mean score
for the suffering statement in the control group was m=1.111 (s=0.251). The mean score for the
suffering statement in the undiagnosed group (Appendix A) was m=1.250 (s=0.208). The mean
score for the suffering statement in the diagnosed group (Appendix B) was m=1.750 (s=0.166).
A univariate ANOVA also found a significant Gender Difference on ratings for the
statement “I think I am currently suffering from Major Depressive Disorder.” The Gender
Difference was F(1,49)=6.677, p=0.013 which means that males and females rated the suffering
statement differently dependent on their gender. The mean rating for males was m=1.056

(s=0.205). The mean rating for females was m=1.685 (s=0.132). There was no interaction
between gender and form on the suffering statement.
The CESD had a maximum score of 30 and the average score on the CESD was m=10.8
(s=0.899) indicating that participants generally had not experienced a large number of
depression symptoms in the past week. It was also found that 58.2% of participants either agreed
or strongly agreed with the statement “I fully understand Major Depressive Disorder”.
Discussion
The findings of this study support the hypothesis that individuals who were exposed to an
account of a clinically diagnosed patient were more likely to claim the probability of themselves
having MDD than individuals who were exposed to an account of a patient with some depression
symptoms that had not been diagnosed with MDD, or a control in which no supplemental
information regarding MDD was given. Participants who were exposed to the synopsis of a
patient suffering from MDD were more likely to self-diagnose by thinking they were currently
suffering from MDD. Participants in the control group received no information pertaining to
MDD and were the least likely of the three groups to self-diagnose. This indicates that there is a
positive relationship between the amount of information a person has about MDD and the
likelihood to self-diagnose—as more information is present, the likelihood to self-diagnose
increases.
The increase in the level of self-diagnosis from the undiagnosed group to the diagnosed
group indicates that the type of information people have access to affects their tendency to self-
diagnose. The only difference between the two variable groups was whether the patient they
were presented with had been diagnosed with MDD or not. Participants who read about a patient
suffering from some symptoms of depression, but not MDD, were less likely to self-diagnose

than participants who read about a patient suffering from MDD. A possible explanation for this
is that reading about a patient who has been diagnosed with MDD increases the likelihood that
someone will diagnose themselves with MDD.
The aim of this study was to form a better understanding about the ways in which
individuals relate to MDD from a perspective of self-diagnosis. It is now understood that the
amount and type of information someone has influences and increases the likelihood that they
will self-diagnose. This plays a tremendous role in the marketing aspect of mental health.
Advertisements for pharmaceuticals often portray an individual suffering from an illness, or list
symptoms of disorders. Exposure to that information is likely to influence the audience in a way
that encourages self-diagnosis. The act of self-diagnosis may have a reciprocal effect on
utilization of medication in which an individual self-diagnoses and seeks medical attention or
purchases medication. Further research regarding the relationship between self-diagnosis and
pharmacology is needed in order to reach an accurate conclusion.
It is also important to understand how much people think they know about a disorder. An
astounding 58.2% of participants agreed that they fully understood Major Depressive Disorder.
In actuality, no one fully understands MDD. The exact nature and cause of mental illness is
largely unknown and is currently being investigated (Uher, 2013). The fact that so many
participants believed they fully understood MDD suggests that people generally have a false
sense of knowledge. Future studies should further investigate the relationship between perceived
understanding of disorders and self-diagnosis.
The implications of self-diagnosis are vast and should be considered seriously. One of the
largest implications of self-diagnosis is misdiagnosis as it may lead to improper treatment and
other consequences. Treatment of mental disorders is often an extensive process requiring years,

if not a lifetime, of commitment to treatment and the desire to become well (Widdowson, 2011).
Without proper treatment, the mental health of an individual may continue to deteriorate and
potentially prevent them from fully recovering.
The high rate of comorbidity in disorders such as MDD complicates diagnosis for
clinicians who are trained in diagnosing and treating mental disorders let alone the general
population (Morrison, Bradley, & Westen, 2003). Mental disorders often occur simultaneously
(comorbidity) or can be masked by one another. Some disorders, such as delusional disorders, do
not present symptoms in a manner that the person experiencing them can properly identify
(Kernberg & Yeomans, 2013). Confusion and lack of knowledge about which symptoms are
actually present would likely decrease the accuracy of self-diagnosis.
It is often the case that a physical problem causes symptoms similar to or the same as
those of a mental illness. Something such as hormone imbalance can significantly impact general
mood, anxiety levels and the ability to lead a normal life. If a person has more or less symptoms
than what they’re reading about, that may influence their self-diagnosis regardless of whether or
not the quantity of symptoms relates to the true problem. Misdiagnosis by self-diagnosis can also
lead people to believe that they have a disorder far more severe than the disorder they actually
have, or don’t have. The worry of having a severe disorder can create a more intense reaction in
the individual being ‘diagnosed’ such as increased or worsened anxiety or depression.
The findings of this study have also indicated that not everyone is equally as likely to
self-diagnose. Women were significantly more likely to self-diagnose MDD than men. This tells
us that women are also more likely to face the challenges of self-diagnosis such as misdiagnosis
and mistreatment. Future studies should explore the ways in which self-diagnosis and
misdiagnosis effect women in particular. It can be hypothesized that women and men face the

same consequences of self-diagnosis and misdiagnosis; however they may face these
consequences at different rates.
Future research should focus on the reasons why people self-diagnose. The implications
of self-diagnosis are such that mental health professions may be at risk. Understanding why self-
diagnosis occurs could enable us to prevent or better the practice of self-diagnosis as a whole. It
is possible that people are ‘forced’ to self-diagnose because they cannot afford healthcare or
medication. Conducting research regarding income level and availability of affordable and
adequate mental health care may provide additional insight to this theory. Another angle to
explore would be whether individuals who are self-diagnosing mental disorders are also seeking
the care of mental health professionals or not. Understanding if individuals are seeking
professional care following self-diagnosis may ease the perceived impacts of self-diagnosis.
Alternative disorders should also be investigated in future research. This study was
strictly relevant to MDD and it must be acknowledged that the general principle of self-diagnosis
may vary among different disorders. Understanding which disorders and illnesses have the
highest rates of self-diagnosis could assist us in stopping self-diagnosis, or providing better
resources for people to consult. Understanding which disorders are affected by self-diagnosis
could also alter marketing strategies used by pharmaceutical companies, insurance companies
and healthcare providers.

References
American College Health Association. (2009). National College Health Assessment II:
Reference Group Data Report Fall 2008. Baltimore: American College Health
Association.
American Psychiatric Association. (1968). Diagnostic and Statistical Manual of Mental
Disorders (2nd ed.). Washington: Author.
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental
Disorders. Washington: Author.
Andresen, E., Malmgren, J., Carter, W., & Patrick, D. (1994). Center for Epidemiological
Studies Short Depression Scale. Retrieved from PsycTESTS, doi: 10.1037/t10141-000.
Callaghan, G., Laraway, S., Snycerski, S., & McGee, S. (2013). Antidepressant Advertising
Effects on Drug Knowledge and Drug Seeking. Journal of Consumer Marketing, 267-
272.
Clegg, J. (2012). Teaching about Mental Health and Illness Through the History of the DSM.
History of Psychology, 364-370.
Costa, P., & McCrae, R. (1992). Revised NEO Personality Inventory (NEO-PI-R).
Psychological Assessment Resources.
deGruy, F. (1997). Mental Healthcare in the Primary Care Setting: A Paradigm Problem.
Families, Systems, & Health, 3-26.
Dennis, J., & Lederman, R. (2013, January 24). ADHS: Division of Behavioral Health Services:
Enhanced Assessment Training for Behavioral Health Technicians. Retrieved from

Arizona Department of Health Services:
http://www.azdhs.gov/bhs/tr_resources/ea/pdf/rd.pdf
Fischer, L., Heinrich, R., Davis, T., Peek, C., & Lucas, S. (1997). Mental Health and Primary
Care in an HMO. Families, Systems, & Health, 379-391.
Gabarron, H., Vidal, R., Haro, A., Boix, S., Jover, B., & Arenas, P. (2002). Prevalencia y
deteccion de desordenes depresivos en atencion primaria (Prevelance and detection of
depressive disorders in primary care). Atencion Primaria, 329-336.
Google. (2013, December 6). Google Trends. Retrieved from Google:
http://www.google.com/trends
Hunt, J., & Eisenberg, D. (2010). Mental Health Problems and Help-Seeking Behavior Among
College Students. Journal of Adolescent Health, 3-10.
Kates, N., & Craven, M. (1998). Managing Mental Health Problems: A Practical Guide for
Primary Care. Seattle: Hogrefe & Huber.
Kernberg, O., & Yeomans, F. (2013). Borderling Personality Disorder, Bipolar Disorder,
Depression, Attention Deficit/Hyperactivity Disorder, and Narcissistic Personality
Disorder: Practical Differential Diagnosis. Bulliten of the Menninger Clinic, 1-22.
Kessler, R., Berglund, P., Demler, O., Jin, R., D, K., Merikangas, K., & Wang, P. (2003). The
Epidemology of Major Depressive Disorder: Results from the National Comorbidity
Survey Replication (NCS-R). Journal of the American Medical Association, 3095-3105.
Kopta, S., Howard, K., Lowry, J., & Beutler, L. (1994). Patterns of Symptomatic Recovery in
Psychotherapy. Journal of Consulting and Clinical Psychology, 1009-1016.

McGrath, P., & Miller, J. (2008). Pharmacologic Management for Treatment-Resistant Unipolar
Depression. Psychiatry, 2372-2389.
Moreno, M., Christakis, D., Egan, K., Jelenchick, L., Cox, E., Young, H., . . . Becker, T. (2012).
A Pilot Evaluation of Associations Between Displayed Depression References on
Facebook and Self-Reported Depression Using a Clinical Scale. The Journal of
Behavioral Helath Services & Research, 295-304.
Morrison, K., Bradley, R., & Westen, D. (2003). The External Validity of Controlled Clinical
Trials of Psychotherapy for Depression and Anxiety: A Naturalistic Study. Psychology
and Psychotherapy: Theory, Research and Practice , 109-132.
National Committee for Mental Hygiene. (1918). Statistical Manual for the Use of Institutions
for the Insane. New York: Author.
Office of the Surgeon General, Army Service Forces. (2000). Medical 203 Nomenclature of
Psychiatric Disorders and Reactions. Journal of Clinical Psychology, 925-934.
Pratt, L., Brody, D., & GU, Q. (2011). Antidepressant use in persons aged 12 and over: United
States, 2005–2008. Hyattsville: National Center for Health Statistics.
Rosenthal, B., & Wilson, W. (2008). Mental Health Services: Use and Disparity Among Diverse
College Students. Journal of American College Health, 61-68.
Soloman, D., Leon, A., Maser, J., Truman, C., Coryell, W., Endicott, J., . . . Keller, M. (2006).
Distinguishing Bipolar Major Depression from Unipolar Major Depression With the
Screening Assessment of Depression-Polarity (SAD-P). Journal of Clinical Psychiatry,
434-442.

Strejilevich, S., Martino, D., Marengo, E., Igoa, A., Fassi, G., Whitham, E., & Ghaemi, S.
(2011). Long-Term Worsening of Bipolar Disorder Related with Frequency of
Antidepressant Exposure. Annals of Clinical Psychiatry, 186-192.
U.S. Census Bureau. (2013, May). Computer and Internet Use in the United States. Retrieved
from United States Census Bureau: http://www.census.gov/prod/2013pubs/p20-569.pdf
Uebelacker, L., Smith, M., Lewis, A., Sasaki, R., & Miller, I. (2009). Treatment of Depression in
a Low-Income Primary Care Setting with Colocated Mental Health Care. Families,
Systems & Health, 161-171.
Uher, R. (2013). The Changing Understanding of the Genetic and Environmental. The Canadian
Journal of Psychiatry, 67-68.
WebMD. (2013, November 18). Signs of Clinical Depression: Symptoms to Watch For.
Retrieved from WebMD: http://www.webmd.com/depression/guide/detecting-depression
Wells, V., Klerman, G., & Deykin, E. (1987). The Prevalence of Depressive Symptoms in
College Students. Social Psychiatry, 20-28.
Widdowson, M. (2011). Depression: A Literature Review on Diagnosis, Subtypes, Patterns of
Recovery, and Psychotherapeutic Models. Transactional Analysis Journal, 351-364.

Appendix A
Questions about Information-Seeking Behaviors
About how often do you use the internet to research information regarding your health (physical
or mental)?
a. Once per week or more
b. Twice per month
c. Once every couple of months
d. A few times per year
About what percentage of your internet research about health is regarding physical health?
a. 0-25%
b. 26-50%
c. 51-75%
d. 76-100%
About what percentage of your internet research about health is regarding mental health?
a. 0-25%
b. 26-50%
c. 51-75%
d. 76-100%
Please select websites you are familiar with:
- WebMD - HealthCentral
- MayoClinic - MedicineNet
- Yahoo Answers - PsychCentral
- Other
Please rate the following items where:
5 = You definitely would 4 = You probably would 3 = Uncertain
2 = You probably would not1 = You definitely would not
______ Would seek information on the internet if you felt more tired than normal.
______ Would seek information on the internet if you felt nauseous several days in a row.
______ Would seek information on the internet if you felt more irritable than normal.
______ Would seek information on the internet if you were experiencing back pain.
______ Would seek medical attention if you felt more tired than normal.
______ Would seek medical attention if you felt nauseous several days in a row.
______ Would seek medical attention if you felt more irritable than normal.
______ Would seek medical attention if you were experiencing back pain.
______ Would consult a Primary Care Physician or Family Doctor for physical health concerns.
______ Would consult a Primary Care Physician or Family Doctor for mental health concerns.
______ Would consult a Mental Health Professional for mental health concerns.
______ Wouldn’t consult any professional about a concern unless it interfered with daily life.

Appendix B
Questions Regarding Self-Identification with MDD for Diagnosed & Undiagnosed Conditions
I am at risk for major depressive disorder.
I think I am currently suffering from Major Depressive Disorder.
I am like the client given in the synopsis above.
Others around me think I have Major Depressive Disorder.
I fully understand Major Depressive Disorder.

Appendix C
Questions Regarding Self-Identification with MDD for Control
I am at risk for major depressive disorder.
I think I am currently suffering from Major Depressive Disorder.
Others around me think I have Major Depressive Disorder.
I fully understand Major Depressive Disorder.

Appendix D
Diagnosed Condition
Jack is a 23-year-old male who has been clinically diagnosed with Major Depressive Disorder.
He is in his final year of undergraduate study at Appletown College. Until recently, he was a
cheerful individual who always loved going to school and hanging out with friends. He used to
go running four or five times a week to keep up his figure and alleviate stress. The last two
months, Jack has been skipping class regularly because he is too tired to get out of bed in the
morning. He feels that his collegiate work will never pay off and that he will never amount to
anything. He is now failing half of his classes and is at risk of being put on academic probation
by the college. On days that Jack does get out of bed, he has little to no energy and finds that he
can’t concentrate on anything. He has not been spending much time with his friends and hasn’t
been answering their calls or texts. To top it all off, Jack has gained a significant amount of
weight in the last two months and has been much more hungry than he used to be.

Appendix E
Undiagnosed Condition
Jack is a 23-year-old male in his final year of undergraduate study at Appletown College. He is
generally a cheerful individual who enjoys going to school and hanging out with friends. He goes
running four or five times a week to keep up his figure and alleviate stress but has managed to
gain almost 10 pounds in the last couple of months. Jack has been missing class because he is
extremely tired and spends most of his day sleeping. He worries that he may not be successful
after he graduates and wonders if he will make it in the corporate world. Jack has been very
irritable lately, too. Jack is partying more frequently than he used to, consuming as many as eight
drinks per night at least two nights per week. He has also been more promiscuous lately, seeing
one or two partners in the same week with no intentions of long-term commitment. Jack has been
seeing a licensed psychologist and it has been confirmed that he is not suffering from Major
Depressive Disorder as he does not meet the necessary criteria.

Identification With MDD

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