A Review of Assistive Technology for College Students with Mood and Anxiety Disorders

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The purpose of this literature review is to highlight the recent articles and findings pertaining to the implementation of assistive technology in the school setting, while focusing specifically on
how this technology can be used as a beneficial tool for students diagnosed with mood and anxiety disorders.

Submitted: August 14, 2018

A A A | A A A

Submitted: August 14, 2018



A Review of Assistive Technology for

College Students with Mood and Anxiety Disorders



Anthony N. Parisi, B.S.



A Special Project

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Arts in Psychology

Department of Psychological Science



Central Connecticut State University

New Britain, Connecticut



July, 2018

Special Project Advisor:

Dr. Carolyn R. Fallahi

Department of Psychological Science



The purpose of this literature review is to highlight the recent articles and findings pertaining to the implementation of assistive technology in the school setting, while focusing specifically on how this technology can be used as a beneficial tool for students diagnosed with mood and anxiety disorders. The presence of assistive technology in the school setting has increased in frequency due to increased research and support demonstrating its overall effectiveness (Bisson, 2017). Many of the academic deficits experienced by individuals struggling with mood and anxiety disorders can be supported through the implementation of assistive technologies. There are countless types of assistive technology that are currently being implemented in schools and classrooms across the country, and we will focus on those technologies that have proven to be most beneficial for mood and anxiety disorders in higher education.










Keyword: Assistive Technology, Mood/Anxiety Disorders, College Students

A Review of Assistive Technology for

College Students with Mood and Anxiety Disorders

Section 1

The purpose of this literature review is to highlight the recent articles and findings pertaining to the implementation of assistive technology in the college setting, while focusing specifically on how this technology can be used as a beneficial tool for students diagnosed with mood and anxiety disorders. The presence of assistive technology in the school setting has increased in frequency due to increased research and support demonstrating its overall effectiveness (Bisson, 2017). There are countless types of assistive technology that are currently being implemented in schools and classrooms across the country, and we will focus on those technologies that have proven to be most beneficial.

In the academic setting, there are many different types of students; all of whom are looking to receive an education and improve the trajectory of their lives. Unfortunately, not every student begins with an equal opportunity at succeeding due to certain medical and cognitive disorders (Banerjee & Lamb, 2016). Anxiety and mood disorders are the most common psychiatric diagnoses on campus, and for that reason, most of the school’s resources for students with disabilities are focused on this population of students. Being diagnosed with these disorders while enrolled in college can have devastating effects on those students’ academic experiences and chances of succeeding. Over the past decade, universities and government officials have taken it upon themselves to figure out how to help these students accomplish their academic goals (Cornell University, 2015).

Assistive technology can make a difference in the academic achievement of students with disabilities (Okolo & Diedrich, 2014); however, it is not completely understood which forms of technology serve to be most beneficial for students specifically diagnosed with mood and anxiety disorders. This review will focus on the benefits of assistive technology in the academic setting, and identify some of the areas where the research is still needed (Pedrelli, Nyer, Yeung, Zulauf, & Wilens, 2014).


As defined by the Georgia Department of Education (2014), assistive technology is any item, piece of equipment or product system, whether acquired commercially, off- the-shelf, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of students with disabilities. Assistive technology has the goal of leveling the playing field for students diagnosed with a disability. Their diagnoses automatically put these students at an academic disadvantage, and the technology looks to improve those disadvantages. We will review all the relevant articles concerning assistive technology implementation for students diagnosed with mood and anxiety disorders.

Mood and anxiety disorders are the most common forms of diagnoses found in college students (Auerbach, Alonso, Axinn, Cuijpers, Ebert, Green, … Bruffaerts, 2016). We will focus on how these extremely prominent diagnoses effect the lives of the individuals experiencing these hardships, and how they help compensate for specific impairments in the academic world. It is estimated that approximately 20.3% of college students are diagnosed with mental health disorders. Of the proposed 20.3% of mental health disorder, anxiety disorders encompassed the largest cohort with 14.7% of the diagnoses, followed closely by mood disorders with 9.9% of the total (Auerbach et al., 2016).

Mood Disorders

Indeed, there are numerous forms of mood disorders, but for the sake of logistics we will only be focusing on three specific disorders: Major Depressive Disorder (MDD), Bipolar I/II Disorder, and Persistent Depressive Disorder (PDD or Dysthymia). We will be specifically looking to understand how individuals with each disorder benefit from the effects of assistive technology. Major Depressive Disorder along with Persistent Depressive Disorder, are two diagnoses that are very similar in definition as well as in regards to symptomology. These diagnoses are the two most common mood disorders found in the general population (Johns Hopkins Medical Health Library, 2018), and they are also two of the most common mental health disorders found in college students (Pedrelli, Nyer, Yeung, Zulauf, & Wilens, 2014).

Major Depressive Disorder has been known to cause significant distress for students. In a study of 115 students diagnosed with Major depressive Disorder, those with most consistent symptoms were found to be significantly impaired in their academic and social relationships (Puig-Antich, Lukens, Daves, 1985). The depressive symptoms associated with Major Depressive Disorder have been proven to hinder the success of college students (Beiter, Nash, McCrady, Rhoades, Linscomb, Clarahan, Sammut, 2015). In the United States, depression associated with Major Depressive Disorder is present in nearly 10% of all university students in the past 12 months (Wolfram, 2010). With the prevalence of Major Depressive Disorder proliferating, it is essential that we understand all of the possible effects and equip these students with the resources they need in order to succeed and participate academically.

Persistent Depressive Disorder, although very similar to Major depressive Disorder, has its own influence on college students. In a study conducted by Garrison, Addy, Jackson, McKeown and Waller (1992), researchers identified that approximately 8% of college aged men experience symptoms consistent with Persistent Depressive Disorder, while 5% of females encounter the same symptoms. These symptoms primarily affect a student’s productivity, which can have a significantly negative impact on academic performance. This impact primarily manifests into missed class time, decreased productivity in the classroom, and significant interpersonal problems with academics (Heiligenstein, Guenther, Hsu and Herman, 2010).

With Mood disorders, depression is the most prominent symptom experienced by students (Bisson, 2017). Researchers and clinicians have seen the effects that depression and mood disorders can have on students and their performance in the school setting. It has been demonstrated that mood disorders and academic performance have an inverse relationship. This means that if a mood disorder has increased levels of severity, then academic performance will decrease (Johnson, Bamer, Yorkston & Amtmann, 2009). A few of the primary symptoms associated with mood disorders are depression, mania, and hypomania. Simon & Wang (2006) were able to conclude that these symptoms created one of the largest barriers to succeeding in the academic and professional field due to missed work days as a primary result of these symptoms. On average, a student or professional could expect to miss approximately 27 work days per year due to the major symptoms associated with mood disorders. Another hurdle that students with mood disorders have to overcome is significant problems with attention levels. Attention or a lack thereof, is one of the primary factors influencing negative or decreased academic performance (Breslau, Miller, Breslau, Bohnert, Lucia, and Schweitzer, 2009).  

Bipolar I/II Disorder are two different disorders that differ based on the severity of the symptoms of mania (American Psychiatric Association, 2013). For this reason, we will address Bipolar I and Bipolar II simply as “Bipolar Disorder (BD)”. Bipolar disorder is not as common of an occurrence in the college setting as MDD and PDD; however, the effects that it has on an individual, especially a college student, are extremely significant because of the unpredictably and serious mental and physical symptoms that occur when the disorder is active (Stiles, Fish, and Vandermause, 2018). For those suffering from BD, symptoms are most prominently triggered by family relationships and academics (Kim, Mikolwitz, Biuckians and Kimberley, 2007). These researchers identified stress as a primary factor for influencing the presence of BD symptoms, thus as stress levels increase, (particularly in the domains of school and home life) the symptoms associated with BD increase at near identical rates. Biederman, Mick, and Faraone (2004) found that 87% of children with BD also had attention deficit/hyperactivity disorder (ADHD). With such a high comorbidity between the two, it isn’t any surprise to see difficulties with attention leading the symptoms that have been shown to affect academic performance (Giedd, 2000).

Anxiety Disorders

Khdour et al. (2016) noted that of all anxiety disorders, Generalized Anxiety Disorder (GAD) and Social Anxiety Disorder (SAD) are the most common diagnoses seen across all ages, races, and ethnicities. These specific anxiety disorders can severely impact social, occupational, and school functioning levels. They have proven to influence behavior and cognition making the overall learning environment much more difficult to comprehend (Murat, 2016). For example, researchers found that individuals with GAD and SAD were hypersensitive to negative feedback, which included avoiding confrontation. This could have a negative impact on the academic setting because a diagnosed student might not show up on test days (high stress situations) or might decide to skip a meeting with a professor to avoid any type of confrontation. These behaviors are clearly counterproductive, but are implemented as coping strategies for students suffering from anxiety-based symptoms. The most prominent symptom of anxiety is feeling uneasy (Bisson, 2017).

As was just previously noted, Generalized Anxiety Disorder (GAD) and Social Anxiety Disorder (SAD) are the two most common anxiety-based diagnoses in both the general population and the collegiate population (Bystritsky, Khalsa, Cameron, & Schiffman, 2013). Both diagnoses resemble each other in very many ways. Generalized Anxiety Disorder is generally described by persistent and constant anxious feelings across all spans of life and environments. Social Anxiety Disorder is similar to GAD in the sense that feelings of anxiety are present; however, these feelings are elevated during specific situations or in certain environments. An example of these situations might include someone with the fear of meeting new people or being in a large group of people. An individual with SAD does not always have feelings of anxiety, but instead when he/she arrives to class for the first day, the anxiety finds a way to express itself. Bisson, (2017) concurred that this is usually triggered by certain events, and for the example student, it pertains to social environments. 

Students diagnosed with Agoraphobia usually express anxious feelings by fearing and avoiding places or situations that might cause that individual to panic due to feelings of helplessness, feeling of being trapped or embarrassed (American Psychiatric Association, 2013). These students experience anxiety similar to that experienced by students with GAD and SAD. Agoraphobia is like GAD in the sense that individuals with Agoraphobia do experience frequent and persistent anxiety; however, this anxiety is usually derived from the fear of fear, or the fear of experiencing anxious symptoms at a later point in time. It is also like SAD in the sense that very frequently this anxiety is related to a few specific situations; however, the anxiety is usually present much prior and leading up to the possible event or situation (Heimberg, Mueller, Holt, Hope, & Liebowitz, 1992).

A proper review of the literature will bring to light the most significant symptoms faced by these students and it will also help us determine which forms of assistive technologies work the best to fill the academic deficits these students are faced with on a day-to-day basis. If we can determine which forms of assistive technologies work the best, we will increase the overall knowledge of the topic and may start a movement that ends with universities redistributing finances with the goal of providing the proper resources to these types of students. If we know what works the best for the largest number of students, we can be sure to invest in assistive technologies with a proven track record of making a meaningful impact on the lives of these students.




Section 2

Assistive Technology

Assistive technology can include any piece of equipment that is used to support a student with disabilities (Carver, Ganus, Ivey, Plummer, & Eubank, 2016). After years of studying the topic, the benefits clearly outweigh any financial concerns in regards to purchasing and providing qualified students with the necessary technological items and resources (Alnahdi, 2014).  The average student, or even professor, may have no idea how prevalent certain forms of assistive technology can be on college campuses across the country (Vines, Wright, Silver, Winchcombe, & Oliver, 2015). In this section, we will look to understand the general prevalence of assistive technology, the primary forms of assistive technology being used, the main uses of assistive technology (what are they used for), as well as highlight some of the misconceptions and stigmas surrounding the use of assistive technology. This section will provide the information necessary to understand the basics of assistive technology, including what it is and how it is implemented. This will create the foundation for the rest of review, where we will be able to incorporate the specific mood and anxiety disorders (and their symptoms) that could benefit from the use of assistive technology.

Prevalence of Assistive Technology

Assistive technology is becoming a more familiar word on a lot of campuses across the country, due to the rise in college students registered as having some form of disability. As many as one in four students at some of the most prestigious colleges in the country are now classified as being disabled; most prominently due to mental health diagnoses like anxiety and depression (Beiter, Nash, McCrady, Rhoades, Linscomb, Clarahan, & Sammut, 2015). This increase in students with mental-health disabilities has, in turn, led to a surge in accommodations, including the use of assistive technologies (Belkin, 2018). This may be in part due to the increased acceptance of mental illness,the increased promotion and encouragement towards students speaking out about their diagnoses with comfort, and the laws relevant to accommodations and assistive technologies (Ravitch, 2016).  Often the law on disabilities is governed by the Americans with Disabilities Act (ADA) of the year 1990.  The Act bars the aspects of discrimination against persons that have disabilities in housing, access to public utilities, education and employment. Stiles, Fish and Vandermause, (2018) identified that ADA gives the definition of disability as that which entails;

  1. Mental or physical form of impairment where sustainability leads to the limitation of either one or many of the major life operations of the person
  2. Documentations of related impairment
  3. Being considered as having an impairment of such kind


The laws regarding accommodations and assistive technologies are significantly different in primary school (K-12) when compared to secondary school (college). In primary school students with certain disabilities are granted 504 plans. Section 504 within the Rehabilitation Act of 1973, is a law that prohibits the discrimination against individuals with disabilities; it ensures that those children are presented with equal access to an education and guarantees that child's success when moving through the primary school system. In 1990 the Americans with Disabilities Act was passed, which focused more prominently on the students enrolled in colleges and universities. Universities are required to provide accommodations for students with qualifying disabilities. The major difference, however, is that secondary students are only guaranteed access to academic material; primary education students are guaranteed success.

Siegmann, Muller & Luecke, (2018) noted that students use these technologies to compensate for certain debilitating symptoms that may present themselves due to their mental health diagnoses. The collegiate setting can be an extremely demanding and overwhelming environment for any type of student, but especially for students with disabilities (Siegmann, Muller & Luecke, 2018). With the continued making of technological breakthroughs, the assistive technology found on campus is only improving as noted by Hollenbeck & Gerhart (2018), and students are continuing to thrive in the classroom (reference).

The need for cost effective and reliable assistive technology is extremely important when it comes to college students with disabilities (Hollenbeck, Noe, & Gerhart, 2018). In 1973, the Rehabilitation Act distributed federal funding to accredited college universities across the country with the primary purpose of providing disabled students with the resources necessary to access and succeed in school (Riemer-Reiss & Wacker, 2011). Since this legislation was passed, there have only been further improvements towards supporting these students, and that has included the development of more effective technologies.


Overview of Assistive Technologies

There are countless forms of assistive technology that have proven to be beneficial in educational settings. Some of these technologies aid students in reading, writing, comprehension, memorization, and prompting techniques (DeRuyter, 2000). Today's technologies allow students with cognitive disabilities to perform functions like record lectures, play back notes, track medications, relieve stress, and monitor mood and anxiety symptoms (Deveau, 2016). These technologies collectively allow student with cognitive impairments to address their problems quicker and more effectively, which ultimately benefits that student tremendously. These claims are further supported by extensive research concerning students with cognitive deficits like mood and anxiety disorders (Gentry, Lau, Molinelli, Fallen, & Kriner, 2012). Students with mood and anxiety disorders have a more difficult time than others when it comes to staying on task, being focused, and maintaining motivation (Newman, Szkodny, Llera, & Przeworski, 2010). Depending upon the specific diagnosis, a form of assistive technology may be more beneficial than others. For example, students who have a hard time remembering their schedules or daily commitments may be introduced to a Palmtop Personal Computer (Mechling, 2007). This personal computer is a small device that the student carries around with them throughout the week. Once per week (or as many times as necessary), the student can input things like due dates, meeting locations and times, and class schedules. The computer is programmed to remind the student that these commitments/activities are approaching and to prepare to complete those reminders. The goal of this technology is not intended to be used forever. Continued use of this computer will increase independence levels and slowly allow the student to gain confidence and the skills necessary to succeed on his/her own. The Palmtop Personal Computer is just one of the dozens of different kinds of assistive technologies that can be seen implemented to students of all ages.

Assistive technology focuses on compensating for a variety of academic deficiencies or “problem areas.” A couple of the most popular forms of assistive technology are recording devices, read-and-write, and speech-to-text software (Messmer, 2013). For example, students with serious anxiety disorders may be obsessive over the perfection of their notes, or they might not be able to keep up with their notes due to the pace of the lecture. There is current technology in place that is used to combat this problem. A Livescribe pen is designed for students who have a hard time keeping up with the pace of a lecture, take unclear notes, have a hard time with hearing, or experience difficulties with organization, as well as numerous other reasons. A Livescribe pen is paired with a specialized notebook, which allows a student to take notes during class on paper. Those notes can then be uploaded to an online database, where students can review their notes and listen to the linked audio which was recorded during the lecture on the pens speaker (Bouck, Flanagan, Miller, & Bassette, 2012). 

Misconceptions Surrounding Assistive Technology

When it comes to the topic of assistive technology on college campuses, there are many misconceptions among students, staff, and faculty that circulate. This is in part due to their lack of education and knowledge concerning its legitimacy and functionality. In this section, we will focus on the most common misconceptions, and break down the faulty beliefs while highlighting their true purposes. The seven primary misconceptions we will be focusing on include:

  • Unfair advantage for students with access to assistive technology (Leveling the playing field vs. unfair advantage),
  • Students can teach themselves the best way to use assistive technology in the classroom setting (living in the age of technology),
  • Assistive technology can take the place of good teaching,
  • In order to reach their academic potentials, students should use assistive technology for everything,
  • Assistive technology reduces levels of motivation,
  • Adults are too old to begin using assistive technology, and
  • All technology is considered assistive technology (Martin, 2017).

The first misconception is the belief that students with access to assistive technology are given an unfair advantage over students who may not have access or privileges to use these types of technologies (Martin, 2017). Assistive technology is primarily used by students who have a cognitive disability that impairs their likelihood of accessing and succeeding in the academic setting. These technologies are only given to qualified students because without them they would be functioning at a level far beneath that of a “normal” student. Assistive technology only provides equal access to the same learning experiences that every student on a college campus deserves to have. The technology as identified by Riemer-Reiss & Wacker (1999), does not control the brain of the student; it simply creates an equally level playing field across all spectrums of students.

The second misconception is the belief that all students are technologically fluent (Martin, 2017). Since we are living in the age of technology, there is the misconception that all students given the privilege to use these technologies have the ability to teach themselves or already know how to use their approved assistive technologies properly. Just because we are living in the age of technology does not mean we can assume that every student knows how to use every single piece of assistive technology. The skills need to be taught by someone experienced with the technology.

The third misconception surrounding assistive technologies is the idea that these resources can take the place of good teaching. Assistive technology is made as an additional tool to be used in conjunction with effective teaching. Assistive technology cannot coach a student to write a thesis, or identify a student’s academic weaknesses. This is where a professor can step in. Academic success according to Wolfran (2010) is achieved through the combination of assistive technology, good teaching, and a learning environment accepting of students with disabilities.

The next misconception is the idea that for students with mood and/or anxiety disorders to reach their academic potential, these students should use assistive technology for all areas of life and should continue to use these resources for an indefinite amount of time (Newman, Szkodny, Llera & Przeworski, 2010). Certain forms of assistive technology may be more beneficial in specific situations or environments, and irrelevant in others. Students with mood and anxiety disorders are encouraged to use their assistive technologies when they need to and not so much when they feel otherwise. Succeeding without assistive technology has been shown to increase a student’s confidence (Martin, 2017). This highlights the concept that assistive technology can and will be an extremely beneficial tool, but is ultimate goal is to aid the student in developing the skills they may be lacking because of their disorder; but to work towards a point in time where they no longer need such resources.

The fifth misconception surrounding assistive technology and students with mood and anxiety disorders is the idea that these resources reduce a student’s levels of motivation (Okolo & Diedrich, 2014). Swain, Hancock, Hainsworth & Bowman (2013) established that some individuals entertain the false narrative that assistive technology can take the place of learning and that a student does not need to exert the same levels of effort if they are using certain forms of technology. Spooner (2014) believed that this is certainly not the case because the technology does not do the work for the student; instead it helps the student access the academic material and completes their work at a competitive level with the rest of the students in their class or program.

The next misconception encompasses the idea that adults or “non-traditional” students are too old to begin using assistive technology, even if they are diagnosed with qualifying disabilities (Parekh, 2017). This concept is completely false. As long as adults (like any individual) are taught how to use these technologies, it will only lead to the development of new and effective academic habits. Again, this can be accomplished by participating in the suggested training that comes with each accommodation recommendation; the student will be just a well off as any other individual.

The last misconception surrounds the notion that all forms of technologies are considered assistive technologies (Mayo Clinic, 2018). This is a much less controversial topic. An example of this would be as follows: a standard computer is a form of technology, but a blind individual would not be able to use this without it being modified. The modification, like inclusion of verbal interpretation, would be a form of assistive technology, but not necessarily the computer itself. (Note: a computer could be a form of assistive tech in a different scenario). Again, this goes back to the idea that all students with disabilities are completely different, and their personal and individual situations heavily influences what type of assistive technology best suits them.

Another extremely important factor that many students with assistive technology face are their own personal fears about what other people will think of them if they find out they are using assistive technology. The stigma of feeling lesser than other students has been proven to invoke feelings of depression and anxiety (Beth, Cohen, Edmondson & Kronish, 2015).  Perhaps a student feels they are not "normal" because they are using certain forms of specialized equipment, and they see many other students with similar situations. Robb (2018) cautioned that this can sometime lead to students not taking advantage of the resources they may so desperately need, simply attempting not to stand out in any way.

According to Kennedy (2017), there are many different misconceptions and stigmas that present themselves on a college campus. Whether it be due to the lack of knowledge on the topic or simple ignorance, either way there are many false pretenses that consume the concept of assistive technologies.

Section 3

Mood Disorders


Mood disorders are one of the most frequently diagnosed psychiatric disorders across all populations. Mood disorders have been found to affect about 20% of the general population in the United States (Gregory, 2018). Because these disorders are so common, many individuals will go untreated, and the actual number may be far greater. Mood disorders are primarily characterized by a serious and significant change in mood; one that tends to affect an individual’s daily activity (Gregory, 2018).

With the prevalence of mood disorders in the United States, researchers and medical professionals have studied the etiology and development of mood disorders (reference needed).  There is still not one indefinite answer, but it is believed that a combination of environmental and biological factors work in unison to create these symptoms and disorders. Family history plays an extremely significant role in one’s personal likelihood of developing similar disorders. Traumatic events have also been identified as being one of the more influential causes regarding the onset of a mood disorder (Gregory, 2018). With mood disorders, there effects and symptoms are so vast that they can affect the diagnosed individual in many different environments and situations. Mood disorders are notoriously known for negatively affecting the social life, relationships, and work life and school performance; especially in the college setting where the environment itself is very structured and demanding (Gregory, 2018).

DSM-5 Diagnostic, Classification and Symptoms

Everyday life is a roller coaster of emotions. You may feel on top of the world one day because of a high-profile promotion or an awesome grade on a test. Another day, you may feel down in the dumps due to relationship problems, financial troubles, or because you got a flat tire on the way to work. These are normal fluctuations in mood that come and go. When your mood starts to have an impact on your daily activities and in your social, educational, and vocational relationships, Mechling (2007) reiterated that you may be suffering from a mood disorder.

There are three primary symptoms that encompass almost the entirety of mood disorders. These symptoms include depression, mania, and bipolar or rapid mood fluctuations. Depression is a primary symptom that is quite debilitating because it causes the diagnosed individual to focus predominantly on feelings of negativity. Although depression is a cognitive symptom, it does have a variety of biological effects. Depression can affect mood, cognition, sleep patterns, and behavior changes like weight loss or gain. Depression is also known to have significant effects on one’s emotional state and well-being. Legg & Watson (2017) pointed out that depression can result in diagnosed individual experiencing significant feelings of apathy, mood swings, general sadness and sensitivity, discontent, and a loss of feelings towards previously pleasurable experiences.

Mania is the second primary, classifying symptom of a mood disorder. Mania is characterized with feelings of high energy and excessive moods (Beth et al., 2015). Elevated moods can last from a few hours to numerous days, and are usually present through most of the day. The most common sub-symptom associated with mania is euphoria (Gregory, 2018). Euphoria can present itself in a variety of different ways, but it is most commonly demonstrated in the form of excessive talking or rapid speech, a decreased need for sleep, highly distractible and inattentive, a lack of personal judgment regarding personal decision (including impulsivity), and the making of reckless decisions (Gregory, 2018).  

All of these symptoms, emotions, and behaviors when combined together can have a detrimental impact on the lives of college students, ultimately putting their grades and chances of succeeding in the academic setting at risk. We will now explore the three most prominent mood disorders, and see how their symptoms compare, and how they more specifically effect a general population of college students.  The mood disorders we will be looking at are: Major Depressive Disorder, Bipolar I/II Disorder, and Persistent Depressive Disorder (Dysthymia).

Major Depressive Disorder is amongst the leading mood disorders in the United States (Siegmann, Muller & Luecke, 2018). It is most common in adults aged 18 and older, making it an extremely relevant diagnosis in the college student population. A National Epidemiological study was conducted in 2013 that revealed approximately 20% of the 36,309 participants met the diagnostic requirements for Major Depressive Disorder at some point within the last 5 years (National Institute of Mental Health, 2018). In order to be diagnosed with Major Depressive Disorder, the individual must be experiencing five out of the nine possible symptoms, with a depressed mood and loss  interest or pleasure, within a two week time frame (American Psychiatric Association, 2013).

Bipolar Disorder is certainly the most serious of mood disorders, given the mood fluctuations between major symptoms and mania for Bipolar I, and major depression and hypomania for Bipolar II (APA, 2013)  and its ability to make life completely unpredictable. One day the individual may wake up feeling great and the next day he/she could feel completely opposite. People with Bipolar Disorder go through intense emotional changes that are quite different from their normalized mood and behavior; these changes can be quite debilitating due to the effect on an individual’s day-to-day feelings (Legg & Krans, 2017).  Bipolar Disorder is often first diagnosed in teenagers, making college students rather susceptible to a positive diagnosis (Khdour et al. 2016). According to the National Institute of Mental Health (2018), only about 2.8% of the United States population is currently diagnosed with Bipolar Disorder, making it a much less common diagnosis; however, when the diagnosis is present, its effects are incomparable to any other mood disorder.

Persistent Depressive Disorder, previously referred to as Dysthymia, is a long-term continuous form of depression (Simon, 2016). This diagnosis is also quite similar to Major Depressive Disorder. The primary identifying factor with Persistent Depressive Disorder is the presence of a depressed mood for most of the day, for more days than not, and lasting for at least two- years (American Psychiatric Association, 2013).  This diagnosis is dependent upon the length of time these feelings of inadequacy and depression are experienced, which is the major differentiating factor between this disorder and any of the other mood disorders (Simon, 2016). In the United States, only 1.5% of adults are diagnosed with Persistent Depressive Disorder, making it a rather uncommon diagnosis, but when it is present we must be able to identify these affected individuals and provide them with the resources necessary.

Major Depressive Disorder has symptoms synonymous to its name. Depression is the primary symptom; however, the effects that the diagnosis has on individuals reaches far beyond depression. Depressed mood and a loss of interest in normally appealing activities are the qualifying symptoms for Major Depressive Disorder (American Psychiatric Association, 2013), but a strong case can  be made for keeping a close eye on symptoms of fatigue, anxiety, sleep disturbance, and neurocognitive and sexual dysfunction (Kennedy, 2017). The Mayo Clinic has also identified a list of secondary symptoms associated with Major Depressive Disorder. These include: irritability and emotional outbursts, insomnia, significant decrease in energy, reduced appetite and/or significant weight loss, slowed speaking and movement, the fixation on past failures, difficulties with attention, suicidal ideations, and physical pain including back discomfort and headaches.

The fact that we have college students in today's academic setting who are juggling all of these symptoms along with the requirements of work and school is astonishing (Fleming, 2017). In many cases, a decrease in academic performance may be the first warning sign that a student is dealing with symptoms of depression and/or Major Depressive Disorder (Robert, 2018). It has also been shown that students with Major Depressive Disorder are significantly less likely to graduate from college or drop out prematurely. Memory deficits are significantly increased in students with Major Depressive Disorder and the effects that this can have on a student’s academics is self-explanatory (Richards, 2018). For example, memory is a vital aspect of life, but more important in the collegiate setting where exams, homework, and quizzes are largely dependent upon memory. Major Depressive Disorder has also been shown to decrease a student's ability to express thoughts and ideas. This can be detrimental in the classroom setting due to many class participation requirements such as giving presentations, answering questions, or participating in discussions (Robert, 2018). When the diagnosed individual is aware of these negative symptoms, it may encourage them to avoid these situations at any and all costs, ultimately resulting in a decrease of academic performance.

Bipolar Disorder is one of the more serious mental health diagnoses in the DSM-5, primarily due to its rapid fluctuation of mood; extreme mood swings from high to low and low to high. The elevated mood levels are referred to as mania or hypomania, while the low moods can also be referred to as depression (Heiligenstein, Guenther, Hsu and Herman, 2010). Meanwhile, the significant nature of those symptoms requires extra attention as cited in Humensky et al (2010).

Mania is the first core symptom we will focus on. Mania presents itself in a variety of ways. Likewise, most patients during a manic episode are irritable and even psychotic (Legg & Watson, 2017). Depression is the second core symptom associated with Bipolar Disorder. As we have stated in previous sections, depression can present itself in a slew of ways. These include feeling hopeless or sad, withdrawing oneself from family and friends, losing interest in enjoyable  activities, a loss of appetite, increased feelings of fatigue and decreased levels of energy, as well as decreased cognitive functioning like lack of memory or concentration (Banerjee and Lamb,2016).  These symptoms present themselves in a variety of environments, and the college setting or classroom is no exception.

Students with Bipolar Disorder are inherently more sensitive to criticism, and their mood can dominate how they perceive instruction or direction from a professor (Breakie, 2017). Organization is another skill that many students diagnosed with Bipolar Disorder struggle with, along with certain forms of cognitive functioning. Changes in his concentration, alertness or processing speed may occur throughout the school week and may even reflect the overall mood stability of the child with bipolar. These symptoms can affect both his behavior and academic performance (Breakie, 2017). An individual with Bipolar Disorder is also at risk for displaying disproportionate emotions; meaning they may over or under react to certain forms of stimulus. A student going through an episode of mania may feel overconfident for an upcoming exam and choose not to study at all, resulting in a very poor grade or take the exam, feel they did well, and fail (Humensky et al. 2010).. On the other hand, that same student could be going through a depressive mood swing, and become so overwhelmed with the idea of an upcoming exam, that he/she cannot even get up in the morning to go to class. This swing from one side of the spectrum to the other is what makes these symptoms so unpredictable and so difficult to cope with.

Persistent Depressive Disorder (Dysthymia)

Persistent Depressive Disorder has symptoms similar to Major Depressive Disorder (Beth, Cohen, Edmondson & Kronish, 2015). The only major differentiating factor is the length of time and the severity of the symptoms. As the name implies, Persistent Depressive Disorders must have symptoms present for at least two complete years (American Psychiatric Association, 2013). Regardless of this fact, the obstacles faced by these students are very serious and need to be addressed appropriately and with the student in mind. Episodes of Major Depressive Disorder can indeed be present during the course of Dysthymia. The primary symptoms associated with Persistent Depressive Disorder include poor heating habits (loss of appetite or overeating), sleep problems (insomnia or hypersomnia), low energy, and low self-esteem, difficulty with decision making, and increased feelings of hopelessness (Bressert, 2017).  

Persistent Depressive Disorder affects all areas of life due to its consuming nature, but its affects in the school setting are quite dramatic. The National Longitudinal Study of Adolescent Health as noted by Glasofer & Gans (2018) found that students with Persistent Depressive Disorder and similar symptoms are less likely to be accepted into a four-year university. Not only does it affect students in college, but it affects their chances of even enrolling in collegiate classes. The most detrimental symptom of Persistent Depressive Disorder in the college setting involves motivation and concentration. This ultimately affects their likelihood of attending class. Another study found that students with Persistent Depressive Disorder had a significantly harder time associating and dealing with their classmates (Humensky, Kuwabara, Fogel, Wells, Goodwin, & Van Voorhees, 2010). Creating and maintaining a support group in college is quite essential when it comes to a student's chance of succeeding each year. Unfortunately, for students with Persistent Depressive Disorder, this is a reality that they have to deal with and must find their own ways of coping and overcoming certain downfalls. Gentry,Lau, Molinelli, Fallen, & Kriner (2012) added the other example on sleep disturbance. Many of students suffer from depression. Some can’t sleep at all, leading to episodes of psychosis. Others can’t fall asleep, leading them to oversleep and miss class.

Assistive Technology for Mood Disorders

In this section we will look to review the literature pertaining to the use of assistive technology on college campuses for students with Mood Disorders. Since the mood disorders we have been focusing on have relatively similar symptoms and effect the diagnosed students alike, we are going to highlight the assistive technologies for all three disorders (Major Depressive Disorder, Bipolar Disorder, and Dysthymia) under one section in attempts of avoiding  repetition. As we mentioned in the previous sections, students with mood disorders experience difficulties with motivation, commitment, memory deficits, expressive deficits, organization, lack of self-esteem and confidence, concentration, and a difficulty with decision making (Beth et al., 2015).  

The first piece of assistive technology that has found itself on college campuses all over the country is the presence of electronic reminders. This can come in a variety of forms such as a simple mobile application, like the one that comes standard on a majority of today's cell phones. It can also take the form of a Personal Digital Assistant. These devices are primarily used for students with memory deficits. A Personal Digital Assistant (PDA) is implemented for students who have a hard time staying on schedule or for students that have medications they need to remember to take daily. The PDA has a built-in alarm system that can be preprogrammed months at a time with the goal of consistently remind the student to complete assignments, arrive on time for meetings, finish homework, and take scheduled medications (Humensky et al., 2010). This piece of assistive technology and the others like it; for example, electronic calendars,  really work to benefit students with mood disorders because it simply gives them one less thing to worry about and helps them stay on top of their lives. This can aid in the reduction of pressure and decreases the chances of certain life stressors trigger an emotional breakdown (Bressert, 2017).

The next piece of assistive technology that students with mood disorders have been known to take advantage of is mood charting. Mood charting is especially helpful for students with Bipolar Disorder because of the consistent and dramatic mood swings. Again, there are a number of software systems as well as mobile applications that have been proven to help students with mood disorders. MoodTrack Diary is an application that allows the user to track moods freely and rate them on a scale of 1-5. The application displays moods on a logistical timeline which makes it extremely easy to visualize your mood cycles (Illinois University, 2018). Over time you will have a better understanding of how and when your moods seem to fluctuate most commonly, and this can allow students to more proactively plan their academic and social lives out, ultimately resulting in a more successful and healthy individual. Another application known as eMoods Mood Charting allows students to track their highs and lows in a more in-depth level, as well as your sleep schedule, medications, and any other symptoms relevant to mood disorders. This application creates a comprehensive report that can be easily sent out to your teachers, therapists, and doctors. This helps everyone involved in your academic and social life to be more aware and understanding of your triggers and mood cycles, and will keep everyone on the same page, which helps to maintain an open line of communication with everyone who should have insight to your situation.

The next type of assistive technology that we will be focusing on for student with mood disorders is a Livescribe Pen. Livescribe Pens are a relatively new form of technology that allows student to take notes while simultaneously recording lecture audio. The notes taken in class can then be uploaded to online database where student can re-listen to a lecture while comparing their individual notes to the audio file attached. As we mentioned in previous sections, students with mood disorders can experience difficulties with concentration and the Livescribe Pen works perfectly for these scenarios. If a student began to feel overwhelmed or simply lost focus during a lecture, they would still have the audio recording of the lecture and could go back and fill in the missing notes, or create more in depth notes. These pens also increase a student’s overall independence because they would never have to rely on a note taker (Simon, 2016). These elevated levels of independence have been proven to help increase levels of self-esteem and confidence, which can ultimately results in a more productive and successful student, regardless of their mood disorder (Simon, 2016). These smartpens are very popular among college students with disabilities because they can use a piece of assistive technology that is subtle, and they do not have to worry about other students judging them or making assumptions about their level of intelligence.

The last form of assistive technology that we will focus on for student with mood disorders is Word Completion and Word Prediction software. Previously in this section it was noted that students with mood disorders can experience difficulties with expression and critical thinking (Spooner, 2014). Word completion and word prediction software is used to assist students with writing assignments or note taking. These specific software programs help students by predicting the current word they are typing, as well as the next word based on grammatical context. Students who find themselves at a loss for words or a lack of ideas may find this software beneficial because it can help them fluently complete writing assignments and notes during class and lectures. Memory loss or cognitive functioning deficits according to Martin & Mihailidis (2017) are also experienced by students with mood disorders, and word prediction software can speed up the writing process as well as help the diagnosed student with word recall and correct spelling. This technology does not write for them, but it provides extra suggestions for the student that they otherwise would not have been able to think of on their own.

The prevalence of students with mood disorders continues to grow each year, and it is becoming even more important to make sure these students are given the proper tools to access academic material in the college setting (Harris & Mullan, 2009). The different types of assistive technologies that we highlighted in this section aims to bring light to the vast number of options these students have, and to demonstrate the true effectiveness of these technologies. Some of the assistive technologies mentioned have been present in the academic setting for many years, like Word Predictors, but there are also a handful of new technologies that are slowly being adopted by Student Disability Services across the country like Livescribe Pens (DeRuyter, 2000). As these technologies continue to expand their presence on collegiate campuses, we will only further our understanding of the true effectiveness of these technologies.


Section 4

Anxiety Disorders


Along with Mood Disorders, Anxiety Disorders are some of the most prevalent forms of mental health disorders in the United States. In the United States, approximately 40 million adults are currently diagnosed with an Anxiety Disorder, which comes out to about 18% of our population (Longheardt, 2016). Everybody experiences feeling of anxiety at some point of time in our lives; it can be either good or bad anxiety. Good anxiety would be the nervousness you experience in heavy traffic. This type of anxiety is good because it increases individualized awareness and helps the driver to avoid getting in an accident. Bad anxiety, which is the basis of an anxiety disorder, would be persistent and excessive fear in non-threatening situations (Longheardt, 2016). These feelings can cause significant distress and may hinder an individual from participating in daily activities.

In the high stress environment of a college campus, the presence of anxiety amongst students is not a concept foreign to very many individuals. The pressure to compete and perform every single day creates a lot of general anxiety. Students use this to motivate themselves to study and complete all assignments and homework; however, not all students have the capabilities to effectively moderate these feelings (reference). As was stated previously, a small amount of anxiety can be very beneficial for college students, and has even been shown to improve academic performance. This type of anxiety is known as facilitating anxiety (Ormrod, 2014). A slight increase in anxious feelings can sometimes be the motivational force that pushes certain students to work a little bit harder. Excessive anxiety, like that experienced by students with anxiety disorders, can distract and interfere with attention to their academic tasks. This section will look to understand three of the most common classifications of anxiety disorders: Generalized Anxiety Disorder, Social Anxiety Disorder, and Agoraphobia.

DSM-5 Diagnostic Classifications and Symptoms

Anxiety is a feeling experienced by every single individual on this planet, and will continue to be experienced for as long as we live. Some individuals may feel anxious when they are assigned a new task at work, or when a student is studying for a final exam or before making an important decision like taking out a mortgage for a home. However, anxiety associated with an anxiety disorder far surpasses these temporary feelings of fear and worry. An individual with an anxiety disorder does not have the ability to regulate these excessive feelings which continue to build up overtime. These feelings have been shown to negative influence the overall lives of the affected individuals, which include social circles, job and academic performance (Messmer, 2013).

Anxious feelings are the defining characteristics of anxiety disorders. The term anxiety refers to the anticipation of a future concern or event that is associated with physical symptoms like muscle tension, as well as avoidance behavior (Parekh, 2017). Another primary symptom associated with anxiety disorders is fear. Fear is an emotional response, biological in nature, which is reactionary to an immediate threat. In anxiety disorders, fear is usually out of proportion to the situation and works against you by preventing you from functioning normally.

The first disorder that we will be focusing on is Generalized Anxiety Disorder (GAD). GAD can only be diagnosed when there are consistent feelings of anxiety and worry regarding a variety of topics. This worry must occur more days than not within a six-month time span. These feelings of worry must also be extremely difficult to control. Finally, the feelings of anxiety and worry must create at least three of six possible physical or cognitive symptoms. These possible symptoms include: restlessness, easily fatigued, impaired concentration, irritability, increased muscle aches, and/or difficulty sleeping (American Psychiatric Association, 2013).  It is not uncommon for these individuals to experience symptoms that make it difficult to carry out daily activities (Glasofer & Gans, 2018). 

Social Anxiety Disorder (SAD) is the next diagnosis that we will focus on in this section. SAD is extremely similar to GAD; however, the primary difference is the fact that these symptoms present themselves when the diagnosed individual is placed into a social situation, or when they perceive the outcome of a future social interaction (Richards, 2018). In order to be diagnosed with SAD, an individual must have persistent fear or one or more social or performance situations in which that individual is/could be exposed to unfamiliar people with the possibility of being scrutinized by others (American Psychiatric Association, 2013). Other requirements for diagnosis include; exposure to these feared situations almost always provokes anxiety or a panic attack, the individual understands that their reaction is unreasonable or excessive, these situations are consciously avoided, and the anxiety interferes with social functioning (American Psychiatric Association, 2013).

Agoraphobia is very similar to both Generalized Anxiety Disorder as well as Social anxiety Disorder. An individual diagnosed with Agoraphobia usually experiences irrational fears when it comes to being in exposed public places. Some of the most common environments that invoke feelings of distress are on public transportation, standing in line, or even just leaving the house (Fleming, 2017). It typically develops around the age of 20 years-old, which is right in the heart of the collegiate age for students.

In order to be diagnosed with Agoraphobia, the individual must experience disproportionate fear when confronted with at least two anxiety provoking situations (i.e. public transportation, crowded areas, standing in line). There must also be an immediate anxiety-based response (i.e. panic attack). The affected individual should also be aware that their personal response is disproportionate to the situation, and they should display avoidance behaviors. All of these symptoms need to be present for at least six months in order to have a qualifying diagnosis of Agoraphobia (American Psychiatric Association, 2013).

Generalized Anxiety Disorder is frequently associated with somatic symptoms like increased heart rate and heart palpitations as a result of chronic anxiety (Boswell, Thompson-Hollands, Farchione, & Barlow, 2013). As the name of the disorder states, Generalized Anxiety Disorder does not discriminate as to what events trigger these feelings of anxiety. Some of the most common symptoms associated with Generalized Anxiety Disorder include feeling nervous, irritable or on edge, having a sense of imminent danger, panic or doom, having an increased heart rate, hyperventilation, sweating, trembling, feeling tired, difficulty with concentration, difficulties with sleep, and gastrointestinal problems (Newman, Llera, Erickson, Przeworski, & Castonguay, 2013). Generalized Anxiety Disorder, like many other anxiety-based disorders, is quite interesting because of the fact that the symptoms associated with this disorder are equally cognitive as well as physical.

As the Anxiety and Depression Association of America states, these anxious feelings can be derived from a slew of situations including: anticipating a natural disaster, money concerns, health, family, or work. These feelings of worry can even keep individuals diagnosed with Generalized Anxiety Disorder to functional socially, have full and meaningful lives, and be gainfully employed. These symptoms can even cause individuals with GAD to avoid certain situations, or may not take advantage of certain opportunities due to their worry (Swain, Hancock, Hainsworth, & Boswman, 2013). If we apply this concept to the collegiate world, or to students diagnosed with this disorder, we may see students not seeking the academic support they may need from faculty.  Generalized Anxiety Disorder also influences concentration, which ultimately can have devastating effects on the diagnosed student's academic chances of succeeding. A lack of concentration can keep a student from accessing material in class, it can create more obstacles for that student to keep a schedule and follow timelines, and it can it makes it difficult for a diagnosed student to sit through a two or three-hour lecture, which is very common on a college campus.

Social Anxiety Disorder has many similar symptoms as Generalized Anxiety Disorder, but we will focus on some of those that differ most significantly. Social Anxiety Disorder, sometimes referred to as social phobia, is defined by an individual experiencing fear due to perceived judgment, negative evaluation, and/or social rejection (Swain et al., 2013).

In the collegiate setting, students with Social Anxiety Disorder will more often than not avoid social or performance situations. If these situations cannot be avoided, these students will struggle to participate due to their increased levels of stress and anxiety. If we look specifically at how these symptoms can affect students, avoidance of social and performance situations often ensue. If a student fears social situations, he will have decreased chances of succeeding academically because simply showing up to a class full of unfamiliar faces will trigger an anxiety attack. On the other hand, if that student perceives the potential situation as being too stressful, they may not even show up to class. The stress may be so great that these students are essentially being denied access to academic material because their symptoms are not even allowing those individuals from participating in classroom activities.

The final anxiety-based disorder that we will be focusing on in this section is Agoraphobia. Agoraphobia is a type of disorder marked by severe panic attacks that keeps most diagnosed individuals grounded in the comfort of their homes. Campbell, Milbourne, Dugan & Wilcox (2016) identified the primary symptoms associated with Agoraphobia being experienced difficulty leaving home alone, inability to stand in crowded lines without debilitating feelings of anxiety, difficulty being in enclosed spaces like movie theaters, elevators, or stores, and the inability to use public transportation, like a bus, taxi, plane or train. These symptoms make it very difficult for diagnosed individuals to assimilate with society. They consistently fear the possibility of escape and embarrassment.

When we look at how Agoraphobia can affect college students specifically, symptoms may include difficulties in leaving home or the dorm room.  If a student lives off campus, and needs to use transportation to get to school each day, we may see difficulty making it to class? Assuming the diagnosed student is able to make it to campus each day, the anxiety they will be dealing with will certainly take away from their concentration levels towards actual classroom material (Carol et al. 1992). These students also must sit in a crowded classroom, sometimes even with a few hundred other students; how can we expect students to succeed in these environments? Overcoming the feelings associated with Agoraphobia usually entail facing your personal fears and dealing with them head on. These students not only have to worry about succeeding in the classroom, but they have to deal with making it to the classroom, sitting through an anxiety-filled lecture, and walk the halls with hundreds if not thousands of other students when class is dismissed (Cook & Hussey, 2012).


Assistive Technology for Anxiety Disorders

This section reviews literature pertaining to the assistive technologies that can be taken advantage of on college campus by students with anxiety disorders. Similar to the section on Mood Disorders, we will look at the three previously stated Anxiety Disorders, and collectively focus on the assistive technologies that benefit these disorders as a whole; not individually. Since the anxiety disorders are so similar in symptomology, it would be repetitive to identify certain forms of assistive technology for each individually mentioned anxiety disorder.

The first grouping of technologies that we will focus on in this section is the mobile applications that look to minimize the feelings of anxiety in the student population. According to the Johnson, Bamer, Yorkston & Amtmann, (2009), there are four mobile applications that have proven to decrease feelings of stress and anxiety for students diagnosed with the aforementioned anxiety disorders. These applications include Breathe2Relax, Headspace, I Can Be Anything, and Stop, Breathe, Think.

Breathe2Relax is a mobile application used primarily as a stress management tool. This application helps students with anxiety disorders to calm their fight-or-flight responses by walking the user through certain diaphragmatic breathing exercises (Newman, Llera, Erickson, Przeworski & Castonguay, 2013). The second mobile application we will focus on is Headspace (Hollenbeck, Noe & Gerhart, 2018). This application allows students to combat feelings of stress and anxiety by improving the overall cognitive well-being of its users through guided meditation sessions. The third application we will focus on is I Can Be anything (Longheardt, 2016). This application is very similar to Headspace in the sense that the application provides guided exercises that help to loosen the constraints of anxiety, phobias, and fears. The last mobile application that we will highlight in this section is Stop, Breathe, Think. This application can be used by students of all ages, young or old. During high anxiety situations or within anxiety prone environments, the user can answer a small series of questions pertaining to their situation and their feelings, and the application will create an individualized guided meditation session based on what the individual is feeling at that specific moment in time (Campbell, Milbourne, Dugan, & Wilcox, 2016).

As was mentioned by Wolfran, (2010), anxiety disorders like Generalized Anxiety Disorder, Social Anxiety Disorder, and Agoraphobia all create circumstances where the diagnosed student may experience difficulties with concentration and attentiveness. When we apply this to the school or classroom setting, we can imagine how difficult basic educational processes (like reading numerous chapters in a science textbook) can actually be for these students. If the student is not able to effectively extract information or retain information from their textbooks due to a lack of concentration and attention characteristics, the student could receive the accommodation of e-text readers (Fennema-Jansen, 2015). E-text readers are hardware devices explicitly designed to read electronic texts. E-text readers will essentially read aloud, the text one would find in a book or on the internet. By converting the appropriate text into audio, a student with anxiety disorders is more often than not, able to concentrate and retain information at a much higher rate than they would if they were to read the exact same material from a textbook (Fennema-Jansen, 2015).

The next piece of assistive technology that we will focus on in this section is the use of ear buds. Ear buds are technically considered a form of low-tech" assistive technology, due to its simplistic form, but the positive affects it has produced is undeniable (Cook & Hussey, 2012). Student with the previously mentioned anxiety disorders are more likely to experience difficulties with concentration and memory (Cook & Hussey, 2012). By wearing ear buds or noise canceling headphones during exams, tests, or quizzes, a student diagnosed with an anxiety disorder is much more likely to receive a higher grade than they would have without the headphones (Parekh, 2017).

Students diagnosed with anxiety can also benefit from organizational software. Students diagnosed with anxiety-based disorders have a significantly more difficult time staying organized and affectively managing their time than non-diagnosed students (Campbell et al. 2016). When it comes to pieces of assistive technology that focus on student's organizational well-being, we are reverted back to the implementation of certain software applications that can be carried out with phone applications (Puig-Antich, et al. 1985). An application referred to as iStudiez Pro is gaining popularity across college campuses; and specifically in the hands of students with diagnosed anxiety disorders (Newman et al., 2013). iStudiez Pro is software that can be downloaded onto any smartphone. It functions by organizing all aspects of social, academic, and professional life. The application serves as a hub for students, allowing them to sync together academic assignments, planners, instructions, and holidays. They are also able to include their class schedules, plan study groups, and systematically prioritize assignments based upon individualized importance. This application is considered a higher standard when applied to the collegiate setting because it can track grades, which has been shown to increase student’s awareness with the factors and behaviors that are influencing their academic progress (Newman et al, 2013).




Section 5



When looking at this literature review, there are a couple very obvious limitations that we face. The first limitation would be the facts that all of the information being provided is coming from articles I have no information concerning their legitimacy with regards to those who did research work on them. Likewise, I owe the information to the authors I have used their ideas to come up with this paper.. The second limitation is the generalizability of the findings of the included studies. Some of the articles referenced in this review came from countries outside the United States.  Although there is significant scientific evidence proving the reliability and validity of these findings, it does not necessarily mean that their sample populations parallel the population here in America.

Need for Future Research

Assistive technology in the academic setting, specific to mood and anxiety disorders, is an invaluable tool that has proven to improve the outcomes and opportunities of success for the individuals using these resources. With that being said, there are also countless limitations to these technologies. A lack of financial resources is one of the major barriers restricting the idea that all students should have access to the varying forms of assistive technologies that their individual diagnosis and symptoms may require. Each university is granted a specific amount of money per year that they are allowed to put towards the implementation of accommodations and assistive technologies for their students.

Since purchasing and implementing certain technologies comes with such a large expense, there needs to be a push towards increasing the use of the scientifically proven mobile applications that each student can take advantage of on an individual basis. A large portion of the research in this review covers the topic of mobile applications.

In this literature review, the topic of mood and anxiety disorders was the primary focus. We chose to focus on these categories of disorders specifically because of their prevalence rates on college campuses. Something that needs to be further researched is how the rest of the disabled student population fares when it comes to their diagnosis and symptomology. We focused on mood and anxiety disorders because they are the largest cohorts of disabled students on college campuses, but there are countless other disorders with large presences that need to be identified and researched.


Alnahdi, G. (2014). Assistive technology in special education and the universal design for learning. Turkish Online Journal of Educational Technology-TOJET, 13(2), 18-23.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental  disorders (5th ed.). Washington, DC: Author.

Anxiety Disorders. (2018). Retrieved May 16, 2018, https://www.nimh.nih.gov/health/topics/anxiety-disorders/index.shtml#part_145333

Auerbach, R., Alonso, J., Axinn, W., Cuijpers, P., Ebert, D., Green, J., …Bruffaerts, R.  (2016). Mental disorders among college students in the WHO World Mental  Health Surveys. Psychological Medicine, 46(14), 2955–2970.  Doi:10.1017/S0033291716001665Banerjee, P., and Lamb, S.? (2016).?A systematic review of factors linked to poor  academic performance of disadvantaged students in science and math in schools.  Cogent Education,?3:1,?doi:?10.1080/2331186X.2016.1178441 

Beiter, R., Nash, M., McCrady, D., Rhoades, M., Linscomb, M., Clarahan, S., and  Sammut, S. (2015). The prevalence and correlates of depression, anxiety, and  stress in a sample of college students. Journal of Affective Disorders. 173: 90-96.

Beiter, R., Nash, R., McCrady, M., Rhoades, D., Linscomb, M., Clarahan, M., & Sammut, S. (2015). The prevalence and correlates of depression, anxiety, and stress in a sample of college students. Journal of affective disorders, 173, 90-96.

Belkin, D. (2018). Are colleges bending the rules for more students, give them extra  help? U.S. Education

Beth, E., Cohen, F., Edmondson, D., & Kronish, I. (2015). State of the art review:  Depression, stress, anxiety, and cardiovascular disease. American Journal of  Hypertension, 28(11), 1295–1302. doi:10.1093/ajh/hpv047

Biederman, J., Mick, E., & Faraone, S.V. (2004). A prospective follow-up study of  pediatric bipolar disorder in boys with attention-deficit/hyperactivity disorder.  Journal of Affective Disorders, 82S, S17–S23.

Bisson, K. (2017). The effect of anxiety and depression on college students’ academic  performance: Exploring social support as a moderator. Digital Commons @  ACU, Electronic Theses and Dissertations. Paper 51. 

Boswell, F., Thompson?Hollands, J., Farchione, J., & Barlow, H. (2013). Intolerance of  uncertainty: A common factor in the treatment of emotional disorders. Journal of  clinical  psychology, 69(6), 630-645.

Bouck, E., Flanagan, A., Miller, B., & Bassette, L. (2012). Technology in action. Journal of Special Education Technology. (27): 4

Breakie, S. (2017). Hope and harmony for people with bipolar disorder: How a child's  bipolar diagnosis can affect the school day. Journal for Bipolar Disorders.

Breslau J, Miller E, Breslau N, Bohnert K, Lucia V, & Schweitzer J. (2209). The impact  of early behavior disturbances on academic achievement in high school. Pediatrics., 123 (6): 1472-1476.

Bressert, S. (2017). Persistent Depressive Disorder (Dysthymia) Symptoms. Psych  Central. Retrieved on June 18, 2018, from https://psychcentral.com/disorders/dysthymic-disorder-symptoms/.

Bystritsky, A., Khalsa, S. S., Cameron, M. E., & Schiffman, J. (2013). Current Diagnosis  and Treatment of Anxiety Disorders. Pharmacy and Therapeutics, 38(1), 30–57.

Campbell, P., Milbourne, S., Dugan, L, & Wilcox, J. (2016). A review of evidence on  practices for teaching young children to use assistive technology devices. Topics in Early Childhood Special Education, 26, 3–13.

Carol Z. Garrison, Cheryl L. Addy, Kirby L. Jackson, Robert E. McKeown, Jennifer L. Waller; Major Depressive Disorder and Dysthymia in Young Adolescents, American Journal of Epidemiology, Volume 135, Issue 7, 1 April 1992, Pages 792–802, https://doi.org/10.1093/oxfordjournals.aje.a116366

Carver, J., Ganus, A., Ivey, J. M., Plummer, T., & Eubank, A. (2016). The impact of mobility assistive technology devices on participation for individuals with disabilities. Disability and Rehabilitation: Assistive Technology, 11(6), 468-477.

Cook, M., & Hussey, M. (2012). A framework for assistive technologies. In Assistive  technologies: Principles and practice (2nd ed., pp. 34–53). St. Louis, MO:  Mosby.

Cornell University (2015). Retrieved July 12, 2018, from https://www.cornell.edu/  strategicplan/objectives.cfm

DeRuyter, F. (2000).?The importance of outcome measures for assistive technology  service delivery systems. Technology and Disability, 6, ?89–104.

Deveau, M. (2016). An exploration of college students with diagnosed mental disorder's  use of  everyday technology. Ithaca College Digital Commons.

Fennema-Jansen, S. (2015). An analysis of assistive technology outcomes in Ohio  schools: Special education students’ access to and participation in general  education and isolating the contribution of assistive technology. Milwaukee: University of Wisconsin.

Fleming, K. (2017). DSM-5 categories: Anxiety disorders and Agoraphobia. Journal of  Therapy and Discovery.

Gentry, T., Lau, S., Molinelli, A., Fallen, & Kriner, R. (2012). The apple iPod touch as avocational support aid for adults with autism: Three case studies. Journal of  Vocational Rehabilitation. 37(2): 75-85. Doi: 10.3233/JVR-2012-0601

Georgia Department of Education (2014). Definition of Assistive Technology. Retrieved July 12, from, http://www.gpat.org/eorgia-project-for-assistive- technology/pages/assistive-technology-definition.aspxGiedd, J. N. (2000). Bipolar disorder and attention-deficit/hyperactivity disorder in  children and adolescents. Journal of Clinical Psychiatry, 61, 31–34.

Glasofer, D. & Gans, S. (2018). How generalized anxiety disorder is diagnosed using the  DSM- 5: Understanding GAD. Journal of Anxiety and Related Disorders.

Gregory, C. (2018). General background information on mood disorders. PsyCom.

Harris, Kathleen, & Mullan. (2009). The National Longitudinal Study of Adolescent to  Adult Health (Add Health), Waves I & II, 1994–1996; Wave III, 2001–2002;  Wave IV, 2007- 2009 [machine-readable data file and documentation]. Chapel  Hill, NC: Carolina Population Center, University of North Carolina at Chapel  Hill.  doi: 10.3886/ICPSR27021.v9.

Heiligenstein, E., Guenther, G., Hsu, K., and Herman, K. (2010). Depression and  academic impairment in college students. Journal of American College Health. 45 (2): 59-64.

Heimberg, R., Mueller, G., Holt, C., Hope, D., & Liebowitz, M. (1992). Assessment of anxiety in social interaction and being observed by others: The Social Interaction Anxiety Scale and the Social Phobia Scale. Behavior therapy, 23(1), 53-73.

Hollenbeck, J., Noe, R., & Gerhart, B. (2018). Human resource management: Gaining a competitive advantage. McGraw-Hill Education.

Humensky, J., Kuwabara, S., Fogel, J., Wells, C., Goodwin, B., & Van Voorhees, B.  (2010). Adolescents with depressive symptoms and their challenges with  learning in school. The Journal of School Nursing?: The Official Publication of  the National Association of School Nurses, 26(5), 377–392.  doi.org/10.1177/1059840510376515.

Johnson, K., Bamer, A., Yorkston, K., & Amtmann, D. (2009). Use of cognitive aids  and other assistive technology by individuals with multiple sclerosis. Disability Rehabilitation Assistive Technology 4(1):1-8. 

Kennedy, S. (2017). Core symptoms of major depressive disorder: Relevance to diagnosis andtreatment. Dialogues in Clinical Neuroscience. 10 (3): 271-277.

Khdour, H., Abushalbaq, O., Mughrabi, I., Imam, A., Gluck, M., Herzallah, M., &  Mustafa, A. (2016). Generalized anxiety disorder and social anxiety disorder, but not panic anxiety disorder, are associated with higher sensitivity to learning from negative feedback: Behavioral and computational investigation. Frontiers in  Innovative Neuroscience 10:20. Doi:10.3389/fnint.2016.00020. 

Kim, E. Y., Miklowitz, D. J., Biuckians, A., & Mullen, K. (2007). Life Stress and the Course Of Early-Onset Bipolar Disorder. Journal of Affective Disorders, 99(1-3),  37–44. http://doi.org/10.1016/j.jad.2006.08.022

Legg, T. & Watson, K. (2017). Could it be Bipolar? 14 Signs to look for. The Healthline  Journal. 3 (2). 

LibGuides: Bipolar Disorder: Common Assistive Technologies. (2018). Retrieved March 15, 2018, from http://guides.library.illinois.edu/c.php?g=498819&p=3415384

Longheardt, M. (2016). Anxiety disorders. National Alliance of Mental Illness.

Martel, A., Derenne, J., Leebens, P. (eds) Promoting Safe and Effective Transitions toCollege for Youth with Mental Health Conditions. Springer, Cham

Martin, S. & Mihailidis, A. (2017). Special issue: Assistive technology (I). British  Journal of Occupational Therapy. (80): 2. 61-62.

Mayo Clinic. (2018). Persistent Depressive Disorder (dysthymia). Retrieved from:  https://www.mayoclinic.org/diseases-conditions/persistent-depressive- disorder/symptoms-causes/syc-20350929

Mechling, L. (2007). Assistive technology as a self-management tool for prompting students with intellectual disabilities to initiate and complete daily tasks: A  literature review. Education and Training in Developmental Disabilities 42(3):252-262.

Messmer, A. (2013). Students with learning disabilities: The effectiveness of using assistive technology. Fisher Digital Publications.

Murat, A. (2016). Analysis of the relationship between prosodic reading skill sand reading anxiety among secondary school students. International Journal of Languages' Education and Teaching, 4(3), 207-216.

National Institute of Mental Health. (2018). Anxiety Disorders. Retrieved from:  gwumc.edu/c.php?g=27779&p=170369.

Newman, M., Llera, J., Erickson, M., Przeworski, A., & Castonguay, G. (2013). Worry and generalized anxiety disorder: a review and theoretical synthesis of evidence on nature, etiology, mechanisms, and treatment. Annual review of clinical psychology, 9, 275-297.

Newman, M., Szkodny, L., Llera, S, & Przeworski, A. (2010). A review of technology- assisted self-help and minimal contact therapies for anxiety and depression: Is  human contact necessary for therapeutic efficacy? Clinical Psychology Review. 31: 89-103. 

Okolo, C., & Diedrich, J. (2014). Twenty-five years later: How is technology used in  the education of students with disabilities? Results of a statewide study. Journal of Special Education Technology, 29(1), 1-20.Ormrod, J. (2014). Anxiety in the classroom: How anxiety affects learning and  performance. Journal for Educational Psychology.

Parekh, R. (2017).  Anxiety disorder. What are they? American Psychiatric Association.

Pedrelli, P., Nyer, M., Yeung, A.,  Zulauf, C & Wilens, T. (2014). College students:  Mental health problems and treatment considerations. Acad Psychiatry. 39(5): 503–511. Doi: 10.1007/s40596-014-0205-9

Puig-Antich J, Lukens E, Davies M, Goetz D, Brennan-Quattrock J, Todak G.  (1985). Psychosocial functioning in prepubertal major depressive disorders. Interpersonal relationships during the depressive episode. Arch Gen Psychiatry. 42(5):500–507. doi:10.1001/archpsyc.1985.01790280082008

Ravitch, D. (2016). The death and life of the great American school system: How testing  and choice are undermining education. Basic Books.

Richards, T. (2018). DSM-5 definition of social anxiety disorder. What is social anxiety?  Social Anxiety Institute.

Riemer-Reiss, M. & Wacker, R. (1999). Assistive technology use and abandonment  among college students with disabilities. International Electronic Journal for  Leadership in Learning. 3.

Robb A. (2018). Coping with highs and lows: A student with bipolar disorder goes to  college.

Robert, R. (2018). Teen depression and school performance. Paradigm Malibu:  Adolescent Treatment.

Siegmann, E., Muller, H. & Luecke, C. (2018). Association of depression and anxiety disorders with autoimmune thyroiditis: A systematic review and meta-analysis. JAMA Psychiatry. 75(6): 577-584. Doi:10.1001/jamapsychiatry.2018.0190.

Simon, A. (2016). The learning impact of smart pens on students with cognitive  disabilities. RESNA.

Simon, G. & Wang, P. (2006). Prevalence and effects of mood disorders on work  performance in a nationally representative smple of U.S. workers. The American  Journal of Psychiatry. 163 (9). 1561-1568. 

Spooner, C. (2014). Assistive Technology Glossary - The ACCESS Project - Colorado  State University. Retrieved April 8, 2018, from  http://accessproject.colostate.edu/disability/modules/at_glossary/at_glossary.php#

Stiles, B., Fish, A., and Vandermause, R. (2018). The compelling and persistent problem of bipolar disorder disguised as major depressive disorder: An integrative review. Journal of American Psychiatric Nurse Association.

Swain, J., Hancock, K., Hainsworth, C., & Bowman, J. (2013). Acceptance and  commitment therapy in the treatment of anxiety: a systematic review. Clinical  psychology review, 33(8), 965-978.Vines, J., Wright, P., Silver, D., Winchcombe, M., & Olivier, P. (2015). Authenticity, relatability and collaborative approaches to sharing knowledge about assistive living technology. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 82-94). ACM.

Wolfran, R. (2010). A program for reducing depressive symptoms and suicidal ideation  in medical students. Journal of Health Studies. 44: 655-665.

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