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7 Depression Research Paper Topic Ideas

Nancy Schimelpfening, MS is the administrator for the non-profit depression support group Depression Sanctuary. Nancy has a lifetime of experience with depression, experiencing firsthand how devastating this illness can be.

Cara Lustik is a fact-checker and copywriter.

In psychology classes, it's common for students to write a depression research paper. Researching depression may be beneficial if you have a personal interest in this topic and want to learn more, or if you're simply passionate about this mental health issue. However, since depression is a very complex subject, it offers many possible topics to focus on, which may leave you wondering where to begin.

If this is how you feel, here are a few research titles about depression to help inspire your topic choice. You can use these suggestions as actual research titles about depression, or you can use them to lead you to other more in-depth topics that you can look into further for your depression research paper.

What Is Depression?

Everyone experiences times when they feel a little bit blue or sad. This is a normal part of being human. Depression, however, is a medical condition that is quite different from everyday moodiness.

Your depression research paper may explore the basics, or it might delve deeper into the  definition of clinical depression  or the  difference between clinical depression and sadness .

What Research Says About the Psychology of Depression

Studies suggest that there are biological, psychological, and social aspects to depression, giving you many different areas to consider for your research title about depression.

Types of Depression

There are several different types of depression  that are dependent on how an individual's depression symptoms manifest themselves. Depression symptoms may vary in severity or in what is causing them. For instance, major depressive disorder (MDD) may have no identifiable cause, while postpartum depression is typically linked to pregnancy and childbirth.

Depressive symptoms may also be part of an illness called bipolar disorder. This includes fluctuations between depressive episodes and a state of extreme elation called mania. Bipolar disorder is a topic that offers many research opportunities, from its definition and its causes to associated risks, symptoms, and treatment.

Causes of Depression

The possible causes of depression are many and not yet well understood. However, it most likely results from an interplay of genetic vulnerability  and environmental factors. Your depression research paper could explore one or more of these causes and reference the latest research on the topic.

For instance, how does an imbalance in brain chemistry or poor nutrition relate to depression? Is there a relationship between the stressful, busier lives of today's society and the rise of depression? How can grief or a major medical condition lead to overwhelming sadness and depression?

Who Is at Risk for Depression?

This is a good research question about depression as certain risk factors may make a person more prone to developing this mental health condition, such as a family history of depression, adverse childhood experiences, stress , illness, and gender . This is not a complete list of all risk factors, however, it's a good place to start.

The growing rate of depression in children, teenagers, and young adults is an interesting subtopic you can focus on as well. Whether you dive into the reasons behind the increase in rates of depression or discuss the treatment options that are safe for young people, there is a lot of research available in this area and many unanswered questions to consider.

Depression Signs and Symptoms

The signs of depression are those outward manifestations of the illness that a doctor can observe when they examine a patient. For example, a lack of emotional responsiveness is a visible sign. On the other hand, symptoms are subjective things about the illness that only the patient can observe, such as feelings of guilt or sadness.

An illness such as depression is often invisible to the outside observer. That is why it is very important for patients to make an accurate accounting of all of their symptoms so their doctor can diagnose them properly. In your depression research paper, you may explore these "invisible" symptoms of depression in adults or explore how depression symptoms can be different in children .

How Is Depression Diagnosed?

This is another good depression research topic because, in some ways, the diagnosis of depression is more of an art than a science. Doctors must generally rely upon the patient's set of symptoms and what they can observe about them during their examination to make a diagnosis. 

While there are certain  laboratory tests that can be performed to rule out other medical illnesses as a cause of depression, there is not yet a definitive test for depression itself.

If you'd like to pursue this topic, you may want to start with the Diagnostic and Statistical Manual of Mental Disorders (DSM). The fifth edition, known as DSM-5, offers a very detailed explanation that guides doctors to a diagnosis. You can also compare the current model of diagnosing depression to historical methods of diagnosis—how have these updates improved the way depression is treated?

Treatment Options for Depression

The first choice for depression treatment is generally an antidepressant medication. Selective serotonin reuptake inhibitors (SSRIs) are the most popular choice because they can be quite effective and tend to have fewer side effects than other types of antidepressants.

Psychotherapy, or talk therapy, is another effective and common choice. It is especially efficacious when combined with antidepressant therapy. Certain other treatments, such as electroconvulsive therapy (ECT) or vagus nerve stimulation (VNS), are most commonly used for patients who do not respond to more common forms of treatment.

Focusing on one of these treatments is an option for your depression research paper. Comparing and contrasting several different types of treatment can also make a good research title about depression.

A Word From Verywell

The topic of depression really can take you down many different roads. When making your final decision on which to pursue in your depression research paper, it's often helpful to start by listing a few areas that pique your interest.

From there, consider doing a little preliminary research. You may come across something that grabs your attention like a new study, a controversial topic you didn't know about, or something that hits a personal note. This will help you narrow your focus, giving you your final research title about depression.

Remes O, Mendes JF, Templeton P. Biological, psychological, and social determinants of depression: A review of recent literature . Brain Sci . 2021;11(12):1633. doi:10.3390/brainsci11121633

National Institute of Mental Health. Depression .

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition . American Psychiatric Association.

National Institute of Mental Health. Mental health medications .

Ferri, F. F. (2019). Ferri's Clinical Advisor 2020 E-Book: 5 Books in 1 . Netherlands: Elsevier Health Sciences.

By Nancy Schimelpfening Nancy Schimelpfening, MS is the administrator for the non-profit depression support group Depression Sanctuary. Nancy has a lifetime of experience with depression, experiencing firsthand how devastating this illness can be.  

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An Exploratory Study of Students with Depression in Undergraduate Research Experiences

• Katelyn M. Cooper
• Logan E. Gin
• M. Elizabeth Barnes
• Sara E. Brownell

*Address correspondence to: Katelyn M. Cooper ( E-mail Address: [email protected] ).

Department of Biology, University of Central Florida, Orlando, FL, 32816

Search for more papers by this author

Biology Education Research Lab, Research for Inclusive STEM Education Center, School of Life Sciences, Arizona State University, Tempe, AZ 85281

Depression is a top mental health concern among undergraduates and has been shown to disproportionately affect individuals who are underserved and underrepresented in science. As we aim to create a more inclusive scientific community, we argue that we need to examine the relationship between depression and scientific research. While studies have identified aspects of research that affect graduate student depression, we know of no studies that have explored the relationship between depression and undergraduate research. In this study, we sought to understand how undergraduates’ symptoms of depression affect their research experiences and how research affects undergraduates’ feelings of depression. We interviewed 35 undergraduate researchers majoring in the life sciences from 12 research-intensive public universities across the United States who identify with having depression. Using inductive and deductive coding, we identified that students’ depression affected their motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing in undergraduate research experiences. We found that students’ social connections, experiencing failure in research, getting help, receiving feedback, and the demands of research affected students’ depression. Based on this work, we articulate an initial set of evidence-based recommendations for research mentors to consider in promoting an inclusive research experience for students with depression.

INTRODUCTION

Depression is described as a common and serious mood disorder that results in persistent feelings of sadness and hopelessness, as well as a loss of interest in activities that one once enjoyed ( American Psychiatric Association [APA], 2013 ). Additional symptoms of depression include weight changes, difficulty sleeping, loss of energy, difficulty thinking or concentrating, feelings of worthlessness or excessive guilt, and suicidality ( APA, 2013 ). While depression results from a complex interaction of psychological, social, and biological factors ( World Health Organization, 2018 ), studies have shown that increased stress caused by college can be a significant contributor to student depression ( Dyson and Renk, 2006 ).

Depression is one of the top undergraduate mental health concerns, and the rate of depression among undergraduates continues to rise ( Center for Collegiate Mental Health, 2017 ). While we cannot discern whether these increasing rates of depression are due to increased awareness or increased incidence, it is clear that is a serious problem on college campuses. The percent of U.S. college students who self-reported a diagnosis with depression was recently estimated to be about 25% ( American College Health Association, 2019 ). However, higher rates have been reported, with one study estimating that up to 84% of undergraduates experience some level of depression ( Garlow et al. , 2008 ). Depression rates are typically higher among university students compared with the general population, despite being a more socially privileged group ( Ibrahim et al. , 2013 ). Prior studies have found that depression is negatively correlated with overall undergraduate academic performance ( Hysenbegasi et al. , 2005 ; Deroma et al. , 2009 ; American College Health Association, 2019 ). Specifically, diagnosed depression is associated with half a letter grade decrease in students’ grade point average ( Hysenbegasi et al. , 2005 ), and 21.6% of undergraduates reported that depression negatively affected their academic performance within the last year ( American College Health Association, 2019 ). Provided with a list of academic factors that may be affected by depression, students reported that depression contributed to lower exam grades, lower course grades, and not completing or dropping a course.

Students in the natural sciences may be particularly at risk for depression, given that such majors are noted to be particularly stressful due to their competitive nature and course work that is often perceived to “weed students out”( Everson et al. , 1993 ; Strenta et al. , 1994 ; American College Health Association, 2019 ; Seymour and Hunter, 2019 ). Science course instruction has also been described to be boring, repetitive, difficult, and math-intensive; these factors can create an environment that can trigger depression ( Seymour and Hewitt, 1997 ; Osborne and Collins, 2001 ; Armbruster et al ., 2009 ; Ceci and Williams, 2010 ). What also distinguishes science degree programs from other degree programs is that, increasingly, undergraduate research experiences are being proposed as an essential element of a science degree ( American Association for the Advancement of Science, 2011 ; President’s Council of Advisors on Science and Technology, 2012 ; National Academies of Sciences, Engineering, and Medicine [NASEM], 2017 ). However, there is some evidence that undergraduate research experiences can add to the stress of college for some students ( Cooper et al. , 2019c ). Students can garner multiple benefits from undergraduate research, including enhanced abilities to think critically ( Ishiyama, 2002 ; Bauer and Bennett, 2003 ; Brownell et al. , 2015 ), improved student learning ( Rauckhorst et al. , 2001 ; Brownell et al. , 2015 ), and increased student persistence in undergraduate science degree programs ( Jones et al. , 2010 ; Hernandez et al. , 2018 ). Notably, undergraduate research experiences are increasingly becoming a prerequisite for entry into medical and graduate programs in science, particularly elite programs ( Cooper et al. , 2019d ). Although some research experiences are embedded into formal lab courses as course-based undergraduate research experiences (CUREs; Auchincloss et al. , 2014 ; Brownell and Kloser, 2015 ), the majority likely entail working with faculty in their research labs. These undergraduate research experiences in faculty labs are often added on top of a student’s normal course work, so they essentially become an extracurricular activity that they have to juggle with course work, working, and/or personal obligations ( Cooper et al. , 2019c ). While the majority of the literature surrounding undergraduate research highlights undergraduate research as a positive experience ( NASEM, 2017 ), studies have demonstrated that undergraduate research experiences can be academically and emotionally challenging for students ( Mabrouk and Peters, 2000 ; Seymour et al. , 2004 ; Cooper et al. , 2019c ; Limeri et al. , 2019 ). In fact, 50% of students sampled nationally from public R1 institutions consider leaving their undergraduate research experience prematurely, and about half of those students, or 25% of all students, ultimately leave their undergraduate research experience ( Cooper et al. , 2019c ). Notably, 33.8% of these individuals cited a negative lab environment and 33.3% cited negative relationships with their mentors as factors that influenced their decision about whether to leave ( Cooper et al. , 2019c ). Therefore, students’ depression may be exacerbated in challenging undergraduate research experiences, because studies have shown that depression is positively correlated with student stress ( Hish et al. , 2019 ).

While depression has not been explored in the context of undergraduate research experiences, depression has become a prominent concern surrounding graduate students conducting scientific research. A recent study that examined the “graduate student mental health crisis” ( Flaherty, 2018 ) found that work–life balance and graduate students’ relationships with their research advisors may be contributing to their depression ( Evans et al. , 2018 ). Specifically, this survey of 2279 PhD and master’s students from diverse fields of study, including the biological/physical sciences, showed that 39% of graduate students have experienced moderate to severe depression. Fifty-five percent of the graduate students with depression who were surveyed disagreed with the statement “I have good work life balance,” compared to only 21% of students with depression who agreed. Additionally, the study highlighted that more students with depression disagreed than agreed with the following statements: their advisors provided “real” mentorship, their advisors provided ample support, their advisors positively impacted their emotional or mental well-being, their advisors were assets to their careers, and they felt valued by their mentors. Another recent study identified that depression severity in biomedical doctoral students was significantly associated with graduate program climate, a perceived lack of employment opportunities, and the quality of students’ research training environment ( Nagy et al. , 2019 ). Environmental stress, academic stress, and family and monetary stress have also been shown to be predictive of depression severity in biomedical doctoral students ( Hish et al. , 2019 ). Further, one study found that self-esteem is negatively correlated and stress is positively correlated with graduate student depression; presumably research environments that challenge students’ self-esteem and induce stress are likely contributing to depressive symptoms among graduate students ( Kreger, 1995 ). While these studies have focused on graduate students, and there are certainly notable distinctions between graduate and undergraduate research, the research-related factors that affect graduate student depression, including work–life balance, relationships with mentors, research environment, stress, and self-esteem, may also be relevant to depression among undergraduates conducting research. Importantly, undergraduates in the United States have reported identical levels of depression as graduate students but are often less likely to seek mental health care services ( Wyatt and Oswalt, 2013 ), which is concerning if undergraduate research experiences exacerbate depression.

Based on the literature on the stressors of undergraduate research experiences and the literature identifying some potential causes of graduate student depression, we identified three aspects of undergraduate research that may exacerbate undergraduates’ depression. Mentoring: Mentors can be an integral part of a students’ research experience, bolstering their connections with others in the science community, scholarly productivity, and science identity, as well as providing many other benefits ( Thiry and Laursen, 2011 ; Prunuske et al. , 2013 ; Byars-Winston et al. , 2015 ; Aikens et al. , 2016 , 2017 ; Thompson et al. , 2016 ; Estrada et al. , 2018 ). However, recent literature has highlighted that poor mentoring can negatively affect undergraduate researchers ( Cooper et al. , 2019c ; Limeri et al. , 2019 ). Specifically, one study of 33 undergraduate researchers who had conducted research at 10 institutions identified seven major ways that they experienced negative mentoring, which included absenteeism, abuse of power, interpersonal mismatch, lack of career support, lack of psychosocial support, misaligned expectations, and unequal treatment ( Limeri et al. , 2019 ). We hypothesize negative mentoring experiences may be particularly harmful for students with depression, because support, particularly social support, has been shown to be important for helping individuals with depression cope with difficult circumstances ( Aneshensel and Stone, 1982 ; Grav et al. , 2012 ). Failure: Experiencing failure has been hypothesized to be an important aspect of undergraduate research experiences that may help students develop some the most distinguishing abilities of outstanding scientists, such as coping with failure, navigating challenges, and persevering ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, experiencing failure and the stress and fatigue that often accompany it may be particularly tough for students with depression ( Aldwin and Greenberger, 1987 ; Mongrain and Blackburn, 2005 ). Lab environment: Fairness, inclusion/exclusion, and social support within one’s organizational environment have been shown to be key factors that cause people to either want to remain in the work place and be productive or to want to leave ( Barak et al. , 2006 ; Cooper et al. , 2019c ). We hypothesize that dealing with exclusion or a lack of social support may exacerbate depression for some students; patients with clinical depression react to social exclusion with more pronounced negative emotions than do individuals without clinical depression ( Jobst et al. , 2015 ). While there are likely other aspects of undergraduate research that affect student depression, we hypothesize that these factors have the potential to exacerbate negative research experiences for students with depression.

Depression has been shown to disproportionately affect many populations that are underrepresented or underserved within the scientific community, including females ( American College Health Association, 2018 ; Evans et al. , 2018 ), first-generation college students ( Jenkins et al. , 2013 ), individuals from low socioeconomic backgrounds ( Eisenberg et al. , 2007 ), members of the LGBTQ+ community ( Eisenberg et al. , 2007 ; Evans et al. , 2018 ), and people with disabilities ( Turner and Noh, 1988 ). Therefore, as the science community strives to be more diverse and inclusive ( Intemann, 2009 ), it is important that we understand more about the relationship between depression and scientific research, because negative experiences with depression in scientific research may be contributing to the underrepresentation of these groups. Specifically, more information is needed about how the research process and environment of research experiences may affect depression.

Given the high rate of depression among undergraduates, the links between depression and graduate research, the potentially challenging environment of undergraduate research, and how depression could disproportionately impact students from underserved communities, it is imperative to begin to explore the relationship between scientific research and depression among undergraduates to create research experiences that could maximize student success. In this exploratory interview study, we aimed to 1) describe how undergraduates’ symptoms of depression affect their research experiences, 2) understand how undergraduate research affects students’ feelings of depression, and 3) identify recommendations based on the literature and undergraduates’ reported experiences to promote a positive research experience for students with depression.

This study was done with an approved Arizona State University Institutional Review Board protocol #7247.

In Fall 2018, we surveyed undergraduate researchers majoring in the life sciences across 25 research-intensive (R1) public institutions across the United States (specific details about the recruitment of the students who completed the survey can be found in Cooper et al. (2019c) ). The survey asked students for their opinions about their undergraduate research experiences and their demographic information and whether they would be interested in participating in a follow-up interview related to their research experiences. For the purpose of this study, we exclusively interviewed students about their undergraduate research experiences in faculty member labs; we did not consider students’ experiences in CUREs. Of the 768 undergraduate researchers who completed the survey, 65% ( n = 496) indicated that they would be interested in participating in a follow-up interview. In Spring 2019, we emailed the 496 students, explaining that we were interested in interviewing students with depression about their experiences in undergraduate research. Our specific prompt was: “If you identify as having depression, we would be interested in hearing about your experience in undergraduate research in a 30–60 minute online interview.” We did not define depression in our email recruitment because we conducted think-aloud interviews with four undergraduates who all correctly interpreted what we meant by depression ( APA, 2013 ). We had 35 students agree to participate in the interview study. The interview participants represented 12 of the 25 R1 public institutions that were represented in the initial survey.

Student Interviews

We developed an interview script to explore our research questions. Specifically, we were interested in how students’ symptoms of depression affect their research experiences, how undergraduate research negatively affects student depression, and how undergraduate research positively affects student depression.

We recognized that mental health, and specifically depression, can be a sensitive topic to discuss with undergraduates, and therefore we tried to minimize any discomfort that the interviewees might experience during the interview. Specifically, we conducted think-aloud interviews with three graduate students who self-identified with having depression at the time of the interview. We asked them to note whether any interview questions made them uncomfortable. We also sought their feedback on questions given their experiences as persons with depression who had once engaged in undergraduate research. We revised the interview protocol after each think-aloud interview. Next, we conducted four additional think-aloud interviews with undergraduates conducting basic science or biology education research who identified with having depression to establish cognitive validity of the questions and to elicit additional feedback about any questions that might make someone uncomfortable. The questions were revised after each think-aloud interview until no question was unclear or misinterpreted by the students and we were confident that the questions minimized students’ potential discomfort ( Trenor et al. , 2011 ). A copy of the final interview script can be found in the Supplemental Material.

All interviews were individually conducted by one of two researchers (K.M.C. and L.E.G.) who conducted the think-aloud interviews together to ensure that their interviewing practices were as similar as possible. The interviews were approximately an hour long, and students received a $15 gift card for their participation.

Personal, Research, and Depression Demographics

All student demographics and information about students’ research experiences were collected using the survey distributed to students in Fall 2018. We collected personal demographics, including the participants’ gender, race/ethnicity, college generation status, transfer status, financial stability, year in college, major, and age. We also collected information about the students’ research experiences, including the length of their first research experiences, the average number of hours they spend in research per week, how they were compensated for research, who their primary mentors were, and the focus areas of their research.

In the United States, mental healthcare is disproportionately unavailable to Black and Latinx individuals, as well as those who come from low socioeconomic backgrounds ( Kataoka et al. , 2002 ; Howell and McFeeters, 2008 ; Santiago et al. , 2013 ). Therefore, to minimize a biased sample, we invited anyone who identified with having depression to participate in our study; we did not require students to be diagnosed with depression or to be treated for depression in order to participate. However, we did collect information about whether students had been formally diagnosed with depression and whether they had been treated for depression. After the interview, all participants were sent a link to a short survey that asked them if they had ever been diagnosed with depression and how, if at all, they had ever been treated for depression. A copy of these survey questions can be found in the Supplemental Material. The combined demographic information of the participants is in Table 1 . The demographics for each individual student can be found in the Supplemental Material.

a Students reported the time they had spent in research 6 months before being interviewed and only reported on the length of time of their first research experiences.

b Students were invited to report multiple ways in which they were treated for their depression; other treatments included lifestyle changes and meditation.

c Students were invited to report multiple means of compensation for their research if they had been compensated for their time in different ways.

d Students were asked whether they felt financially stable, particularly during the undergraduate research experience.

e Students reported who they work/worked with most closely during their research experiences.

f Staff members included lab coordinators or lab managers.

g Other focus areas of research included sociology, linguistics, psychology, and public health.

Interview Analysis

The initial interview analysis aimed to explore each idea that a participant expressed ( Charmaz, 2006 ) and to identify reoccurring ideas throughout the interviews. First, three authors (K.M.C., L.E.G., and S.E.B.) individually reviewed a different set of 10 interviews and took detailed analytic notes ( Birks and Mills, 2015 ). Afterward, the authors compared their notes and identified reoccurring themes throughout the interviews using open coding methods ( Saldaña, 2015 ).

Once an initial set of themes was established, two researchers (K.M.C. and L.E.G.) individually reviewed the same set of 15 randomly selected interviews to validate the themes identified in the initial analysis and to screen for any additional themes that the initial analysis may have missed. Each researcher took detailed analytic notes throughout the review of an interview, which they discussed after reviewing each interview. The researchers compared what quotes from each interview they categorized into each theme. Using constant comparison methods, they assigned quotes to each theme and constantly compared the quotes to ensure that each quote fit within the description of the theme ( Glesne and Peshkin, 1992 ). In cases in which quotes were too different from other quotes, a new theme was created. This approach allowed for multiple revisions of the themes and allowed the authors to define a final set of codes; the researchers created a final codebook with refined definitions of emergent themes (the final coding rubric can be found in the Supplemental Material). Once the final codebook was established, the researchers (K.M.C. and L.E.G.) individually coded seven additional interviews (20% of all interviews) using the coding rubric. The researchers compared their codes, and their Cohen’s κ interrater score for these seven interviews was at an acceptable level (κ  =  0.88; Landis and Koch, 1977 ). One researcher (L.E.G.) coded the remaining 28 out of 35 interviews. The researchers determined that data saturation had been reached with the current sample and no further recruitment was needed ( Guest et al. , 2006 ). We report on themes that were mentioned by at least 20% of students in the interview study. In the Supplemental Material, we provide the final coding rubric with the number of participants whose interview reflected each theme ( Hannah and Lautsch, 2011 ). Reporting the number of individuals who reported themes within qualitative data can lead to inaccurate conclusions about the generalizability of the results to a broader population. These qualitative data are meant to characterize a landscape of experiences that students with depression have in undergraduate research rather than to make claims about the prevalence of these experiences ( Glesne and Peshkin, 1992 ). Because inferences about the importance of these themes cannot be drawn from these counts, they are not included in the results of the paper ( Maxwell, 2010 ). Further, the limited number of interviewees made it not possible to examine whether there were trends based on students’ demographics or characteristics of their research experiences (e.g., their specific area of study). Quotes were lightly edited for clarity by inserting clarification brackets and using ellipses to indicate excluded text. Pseudonyms were given to all students to protect their privacy.

The Effect of Depressive Symptoms on Undergraduate Research

We asked students to describe the symptoms associated with their depression. Students described experiencing anxiety that is associated with their depression; this could be anxiety that precedes their depression or anxiety that results from a depressive episode or a period of time when an individual has depression symptoms. Further, students described difficulty getting out of bed or leaving the house, feeling tired, a lack of motivation, being overly self-critical, feeling apathetic, and having difficulty concentrating. We were particularly interested in how students’ symptoms of depression affected their experiences in undergraduate research. During the think-aloud interviews that were conducted before the interview study, graduate and undergraduate students consistently described that their depression affected their motivation in research, their creativity in research, and their productivity in research. Therefore, we explicitly asked undergraduate researchers how, if at all, their depression affected these three factors. We also asked students to describe any additional ways in which their depression affected their research experiences. Undergraduate researchers commonly described five additional ways in which their depression affected their research; for a detailed description of each way students’ research was affected and for example quotes, see Table 2 . Students described that their depression negatively affected their productivity in the lab. Commonly, students described that their productivity was directly affected by a lack of motivation or because they felt less creative, which hindered the research process. Additionally, students highlighted that they were sometimes less productive because their depression sometimes caused them to struggle to engage intellectually with their research or caused them to have difficulty remembering or concentrating; students described that they could do mundane or routine tasks when they felt depressed, but that they had difficulty with more complex and intellectually demanding tasks. However, students sometimes described that even mundane tasks could be difficult when they were required to remember specific steps; for example, some students struggled recalling a protocol from memory when their depression was particularly severe. Additionally, students noted that their depression made them more self-conscious, which sometimes held them back from sharing research ideas with their mentors or from taking risks such as applying to competitive programs. In addition to being self-conscious, students highlighted that their depression caused them to be overly self-critical, and some described experiencing imposter phenomenon ( Clance and Imes, 1978 ) or feeling like they were not talented enough to be in research and were accepted into a lab by a fluke or through luck. Finally, students described that depression often made them feel less social, and they struggled to socially engage with other members of the lab when they were feeling down.

The Effect of Undergraduate Research Experiences on Student Depression

We also wanted to explore how research impacted students’ feelings of depression. Undergraduates described how research both positively and negatively affected their depression. In the following sections, we present aspects of undergraduate research and examine how each positively and/or negatively affected students’ depression using embedded student quotes to highlight the relationships between related ideas.

Lab Environment: Relationships with Others in the Lab.

Some aspects of the lab environment, which we define as students’ physical, social, or psychological research space, could be particularly beneficial for students with depression.

Specifically, undergraduate researchers perceived that comfortable and positive social interactions with others in the lab helped their depression. Students acknowledged how beneficial their relationships with graduate students and postdocs could be.

Marta: “I think always checking in on undergrads is important. It’s really easy [for us] to go a whole day without talking to anybody in the lab. But our grad students are like ‘Hey, what’s up? How’s school? What’s going on?’ (…) What helps me the most is having that strong support system. Sometimes just talking makes you feel better, but also having people that believe in you can really help you get out of that negative spiral. I think that can really help with depression.”

Kelley: “I know that anytime I need to talk to [my postdoc mentors] about something they’re always there for me. Over time we’ve developed a relationship where I know that outside of work and outside of the lab if I did want to talk to them about something I could talk to them. Even just talking to someone about hobbies and having that relationship alone is really helpful [for depression].”

In addition to highlighting the importance of developing relationships with graduate students or postdocs in the lab, students described that forming relationships with other undergraduates in the lab also helped their depression. Particularly, students described that other undergraduate researchers often validated their feelings about research, which in turn helped them realize that what they are thinking or feeling is normal, which tended to alleviate their negative thoughts. Interestingly, other undergraduates experiencing the same issues could sometimes help buffer them from perceiving that a mentor did not like them or that they were uniquely bad at research. In this article, we use the term “mentor” to refer to anyone who students referred to in the interviews as being their mentors or managing their research experiences; this includes graduate students, postdoctoral scholars, lab managers, and primary investigators (PIs).

Abby: “One of my best friends is in the lab with me.  A lot of that friendship just comes from complaining about our stress with the lab and our annoyance with people in the lab. Like when we both agree like, ‘Yeah, the grad students were really off today, it wasn’t us,’ that helps. ‘It wasn’t me, it wasn’t my fault that we were having a rough day in lab; it was the grad students.’ Just being able to realize, ‘Hey, this isn’t all caused by us,’ you know? (…) We understand the stresses in the lab. We understand the details of what each other are doing in the lab, so when something doesn’t work out, we understand that it took them like eight hours to do that and it didn’t work. We provide empathy on a different level.”

Meleana: “It’s great to have solidarity in being confused about something, and it’s just that is a form of validation for me too. When we leave a lab meeting and I look at [another undergrad] I’m like, ‘Did you understand anything that they were just saying?’ And they’re like, ‘Oh, no.’ (…) It’s just really validating to hear from the other undergrads that we all seem to be struggling with the same things.”

Developing positive relationships with faculty mentors or PIs also helped alleviate some students’ depressive feelings, particularly when PIs shared their own struggles with students. This also seemed to normalize students’ concerns about their own experiences.

Alexandra: “[Talking with my PI] is helpful because he would talk about his struggles, and what he faced. A lot of it was very similar to my struggles.  For example, he would say, ‘Oh, yeah, I failed this exam that I studied so hard for. I failed the GRE and I paid so much money to prepare for it.’ It just makes [my depression] better, like okay, this is normal for students to go through this. It’s not an out of this world thing where if you fail, you’re a failure and you can’t move on from it.”

Students’ relationships with others in the lab did not always positively impact their depression. Students described instances when the negative moods of the graduate students and PIs would often set the tone of the lab, which in turn worsened the mood of the undergraduate researchers.

Abby: “Sometimes [the grad students] are not in a good mood. The entire vibe of the lab is just off, and if you make a joke and it hits somebody wrong, they get all mad. It really depends on the grad students and the leadership and the mood that they’re in.”

Interviewer: “How does it affect your depression when the grad students are in a bad mood?”

Abby: “It definitely makes me feel worse. It feels like, again, that I really shouldn’t go ask them for help because they’re just not in the mood to help out. It makes me have more pressure on myself, and I have deadlines I need to meet, but I have a question for them, but they’re in a bad mood so I can’t ask. That’s another day wasted for me and it just puts more stress, which just adds to the depression.”

Additionally, some students described even more concerning behavior from research mentors, which negatively affected their depression.

Julie: “I had a primary investigator who is notorious in the department for screaming at people, being emotionally abusive, unreasonable, et cetera. (…) [He was] kind of harassing people, demeaning them, lying to them, et cetera, et cetera. (…) Being yelled at and constantly demeaned and harassed at all hours of the day and night, that was probably pretty bad for me.”

While the relationships between undergraduates and graduate, postdoc, and faculty mentors seemed to either alleviate or worsen students’ depressive symptoms, depending on the quality of the relationship, students in this study exclusively described their relationships with other undergraduates as positive for their depression. However, students did note that undergraduate research puts some of the best and brightest undergraduates in the same environment, which can result in students comparing themselves with their peers. Students described that this comparison would often lead them to feel badly about themselves, even though they would describe their personal relationship with a person to be good.

Meleana: “In just the research field in general, just feeling like I don’t really measure up to the people around me [can affect my depression]. A lot of the times it’s the beginning of a little spiral, mental spiral. There are some past undergrads that are talked about as they’re on this pedestal of being the ideal undergrads and that they were just so smart and contributed so much to the lab. I can never stop myself from wondering like, ‘Oh, I wonder if I’m having a contribution to the lab that’s similar or if I’m just another one of the undergrads that does the bare minimum and passes through and is just there.’”

Natasha: “But, on the other hand, [having another undergrad in the lab] also reminded me constantly that some people are invested in this and meant to do this and it’s not me. And that some people know a lot more than I do and will go further in this than I will.”

While students primarily expressed that their relationships with others in the lab affected their depression, some students explained that they struggled most with depression when the lab was empty; they described that they did not like being alone in the lab, because a lack of stimulation allowed their minds to be filled with negative thoughts.

Mia: “Those late nights definitely didn’t help [my depression]. I am alone, in the entire building.  I’m left alone to think about my thoughts more, so not distracted by talking to people or interacting with people. I think more about how I’m feeling and the lack of progress I’m making, and the hopelessness I’m feeling. That kind of dragged things on, and I guess deepened my depression.”

Freddy: “Often times when I go to my office in the evening, that is when I would [ sic ] be prone to be more depressed. It’s being alone. I think about myself or mistakes or trying to correct mistakes or whatever’s going on in my life at the time. I become very introspective. I think I’m way too self-evaluating, way too self-deprecating and it’s when I’m alone when those things are really, really triggered. When I’m talking with somebody else, I forget about those things.”

In sum, students with depression highlighted that a lab environment full of positive and encouraging individuals was helpful for their depression, whereas isolating or competitive environments and negative interactions with others often resulted in more depressive feelings.

Doing Science: Experiencing Failure in Research, Getting Help, Receiving Feedback, Time Demands, and Important Contributions.

In addition to the lab environment, students also described that the process of doing science could affect their depression. Specifically, students explained that a large contributor to their depression was experiencing failure in research.

Interviewer: “Considering your experience in undergraduate research, what tends to trigger your feelings of depression?”

Heather: “Probably just not getting things right. Having to do an experiment over and over again. You don’t get the results you want. (…) The work is pretty meticulous and it’s frustrating when I do all this work, I do a whole experiment, and then I don’t get any results that I can use. That can be really frustrating. It adds to the stress. (…) It’s hard because you did all this other stuff before so you can plan for the research, and then something happens and all the stuff you did was worthless basically.”

Julie: “I felt very negatively about myself [when a project failed] and pretty panicked whenever something didn’t work because I felt like it was a direct reflection on my effort and/or intelligence, and then it was a big glaring personal failure.”

Students explained that their depression related to failing in research was exacerbated if they felt as though they could not seek help from their research mentors. Perceived insufficient mentor guidance has been shown to be a factor influencing student intention to leave undergraduate research ( Cooper et al. , 2019c ). Sometimes students talked about their research mentors being unavailable or unapproachable.

Michelle: “It just feels like [the graduate students] are not approachable. I feel like I can’t approach them to ask for their understanding in a certain situation. It makes [my depression] worse because I feel like I’m stuck, and that I’m being limited, and like there’s nothing I can do. So then I kind of feel like it’s my fault that I can’t do anything.”

Other times, students described that they did not seek help in fear that they would be negatively evaluated in research, which is a fear of being judged by others ( Watson and Friend, 1969 ; Weeks et al. , 2005 ; Cooper et al. , 2018 ). That is, students fear that their mentor would think negatively about them or judge them if they were to ask questions that their mentor thought they should know the answer to.

Meleana: “I would say [my depression] tends to come out more in being more reserved in asking questions because I think that comes more like a fear-based thing where I’m like, ‘Oh, I don’t feel like I’m good enough and so I don’t want to ask these questions because then my mentors will, I don’t know, think that I’m dumb or something.’”

Conversely, students described that mentors who were willing to help them alleviated their depressive feelings.

Crystal: “Yeah [my grad student] is always like, ‘Hey, I can check in on things in the lab because you’re allowed to ask me for that, you’re not totally alone in this,’ because he knows that I tend to take on all this responsibility and I don’t always know how to ask for help. He’s like, ‘You know, this is my lab too and I am here to help you as well,’ and just reminds me that I’m not shouldering this burden by myself.”

Ashlyn: “The graduate student who I work with is very kind and has a lot of patience and he really understands a lot of things and provides simple explanations. He does remind me about things and he will keep on me about certain tasks that I need to do in an understanding way, and it’s just because he’s patient and he listens.”

In addition to experiencing failure in science, students described that making mistakes when doing science also negatively affected their depression.

Abby: “I guess not making mistakes on experiments [is important in avoiding my depression]. Not necessarily that your experiment didn’t turn out to produce the data that you wanted, but just adding the wrong enzyme or messing something up like that. It’s like, ‘Oh, man,’ you know? You can get really down on yourself about that because it can be embarrassing.”

Commonly, students described that the potential for making mistakes increased their stress and anxiety regarding research; however, they explained that how other people responded to a potential mistake was what ultimately affected their depression.

Briana: “Sometimes if I made a mistake in correctly identifying an eye color [of a fly], [my PI] would just ridicule me in front of the other students. He corrected me but his method of correcting was very discouraging because it was a ridicule. It made the others laugh and I didn’t like that.”

Julie: “[My PI] explicitly [asked] if I had the dedication for science. A lot of times he said I had terrible judgment. A lot of times he said I couldn’t be trusted. Once I went to a conference with him, and, unfortunately, in front of another professor, he called me a klutz several times and there was another comment about how I never learn from my mistakes.”

When students did do things correctly, they described how important it could be for them to receive praise from their mentors. They explained that hearing praise and validation can be particularly helpful for students with depression, because their thoughts are often very negative and/or because they have low self-esteem.

Crystal: “[Something that helps my depression is] I have text messages from [my graduate student mentor] thanking me [and another undergraduate researcher] for all of the work that we’ve put in, that he would not be able to be as on track to finish as he is if he didn’t have our help.”

Interviewer: “Why is hearing praise from your mentor helpful?”

Crystal: “Because a lot of my depression focuses on everybody secretly hates you, nobody likes you, you’re going to die alone. So having that validation [from my graduate mentor] is important, because it flies in the face of what my depression tells me.”

Brian: “It reminds you that you exist outside of this negative world that you’ve created for yourself, and people don’t see you how you see yourself sometimes.”

Students also highlighted how research could be overwhelming, which negatively affected their depression. Particularly, students described that research demanded a lot of their time and that their mentors did not always seem to be aware that they were juggling school and other commitments in addition to their research. This stress exacerbated their depression.

Rose: “I feel like sometimes [my grad mentors] are not very understanding because grad students don’t take as many classes as [undergrads] do. I think sometimes they don’t understand when I say I can’t come in at all this week because I have finals and they’re like, ‘Why though?’”

Abby: “I just think being more understanding of student life would be great. We have classes as well as the lab, and classes are the priority. They forget what it’s like to be a student. You feel like they don’t understand and they could never understand when you say like, ‘I have three exams this week,’ and they’re like, ‘I don’t care. You need to finish this.’”

Conversely, some students reported that their research labs were very understanding of students’ schedules. Interestingly, these students talked most about how helpful it was to be able to take a mental health day and not do research on days when they felt down or depressed.

Marta: “My lab tech is very open, so she’ll tell us, ‘I can’t come in today. I have to take a mental health day.’ So she’s a really big advocate for that. And I think I won’t personally tell her that I’m taking a mental health day, but I’ll say, ‘I can’t come in today, but I’ll come in Friday and do those extra hours.’ And she’s like, ‘OK great, I’ll see you then.’  And it makes me feel good, because it helps me take care of myself first and then I can take care of everything else I need to do, which is amazing.”

Meleana: “Knowing that [my mentors] would be flexible if I told them that I’m crazy busy and can’t come into work nearly as much this week [helps my depression]. There is flexibility in allowing me to then care for myself.”

Interviewer: “Why is the flexibility helpful given the depression?”

Meleana: “Because sometimes for me things just take a little bit longer when I’m feeling down. I’m just less efficient to be honest, and so it’s helpful if I feel like I can only go into work for 10 hours in a week. It declutters my brain a little bit to not have to worry about all the things I have to do in work in addition the things that I need to do for school or clubs, or family or whatever.”

Despite the demanding nature of research, a subset of students highlighted that their research and research lab provided a sense of stability or familiarity that distracted them from their depression.

Freddy: “I’ll [do research] to run away from those [depressive] feelings or whatever. (…) I find sadly, I hate to admit it, but I do kind of run to [my lab]. I throw myself into work to distract myself from the feelings of depression and sadness.”

Rose: “When you’re sad or when you’re stressed you want to go to things you’re familiar with. So because lab has always been in my life, it’s this thing where it’s going to be there for me I guess. It’s like a good book that you always go back to and it’s familiar and it makes you feel good. So that’s how lab is. It’s not like the greatest thing in the world but it’s something that I’m used to, which is what I feel like a lot of people need when they’re sad and life is not going well.”

Many students also explained that research positively affects their depression because they perceive their research contribution to be important.

Ashlyn: “I feel like I’m dedicating myself to something that’s worthy and something that I believe in. It’s really important because it contextualizes those times when I am feeling depressed. It’s like, no, I do have these better things that I’m working on. Even when I don’t like myself and I don’t like who I am, which is again, depression brain, I can at least say, ‘Well, I have all these other people relying on me in research and in this area and that’s super important.’”

Jessica: “I mean, it just felt like the work that I was doing had meaning and when I feel like what I’m doing is actually going to contribute to the world, that usually really helps with [depression] because it’s like not every day you can feel like you’re doing something impactful.”

In sum, students highlighted that experiencing failure in research and making mistakes negatively contributed to depression, especially when help was unavailable or research mentors had a negative reaction. Additionally, students acknowledged that the research could be time-consuming, but that research mentors who were flexible helped assuage depressive feelings that were associated with feeling overwhelmed. Finally, research helped some students’ depression, because it felt familiar, provided a distraction from depression, and reminded students that they were contributing to a greater cause.

We believe that creating more inclusive research environments for students with depression is an important step toward broadening participation in science, not only to ensure that we are not discouraging students with depression from persisting in science, but also because depression has been shown to disproportionately affect underserved and underrepresented groups in science ( Turner and Noh, 1988 ; Eisenberg et al. , 2007 ; Jenkins et al. , 2013 ; American College Health Association, 2018 ). We initially hypothesized that three features of undergraduate research—research mentors, the lab environment, and failure—may have the potential to exacerbate student depression. We found this to be true; students highlighted that their relationships with their mentors as well as the overall lab environment could negatively affect their depression, but could also positively affect their research experiences. Students also noted that they struggled with failure, which is likely true of most students, but is known to be particularly difficult for students with depression ( Elliott et al. , 1997 ). We expand upon our findings by integrating literature on depression with the information that students provided in the interviews about how research mentors can best support students. We provide a set of evidence-based recommendations focused on mentoring, the lab environment, and failure for research mentors wanting to create more inclusive research environments for students with depression. Notably, only the first recommendation is specific to students with depression; the others reflect recommendations that have previously been described as “best practices” for research mentors ( NASEM, 2017 , 2019 ; Sorkness et al. , 2017 ) and likely would benefit most students. However, we examine how these recommendations may be particularly important for students with depression. As we hypothesized, these recommendations directly address three aspects of research: mentors, lab environment, and failure. A caveat of these recommendations is that more research needs to be done to explore the experiences of students with depression and how these practices actually impact students with depression, but our national sample of undergraduate researchers with depression can provide an initial starting point for a discussion about how to improve research experiences for these students.

Recommendations to Make Undergraduate Research Experiences More Inclusive for Students with Depression

Recognize student depression as a valid illness..

Allow students with depression to take time off of research by simply saying that they are sick and provide appropriate time for students to recover from depressive episodes. Also, make an effort to destigmatize mental health issues.

Undergraduate researchers described both psychological and physical symptoms that manifested as a result of their depression and highlighted how such symptoms prevented them from performing to their full potential in undergraduate research. For example, students described how their depression would cause them to feel unmotivated, which would often negatively affect their research productivity. In cases in which students were motivated enough to come in and do their research, they described having difficulty concentrating or engaging in the work. Further, when doing research, students felt less creative and less willing to take risks, which may alter the quality of their work. Students also sometimes struggled to socialize in the lab. They described feeling less social and feeling overly self-critical. In sum, students described that, when they experienced a depressive episode, they were not able to perform to the best of their ability, and it sometimes took a toll on them to try to act like nothing was wrong, when they were internally struggling with depression. We recommend that research mentors treat depression like any other physical illness; allowing students the chance to recover when they are experiencing a depressive episode can be extremely important to students and can allow them to maximize their productivity upon returning to research ( Judd et al. , 2000 ). Students explained that if they are not able to take the time to focus on recovering during a depressive episode, then they typically continue to struggle with depression, which negatively affects their research. This sentiment is echoed by researchers in psychiatry who have found that patients who do not fully recover from a depressive episode are more likely to relapse and to experience chronic depression ( Judd et al. , 2000 ). Students described not doing tasks or not showing up to research because of their depression but struggling with how to share that information with their research mentors. Often, students would not say anything, which caused them anxiety because they were worried about what others in the lab would say to them when they returned. Admittedly, many students understood why this behavior would cause their research mentors to be angry or frustrated, but they weighed the consequences of their research mentors’ displeasure against the consequences of revealing their depression and decided it was not worth admitting to being depressed. This aligns with literature that suggests that when individuals have concealable stigmatized identities, or identities that can be hidden and that carry negative stereotypes, such as depression, they will often keep them concealed to avoid negative judgment or criticism ( Link and Phelan, 2001 ; Quinn and Earnshaw, 2011 ; Jones and King, 2014 ; Cooper and Brownell, 2016 ; Cooper et al. , 2019b ; Cooper et al ., unpublished data ). Therefore, it is important for research mentors to be explicit with students that 1) they recognize mental illness as a valid sickness and 2) that students with mental illness can simply explain that they are sick if they need to take time off. This may be useful to overtly state on a research website or in a research syllabus, contract, or agreement if mentors use such documents when mentoring undergraduates in their lab. Further, research mentors can purposefully work to destigmatize mental health issues by explicitly stating that struggling with mental health issues, such as depression and anxiety, is common. While we do not recommend that mentors ask students directly about depression, because this can force students to share when they are not comfortable sharing, we do recommend providing opportunities for students to reveal their depression ( Chaudoir and Fisher, 2010 ). Mentors can regularly check in with students about how they’re doing, and talk openly about the importance of mental health, which may increase the chance that students may feel comfortable revealing their depression ( Chaudoir and Quinn, 2010 ; Cooper et al ., unpublished data ).

Foster a Positive Lab Environment.

Encourage positivity in the research lab, promote working in shared spaces to enhance social support among lab members, and alleviate competition among undergraduates.

Students in this study highlighted that the “leadership” of the lab, meaning graduate students, postdocs, lab managers, and PIs, were often responsible for establishing the tone of the lab; that is, if they were in a bad mood it would trickle down and negatively affect the moods of the undergraduates. Explicitly reminding lab leadership that their moods can both positively and negatively affect undergraduates may be important in establishing a positive lab environment. Further, students highlighted how they were most likely to experience negative thoughts when they were alone in the lab. Therefore, it may be helpful to encourage all lab members to work in a shared space to enhance social interactions among students and to maximize the likelihood that undergraduates have access to help when needed. A review of 51 studies in psychiatry supported our undergraduate researchers’ perceptions that social relationships positively impacted their depression; the study found that perceived emotional support (e.g., someone available to listen or give advice), perceived instrumental support (e.g., someone available to help with tasks), and large diverse social networks (e.g., being socially connected to a large number of people) were significantly protective against depression ( Santini et al. , 2015 ). Additionally, despite forming positive relationships with other undergraduates in the lab, many undergraduate researchers admitted to constantly comparing themselves with other undergraduates, which led them to feel inferior, negatively affecting their depression. Some students talked about mentors favoring current undergraduates or talking positively about past undergraduates, which further exacerbated their feelings of inferiority. A recent study of students in undergraduate research experiences highlighted that inequitable distribution of praise to undergraduates can create negative perceptions of lab environments for students (Cooper et al. , 2019). Further, the psychology literature has demonstrated that when people feel insecure in their social environments, it can cause them to focus on a hierarchical view of themselves and others, which can foster feelings of inferiority and increase their vulnerability to depression ( Gilbert et al. , 2009 ). Thus, we recommend that mentors be conscious of their behaviors so that they do not unintentionally promote competition among undergraduates or express favoritism toward current or past undergraduates. Praise is likely best used without comparison with others and not done in a public way, although more research on the impact of praise on undergraduate researchers needs to be done. While significant research has been done on mentoring and mentoring relationships in the context of undergraduate research ( Byars-Winston et al. , 2015 ; Aikens et al. , 2017 ; Estrada et al. , 2018 ; Limeri et al. , 2019 ; NASEM, 2019 ), much less has been done on the influence of the lab environment broadly and how people in nonmentoring roles can influence one another. Yet, this study indicates the potential influence of many different members of the lab, not only their mentors, on students with depression.

Develop More Personal Relationships with Undergraduate Researchers and Provide Sufficient Guidance.

Make an effort to establish more personal relationships with undergraduates and ensure that they perceive that they have access to sufficient help and guidance with regard to their research.

When we asked students explicitly how research mentors could help create more inclusive environments for undergraduate researchers with depression, students overwhelmingly said that building mentor–student relationships would be extremely helpful. Students suggested that mentors could get to know students on a more personal level by asking about their career interests or interests outside of academia. Students also remarked that establishing a more personal relationship could help build the trust needed in order for undergraduates to confide in their research mentors about their depression, which they perceived would strengthen their relationships further because they could be honest about when they were not feeling well or their mentors might even “check in” with them in times where they were acting differently than normal. This aligns with studies showing that undergraduates are most likely to reveal a stigmatized identity, such as depression, when they form a close relationship with someone ( Chaudoir and Quinn, 2010 ). Many were intimidated to ask for research-related help from their mentors and expressed that they wished they had established a better relationship so that they would feel more comfortable. Therefore, we recommend that research mentors try to establish relationships with their undergraduates and explicitly invite them to ask questions or seek help when needed. These recommendations are supported by national recommendations for mentoring ( NASEM, 2019 ) and by literature that demonstrates that both social support (listening and talking with students) and instrumental support (providing students with help) have been shown to be protective against depression ( Santini et al. , 2015 ).

Treat Undergraduates with Respect and Remember to Praise Them.

Avoid providing harsh criticism and remember to praise undergraduates. Students with depression often have low self-esteem and are especially self-critical. Therefore, praise can help calibrate their overly negative self-perceptions.

Students in this study described that receiving criticism from others, especially harsh criticism, was particularly difficult for them given their depression. Multiple studies have demonstrated that people with depression can have an abnormal or maladaptive response to negative feedback; scientists hypothesize that perceived failure on a particular task can trigger failure-related thoughts that interfere with subsequent performance ( Eshel and Roiser, 2010 ). Thus, it is important for research mentors to remember to make sure to avoid unnecessarily harsh criticisms that make students feel like they have failed (more about failure is described in the next recommendation). Further, students with depression often have low self-esteem or low “personal judgment of the worthiness that is expressed in the attitudes the individual holds towards oneself” ( Heatherton et al. , 2003 , p. 220; Sowislo and Orth, 2013 ). Specifically, a meta-analysis of longitudinal studies found that low self-esteem is predictive of depression ( Sowislo and Orth, 2013 ), and depression has also been shown to be highly related to self-criticism ( Luyten et al. , 2007 ). Indeed, nearly all of the students in our study described thinking that they are “not good enough,” “worthless,” or “inadequate,” which is consistent with literature showing that people with depression are self-critical ( Blatt et al. , 1982 ; Gilbert et al. , 2006 ) and can be less optimistic of their performance on future tasks and rate their overall performance on tasks less favorably than their peers without depression ( Cane and Gotlib, 1985 ). When we asked students what aspects of undergraduate research helped their depression, students described that praise from their mentors was especially impactful, because they thought so poorly of themselves and they needed to hear something positive from someone else in order to believe it could be true. Praise has been highlighted as an important aspect of mentoring in research for many years ( Ashford, 1996 ; Gelso and Lent, 2000 ; Brown et al. , 2009 ) and may be particularly important for students with depression. In fact, praise has been shown to enhance individuals’ motivation and subsequent productivity ( Hancock, 2002 ; Henderlong and Lepper, 2002 ), factors highlighted by students as negatively affecting their depression. However, something to keep in mind is that a student with depression and a student without depression may process praise differently. For a student with depression, a small comment that praises the student’s work may not be sufficient for the student to process that comment as praise. People with depression are hyposensitive to reward or have reward-processing deficits ( Eshel and Roiser, 2010 ); therefore, praise may affect students without depression more positively than it would affect students with depression. Research mentors should be mindful that students with depression often have a negative view of themselves, and while students report that praise is extremely important, they may have trouble processing such positive feedback.

Normalize Failure and Be Explicit about the Importance of Research Contributions.

Explicitly remind students that experiencing failure is expected in research. Also explain to students how their individual work relates to the overall project so that they can understand how their contributions are important. It can also be helpful to explain to students why the research project as a whole is important in the context of the greater scientific community.

Experiencing failure has been thought to be a potentially important aspect of undergraduate research, because it may provide students with the potential to develop integral scientific skills such as the ability to navigate challenges and persevere ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, in the interviews, students described that when their science experiments failed, it was particularly tough for their depression. Students’ negative reaction to experiencing failure in research is unsurprising, given recent literature that has predicted that students may be inadequately prepared to approach failure in science ( Henry et al. , 2019 ). However, the literature suggests that students with depression may find experiencing failure in research to be especially difficult ( Elliott et al. , 1997 ; Mongrain and Blackburn, 2005 ; Jones et al. , 2009 ). One potential hypothesis is that students with depression may be more likely to have fixed mindsets or more likely to believe that their intelligence and capacity for specific abilities are unchangeable traits ( Schleider and Weisz, 2018 ); students with a fixed mindset have been hypothesized to have particularly negative responses to experiencing failure in research, because they are prone to quitting easily in the face of challenges and becoming defensive when criticized ( Forsythe and Johnson, 2017 ; Dweck, 2008 ). A study of life sciences undergraduates enrolled in CUREs identified three strategies of students who adopted adaptive coping mechanisms, or mechanisms that help an individual maintain well-being and/or move beyond the stressor when faced with failure in undergraduate research: 1) problem solving or engaging in strategic planning and decision making, 2) support seeking or finding comfort and help with research, and 3) cognitive restructuring or reframing a problem from negative to positive and engaging in self encouragement ( Gin et al. , 2018 ). We recommend that, when undergraduates experience failure in science, their mentors be proactive in helping them problem solve, providing help and support, and encouraging them. Students also explained that mentors sharing their own struggles as undergraduate and graduate students was helpful, because it normalized failure. Sharing personal failures in research has been recommended as an important way to provide students with psychosocial support during research ( NASEM, 2019 ). We also suggest that research mentors take time to explain to students why their tasks in the lab, no matter how small, contribute to the greater research project ( Cooper et al. , 2019a ). Additionally, it is important to make sure that students can explain how the research project as a whole is contributing to the scientific community ( Gin et al. , 2018 ). Students highlighted that contributing to something important was really helpful for their depression, which is unsurprising, given that studies have shown that meaning in life or people’s comprehension of their life experiences along with a sense of overarching purpose one is working toward has been shown to be inversely related to depression ( Steger, 2013 ).

Limitations and Future Directions

This work was a qualitative interview study intended to document a previously unstudied phenomenon: depression in the context of undergraduate research experiences. We chose to conduct semistructured interviews rather than a survey because of the need for initial exploration of this area, given the paucity of prior research. A strength of this study is the sampling approach. We recruited a national sample of 35 undergraduates engaged in undergraduate research at 12 different public R1 institutions. Despite our representative sample from R1 institutions, these findings may not be generalizable to students at other types of institutions; lab environments, mentoring structures, and interactions between faculty and undergraduate researchers may be different at other institution types (e.g., private R1 institutions, R2 institutions, master’s-granting institutions, primarily undergraduate institutions, and community colleges), so we caution against making generalizations about this work to all undergraduate research experiences. Future work could assess whether students with depression at other types of institutions have similar experiences to students at research-intensive institutions. Additionally, we intentionally did not explore the experiences of students with specific identities owing to our sample size and the small number of students in any particular group (e.g., students of a particular race, students with a graduate mentor as the primary mentor). We intend to conduct future quantitative studies to further explore how students’ identities and aspects of their research affect their experiences with depression in undergraduate research.

The students who participated in the study volunteered to be interviewed about their depression; therefore, it is possible that depression is a more salient part of these students’ identities and/or that they are more comfortable talking about their depression than the average population of students with depression. It is also important to acknowledge the personal nature of the topic and that some students may not have fully shared their experiences ( Krumpal, 2013 ), particularly those experiences that may be emotional or traumatizing ( Kahn and Garrison, 2009 ). Additionally, our sample was skewed toward females (77%). While females do make up approximately 60% of students in biology programs on average ( Eddy et al. , 2014 ), they are also more likely to report experiencing depression ( American College Health Association, 2018 ; Evans et al. , 2018 ). However, this could be because women have higher rates of depression or because males are less likely to report having depression; clinical bias, or practitioners’ subconscious tendencies to overlook male distress, may underestimate depression rates in men ( Smith et al. , 2018 ). Further, females are also more likely to volunteer to participate in studies ( Porter and Whitcomb, 2005 ); therefore, many interview studies have disproportionately more females in the data set (e.g., Cooper et al. , 2017 ). If we had been able to interview more male students, we might have identified different findings. Additionally, we limited our sample to life sciences students engaged in undergraduate research at public R1 institutions. It is possible that students in other majors may have different challenges and opportunities for students with depression, as well as different disciplinary stigmas associated with mental health.

In this exploratory interview study, we identified a variety of ways in which depression in undergraduates negatively affected their undergraduate research experiences. Specifically, we found that depression interfered with students’ motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing. We also identified that research can negatively affect depression in undergraduates. Experiencing failure in research can exacerbate student depression, especially when students do not have access to adequate guidance. Additionally, being alone or having negative interactions with others in the lab worsened students’ depression. However, we also found that undergraduate research can positively affect students’ depression. Research can provide a familiar space where students can feel as though they are contributing to something meaningful. Additionally, students reported that having access to adequate guidance and a social support network within the research lab also positively affected their depression. We hope that this work can spark conversations about how to make undergraduate research experiences more inclusive of students with depression and that it can stimulate additional research that more broadly explores the experiences of undergraduate researchers with depression.

Important note

If you or a student experience symptoms of depression and want help, there are resources available to you. Many campuses provide counseling centers equipped to provide students, staff, and faculty with treatment for depression, as well as university-dedicated crisis hotlines. Additionally, there are free 24/7 services such as Crisis Text Line, which allows you to text a trained live crisis counselor (Text “CONNECT” to 741741; Text Depression Hotline , 2019 ), and phone hotlines such as the National Suicide Prevention Lifeline at 1-800-273-8255 (TALK). You can also learn more about depression and where to find help near you through the Anxiety and Depression Association of American website: https://adaa.org ( Anxiety and Depression Association of America, 2019 ) and the Depression and Biopolar Support Alliance: http://dbsalliance.org ( Depression and Biopolar Support Alliance, 2019 ).

ACKNOWLEDGMENTS

We are extremely grateful to the undergraduate researchers who shared their thoughts and experiences about depression with us. We acknowledge the ASU LEAP Scholars for helping us create the original survey and Rachel Scott for her helpful feedback on earlier drafts of this article. L.E.G. was supported by a National Science Foundation (NSF) Graduate Fellowship (DGE-1311230) and K.M.C. was partially supported by a Howard Hughes Medical Institute (HHMI) Inclusive Excellence grant (no. 11046) and an NSF grant (no. 1644236). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or HHMI.

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• Dominant Learning Styles of Interior Design Students in Generation Z 26 July 2021 | Journal of Interior Design, Vol. 46, No. 4
• Linking Emotional Intelligence, Physical Activity and Aggression among Undergraduates 26 November 2021 | International Journal of Environmental Research and Public Health, Vol. 18, No. 23
• Advancing undergraduate synthetic biology education: insights from a Canadian iGEM student perspective Canadian Journal of Microbiology, Vol. 67, No. 10
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Submitted: 4 November 2019 Revised: 24 February 2020 Accepted: 6 March 2020

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Home — Essay Samples — Nursing & Health — Psychiatry & Mental Health — Depression

Essays About Depression

Depression essay topic examples.

Explore topics like the impact of stigma on depression, compare it across age groups or in literature and media, describe the emotional journey of depression, discuss how education can help, and share personal stories related to it. These essay ideas offer a broad perspective on depression, making it easier to understand and engage with this important subject.

Argumentative Essays

Argumentative essays require you to analyze and present arguments related to depression. Here are some topic examples:

• 1. Argue whether mental health stigma contributes to the prevalence of depression in society.
• 2. Analyze the effectiveness of different treatment approaches for depression, such as therapy versus medication.

Example Introduction Paragraph for an Argumentative Essay: Depression is a pervasive mental health issue that affects millions of individuals worldwide. This essay delves into the complex relationship between mental health stigma and the prevalence of depression in society, examining the barriers to seeking help and the consequences of this stigma.

Example Conclusion Paragraph for an Argumentative Essay: In conclusion, the analysis of mental health stigma's impact on depression underscores the urgent need to challenge and dismantle the stereotypes surrounding mental health. As we reflect on the far-reaching consequences of stigma, we are called to create a society that fosters empathy, understanding, and open dialogue about mental health.

Compare and Contrast Essays

Compare and contrast essays enable you to examine similarities and differences within the context of depression. Consider these topics:

• 1. Compare and contrast the symptoms and risk factors of depression in adolescents and adults.
• 2. Analyze the similarities and differences between the portrayal of depression in literature and its depiction in modern media.

Example Introduction Paragraph for a Compare and Contrast Essay: Depression manifests differently in various age groups and mediums of expression. This essay embarks on a journey to compare and contrast the symptoms and risk factors of depression in adolescents and adults, shedding light on the unique challenges faced by each demographic.

Example Conclusion Paragraph for a Compare and Contrast Essay: In conclusion, the comparison and contrast of depression in adolescents and adults highlight the importance of tailored interventions and support systems. As we contemplate the distinct challenges faced by these age groups, we are reminded of the need for age-appropriate mental health resources and strategies.

Descriptive Essays

Descriptive essays allow you to vividly depict aspects of depression, whether it's the experience of the individual or the societal impact. Here are some topic ideas:

• 1. Describe the emotional rollercoaster of living with depression, highlighting the highs and lows of the experience.
• 2. Paint a detailed portrait of the consequences of untreated depression on an individual's personal and professional life.

Example Introduction Paragraph for a Descriptive Essay: Depression is a complex emotional journey that defies easy characterization. This essay embarks on a descriptive exploration of the emotional rollercoaster that individuals with depression experience, delving into the profound impact it has on their daily lives.

Example Conclusion Paragraph for a Descriptive Essay: In conclusion, the descriptive portrayal of the emotional rollercoaster of depression underscores the need for empathy and support for those grappling with this condition. Through this exploration, we are reminded of the resilience of the human spirit and the importance of compassionate understanding.

Persuasive Essays

Persuasive essays involve arguing a point of view related to depression. Consider these persuasive topics:

• 1. Persuade your readers that incorporating mental health education into the school curriculum can reduce the prevalence of depression among students.
• 2. Argue for or against the idea that employers should prioritize the mental well-being of their employees to combat workplace depression.

Example Introduction Paragraph for a Persuasive Essay: The prevalence of depression underscores the urgent need for proactive measures to address mental health. This persuasive essay asserts that integrating mental health education into the school curriculum can significantly reduce the prevalence of depression among students, offering them the tools to navigate emotional challenges.

Example Conclusion Paragraph for a Persuasive Essay: In conclusion, the persuasive argument for mental health education in schools highlights the potential for early intervention and prevention. As we consider the well-being of future generations, we are called to prioritize mental health education as an essential component of a holistic education system.

Narrative Essays

Narrative essays offer you the opportunity to tell a story or share personal experiences related to depression. Explore these narrative essay topics:

• 1. Narrate a personal experience of overcoming depression or supporting a loved one through their journey.
• 2. Imagine yourself in a fictional scenario where you advocate for mental health awareness and destigmatization on a global scale.

Example Introduction Paragraph for a Narrative Essay: Personal experiences with depression can be transformative and enlightening. This narrative essay delves into a personal journey of overcoming depression, highlighting the challenges faced, the support received, and the lessons learned along the way.

Example Conclusion Paragraph for a Narrative Essay: In conclusion, the narrative of my personal journey through depression reminds us of the resilience of the human spirit and the power of compassion and understanding. As we reflect on our own experiences, we are encouraged to share our stories and contribute to the ongoing conversation about mental health.

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The Issue of Depression: Mental Battle

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Depression, known as major depressive disorder or clinical depression, is a psychological condition characterized by enduring feelings of sadness and a significant loss of interest in activities. It is a mood disorder that affects a person's emotional state, thoughts, behaviors, and overall well-being.

Its origin can be traced back to ancient civilizations, where melancholia was described as a state of sadness and melancholy. In the 19th century, depression began to be studied more systematically, and terms such as "melancholic depression" and "nervous breakdown" emerged. The understanding and classification of depression have evolved over time. In the early 20th century, Sigmund Freud and other psychoanalysts explored the role of unconscious conflicts in the development of depression. In the mid-20th century, the Diagnostic and Statistical Manual of Mental Disorders (DSM) was established, providing a standardized criteria for diagnosing depressive disorders.

Biological Factors: Genetic predisposition plays a role in depression, as individuals with a family history of the disorder are at a higher risk. Psychological Factors: These may include a history of trauma or abuse, low self-esteem, pessimistic thinking patterns, and a tendency to ruminate on negative thoughts. Environmental Factors: Adverse life events, such as the loss of a loved one, financial difficulties, relationship problems, or chronic stress, can increase the risk of depression. Additionally, living in a socioeconomically disadvantaged area or lacking access to social support can be contributing factors. Health-related Factors: Chronic illnesses, such as cardiovascular disease, diabetes, and chronic pain, are associated with a higher risk of depression. Substance abuse and certain medications can also increase vulnerability to depression. Developmental Factors: Certain life stages, including adolescence and the postpartum period, bring about unique challenges and changes that can contribute to the development of depression.

Depression is characterized by a range of symptoms that affect an individual's emotional, cognitive, and physical well-being. These characteristics can vary in intensity and duration but generally include persistent feelings of sadness, hopelessness, and a loss of interest or pleasure in activities once enjoyed. One prominent characteristic of depression is a noticeable change in mood, which can manifest as a constant feeling of sadness or emptiness. Individuals may also experience a significant decrease or increase in appetite, leading to weight loss or gain. Sleep disturbances, such as insomnia or excessive sleepiness, are common as well. Depression can impact cognitive functioning, causing difficulties in concentration, decision-making, and memory recall. Negative thoughts, self-criticism, and feelings of guilt or worthlessness are also common cognitive symptoms. Furthermore, physical symptoms may arise, including fatigue, low energy levels, and a general lack of motivation. Physical aches and pains, without an apparent medical cause, may also be present.

The treatment of depression typically involves a comprehensive approach that addresses both the physical and psychological aspects of the condition. It is important to note that the most effective treatment may vary for each individual, and a personalized approach is often necessary. One common form of treatment is psychotherapy, which involves talking to a mental health professional to explore and address the underlying causes and triggers of depression. Cognitive-behavioral therapy (CBT) is a widely used approach that helps individuals identify and change negative thought patterns and behaviors associated with depression. In some cases, medication may be prescribed to help manage depressive symptoms. Antidepressant medications work by balancing neurotransmitters in the brain that are associated with mood regulation. It is crucial to work closely with a healthcare provider to find the right medication and dosage that suits an individual's needs. Additionally, lifestyle changes can play a significant role in managing depression. Regular exercise, a balanced diet, sufficient sleep, and stress reduction techniques can all contribute to improving mood and overall well-being. In severe cases of depression, when other treatments have not been effective, electroconvulsive therapy (ECT) may be considered. ECT involves administering controlled electric currents to the brain to induce a brief seizure, which can have a positive impact on depressive symptoms.

1. According to the World Health Organization (WHO), over 264 million people worldwide suffer from depression, making it one of the leading causes of disability globally. 2. Depression can affect people of all ages, including children and adolescents. In fact, the prevalence of depression in young people is increasing, with an estimated 3.3 million adolescents in the United States experiencing at least one major depressive episode in a year. 3. Research has shown that there is a strong link between depression and other physical health conditions. People with depression are more likely to experience chronic pain, cardiovascular diseases, and autoimmune disorders, among other medical conditions.

The topic of depression holds immense significance and should be explored through essays due to its widespread impact on individuals and society as a whole. Understanding and raising awareness about depression is crucial for several reasons. Firstly, depression affects a significant portion of the global population, making it a pressing public health issue. Exploring its causes, symptoms, and treatment options can contribute to better mental health outcomes and improved quality of life for individuals affected by this condition. Additionally, writing an essay about depression can help combat the stigma surrounding mental health. By promoting open discussions and providing accurate information, essays can challenge misconceptions and foster empathy and support for those experiencing depression. Furthermore, studying depression allows for a deeper examination of its complex nature, including its psychological, biological, and sociocultural factors. Lastly, essays on depression can highlight the importance of early detection and intervention, promoting timely help-seeking behaviors and reducing the burden of the condition on individuals and healthcare systems. By shedding light on this critical topic, essays have the potential to educate, inspire action, and contribute to the overall well-being of individuals and society.

1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. 2. World Health Organization. (2017). Depression and other common mental disorders: Global health estimates. World Health Organization. 3. Kessler, R. C., Bromet, E. J., & Quinlan, J. (2013). The burden of mental disorders: Global perspectives from the WHO World Mental Health Surveys. Cambridge University Press. 4. Beck, A. T., Rush, A. J., Shaw, B. F., & Emery, G. (1979). Cognitive therapy of depression. Guilford Press. 5. Nierenberg, A. A., & DeCecco, L. M. (2001). Definitions and diagnosis of depression. The Journal of Clinical Psychiatry, 62(Suppl 22), 5-9. 6. Greenberg, P. E., Fournier, A. A., Sisitsky, T., Pike, C. T., & Kessler, R. C. (2015). The economic burden of adults with major depressive disorder in the United States (2005 and 2010). Journal of Clinical Psychiatry, 76(2), 155-162. 7. Cuijpers, P., Berking, M., Andersson, G., Quigley, L., Kleiboer, A., & Dobson, K. S. (2013). A meta-analysis of cognitive-behavioural therapy for adult depression, alone and in comparison with other treatments. Canadian Journal of Psychiatry, 58(7), 376-385. 8. Hirschfeld, R. M. A. (2014). The comorbidity of major depression and anxiety disorders: Recognition and management in primary care. Primary Care Companion for CNS Disorders, 16(2), PCC.13r01611. 9. Rush, A. J., Trivedi, M. H., Wisniewski, S. R., Nierenberg, A. A., Stewart, J. W., Warden, D., ... & Fava, M. (2006). Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR*D report. American Journal of Psychiatry, 163(11), 1905-1917. 10. Kendler, K. S., Kessler, R. C., Walters, E. E., MacLean, C., Neale, M. C., Heath, A. C., & Eaves, L. J. (1995). Stressful life events, genetic liability, and onset of an episode of major depression in women. American Journal of Psychiatry, 152(6), 833-842.

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Depression articles from across Nature Portfolio

Depression refers to a state of low mood that can be accompanied with loss of interest in activities that the individual normally perceived as pleasurable, altered appetite and sleep/wake balance. Its severe form, major depression is classified as a mood disorder.

Latest Research and Reviews

Eye-tracking evidence of a relationship between attentional bias for emotional faces and depression severity in patients with treatment-resistant depression

• Laetitia Imbert
• Cécilia Neige
• Jerome Brunelin

Increasing psychopharmacology clinical trial success rates with digital measures and biomarkers: Future methods

• Jacob E. Reiter
• Stefanie Nickels
• Andrew Trister

The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression

Identifying modifiable risk factors that could prevent depression is important. Here, the authors show increased risks of incident depression in pre-frail and frail individuals and highlight the mediating role of brain structure and inflammation.

• Rongtao Jiang
• Stephanie Noble
• Dustin Scheinost

Anxiety, depression and distress outcomes from the Health4Life intervention for adolescent mental health: a cluster-randomized controlled trial

The authors present the secondary outcomes from a cluster-randomized controlled trial of the Health4Life multiple health behavior change intervention. The intervention showed short-term benefits for distress and depressive symptoms but was not more effective than an active control condition.

• K. E. Champion
• N. C. Newton

Astrocytic ALKBH5 in stress response contributes to depressive-like behaviors in mice

The regulatory mechanism and function of astrocytic epigenetic effects on depression remain to be explored. Here, the authors show astrocytic ALKBH5 contributes to depressive-like behaviors via the m6A RNA methylation of GLT-1.

Severe mental illness and mortality in sepsis and septic shock: a systematic review and meta-analysis

• Ines Lakbar
• Eloise Maakaron
• Guillaume Fond

News and Comment

Placebo response in rct for antidepressant may not always be the ‘villain’ to fight: are kor antagonists possibly affecting the intrinsic placebo response.

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Internet use and teen mental health: it’s about more than just screen time

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Social-media influence on teen mental health goes beyond just cause and effect

• Michael A. Spikes

The personal brain

• Giovanni Stanghellini
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Interpersonal therapy can be an effective tool against the devastating effects of loneliness

• Myrna M. Weissman
• Jennifer J. Mootz

On assumptions and key issues in electric field modeling for ECT

• Zhi-De Deng
• Miklos Argyelan
• Christopher C. Abbott

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327 Depression Essay Titles & Examples

When choosing a title about depression, you have to remain mindful since this is a sensitive subject. This is why our experts have listed 177 depression essay topics to help you get started.

🌧️ How to Write a Depression Essay: Do’s and Don’ts

🏆 unique titles about depression, 🥇 most interesting depression title ideas, 📌 good titles for depression essay, ✅ simple & easy depression essay titles, 🎓 interesting topics to write about depression, 📑 good research topics about depression.

• ❓ Research Questions for a Depression Essay

Depression is a disorder characterized by prolonged periods of sadness and loss of interest in life. The symptoms include irritability, insomnia, anxiety, and trouble concentrating. This disorder can produce physical problems, self-esteem issues, and general stress in a person’s life. Difficult life events and trauma are typical causes of depression. Want to find out more? Check out our compilation below.

A depression essay is an important assignment that will help you to explore the subject and its impact on people. Writing this type of paper may seem challenging at first, but there are some secrets that will make achieving a high grade much easier. Check below for a list of do’s and don’ts to get started!

DO select a narrow topic. Before starting writing, define the subject of the paper, and write down some possible titles. This will help you to focus your thoughts instead of offering generic information that can easily be found on Wikipedia. Consider writing about a particular population or about the consequences of depression. For example, a teenage depression essay could earn you excellent marks! If you find this step challenging, try searching for depression essay topics online. This will surely give you some inspiration.

DON’T copy from peers or other students. Today, tutors are usually aware of the power of the Internet and will check your paper for plagiarism. Hence, if you copy information from other depression essays, you could lose a lot of marks. You could search for depression essay titles or sample papers online, but avoid copying any details from these sources.

DO your research before starting. High-quality research is crucial when you write essays on mental health issues. There are plenty of online resources that could help you, including Google Scholar, PubMed, and others. To find relevant scientific articles, search for your primary and secondary topics of interest. Then filter results by relevance, publication date, and access type. This will help you to identify sources that you can view online and use to support your ideas.

DON’T rely on unverified sources. This is a crucial mistake many students make that usually results in failing the paper. Sources that are not academic, such as websites, blogs, and Wiki pages, may contain false or outdated information. Some exceptions are official publications and web pages of medical organizations, such as the CDC, APA, and the World Health Organization.

DO consider related health issues. Depression is often associated with other mental or physical health issues, so you should reflect on this in your paper. Some examples of problems related to depression are suicide, self-harm, eating disorders, and panic attack disorder. To show your in-depth understanding of the issue, you could write a depression and anxiety essay that shows the relationship between the two. Alternatively, you can devote one or two paragraphs to examining the prevalence of other mental health problems in people with depression.

DON’T include personal opinions and experiences unless required. A good essay on the subject of depression should be focused and objective. Hence, you should rely on research rather than on your understanding of the theme. For example, if you have to answer the question “What is depression?” look for scientific articles or official publications that contain the definition rather than trying to explain it in your own words.

DON’T forget about structure. The structure of your essay helps to present arguments or points logically, thus assisting the reader in making sense of the information. A good thing to do is to write a depression essay outline before you start the paper. You should list your key points supported by relevant depression quotes from academic publications. Follow the outline carefully to avoid gaps and inconsistencies.

Use these do’s and don’ts, and you will be able to write an excellent paper on depression! If you want to see more tips and tricks that will help you elevate your writing, look around our website!

• Depression and Grief in the “Ordinary People” Film At the end of the film, he is healed and ready to forgive his mother and stop blaming himself. I believe that the relationship between Conrad and his therapist, Dr.
• Understanding Teen Depression Impacts of depression on teenagers Depression is characterized by several effects; however, most of them impact negatively to the teens. For instance, a considerable percentage of teens use extra-curriculum activities such as sports and games, […]
• Report Writing About Depression There is concrete evidence that many people in Australia tend to believe that depression is the cause of all suicide deaths in the world, but this not true.
• Social Networking and Depression The findings of the study confirmed that once an individual engages in social networking, his or her feeling of safety goes down and depression mood emerges meaning that a correlation between depression and social networking […]
• Depression, Grief, Loss in “Ordinary People” Film The coach is curious to know Conrad’s experiences at the hospital and the use of ECT. Towards the end of the film, Conrad reveals to the therapist that he feels guilty about his brother’s death.
• Beck Depression Inventory, Its History and Benefits Therefore, the detection of depression at its early stage, the evaluation of the risks, and the definition of the level of depression are the main goals.
• Cognitive Behavioral Therapy in Treating Depression CBT works on the principle that positive thoughts and behaviour heralds positive moods and this is something that can be learned; therefore, by learning to think and behave positively, someone may substitute negative thoughts with […]
• Anxiety and Depression Among College Students The central hypothesis for this study is that college students have a higher rate of anxiety and depression. Some of the materials to be used in the study will include pencils, papers, and tests.
• Beck Depression Inventory in Psychological Practice Beck in the 1990s, the theory disrupted the traditional flow of Freudian theories development and introduced the audience to the concept of cognitive development, therefore, inviting psychologists to interpret the changes in the patient’s emotional […]
• Biological and Social-Cognitive Perspectives on Depression The social-cognitive perspective states that the disorder’s development is influenced by the events in the patient’s life and their way of thinking.
• Case Study of Depression and Mental Pressure Alison believes that her illness is severe and taking a toll all the time, and the environment is worsening the condition.
• The Problem of Childhood Depression Thus, it is essential to explore the reasons for the disease and possible ways to treat depression in kids. In kids, the prevention of depression is fundamental to understanding the cause of the poor mood […]
• Emotional Wellness: The Issue of Depression Through Different Lenses As for the humanities lens, the increasing prevalence of depression causes the institution of religion to incorporate the issue into major confessions’ mindsets and messages.
• Depression Among High School Students The specific problem surrounding the issue of depression among adolescents is the absence of timely diagnosis as the first step to depression management.
• The Difference Between Art Deco and Depression Modern Design By and whole, Art Deco and Depression differ in their characteristics and their meanings as they bring unlike messages to the viewers.
• The Effects of Cognitive Behavioral Therapy (CBT) on Depression in Adults Introduction It is hard to disagree that there is a vast number of mental disorders that prevent people from leading their normal lives and are quite challenging to treat. One such psychological condition is depression (Li et al., 2020). Since there is a social stigma of depression, and some of its symptoms are similar to […]
• Depression Among University Students The greatest majority of the affected individuals in different universities will be unable to take good care of their bodies and living rooms.
• Depression and Melancholia Expressed by Hamlet The paper will not attempt and sketch the way the signs or symptoms of depression/melancholia play a part in the way Shakespeare’s period or culture concerning depression/melancholia, but in its place portrays the way particular […]
• Depression in Older Adults The understanding and modification of the contributions of these factors is the ultimate goal of the clinicians who engage in the treatment of depression.
• Depression as a Psychological Disorder Summarizing and evaluating the information that trusted journals have published on the topic of depression might help create a well-rounded review of the condition and the scientific community’s understanding of it.
• Depression and Its Causes in the Modern Society The higher instances of depression among women can be explained using a number of reasons including the lifestyle of the modern woman and her role in the society.
• Postpartum Depression in African American Women As far as African American women are concerned, the issue becomes even more complex due to several reasons: the stigma associated with the mental health of African American women and the mental health complications that […]
• Depression Symptoms and Cognitive Behavior Therapy The tone of the article is informative and objective, throughout the text the authors maintain an academic and scientific mood. The structure of the article is well organized and easy to read.
• Proposal on Depression in Middle-Aged Women By understand the aspect of unhappiness among the young women; it will be easier for the healthcare institutions to formulate effective and appropriate approaches to reduce the menace in the society.
• Biological Psychology: Lesion Studies and Depression Detection The purpose of this article is to share the research findings and discussion on the new methodological developments of Lesion studies.
• Using AI to Diagnose and Treat Depression One of the main features of AI is the ability to machine learning, that is, to use data from past experiences to learn and modify algorithms in the future.
• Artificial Intelligence Bot for Depression By increasing the availability and accessibility of mental health services, these technologies may also contribute to the development of cognitive science practices in Malaysia.
• COVID-Related Depression: Lingering Signs of Depression The purpose of the article is to depict the research in a more approachable way, while the latter accentuates the importance of various factors and flaws of the results. While the former is more simplified, […]
• Depression and Anxiety Among African Americans Finally, it should be insightful to understand the attitudes of friends and family members, so 5 additional interviews will be conducted with Black and White persons not having the identified mental conditions. The selected mental […]
• Depression in Dialysis Patients: Treatment and Management If I were to conduct experimental research about the treatment and management of depression in dialysis patients, I would focus on finding the most effective and safe medication for the condition among adults.
• The Serotonin Theory of Depression by Moncrieff et al. The serotonin theory of depression is closely related to antidepressants since the advent of SSRIs played a significant role in the popularization of the theory.
• Avery’s Depression in “The Flick” Play by Baker The emotional and mental state of Avery, the only African-American character out of the three, is fairly obvious from the get-go when asked about why he is so depressed, the answer is: “Um.
• Depression: A Quantitative-Qualitative Analysis A decision tree can be used due to the nature of the research question or hypothesis in place, the measurement of the dependent or research variable, the number of groups or independent variable levels, and […]
• Depression Detection Tests Analysis The problem of the abundance of psychological tests leads to the need to compare multiple testing options for indicators of their purpose, features, and interpretations of the evaluation and validity.
• Nursing Care for Patients With COVID-19 & Depression The significance of the selected problem contributed to the emergence of numerous research works devoted to the issue. This approach to choosing individuals guaranteed the increased credibility of findings and provided the authors with the […]
• 16 Personality Factors Test for Depression Patient Pablos results, it is necessary to understand the interaction and pattern of the scores of the primary factors. A combination of high Apprehension and high Self-Reliance is a pattern describing a tendency to isolate oneself.
• Depression in a 30-Year-Old Female Client In the given case, it would be useful to identify the patterns in Alex’s relationships and reconsider her responses to her partner.
• Using the Neuman Model in the Early Diagnosis of Depression In the history of the academic development of nursing theories, there are a variety of iconic figures who have made significant contributions to the evolution of the discipline: one of them is Betty Neuman.
• Depression in Primary Care: Screening and Diagnosis The clinical topics for this research are the incidence of depression in young adults and how to diagnose this disorder early in the primary care setting using screening tools such as PHQ9.
• Major Depression and Cognitive Behavior Therapy Since the intervention had no significant effect on Lola, the paper will explore the physical health implication of anxiolytics and antidepressants in adolescents, including the teaching strategies that nurses can utilize on consumers to recognize […]
• Jungian Psychotherapy for Depression and Anxiety They work as a pizza delivery man in their spare time from scientific activities, and their parents also send them a small amount of money every month.S.migrated to New York not only to get an […]
• COVID-19 and Depression: The Impact of Nursing Care and Technology Nevertheless, combatting depression is a crucial step in posing positive achievements to recover from mental and physical wellness caused by COVID-19.
• Depression Disorder Intervention The researchers evaluated the socioemotional signs of mental illnesses in a sample of diagnostically referred adolescents with clinical depression required to undergo regular cognitive behavioral therapy in a medical setting.
• Financial Difficulties in Childhood and Adult Depression in Europe The authors found that the existence of closer ties between the catalyst of depression and the person suffering from depression leads to worse consequences.
• Activity During Pregnancy and Postpartum Depression Studies have shown that women’s mood and cardiorespiratory fitness improve when they engage in moderate-intensity physical activity in the weeks and months after giving birth to a child.
• Clinical Depression: Causes and Development Therefore, according to Aaron Beck, the causes and development of depression can be explained through the concepts of schema and negative cognitive triad.
• Aspects of Working With Depression It also contributes to the maintenance and rooting of a bad mood, as the patient has sad thoughts due to the fact that the usual does not cause satisfaction.
• Depression Among Nurses in COVID-19 Wards The findings are of great significance to researchers and governments and can indicate the prevalence of anxiety and depression among nurses working in COVID-19 wards in the North-East of England during the pandemic.
• Depression Associated With Sleep Disorders Y, Chang, C. Consequently, it directly affects the manifestation of obstructive sleep apnea, restless leg syndrome, and periodic limb movement disorder in people with depression.
• Depression in a 25-Year-Old Male Patient Moreover, a person in depression complains of the slowness in mental processes, notes the oppression of instincts, the loss of the instinct of self-preservation, and the lack of the ability to enjoy life.
• Aspects and Manifestation of Depression Although, symptoms of depression in young people, in contrast to older adults, are described by psychomotor agitation or lethargy, fatigue, and loss of energy.
• Complementary Therapy for Postpartum Depression in Primary Care Thus, the woman faced frustration and sadness, preventing her from taking good care of the child, and the lack of support led to the emergence of concerns similar to those in the past.
• Depression and Anxiety Clinical Case Many of the factors come from the background and life experiences of the patient. The client then had a chance to reflect on the results and think of the possible alternative thoughts.
• Uncontrolled Type 2 Diabetes and Depression Treatment The data synthesis demonstrates that carefully chosen depression and anxiety treatment is likely to result in better A1C outcomes for the patient on the condition that the treatment is regular and convenient for the patients.
• Technology to Fight Postpartum Depression in African American Women I would like to introduce the app “Peanut” the social network designed to help and unite women exclusively, as a technology aimed at fighting postpartum depression in African American Women.
• Complementary Therapy in Treatment of Depression Such practices lower the general level of anxiety and remove the high risks of manifestation of states of abulia, that is, clinical lack of will and acute depression.
• Social Determinants of Health and Depression Among African American Adults The article “Social Determinants of Health and Depression among African American Adults: A Scoping Review of Current Research” examines the current research on the relationship between social determinants of health and depression among African American […]
• Outcomes Exercise Has on Depression for People Between 45-55 Years According to the WHO, the rate of depression in the U.S.was 31. 5% as of October 2021, with the majority of the victims being adults aged between 45 and 55 years.
• The Postpartum Depression in Afro-Americans Policy The distribution of the funds is managed and administered on the state level. Minnesota and Maryland focused on passing the legislation regulating the adoption of Medicaid in 2013.
• Depression Among the Medicare Population in Maryland The statistics about the prevalence and comorbidity rates of depression are provided from the Medicare Chronic Conditions Dashboard and are portrayed in the table included in the paper.
• Depression as Public Health Population-Based Issue In regard to particular races and ethnicities, CDC provided the following breakdown of female breast cancer cases and deaths: White women: 128 new cases and 20 deaths per 100.
• Managing Mental Health Medications for Depression and its Ethical Contradiction The second objective is to discover ethical contradictions in such treatment for people of various cultures and how different people perceive the disorder and react to the medication.
• Aspects of Depression and Obesity In some cases, people with mild to severe depression choose not to seek professional care and instead try to overcome their depression with self-help or the support of family and friends.
• Antidepressant Treatment of Adolescent Depression At the same time, scientists evidenced that in the case of negative exposure to stress and depression, the human organism diminishes BDNF expression in the hippocampus.
• Online Peer Support Groups for Depression and Anxiety Disorder The main objective of peer support groups is connecting people with the same life experiences and challenges to share and support each other in healing and recovery.
• Depression in Adolescence and Treatment Approaches The age of adolescence, commonly referred to as children aged 10-19, is characterized by a variety of changes to one’s physical and mental health, as the child undergoes several stages of adjustment to the environment […]
• Emotional Encounter With a Patient With Major Depression Disorder I shared this idea with him and was trying to create the treatment plan, sharing some general thoughts on the issue.
• Childhood Depression in Sub-Saharan Africa According to Sterling et al, depression in early childhood places a significant load on individuals, relatives, and society by increasing hospitalization and fatality and negatively impacting the quality of life during periods of severe depression.
• Anxiety and Depression: The Case Study As he himself explained, he is not used to positive affirmation due to low self-esteem, and his family experiences also point to the fact that he was not comforted often as a child.
• Breastfeeding and Risk of Postpartum Depression The primary goal of the research conducted by Islam et al.was to analyze the correlation between exclusive breastfeeding and the risk of postpartum depression among new mothers.
• Nursing Intervention in Case of Severe Depression The patient was laid off from work and went through a divorce in the year. This led to a change in prescribed medications, and the patient was put on tricyclic anti-depressants.
• Screening for Depression in Acute Care The literature review provides EB analysis for the topic of depression to identify the need for an appropriate screening tool in addition to the PHQ-9 in the assessment evaluation process.
• Social Media Use and the Risk of Depression Thapa and Subedi explain that the reason for the development of depressive symptoms is the lack of face to face conversation and the development of perceived isolation. Is there a relationship between social media use […]
• Depression in the Field of a Healthcare Administrator According to Davey and Harrison, the most challenging part of healthcare administration in terms of depression is the presence of distorted views, shaped by patients’ thoughts.
• The Treatment of Adolescents With Depression While treating a teenager with depression, it is important to maintain the link between the cause of the mental illness’ progression and the treatment.
• Depression in the Lens of History and Humanities In terms of history, this paper analyzes the origin of depression and the progress made over the years in finding treatment and preventive mechanisms.
• Depression in the Black Community The speaker said that her counselor was culturally sensitive, which presumes that regardless of the race one belongs to, a specialist must value their background.
• Loneliness and Depression During COVID-19 While the article discusses the prevalence of loneliness and depression among young people, I agree that young people may be more subject to mental health problems than other population groups, but I do not agree […]
• Depression Screening in the Acute Setting Hence, it is possible to develop a policy recommending the use of the PHQ-9, such as the EBDST, in the acute setting.
• Ketamine for Treatment-Resistant Depression: Neurobiology and Applications It is known that a violation of the functions of the serotonergic pathways leads to various mental deviations, the most typical of which is clinical depression.
• Treating Obesity Co-Occurring With Depression In most cases, the efficiency of obesity treatment is relatively low and commonly leads to the appearance of a comorbid mental health disorder depression.
• Treadmill Exercise Ameliorates Social Isolation-Induced Depression The groups included: the social isolation group, the control group, and the exercise and social isolation and exercise group. In the treadmill exercise protocol, the rat pups ran on the treadmill once a day for […]
• Depression and Anxiety Among Chronic Pain Patients The researchers used The Depression Module of the Patient Health Questionnaire and the Generalized Anxiety Disorder Scale to interview participants, evaluate their answers, and conduct the study.
• The Depression Construct and Instrument Analysis For the therapist, this scaling allows to assess the general picture of the patient’s psychological state and obtain a result that is suitable for measurement.
• Stress and Depression Among Nursing Students The study aims to determine how different the manifestations of stress and depression are among American nursing students compared to students of other disciplines and what supports nursing students in continuing their education.
• Depression in Diabetes Patients The presence of depression concomitant to diabetes mellitus prevents the adaptation of the patient and negatively affects the course of the underlying disease.
• Depression among Homosexual Males The literature used for the research on the paper aims to overview depression among homosexual males and describe the role of the nurse and practices based on the Recovery Model throughout the depression.
• “What the Depression Did to People” by Edward Robb Ellis Nevertheless, the way the facts are grouped and delivered could be conducive to students’ ability to develop a clearer picture of the catastrophic downturn’s influences on the nation’s and the poor population’s mentalities.
• Economic Inequality During COVID-19: Correlation With Depression and Addiction Thus, during the pandemic, people with lower incomes experienced depression and increased their addictive behaviors to cope with the stress of COVID-19.
• Obesity Co-Occurring With Depression The assessment will identify the patient with the two conditions, address the existing literature on the issue, examine how patients are affected by organizational and governmental policies, and propose strategies to improve the patient experience.
• Depression in the Black and Minority Ethnic Groups The third sector of the economy includes all non-governmental, non-profit, voluntary, philanthropic, and charitable organizations and social enterprises specializing in various types of activities, which did not find a place in either the public or […]
• A Description on the Topic Screening Depression If there is the implementation of evidence-based care, a reduction in the proportion of disability for patients with depression would be expected. A proposal was written describing the need for screening depression patients of nearly […]
• “Disclosure of Symptoms of Postnatal Depression, …” by Carolyn Chew-Graham Critique In light of hypothesizing the research question, the researchers suggest that health practitioners have the ability to create a conducive environment for the disclosure of information.
• Depression – Psychotherapeutic Treatment Taking into account the fact that the specialist is not able to prescribe the medicine or a sort of treatment if he/she is not sure in the positive effect it might have on the health […]
• Depression as a Major Health Issue The purpose of the study was to examine the implications of cognitive behavior approaches for depression in old women receiving health care in different facilities.
• Effective Ways to Address Anxiety and Depression Looking deep into the roots of the problem will provide a vast and detailed vision of it, and will help to develop ways to enhance the disorders.
• Einstepam: The Treatment of Depression The treatment of depression has greatly revolutionized since the development of tricyclic antidepressants and monoamine oxidase inhibitors in the 1950s. In the brain, it inhibits the NMDA receptors and isoforms of NOS.
• The Potential of Psilocybin in Treating Depression First of all, it is essential to understand the general effects of psilocybin on the brain that are present in the current literature.
• Depression Among High School Students The major problem surrounding depression among adolescents is that they are rarely diagnosed in time and therefore do not receive treatment they need.
• NICE Guidelines for Depression Management: Project Proposal This topic is of importance for VEGA because the center does not employ any specific depression management guidelines.
• Depression: Diagnostics, Prevention and Treatment Constant communication with the patient and their relatives, purposeful questioning of the patient, special scales and tests, active observation of the patient’s appearance and behavior are the steps in the nursing diagnosis of depression.
• Depression and Anxiety Intervention Plan John’s Wort to intervene for her condition together with the prescribed anti-depressant drugs, I would advise and educate her on the drug-to-drug relations, and the various complications brought about by combining St. Conducting proper patient […]
• The Use of Psychedelic Drugs in Treating Depression This study aims to establish whether depressive patients can significantly benefit from psilocybin without substantial side effects like in the case of other psychedelic drugs.
• Postpartum Depression Among the Low-Income U.S. Mothers Mothers who take part in the programs develop skills and knowledge to use the existing social entities to ensure that they protect themselves from the undesirable consequences associated with the PPD and other related psychological […]
• The Beck Depression Contrast (BDI) The second difference between the two modes of the BDI is in the methodology of conducting the survey. This is where the interviewer first gets the history of the patient to try and get the […]
• Depression: Description, Symptoms and Diagnosis, Prognosis and Treatment A diagnosis is made in situations where the symptoms persist for at least two weeks and lead to a change in the individual’s level of functioning.
• Psychedelic Drugs and Their Effects on Anxiety and Depression The participants must also be willing to remain in the study for the duration of the experiments and consent to the drugs’ use.
• VEGA Medical Center: The Quality of Depression Management This presentation is going to provide an overview of a project dedicated to the implementation of NICE guidelines at the VEGA Medical Center.
• Anxiety and Depression in Hispanic Youth in Monmouth County Therefore, the Health Project in Monmouth County will help Hispanic children and adolescents between the ages of 10 and 19 to cope with anxiety and depression through behavioral therapy.
• Anxiety Disorders and Depression In her case, anxiety made her feel that she needed to do more, and everything needed to be perfect. She noted that the background of her depression and anxiety disorders was her family.
• Clinical Case Report: Depression It is possible to assume that being in close contact with a person who has depression also increases the probability of experiencing its symptoms.
• PICO Analysis of Depression In other words, the causes of the given mental disorder can highly vary, and there is no sufficient evidence to point out a primary factor that triggers depression.
• Interventions for Treating Depression after Stroke Inherently, the link between depression and stroke can be analyzed on the basis of post-stroke depression that is identified as the major neuropsychiatric corollary of stroke.
• Depression: The Implications and Challenges in Managing the Illness At home, these people lack interest in their family and are not be able to enjoy the shared activities and company of the family.
• Expression Symptoms of Depression A major finding of the critique is that although the research method and design are appropriate to this type of study, the results may be speculative in their validity and reliability as the researchers used […]
• Researching Postnatal Depression Health professionals suggest that the fluctuations in the level of hormones cause changes in the chemical composition of the brain. The researcher has stated that the sample was selected from the general practitioners and health […]
• The Older Women With Depression Living in Long-Term Care The researchers used the probability-sampling method to select the institutions that were included in the study. The health care professionals working in the nursing homes were interviewed to ascertain the diagnosis of depression as well […]
• Medical Evaluation: 82-Year-Old Patient With Depression Her extreme level of weakness unfolded when the patient admitted that she lacked the strength to stand on her feet and to head back to her sleeping bed on a disastrous night.Mrs.
• Depression in Adults: Community Health Needs The challenge of depression in the elderly is the recognition of signs and symptoms or the frequent underreporting of the symptoms of depression in adults over the age of 65.
• The Discussion about Depression in Older Patients Depression is often identified as the most prevalent psychiatric disorder in the elderly and is usually determined by symptoms that belong to somatic, affective, and cognitive categories.
• Depression in Older People in Australia Although a good number of depressed elderly patients aspire to play an active role in the treatment decision-making process, some prefer to delegate this role to their doctors.
• In-Vitro Fertilization and Postpartum Depression The research was conducted through based on professional information sources and statistical data collected from the research study used to further validate the evidence and outcome of this study.
• Depression: Screening and Diagnosis What he tries to do is to live a day and observe the changes that occur around. What do you do to change your attitude to life?
• Depression in Australia. Evaluation of Different Factors In attempts to identify the biological causes of depression, the researchers focus on the analysis of brain functioning, chemical mediators, their correlations with the neurologic centers in the brain, and impact on the limbic system […]
• Mental Health Paper: Depression The prevalence of mental health conditions has been the subject of many studies, with most of these highlighting the increase in these illnesses.
• The Two Hit Model of Cytokine-Induced-Depression The association between IL-6 polymorphism and reduced risk of depressive symptoms confirms the role of the inflammatory response system in the pathophysiology of IFN-alpha-induced depression.
• Ante-Partum & Postpartum Exposure to Maternal Depression The researchers engaged in the research work on this particular study topic by approaching it on the basis of maternal behavior and circumstances, as they connect to depressive conditions in their own lives and the […]
• Depression in Australia, How Treat This Disorder According to The World Health Organization, depression is defined as a disorder in the mental health system that is presented with feelings of guiltiness, low concentration, and a decrease in the need for sleep.
• Steroid Use and Teen Depression In this manner, the researcher will be in a position to determine which of the two indicators is strongest, and then later, the indicators can be narrowed down to the most basic and relevant.
• Depression Among Minority Groups Mental disorders are among the major problems facing the health sector in America and across the world in the contemporary society.
• Aspects and Definition of Depression: Psychiatry This is the personal counseling of a patient with the doctor, and it is one of the very best processes. In the case of a physician dealing with a mental patient, the most preferable way […]
• Alcoholism and Depression: Intervention Strategies The intention of the research paper is to assess if indeed there is an association between alcoholism as manifested by Jackson, and a case of depression.
• Depression and Paranoid Personality Disorder Bainbridge include: The analysis of paranoia and anxiety caused by substance abuse reveals that the diagnosis can be correct based on the symptoms, but the long-lasting nature of the symptoms rejects this diagnosis in favor […]
• Antidepressant Drugs for Depression or Dysthymia These are the newer form of antidepressant that are based on both the principle of serotonin reuptake prevention and norepinephrine action.
• The Relationship of Type 2 Diabetes and Depression Type 2 diabetes is generally recognized as an imbalance between insulin sensitivity and beta cell function We have chosen a rural area in Wisconsin where we can focus our study and select a group of […]
• Teenage Depression and Alcoholism There also has been a demonstrated connection between alcoholism and depression in all ages; as such, people engage in alcoholism as a method of self medication to dull the feelings of depression, hopelessness and lack […]
• “Relationships of Problematic Internet Use With Depression”: Study Strengths and Weaknesses One of the study strengths is that the subject selection process is excellently and well-designed, where the subjects represent the study sample, in general.
• Depression Treatment: Biopsychosocial Theory More to the point, the roles of nurses, an interprofessional team, and the patient’s family will be examined regarding the improvement of Majorie’s health condition.
• Postpartum Depression and Its Impact on Infants The goal of this research was “to investigate the prevalence of maternal depressive symptoms at 5 and 9 months postpartum in a low-income and predominantly Hispanic sample, and evaluate the impact on infant weight gain, […]
• Postpartum Depression: Statistics and Methods of Diagnosis The incorporation of the screening tools into the existing electronic medical support system has proved to lead to positive outcomes for both mothers and children.
• Comorbidity of Depression and Pain It is also known that dysregulation of 5-HT receptors in the brain is directly related to the development of depression and the regulation of the effects of substance P, glutamate, GABA and other pain mediators. […]
• Hallucinations and Geriatric Depression Intervention Sandy has asserted further that the cleaners at the residence have been giving him the wrong medication since they are conspiring to end his life with the FBI.Mr.
• Changes in Approaches to the Treatment of Depression Over the Past Decade In spite of the fact that over the past decade many approaches to the treatment of depression remained the same, a lot of new methods appeared and replaced some old ones due to the development […]
• Management of Treatment-Resistant Depression The significance of the problem, the project’s aims, the impact that the project may have on the nursing practice, and the coverage of this condition are the primary focuses of this paper.
• Teenage Depression: Psychology-Based Treatment This finding underlines the need to interrogate the issue of depression’s ontology and epistemology. Hence, there is the need to have an elaborate and comprehensive policy for addressing teenage depression.
• Depression and Anxiety in Dialysis Patients However, the study indicates the lack of research behind the connection of depression and cognitive impairment, which is a significant limitation to the conclusive statement.
• Adolescent Grief and Depression In looking for an activity that may help him or her keep away from the pain he or she is experiencing, the victim may decide to engage in sexual activities. Later, the adolescent is also […]
• Suicide and Depression in Students Students who belong to racial and ethnic minorities constitute the group of risk connected with high depression and suicidal rates and it is the primary task of health teachers to reduce suicidal rates among all […]
• Depression Disorder: Key Factors Epidemiology refers to the study of the distribution and determinants of health related events in specific populations and its applications to health problems.
• Depression Effects of School Children However the present difficulties that he is going through being a 16 year old; may be associated to a possible cause of Down syndrome complications, or the feelings and behavioral deficiency he associates to the […]
• Depression, Hallucination, and Suicide: Mental Cases How they handle the process determines the kind of aftermath they will experience for instance it can take the route of hallucinations which is treatable or suicide which is irreversible thus how each case is […]
• Depression, Its Perspective and Management Therefore this paper seeks to point out that stress is a major ingredient of depression; show the causes, symptoms, highlight how stresses is manifested in different kinds of people, show how to manage stress that […]
• Daily Living, Depression, and Social Support Activities of Elderly Turkish People Navigating the delicate and often convoluted maze of the current issues affecting the elderly has continued to present challenges to the professionals in the field especially with the realization that these issues and needs are […]
• The Theory of Personality Psychology During Depression The study concerns personality pathology, and the results of the treatment given to patients who are under depression, and how personalities may have adverse effects on the consequences of the cure.
• Depression and the Media Other components of the cognitive triad of depression are the aspect of seeing the environment as overwhelming and that one is too small to make an impact and also seeing the future as bleak and […]
• Poor Body Image, Anxiety, and Depression: Women Who Undergo Breast Implants H02: There is no difference in overt attractiveness to, and frequency of intimacy initiated by, the husband or cohabitating partner of a breast implant patient both before and after the procedure.
• Reducing Anxiety and Depression With Exercise Regardless of the type of results achieved, it is recommendable for people undergoing mental problems like depression and anxiety to exercise regularly.
• Depression: A Cognitive Perspective Therefore, the cause of depression on this line may be a real shortage of skills, accompanied by negative self-evaluation because the individual is more likely to see the negative aspects or the skills he lacks […]
• Stress, Depression and Psychoneuroimmunology The causes and symptoms of stress may vary from person to person and the symptoms can be mental as well as physical.
• A Critical Evaluation of Major Depression This paper has actively shown how factors such as financial insecurity, job loss, income, and educational inequalities, lifestyle diseases, and breakdown of the social fabric have acted to propel the mental disorder by making use […]
• Depression, Substance Abuse and Suicide in Elderly
• Adult Depression Sufferer’s and Withdrawal From Family and Friends
• Depression: Helping Students in the Classroom
• Major Depression: Treating Depression in the Context of Marital Discord
• Family Therapy for Treating Major Depression
• Adverse Childhood Experiences Cause Depression
• Depression and Alzheimer’s Disease
• Rumination, Perfectionism and Depression in Young People
• “Gender Differences in Depression” by Nolen-Hoeksema
• Anxiety and Depression Disorders
• Beck’s Cognitive Therapy Approach to Depression Treatment
• Cannabis Abuse Increases the Risk of Depression
• Depression: Risk Factors, Incidence, Preventive Measures & Prognostic Factors
• Depression Diagnostics Methods
• Concept Analysis of Loneliness, Depression, Self-esteem
• Teen Suicide and Depression
• Depression and Diabetes Association in Adults
• The Correlation Between Perfectionism and Depression
• Geriatric Dementia, Delirium, and Depression
• Dementia, Delirium, and Depression in Older Adults
• Dealing with Depression in the Workplace
• Depression in People With Alcohol Dependence
• Depression and Anxiety Due to School and Work-Related Stress
• Creating a Comprehensive Psychological Treatment Plan: Depression
• Experimental Psychology. Bouldering for Treating Depression
• Depression and Psychotherapy in Adolescence
• Postpartum Depression: Treatment and Therapy
• Atypical Depression Symptoms and Treatment
• Dementia, Delirium, and Depression in Frail Elders
• Depression & Patient Safety: Speak Up Program
• Mindfulness Meditation Therapy in Depression Cases
• A Review of Postpartum Depression and Continued Post Birth Support
• Psychodynamic Therapy for Depression
• Depression Screening in Primary Care for Adolescents
• Freud’s Depression: Cognitive-Behavioral Interventions
• Optimal Mental Health Approaches: Depression & Anxiety
• Great Depression in “A Worn Path” by Eudora Welty
• Depression in Adolescents and Interventions
• Bipolar Disorder: Reoccurring Hypomania & Depression
• Postpartum Depression: Understanding the Needs of Women
• Major Depression Treatment During Pregnancy
• Patients’ Depression and Practitioners’ Suggestions
• Traditional Symptoms of Depression
• Social Media Impact on Depression and Eating Disorder
• Anxiety and Depression in Children and Adolescents
• Depression Studies and Online Research Sources
• Depression and Drug Dependence Treatment and Support
• Depression Explanation in Psychological Theories
• Food Insecurity and Depression in Poor Families
• Peer Popularity and Depression Among Adolescents
• Alcohol Abuse, Depression and Human Trafficking
• Depression Assessment Using Intake Notes
• Depression in Adolescents and Cognitive Therapy
• Diagnosing Depression: Implementation and Evaluation Plan
• Beck Depression Inventory: Evaluation Plan
• Depression in Iranian Women and Health Policies
• Depression Patients and Psychiatrist’s Work
• Depression Patients’ Needs and Treatment Issues
• Suicide and Depression: Connection, Signs and Age
• Health Promotion: Depression Awareness in Teenagers
• Depression and Cancer in Caucasian Female Patient
• Depression in Patients with Comorbidity
• Depression After Transcranial Magnetic Stimulation Treatment
• Depression and Psychosis: 32-Year-Old Female Patient
• Postpartum Depression and Acute Depressive Symptoms
• Women with Heart Disease: Risk of Depression
• Postpartum Depression and Its Peculiarities
• Exercises as a Treatment for Depression
• Depression Treatment Changes in 2006-2017
• Depression in Elders: Social Factors
• False Memories in Patients with Depression
• Postpartum Depression Analysis in “Yellow Wallpaper”
• The Canadian Depression Causes
• Widowhood Effects on Men’s and Women’s Depression
• Teen Website: Fish Will Keep Depression Away
• Bipolar Expeditions: Mania and Depression
• Obesity and Major Depression Association
• Fast Food, Obesity, Depression, and Other Issues
• Depression in the Future Public Health
• Depression: Patients With a Difficult Psychological State
• Depression: Pathophysiology and Treatment
• Stress, Depression, and Responses to Them
• Problem of the Depression in Teenagers
• Supporting the Health Needs of Patients With Parkinson’s, Preeclampsia, and Postpartum Depression
• Hamilton Depression Rating Scale Application
• Psychological Measures: The Beck Depression Inventory
• Yoga for Depression and Anxiety
• Sleep Disturbance, Depression, Anxiety Correlation
• Depression in Late Life: Interpersonal Psychotherapy
• Postpartum Depression and Comorbid Disorders
• Arab-Americans’ Acculturation and Depression
• Organizational Behaviour: Depression in the Workplace
• Relationship Between Depression and Sleep Disturbance
• Child’s Mental Health and Depression in Adulthood
• Parents’ Depression and Toddler Behaviors
• Managing Stress and Depression at Work Places – Psychology
• Job’ Stress and Depression
• Depression Measurements – Psychology
• Methodological Bias Associated with Sex Depression
• Relationship Between Sleep and Depression in Adolescence
• The Effects of Depression on Physical Activity
• Psychological Disorder: Depression
• Depression and Workplace Violence
• The Effects of Forgiveness Therapy on Depression, Anxiety and Posttraumatic Stress for Women After Spousal Emotional Abuse
• Depression Diagnosis and Theoretical Models
• The Impact of Exercise on Women Who Suffer From Depression
• Evolutionary Psychology: Depression
• Effect of Social Media on Depression
• Depression in the Elderly
• Poly-Substance Abuse in Adolescent Males With Depression
• How Does Peer Pressure Contribute to Adolescent Depression?
• How Do Genetic and Environmental Factors Contribute To The Expression of Depression?
• Depression and Cognitive Therapy
• Cognitive Treatment of Depression
• Book Review: “Breadwinning Daughters: Young Women Working in a Depression- Era City, 1929-1939” by Katrina Srigley
• Depression: A Critical Evaluation
• Psychopharmacological Treatment for Depression
• “Breadwinning Daughters: Young Working Women in a Depression-Era City” by Katrina Srigley
• Depression in female adolescents
• Interpersonal Communication Strategies Regarding Depression
• Depression: Law Enforcement Officers and Stress
• Social Influences on Behavior: Towards Understanding Depression and Alcoholism Based on Social Situations
• Depression Experiences in Law Enforcement
• Childhood Depression & Bi-Polar Disorder
• Depression Psychological Evaluation
• Concept of Childhood Depression
• Correlation Between Multiple Pregnancies and Postpartum Depression or Psychosis
• Depression and Its Effects on Participants’ Performance in the Workplace
• Catatonic Depression: Etiology and Management
• The Children’s Depression Inventory (CDI) Measure
• Depression: A Cross-Cultural Perspective
• Depression Levels and Development
• Depression Treatment: Rational Emotive Behavior Therapy
• Concept of Depression Disorder
• Does Divorce Have a Greater Impact on Men than on Women in Terms of Depression?
• Oral versus Written Administration of the Geriatric Depression Scale

❓Research Questions for a Depression Essay

• Does Poverty Impact Depression in African American Adolescents and the Development of Suicidal Ideations?
• Does Neighborhood Violence Lead to Depression Among Caregivers of Children With Asthma?
• Does Parent Depression Correspond With Child Depression?
• How Depression Affects Our Lives?
• Does Brain-Derived Neurotrophic Factor Have an Effect on Depression Levels in Elderly Women?
• How Can Overcome Depression Through 6 Lifestyle Changes?
• Does Maternal Depression Have a Negative Effect on Parent-Child Attachment?
• Can Providers’ Education About Postpartum Depression?
• Can Vacation Help With Depression?
• How Children Deal With Depression?
• Can Diet Help Stop Depression and Violence?
• Does Depression Assist Eating Disorders?
• Does Depression Lead to Suicide and Decreased Life Expectancy?
• Can Obesity Cause Depression?
• Can Exercise Increase Fitness and Reduce Weight in Patients With Depression?
• Does Fruit and Vegetable Consumption During Adolescence Predict Adult Depression?
• Does Depression Cause Cancer?
• Does Money Relieve Depression?
• Does the Average Person Experience Depression Throughout Their Life?
• Are Vaccines Cause Depression?
• Does Social Anxiety Lead to Depression?
• Does Stress Cause Depression?
• How Bipolar and Depression Are Linked?
• Does Postpartum Depression Affect Employment?
• Does Postpartum Depression Predict Emotional and Cognitive Difficulties in 11-Year-Olds?
• Does Regular Exercise Reduce Stress Levels, and Thus Reduce Symptoms of Depression?
• Does the Natural Light During Winters Really Create Depression?
• How Can Art Overcome Depression?
• How Anxiety and Depression Are Connected?
• Does Positive Psychology Ease Symptoms of Depression?
• Bullying Research Topics
• Conflict Research Topics
• Cognitive Behavioral Therapy Topics
• Disease Questions
• Burnout Questions
• Hyperactivity Disorder Research Ideas
• Insomnia Questions
• Eating Disorders Questions
• Chicago (A-D)
• Chicago (N-B)

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Depression Research Paper

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Even for professionals the use of the term depression can vary. In 1987, Kendall and colleagues noted that “The professional use of the term depression has several levels of reference: symptom, syndrome, nosologic disorder . . . . Depression itself can be a symptom – for example, being sad. As a syndrome, depression is a constellation of signs and symptoms that cluster together . . . . The syndrome of depression is itself a psychological dysfunction but can also be present, in secondary ways, in other diagnosed disorders. Finally, for depression to be a nosologic category careful diagnostic procedures are required during which other potential diagnostic categories are excluded. The presumption, of course, is that a discrete nosologic entity will ultimately prove to be etiologically distinct from other discrete entities, with associated differences likely in course, prognosis, and treatment response.” It is this likely nosologic disorder of depression that we will discuss.

I. Definition of Depression

A. symptoms of depression, b. comorbidity: the relationship between depression and anxiety, ii. diagnostic classification, a. major depressive disorder, b. dysthymic disorder, c. bipolar i disorder, d. bipolar ii disorder, e. cyclothymic disorder, iii. exploratory categories of depressive disorders, a. premenstrual dysphoric disorder, b. minor depressive disorder, c. recurrent brief depressive disorder, d. mixed anxiety-depressive disorder, iv. epidemiology, a. prevalence, 1. national prevalence, 2. international prevalence, b. age differences, c. sex and ethnic differences, d. environmental correlates, v. etiological theories of depression, a. psychological theories, 1. psychoanalytic approaches, 2. interpersonal approaches, 3. cognitive approaches, b. biological theories, 1. genetic approaches, 2. neurotransmitter approaches, vi. protective factors, a. social support, b. coping styles.

Any definition of depression must begin with the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). The DSM-IV represents the official diagnostic classification system of the American Psychiatric Association and provides the criteria that are used to diagnosis depression. These criteria consist of the symptoms of depression. In order to make a diagnosis of depression, at least five out of nine possible symptoms must be present. These include (1) depressed mood; (2) diminished pleasure or interest in activities; (3) significant weight loss or weight gain; (4) insomnia or hypersomnia; (5) agitation; (6) fatigue or loss of energy; (7) thoughts of worthlessness or inappropriate guilt; (8) diminished concentration ability; and (9) thoughts of death or suicide.

Symptoms of depression may vary according to an individual’s age and culture. Children who are depressed, for instance, may express symptoms of irritability rather than sadness. They may also fail to make expected weight gains rather than lose weight. On the other end of the age continuum, older adults are more likely than younger adults to experience symptoms such as loss of appetite, loss of interest, and thoughts of death. Cultural differences also exist in report of depressive symptoms. One study, for example, found that depressed Jewish patients reported more somatic symptoms, and less guilt, than did non-Jewish patients. Another study that examined depressive symptomatology in American, Korean, Philippine, and Taiwanese college students found that Taiwanese students reported the lowest numbers of somatic symptoms and the highest numbers of affective symptoms. The other ethnic groups reporting similar levels of these symptoms. One’s age and culture thus seems to affect how depression is expressed.

Comorbidity refers to the occurrence of more than one disorder at the same time. Although researchers and clinicians generally acknowledge depression as a distinct disorder, it does overlap with a variety of other difficulties. Much current research on this overlap has focused on the relationship between anxiety and depression. This is not surprising, given the high rates of comorbidity found in studies of the two disorder types. For example, one study found that 63% of a group of patients with panic disorder also experienced major depression. One possible explanation provided for such overlap lies in the concept of “negative affectivity.” In 1984, Watson and Clark described individuals with high levels of negative affectivity as having a tendency “to be distressed and upset and have a negative view of self, whereas those low on the dimension are relatively content and secure and satisfied with themselves.” Other characteristics of high negative affectivity include nervousness, tension, worry, anger, scorn, revulsion, guilt, self-dissatisfaction, rejectedness, and sadness.

Both anxiety and depression seem to consist of high negative affectivity. There are however, important differences between depression and anxiety. While both depression and anxiety are characterized by high levels of negative affect, only depression is related to lowered levels of positive affect. Thus, depressed individuals tend to display both high negative affect and low positive affect, whereas anxious individuals display high negative affect and may or may not have lowered positive affect–the level of positive affect is unrelated to one’s anxiety state. Research on negative affect as a link between anxiety and depression is continuing at a rapid pace.

Earlier we noted the DSM-IV. The DSM-IV is the most widely used classification scheme for psychiatric disorders in North America. According to this manual, there are five types of mood disorders that include depression as a significant component. These are (1) Major Depressive Disorder; (2) Dysthymic Disorder; (3) Bipolar I Disorder; (4) Bipolar II Disorder; and (5) Cyclothymic Disorder. Each of these classifications differs in terms of etiology, course, and symptomatology.

For a diagnosis of Major Depressive Disorder (MDD), DSM-IV specifies that at least five symptoms must occur for a period of at least 2 weeks. Chief among these symptoms is depressed mood that occurs most of the day, nearly every day for at least 2 weeks, or significantly diminished interest or pleasure in virtually all activities most of the day, nearly every day for the 2-week period.

MDD can be further classified according to severity (i.e., mild, moderate, severe without psychotic features, severe with psychotic features), course (e.g., single episode versus recurrent episodes), and presentation (e.g., with catatonic features, with melancholic features). Psychotic features of depression include such experiences as delusions (i.e., false beliefs) and hallucinations (i.e., sensory experiences that have no basis in reality). A delusion, for example, would be a person who believes that she is dead. Catatonic features of depression involve psychomotor disturbances such as excessive movement or stupor. Melancholic features include the inability to experience pleasure even when good things happen and a lack of interest in previously pleasurable activities. No matter what the specific characteristics of a given individual’s disturbance, MDD is, by definition, extremely distressing to the sufferer and is associated with significant impairment in important areas of the person’s life (e.g., at work, home or school).

Dysthymic Disorder is characterized by a chronic depressed mood that lasts at least 2 years in adults and at least 1 year in children and adolescents. This depressed mood is accompanied by at least two of the following six depressive symptoms: (1) poor appetite or overeating; (2) insomnia or hypersomnia; (3) low energy or fatigue; (4) low self-esteem; (5) poor concentration or difficulty making decisions; and (6) feelings of hopelessness. As fewer depressive symptoms are required to make a diagnosis, Dysthymic Disorder is often considered a milder form of depression than MDD. However, it can be just as upsetting to the sufferer and can cause just as much impairment. In addition, Dysthymic Disorder may occur in combination with episodes of major depression. When Dysthymic Disorder occurs along with major depression, the individual is considered to be suffering from a “double depression.” The co-occurrence of MDD and dysthymia is not uncommon.

The hallmark characteristic of Bipolar I Disorder is mania. According to DSM-IV, a manic episode is characterized by elevated, expansive, or irritable mood that is persistent and distinctly different from normal elevated or irritable moods. This period is accompanied by at least three of seven possible symptoms. These symptoms include (1) inflated self-esteem; (2) a decreased need for sleep; (3) unusual talkativeness; (4) the feeling that one’s thoughts are racing; (5) increased distractibility; (6) increased activity; (7) involvement in pleasurable but potentially harmful activities (e.g., sexual indiscretions).

Bipolar I Disorder is typically recurrent; according to DSM-IV, additional episodes occur in more than 90% of individuals who have had a single manic episode. The manic episodes of those with Bipolar I Disorder are often intermixed with periods of depression. Like those with MDD, people with Bipolar I Disorder may exhibit psychotic, catatonic, and melancholic features as part of either their mania or their depression.

Bipolar II Disorder is characterized by periods of hypomania intermixed with periods of depression. Hypomanic episodes are characterized by the same symptoms as manic episodes. However, hypomanic episodes are shorter (e.g., 4 days in duration) and are associated with less impairment. While manic episodes may include psychotic features, interrupt daily functioning, and require hospitalization, hypomanic episodes typically do not. The depression experienced as part of Bipolar II Disorder, however, can be just as severe as that experienced in MDD and Bipolar I Disorder.

Cyclothymic disorder is characterized by hypomanic periods intermixed with depressive periods that are not as severe as those experienced in MDD, Bipolar I Disorder, and Bipolar II Disorder. In Cyclothymia, the periods of mood disturbance may alternate rapidly, with little respite from affective difficulties. For a diagnosis of Cyclothymia these periods of shifting moods must be problematic for at least 2 years in adults and at least i year in children and adolescents.

In addition to the five official diagnoses, DSM-IV has denoted four classifications for further study that include depression as a significant component. Such classifications are not yet considered to be disorders and more information is needed on factors such as symptom presentation, etiology, and degree of impairment to sufferers before these might be considered disorders in their own right. Nevertheless, these may represent serious problems and even though they are currently exploratory, we describe them here. They are: (1) Premenstrual Dysphoric Disorder; (2) Minor Depressive Disorder; (3) Recurrent Brief Depressive Disorder; and (4) Mixed Anxiety-Depressive Disorder.

Premenstrual Dysphoric Disorder is characterized by several hallmark symptoms of depression (e.g., decreased interest in usual activities, depressed mood, difficulty sleeping or sleeping too much) in addition to symptoms such as affective lability, feelings of being overwhelmed or out of control, and food cravings. In order to meet the criteria that have been proposed for this diagnosis, such symptoms must have occurred during the late luteal phase of most of a woman’s menstrual cycles in the past year. As a number of authors have pointed out, such a classification has potentially serious social, political, and legal ramifications for women. For example, some have argued that if this classification is adopted as an orificial diagnosis then women might be stigmatized as more unstable than or inferior to men. Arguments such as this keep the classification of Premenstrual Dysphoric Disorder a topic of considerable debate.

Minor Depressive Disorder is characterized by fewer depressive symptoms than are seen in MDD. The level of impairment is also less than that associated with MDD. To meet the proposed criteria for Minor Depressive Disorder, a person must demonstrate either a depressed mood or loss of interest and two additional symptoms of a Major Depressive Episode. If this classification were included in future DSM editions as a disorder, it would constitute a residual category to be used only after the other mood disorders have been ruled out.

The principle difference between Recurrent Brief Depressive Disorder and MDD is one of duration. Recurrent Brief Depressive Disorder is characterized by periods of depression that meet all of the criteria for a Major Depressive Episode except for the duration requirement. While in major depressive episodes, symptoms must last at least 2 weeks, in recurrent brief depressive episodes, symptoms must last at least 2 but less than 14 days. In addition, these brief episodes must occur at least once a month for 12 months to meet criteria for the classification of Recurrent Brief Depressive Disorder. Recurrent Brief Depressive Disorder is quite similar to MDD in its age of onset and family incidence rates, thus raising questions as to whether this should be considered a distinct disorder.

The impetus behind a mixed anxious-depressed category lies in the finding that there are many people suffering from symptoms of anxiety and depression who do not meet criteria for any DSM anxiety or mood disorder, but who are nonetheless significantly impaired by their difficulties. The classification of Mixed Anxiety-Depressive Disorder is characterized by a dysphoric mood for at least 1 month in addition to at least four additional symptoms that primarily reflect anxiety (e.g., mind going blank, worry, hypervigilance). The primary argument in favor of adopting this proposed disorder is that it would cover the large number of people who have significant impairment linked to depression and anxiety but who do not fall into any currently existing diagnostic category. The primary argument against this classification is that people suffering from both depression and anxiety could in fact be categorized into already existing disorders with the use of more precise assessment methods.

Epidemiology refers to information about the incidence and prevalence of disorders in a population. A prevalence rate refers to the number of people who have a given disorder during a particular time period (e.g., the percentage of people in given location diagnosed with MDD within a 1-year period of time). An incidence rate refers to the number of new cases of a disorder which occur during a given time period (e.g., the number of people diagnosed with Dysthymic Disorder during April 1996). Because the distribution of a disorder can be examined to determine whether it correlates with other factors, epidemiological information can be important for understanding some of the possible causes and correlates of depression.

Two recent large-scale surveys of psychopathology in the United States have provided differing prevalence data on depression. Using diagnostic criteria from the revised 3rd Edition of the DSM (DSM-III-R), the Epidemiologic Catchment Area (ECA) study examined the rates of depression in five sites: New Haven, Baltimore, St. Louis, Los Angeles, and Durham. The ECA study found the lifetime prevalence of major depression (i.e., the number of people experiencing major depression during any point in life) to be 4.9% and the lifetime prevalence of dysthymia to be 3.2%. Alternatively, the National Comorbidity Survey (NCS) reported much higher prevalence rates: 14.9% for lifetime major depression and 6.4% for dysthymia. The discrepancies between these two studies may be accounted for by the different assessment instruments used, slightly different diagnostic criteria employed, and different age ranges studied (i.e., the ECA sample was 18 years of age or older, whereas the NCS sample ranged in age from 15 to 54 years). According to the ECA study, prevalence rates for bipolar disorders were much lower; lifetime prevalence of these disorders was .8% for Bipolar I and .5% for Bipolar II. The NCS lifetime prevalence for manic episode was somewhat higher: 1.6 %. Even though these epidemiological studies reported somewhat discrepant rates, they are in agreement that mood disorders are relatively common in the United States.

A number of studies have examined the community prevalence of major depression in countries besides the United States. International lifetime prevalence rates vary widely, from a low of 3.3% in Seoul to a high of 15.1% among New Zealand residents aged 25 to 46. While such differences may indeed reflect true international differences in the occurrence of depression, other factors such as cultural differences in the sensitivity of the instruments used to assess disorder and different sample ages may also account for this range. In prevalence studies focusing on bipolar illness, ranges from .07% in Sweden to 7% in Ireland have been reported. Most studies, however, place prevalence at about 1% for bipolar illnesses, consistent with data from the ECA and NCS studies.

The ECA study also reported incidence rates of depression for various age groups. For men, major depression was highest among those aged 18 to 29. A large decline in incidence was noted for men aged 45 and older. For women, the incidence of major depression was highest in the group aged 30 to 44 and did not decline until age 65.

According to the ECA study, lifetime prevalence rates of major depression, dysthymia, and all mood disorders are approximately twice as high for women as for men. Women’s lifetime rates were 7.0%, 4.1%, and 10.2%, respectively, while rates for men were 2.6%, 2.2 %, and 5.2 %, respectively. These differences occur across a variety of ethnic groups (e.g., African American, Hispanic, Caucasian) even when differences in education, income, and occupations are controlled. Sex differences are also found in countries besides the United States. While sex differences in depression are among the most stable of findings across studies, no sex differences in the rates of bipolar disorder are reliably found.

Although sex difference in the incidence of depression occur across different ethnic groups, there are some differences among these groups overall. For instance, the ECA study found higher rates of Major Depression and Dysthymia among Caucasians and Hispanics than among African Americans. However, few difference in the rates of bipolar disorders among the three groups were found.

The ECA study also examined a number of environmental correlates of depression and bipolar disorders. This study found that people who were separated or divorced had higher 1-year prevalence rates of major depression (6.3%) than those who were never married (2.8%), currently married (2.1%), or widowed (2.1%). This was also true of those with bipolar disorders, although the rates for those separated or divorced versus never married were nearly identical (1.7% versus 1.6%). The 1-year prevalence rate of major depression was also higher among the unemployed than the employed (3.4% versus 2.2%), but the rate was nearly identical for those with bipolar disorders (1.1% versus 1.0%). In addition, the ECA study found higher rates of major depression among white-collar workers and those with at least 12 years of education, but lower rates of depression among those with annual incomes of $15,000 or more. Consistent with the major depression findings, bipolar disorders were also less prevalent among those with annual incomes of $15,000 or more. Bipolar disorders were also found to be the most prevalent among none-white-collar workers with less than 12 years of education. Overall, these socioeconomic status differences were quite small.

A variety of different psychological theories of the causes of depression have been proposed. These can be grouped in psychoanalytic, interpersonal, and cognitive.

The first psychoanalytic writers to theorize about the etiology of depression were Sigmund Freud and his student, Karl Abraham. As would be expected, there are a number of similarities in the theories proposed by Freud and Abraham. First, both Freud and Abraham believed that some people are predisposed to experience depression. For Abraham, this predisposition consisted of anatomical anomalies that allowed a person to experience a great deal of oral eroticism. For Freud, this predisposition consisted of narcissistic object choices (e.g., object choices which are so similar to the self that love of the object is truly love of self). Second, both believed that a predisposition to experience depression was not, in and of itself, enough to cause depression. In order to experience a depression, a predisposed individual must also experience the loss of a loved object (e.g., through death or rejection).

Despite these basic similarities, the two theorists diverge somewhat on how depression occurs once a loss has been experienced. For Abraham, the loss of a loved object in a person predisposed to depression triggers a regression to the oral stage of psychosexual development. Such a regression is meant to achieve three purposes: (1) to increase pleasure; (2) to hold on to the object through oral incorporation; and (3) to discharge one’s aggressive impulses on to the object. Such a regression manifests itself most saliently in the depressive symptoms of eating too much or too little. For Freud, the loss of a loved object possesses different implications. Since the lost object was a narcissistic choice and thus represented the self, loss of the object means loss of the self. This loss of self triggers feelings of anger and depression. The energy associated with these negative feelings is withdrawn from the lost object and brought inward, in a process called introjection. Thus, depression as conceptualized by Freud is often summarized as “anger turned inward.” For Freud, the difference between sadness and “true” depression was the difference between “this is awful” and “I am awful.” Freud further extended his theory to account for the mania characteristic of bipolar depressive disorders. He hypothesized that, once the feelings of anger and depression over loss of the object are resolved, the energy associated with these negative feelings is freed for other purposes. In a person with bipolar disorder, this freed energy is used to zealousy search for new objects, thus accounting for the symptoms of mania.

More recent psychoanalytic theorists have focused on the superego’s role in depression. Some theorists, for example, have suggested that depression is distinguished from other states such as shame, apathy, or resentment by the presence of guilt. As guilt results only from an intrapsychic conflict of the superego, the superego is necessarily implicated in depression. One result of these differences in etiological focus has been the proposition of two forms of depression: anaclitic and introjective. Anaclitic depression is characterized by feelings of helplessness, inferiority, and being unloved. Anaclitic depression is proposed to be associated with the earlier stages of development and is most closely associated with the theorizing of Abraham and Freud. Alternatively, introjective depression focuses on feelings of unworthiness and failure to measure up to expectations and standards. It is associated with later stages of development, and more closely aligned with the works of later psychoanalytic theorists. Although much of psychoanalytic theory has been criticized on grounds that it has not been empirically tested, the distinction between anaclitic and introjectire depressions has been empirically examined and found to be valid. Psychoanalytic theorists have accounted for the development of bipolar disorders as well. Most notable amongst these theorists is Melanie Klein, who expanded upon the work of Freud.

Interpersonal approaches to the etiology and maintenance of depression focus on the interplay between a depressed person and his or her relations with others. Empirical research in this area has taken several directions. For example, some researchers focus on the role of social skills in depression, asking such questions as whether depressed people have poor social skills and whether the lack of such skills results in decreased reinforcement from others and consequent depression. Other research has evaluated the types of communications depressed people emit (e.g., sadness, hopelessness) and the effects these communications have on others. If others find the communications of depressed persons aversive, they will likely avoid such persons, which may then exacerbate depressive symptoms such as isolation and loneliness. Still others address the interplay between stress, social support, and depression. All of these lines of research have found some support; interpersonal research highlights the fact that depression is caused by a multitude of factors in interplay with one another.

Much of the research converges on the theoretical idea that depression is maintained by a vicious cycle that is caused by disruptions in interpersonal interactions. For instance, many depressed individuals quite understandably seek out social support from others. If this support does not alleviate the negative feelings, further support is sought. This intensified support seeking, however, has the paradoxical effect of pushing away those who have been supportive. That is, as individuals begin to feel that their support capacity has been exhausted they pull back from the depressed person, leading to an even further intensification of social support seeking, and the further distancing of potentially supportive people.

Interpersonal factors in the etiology of bipolar depressive disorders have not received as much research attention as such factors in unipolar depressive disorders. Nonetheless, persons with both types of depressive disorders seem to have difficulties in retaining social support. Indeed, in one recent study, people with bipolar disorder perceived their social supports as less available to them and as less adequate in the amount of support received than people in a community sample. Furthermore, perceptions of social support availability seemed to decrease as the duration of illness increased. Thus, it seems likely that social support plays a role in bipolar as well as unipolar depressive disorders.

Currently, cognitive approaches are among the most widely studied theories in the etiology of depression. One of the most influential of these theories was proposed by Aaron Beck in 1967. Beck argued that all individuals possess cognitive structures called schemas that guide the ways information in the environment is attended to and interpreted. Such schemas are determined from childhood by our interactions with the external world. For example, a child who is constantly criticized may begin to believe she is worthless. She might then begin to interpret every failure experience as further evidence of her worthlessness. If this negative processing of information is not changed, it will become an enduring part of her cognitive organization, that is, a schema. When this schema is activated (e.g., by a poor grade on a test or any other failure experience), it will predispose her to depressive feelings (e.g., I’m no good). Beck stated that, as a result of this faulty information processing, depressed persons demonstrate a cognitive triad of negative thoughts about themselves, the world, and the future. He further extended his argument to include the manic phases of bipolar depressive disorders. Beck stated that such phases are characterized by a manic triad of irrationally positive thoughts about oneself, the world, and the future. Like the depressive triad in unipolar depressive disorders, the manic triad in bipolar depressive disorders was hypothesized to lead to the symptoms of mania, such as inflated selfesteem and extremely elevated mood.

There is widespread agreement that depression can be caused by different factors. Some theorists have argued that dysfunctional cognitions cause only a subset of depressions. Termed the “negative cognition” subtype, this type of depression is brought about by either the kinds of schemas discussed by Aaron Beck or by dysfunctional attributional patterns that lead depressed people to take responsibility for the occurrence of negative events, and to avoid taking responsibility for positive events. This dysfunctional attributional pattern can lead to a sense of hopelessness that results in a “hopelessness depression,” a component of negative cognition depression.

Although there are a variety of biologically based theories of depression, they can be broken down into two general approaches: genetic and neurotransmitter.

Genetic approaches suggest that depression is the result of inheriting genes that predispose to occurrence of depression. Three types of studies that are used to investigate genetic inheritance of depression illustrate this approach. These studies consist of family studies, twin studies, and adoption studies. In a typical family study, families with a depressed member are interviewed to determine how many other family members have or had an affective disorder. In twin studies, the concordance rate of affective disorder between monozygotic and dizygotic twin pairs is compared. Because monozygotic twins have identical genes, if genetic theories are correct then concordance rates of depression should be higher than for dizygotic twins (who have similar but not identical genes). In adoption studies, two strategies are most often used. In the first, the rate of depressive disorder in the biological parents of adopted persons with and without affective disorders is compared. In the second, the rate of depressive disorders is compared between adopted children with and without affectively disordered biological parents. Adoption studies have an advantage over family and twin studies, as the effects of environment on affective disorder are reduced in this design. However, adoption studies constitute the least-used approach to investigating genetic factors in depression; the difficulty of obtaining complete records on adoptees and their biological parents makes this design quite prohibitive.

Despite design differences, all three genetic approaches to the etiology of depression have yielded similar results: depression is heritable to at least some degree. A recent review of the research literature, for example, found rates of affective disorders among first-degree relatives of unipolar-disordered individuals ranging from 11.8% to 32.2%. Rates of affective disorders among first-degree relatives of bipolardisordered individuals ranged from 10.6% to 33.1%. Rates of affective disorder among first-degree relatives of normal individuals ranged from 4.8% to 6.3. In twin studies of unipolar and bipolar depression, concordance rates ranged from .04 to 1.0 for monozygotic twins, and from 0.0 to .43 to dizygotic twins, with the majority of studies reviewed reporting no concordance for dizygotic twins. The results of genetic investigations clearly suggest that there is a genetic component to depression, although the exact nature and functioning of this component is thus far still unknown.

Research on brain chemistry as an etiological factor in unipolar depression has focused on two monoamine neurotransmitters: norepinephrine (NE) and serotonin (5-HT). Initially, researchers believed that depression was due to a lack of NE in the brain, and later, to a lack of both NE and 5-HT. However, several difficulties with these hypotheses arose: (1) While the effects of antidepressants on monoamine levels start within hours of taking the medication, decreased depression levels do not become apparent until weeks later. (2) Some drugs that do not affect monoamine levels alleviate depression. (3) Some drugs that increase monoamine levels do not alleviate depression. Thus, researchers have directed their efforts to investigating more complicated relations between these neurotransmitters and depression. Recent efforts have included the study of receptor site hyposensitivity, relationships between NE and 5-HT, and relationships between. 5-HT and the neurotransmitter dopamine (DA).

Research on brain chemistry as in etiological factor in bipolar depression has followed much the same course as such research on unipolar depression. Initially, researchers believed that the mania characteristic of bipolar disorders was due to excesses of the neurotransmitters NE and 5-HT, exactly opposite the belief for depression. However, difficulties arose with this hypothesis, including findings that (1) lithium, the medical treatment of choice for bipolar disorder which seems to affect both NE and 5-HT, was effective at controlling both depression and mania, and (2) both depression and mania may be characterized by lower levels of 5-HT. Thus, as with unipolar depression, researchers of bipolar depression have begun investigating more complicated relationships between bipolar depression and neurotransmitters. Similar to the recent efforts concerning unipolar depression, researchers have investigated interactions between 5-HT and DA, interactions between NE and DA, and receptor site hypersensitivity. These types of investigations represent promising areas of research in elucidating the multifaceted etiology of depression. Certainly, biology and psychology are implicated in the causes of depression, both unipolar and bipolar forms.

Given the potentially devastating effects of depression, many researchers have devoted their efforts to studying factors that decrease the likelihood of becoming depressed or decrease the amount of time spent in depressive episodes. Among the most widely studied of such protective factors are social support and coping styles.

There are numerous facets to the concept of social support. For example, social support can be conceived as the number of persons one can rely on for support. Social support can also be conceived as the amount of support received, regardless of the number of persons one receives support from. In addition, socially supportive relationships can be conceptualized on a continuum of quality from very poor to very good. Examination of all these facets has proven important in understanding relationships between depression and social support.

Overall, people in contact with numerous socially supportive persons are less likely to have mental health difficulties, including depression. In addition, those who perceive a great deal of support from others are less likely to be negatively affected by stressors that might lead to depression. For people who have become depressed, having a confidant such as a spouse or best friend and a supportive family is related to greater success in treatment. The quality of such relationships is also important to treatment. In one study, for example, depressed persons with good-quality confidant relationships needed shorter periods of treatment than those with poor-quality confidant relationships.

The effects of social support for people with bipolar depressive disorders have not been as well studied as the effects for people with unipolar depressive disorders. Nonetheless, research suggests that social support is indeed beneficial for people with bipolar disorders. In one study, for example, a great deal of available social support was related to fewer psychological symptoms, better social adjustment, and better overall functioning.

Ways of coping with stressors can be roughly divided into two categories: approach strategies and avoidance strategies. Approach strategies are characterized by identifying the problematic situation, devising reasonable solutions to it, an implementing those solutions. Avoidance strategies include trying not to think about the problem, wishing the problem did not exist, and fantasizing about life without the problem. Overall, approach strategies seem to help people cope with stressors that might otherwise lead to depression. In addition, use of approach strategies is associated with better treatment outcome for those who become depressed. Conversely, people who use avoidance strategies to cope with stress seem more likely to become depressed and to have poorer treatment outcomes.

As with the effects of social support, research on coping styles among people with bipolar depressive disorders is scarce. Nonetheless, one recent study that examined differences in coping between high- and low-functioning people with bipolar disorders suggested that avoidant coping styles are associated with poorer functioning. Thus, relationships between coping styles and bipolar depressive disorders and coping and unipolar depressive disorders may be similar.

Bibliography:

• Beck, A. T. (1967). Depression: Causes and treatment. Philadelphia: University of Pennsylvania Press.
• Beckham, E. E., & Leber W. R. (1995). (Eds.). Handbook of depression (2nd ed. ). New York: Guilford Press.
• Cicchetti, D., & Toth, S. L. (1992). (Eds.). Developmental perspectives on depression. Rochester, NY: University of Rochester Press.
• Craig, K. D., & Dobson, K. S. (1995). (Eds.). Anxiety and depression in children and adults. Thousand Oaks, CA: Sage.
• Kendall, P. C., Hollon, S. D., Beck, A. T., Hammen, C. L., & Ingram, R. E. (1987). Issues and recommendations regarding use of the Beck Depression Inventory. Cognitive Therapy and Research, 11,289-299.
• Ingrain, R. E., Miranda, J., & Segal, Z. V. (in press). Cognitive vulnerability to depression. New York: Guilford Press.
• Robins, L. N., & Regier, D. A. (1991). (Eds.). Psychiatric disorders in America. New York: The Free Press.

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Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts

• 1 Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
• 2 Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
• 3 School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
• 4 School of Medical Sciences, Örebro University, Örebro, Sweden
• 5 Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
• 6 MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom

Question   Could multitrait polygenic risk scores be used to strengthen genetic prediction of longitudinal depression across adolescence?

Findings   In this longitudinal cohort replication study of 14 112 adolescents, stronger effect sizes of multitrait polygenic risk association with adverse depression trajectories were found compared with unitrait genetic risk.

Meaning   Longitudinal depression has a robust genetic underpinning, and leveraging shared genetic information across multiple psychiatric traits may strengthen prediction models of depression in adolescence.

Importance   Adolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.

Objective   To investigate univariate and multivariate genetic risk for adolescent depression trajectories and assess generalizability across ancestries.

Design, Setting, and Participants   This cohort study entailed longitudinal growth modeling followed by polygenic risk score (PRS) association testing for individual and multitrait genetic models. Two longitudinal cohorts from the US and UK were used: the Adolescent Brain and Cognitive Development (ABCD; N = 11 876) study and the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8787) study. Included were adolescents with genetic information and depression measures at up to 8 and 4 occasions, respectively. Study data were analyzed January to July 2023.

Main Outcomes and Measures   Trajectories were derived from growth mixture modeling of longitudinal depression symptoms. PRSs were computed for depression, anxiety, neuroticism, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism in European ancestry. Genomic structural equation modeling was used to build multitrait genetic models of psychopathology followed by multitrait PRS. Depression PRSs were computed in African, East Asian, and Hispanic ancestries in the ABCD cohort only. Association testing was performed between all PRSs and trajectories for both cohorts.

Results   A total sample size of 14 112 adolescents (at baseline: mean [SD] age, 10.5 [0.5] years; 7269 male sex [52%]) from both cohorts were included in this analysis. Distinct depression trajectories (stable low, adolescent persistent, increasing, and decreasing) were replicated in the ALSPAC cohort (6096 participants; 3091 female [51%]) and ABCD cohort (8016 participants; 4274 male [53%]) between ages 10 and 17 years. Most univariate PRSs showed significant uniform associations with persistent trajectories, but fewer were significantly associated with intermediate (increasing and decreasing) trajectories. Multitrait PRSs—derived from a hierarchical factor model—showed the strongest associations for persistent trajectories (ABCD cohort: OR, 1.46; 95% CI, 1.26-1.68; ALSPAC cohort: OR, 1.34; 95% CI, 1.20-1.49), surpassing the effect size of univariate PRS in both cohorts. Multitrait PRSs were associated with intermediate trajectories but to a lesser extent (ABCD cohort: hierarchical increasing, OR, 1.27; 95% CI, 1.13-1.43; decreasing, OR, 1.23; 95% CI, 1.09-1.40; ALSPAC cohort: hierarchical increasing, OR, 1.16; 95% CI, 1.04-1.28; decreasing, OR, 1.32; 95% CI, 1.18-1.47). Transancestral genetic risk for depression showed no evidence for association with trajectories.

Conclusions and Relevance   Results of this cohort study revealed a high multitrait genetic loading of persistent symptom trajectories, consistent across traits and cohorts. Variability in univariate genetic association with intermediate trajectories may stem from environmental factors. Multitrait genetics may strengthen depression prediction models, but more diverse data are needed for generalizability.

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Grimes PZ , Adams MJ , Thng G, et al. Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts. JAMA Psychiatry. Published online May 15, 2024. doi:10.1001/jamapsychiatry.2024.0983

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• Published: 16 May 2024

Procrastination, depression and anxiety symptoms in university students: a three-wave longitudinal study on the mediating role of perceived stress

• Anna Jochmann 1 ,
• Burkhard Gusy 1 ,
• Tino Lesener 1 &
• Christine Wolter 1  

BMC Psychology volume  12 , Article number:  276 ( 2024 ) Cite this article

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Metrics details

It is generally assumed that procrastination leads to negative consequences. However, evidence for negative consequences of procrastination is still limited and it is also unclear by which mechanisms they are mediated. Therefore, the aim of our study was to examine the harmful consequences of procrastination on students’ stress and mental health. We selected the procrastination-health model as our theoretical foundation and tried to evaluate the model’s assumption that trait procrastination leads to (chronic) disease via (chronic) stress in a temporal perspective. We chose depression and anxiety symptoms as indicators for (chronic) disease and hypothesized that procrastination leads to perceived stress over time, that perceived stress leads to depression and anxiety symptoms over time, and that procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress.

To examine these relationships properly, we collected longitudinal data from 392 university students at three occasions over a one-year period and analyzed the data using autoregressive time-lagged panel models.

Procrastination did lead to depression and anxiety symptoms over time. However, perceived stress was not a mediator of this effect. Procrastination did not lead to perceived stress over time, nor did perceived stress lead to depression and anxiety symptoms over time.

Conclusions

We could not confirm that trait procrastination leads to (chronic) disease via (chronic) stress, as assumed in the procrastination-health model. Nonetheless, our study demonstrated that procrastination can have a detrimental effect on mental health. Further health outcomes and possible mediators should be explored in future studies.

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Introduction

“Due tomorrow? Do tomorrow.”, might be said by someone who has a tendency to postpone tasks until the last minute. But can we enjoy today knowing about the unfinished task and tomorrow’s deadline? Or do we feel guilty for postponing a task yet again? Do we get stressed out because we have little time left to complete it? Almost everyone has procrastinated at some point when it came to completing unpleasant tasks, such as mowing the lawn, doing the taxes, or preparing for exams. Some tend to procrastinate more frequently and in all areas of life, while others are less inclined to do so. Procrastination is common across a wide range of nationalities, as well as socioeconomic and educational backgrounds [ 1 ]. Over the last fifteen years, there has been a massive increase in research on procrastination [ 2 ]. Oftentimes, research focuses on better understanding the phenomenon of procrastination and finding out why someone procrastinates in order to be able to intervene. Similarly, the internet is filled with self-help guides that promise a way to overcome procrastination. But why do people seek help for their procrastination? Until now, not much research has been conducted on the negative consequences procrastination could have on health and well-being. Therefore, in the following article we examine the effect of procrastination on mental health over time and stress as a possible facilitator of this relationship on the basis of the procrastination-health model by Sirois et al. [ 3 ].

Procrastination and its negative consequences

Procrastination can be defined as the tendency to voluntarily and irrationally delay intended activities despite expecting negative consequences as a result of the delay [ 4 , 5 ]. It has been observed in a variety of groups across the lifespan, such as students, teachers, and workers [ 1 ]. For example, some students tend to regularly delay preparing for exams and writing essays until the last minute, even if this results in time pressure or lower grades. Procrastination must be distinguished from strategic delay [ 4 , 6 ]. Delaying a task is considered strategic when other tasks are more important or when more resources are needed before the task can be completed. While strategic delay is viewed as functional and adaptive, procrastination is classified as dysfunctional. Procrastination is predominantly viewed as the result of a self-regulatory failure [ 7 ]. It can be understood as a trait, that is, as a cross-situational and time-stable behavioral disposition [ 8 ]. Thus, it is assumed that procrastinators chronically delay tasks that they experience as unpleasant or difficult [ 9 ]. Approximately 20 to 30% of adults have been found to procrastinate chronically [ 10 , 11 , 12 ]. Prevalence estimates for students are similar [ 13 ]. It is believed that students do not procrastinate more often than other groups. However, it is easy to examine procrastination in students because working on study tasks requires a high degree of self-organization and time management [ 14 ].

It is generally assumed that procrastination leads to negative consequences [ 4 ]. Negative consequences are even part of the definition of procrastination. Research indicates that procrastination is linked to lower academic performance [ 15 ], health impairment (e.g., stress [ 16 ], physical symptoms [ 17 ], depression and anxiety symptoms [ 18 ]), and poor health-related behavior (e.g., heavier alcohol consumption [ 19 ]). However, most studies targeting consequences of procrastination are cross-sectional [ 4 ]. For that reason, it often remains unclear whether an examined outcome is a consequence or an antecedent of procrastination, or whether a reciprocal relationship between procrastination and the examined outcome can be assumed. Additionally, regarding negative consequences of procrastination on health, it is still largely unknown by which mechanisms they are mediated. Uncovering such mediators would be helpful in developing interventions that can prevent negative health consequences of procrastination.

The procrastination-health model

The first and only model that exclusively focuses on the effect of procrastination on health and the mediators of this effect is the procrastination-health model [ 3 , 9 , 17 ]. Sirois [ 9 ] postulates three pathways: An immediate effect of trait procrastination on (chronic) disease and two mediated pathways (see Fig.  1 ).

Adopted from the procrastination-health model by Sirois [ 9 ]

The immediate effect is not further explained. Research suggests that procrastination creates negative feelings, such as shame, guilt, regret, and anger [ 20 , 21 , 22 ]. The described feelings could have a detrimental effect on mental health [ 23 , 24 , 25 ].

The first mediated pathway leads from trait procrastination to (chronic) disease via (chronic) stress. Sirois [ 9 ] assumes that procrastination creates stress because procrastinators are constantly aware of the fact that they still have many tasks to complete. Stress activates the hypothalamic-pituitary-adrenocortical (HPA) system, increases autonomic nervous system arousal, and weakens the immune system, which in turn contributes to the development of diseases. Sirois [ 9 ] distinguishes between short-term and long-term effects of procrastination on health mediated by stress. She believes that, in the short term, single incidents of procrastination cause acute stress, which leads to acute health problems, such as infections or headaches. In the long term, chronic procrastination, as you would expect with trait procrastination, causes chronic stress, which leads to chronic diseases over time. There is some evidence in support of the stress-related pathway, particularly regarding short-term effects [ 3 , 17 , 26 , 27 , 28 ]. However, as we mentioned above, most of these studies are cross-sectional. Therefore, the causal direction of these effects remains unclear. To our knowledge, long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress have not yet been investigated.

The second mediated pathway leads from trait procrastination to (chronic) disease via poor health-related behavior. According to Sirois [ 9 ], procrastinators form lower intentions to carry out health-promoting behavior or to refrain from health-damaging behavior because they have a low self-efficacy of being able to care for their own health. In addition, they lack the far-sighted view that the effects of health-related behavior only become apparent in the long term. For the same reason, Sirois [ 9 ] believes that there are no short-term, but only long-term effects of procrastination on health mediated by poor health-related behavior. For example, an unhealthy diet leads to diabetes over time. The findings of studies examining the behavioral pathway are inconclusive [ 3 , 17 , 26 , 28 ]. Furthermore, since most of these studies are cross-sectional, they are not suitable for uncovering long-term effects of trait procrastination on (chronic) disease mediated by poor health-related behavior.

In summary, previous research on the two mediated pathways of the procrastination-health model mainly found support for the role of (chronic) stress in the relationship between trait procrastination and (chronic) disease. However, only short-term effects have been investigated so far. Moreover, longitudinal studies are needed to be able to assess the causal direction of the relationship between trait procrastination, (chronic) stress, and (chronic) disease. Consequently, our study is the first to examine long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, using a longitudinal design. (Chronic) disease could be measured by a variety of different indicators (e.g., physical symptoms, diabetes, or coronary heart disease). We choose depression and anxiety symptoms as indicators for (chronic) disease because they signal mental health complaints before they manifest as (chronic) diseases. Additionally, depression and anxiety symptoms are two of the most common mental health complaints among students [ 29 , 30 ] and procrastination has been shown to be a significant predictor of depression and anxiety symptoms [ 18 , 31 , 32 , 33 , 34 ]. Until now, the stress-related pathway of the procrastination-health model with depression and anxiety symptoms as the health outcome has only been analyzed in one cross-sectional study that confirmed the predictions of the model [ 35 ].

The aim of our study is to evaluate some of the key assumptions of the procrastination-health model, particularly the relationships between trait procrastination, (chronic) stress, and (chronic) disease over time, surveyed in the following analysis using depression and anxiety symptoms.

In line with the key assumptions of the procrastination-health model, we postulate (see Fig.  2 ):

Procrastination leads to perceived stress over time.

Perceived stress leads to depression and anxiety symptoms over time.

Procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress.

The section of the procrastination-health model we examined

Materials and methods

Our study was part of a health monitoring at a large German university Footnote 1 . Ethical approval for our study was granted by the Ethics Committee of the university’s Department of Education and Psychology. We collected the initial data in 2019. Two occasions followed, each at an interval of six months. In January 2019, we sent out 33,267 invitations to student e-mail addresses. Before beginning the survey, students provided their written informed consent to participate in our study. 3,420 students took part at the first occasion (T1; 10% response rate). Of these, 862 participated at the second (T2) and 392 at the third occasion (T3). In order to test whether dropout was selective, we compared sociodemographic and study specific characteristics (age, gender, academic semester, number of assessments/exams) as well as behavior and health-related variables (procrastination, perceived stress, depression and anxiety symptoms) between the participants of the first wave ( n  = 3,420) and those who participated three times ( n  = 392). Results from independent-samples t-tests and chi-square analysis showed no significant differences regarding sociodemographic and study specific characteristics (see Additional file 1: Table S1 and S2 ). Regarding behavior and health-related variables, independent-samples t-tests revealed a significant difference in procrastination between the two groups ( t (3,409) = 2.08, p  < .05). The mean score of procrastination was lower in the group that participated in all three waves.

The mean age of the longitudinal respondents was 24.1 years ( SD  = 5.5 years), the youngest participants were 17 years old, the oldest one was 59 years old. The majority of participants was female (74.0%), 7 participants identified neither as male nor as female (1.8%). The respondents were on average enrolled in the third year of studying ( M  = 3.9; SD  = 2.3). On average, the students worked about 31.2 h ( SD  = 14.1) per week for their studies, and an additional 8.5 h ( SD  = 8.5) for their (part-time) jobs. The average income was €851 ( SD  = 406), and 4.9% of the students had at least one child. The students were mostly enrolled in philosophy and humanities (16.5%), education and psychology (15.8%), biology, chemistry, and pharmacy (12.5%), political and social sciences (10.6%), veterinary medicine (8.9%), and mathematics and computer science (7.7%).

We only used established and well evaluated instruments for our analyses.

• Procrastination

We adopted the short form of the Procrastination Questionnaire for Students (PFS-4) [ 36 ] to measure procrastination. The PFS-4 assesses procrastination at university as a largely stable behavioral disposition across situations, that is, as a trait. The questionnaire consists of four items (e.g., I put off starting tasks until the last moment.). Each item was rated on a 5-point scale ((almost) never = 1 to (almost) always = 5) for the last two weeks. All items were averaged, with higher scores indicating a greater tendency to procrastinate. The PFS-4 has been proven to be reliable and valid, showing very high correlations with other established trait procrastination scales, for example, with the German short form of the General Procrastination Scale [ 37 , 38 ]. We also proved the scale to be one-dimensional in a factor analysis, with a Cronbach’s alpha of 0.90.

Perceived stress

The Heidelberger Stress Index (HEI-STRESS) [ 39 ] is a three-item measure of current perceived stress due to studying as well as in life in general. For the first item, respondents enter a number between 0 (not stressed at all) and 100 (completely stressed) to indicate how stressed their studies have made them feel over the last four weeks. For the second and third item, respondents rate on a 5-point scale how often they feel “stressed and tense” and as how stressful they would describe their life at the moment. We transformed the second and third item to match the range of the first item before we averaged all items into a single score with higher values indicating greater perceived stress. We proved the scale to be one-dimensional and Cronbach’s alpha for our study was 0.86.

Depression and anxiety symptoms

We used the Patient Health Questionnaire-4 (PHQ-4) [ 40 ], a short form of the Patient Health Questionnaire [ 41 ] with four items, to measure depression and anxiety symptoms. The PHQ-4 contains two items from the Patient Health Questionnaire-2 (PHQ-2) [ 42 ] and the Generalized Anxiety Disorder Scale-2 (GAD-2) [ 43 ], respectively. It is a well-established screening scale designed to assess the core criteria of major depressive disorder (PHQ-2) and generalized anxiety disorder (GAD-2) according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). However, it was shown that the GAD-2 is also appropriate for screening other anxiety disorders. According to Kroenke et al. [ 40 ], the PHQ-4 can be used to assess a person’s symptom burden and impairment. We asked the participants to rate how often they have been bothered over the last two weeks by problems, such as “Little interest or pleasure in doing things”. Response options were 0 = not at all, 1 = several days, 2 = more than half the days, and 3 = nearly every day. Calculated as the sum of the four items, the total scores range from 0 to 12 with higher scores indicating more frequent depression and anxiety symptoms. The total scores can be categorized as none-to-minimal (0–2), mild (3–5), moderate (6–8), and severe (9–12) depression and anxiety symptoms. The PHQ-4 was shown to be reliable and valid [ 40 , 44 , 45 ]. We also proved the scale to be one-dimensional in a factor analysis, with a Cronbach’s alpha of 0.86.

Data analysis

To test our hypotheses, we performed structural equation modelling (SEM) using R (Version 4.1.1) with the package lavaan. All items were standardized ( M  = 0, SD  = 1). Due to the non-normality of some study variables and a sufficiently large sample size of N near to 400 [ 46 ], we used robust maximum likelihood estimation (MLR) for all model estimations. As recommended by Hu and Bentler [ 47 ], we assessed the models’ goodness of fit by chi-square test statistic, root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), Tucker-Lewis index (TLI), and comparative fit index (CFI). A non-significant chi-square indicates good model fit. Since chi-square is sensitive to sample size, we also evaluated fit indices less sensitive to the number of observations. RMSEA and SRMR values of 0.05 or lower as well as TLI and CFI values of 0.97 or higher indicate good model fit. RMSEA values of 0.08 or lower, SRMR values of 0.10 or lower, as well as TLI and CFI values of 0.95 or higher indicate acceptable model fit [ 48 , 49 ]. First, we conducted confirmatory factor analysis for the first occasion, defining three factors that correspond to the measures of procrastination, perceived stress, and depression and anxiety symptoms. Next, we tested for measurements invariance over time and specified the measurement model, before testing our hypotheses.

Measurement invariance over time

To test for measurement invariance over time, we defined one latent variable for each of the three occasions, corresponding to the measures of procrastination, perceived stress, and depression and anxiety symptoms, respectively. As recommended by Geiser and colleagues [ 50 ], the links between indicators and factors (i.e., factor loadings and intercepts) should be equal over measurement occasions; therefore, we added indicator specific factors. A first and least stringent step of testing measurement invariance is configural invariance (M CI ). It was examined whether the included constructs (procrastination, perceived stress, depression and anxiety symptoms) have the same pattern of free and fixed loadings over time. This means that the assignment of the indicators to the three latent factors over time is supported by the underlying data. If configural invariance was supported, restrictions for the next step of testing measurement invariance (metric or weak invariance; M MI ) were added. This means that each item contributes to the latent construct to a similar degree over time. Metric invariance was tested by constraining the factor loadings of the constructs over time. The next step of testing measurement invariance (scalar or strong invariance; M SI ) consisted of checking whether mean differences in the latent construct capture all mean differences in the shared variance of the items. Scalar invariance was tested by constraining the item intercepts over time. The constraints applied in the metric invariance model were retained [ 51 ]. For the last step of testing measurement invariance (residual or strict invariance; M RI ), the residual variables were also set equal over time. If residual invariance is supported, differences in the observed variables can exclusively be attributed to differences in the variances of the latent variables.

We used the Satorra-Bentler chi-square difference test to evaluate the superiority of a more stringent model [ 52 ]. We assumed the model with the largest number of invariance restrictions – which still has an acceptable fit and no substantial deterioration of the chi-square value – to be the final model [ 53 ]. Following previous recommendations, we considered a decrease in CFI of 0.01 and an increase in RMSEA of 0.015 as unacceptable to establish measurement invariance [ 54 ]. If a more stringent model had a significant worse chi-square value, but the model fit was still acceptable and the deterioration in model fit fell within the change criteria recommended for CFI and RMSEA values, we still considered the more stringent model to be superior.

Hypotheses testing

As recommended by Dormann et al. [ 55 ], we applied autoregressive time-lagged panel models to test our hypotheses. In the first step, we specified a model (M 0 ) that only included the stabilities of the three variables (procrastination, perceived stress, depression and anxiety symptoms) over time. In the next step (M 1 ), we added the time-lagged effects from procrastination (T1) to perceived stress (T2) and from procrastination (T2) to perceived stress (T3) as well as from perceived stress (T1) to depression and anxiety symptoms (T2) and from perceived stress (T2) to depression and anxiety symptoms (T3). Additionally, we included a direct path from procrastination (T1) to depression and anxiety symptoms (T3). If this path becomes significant, we can assume a partial mediation [ 55 ]. Otherwise, we can assume a full mediation. We compared these nested models using the Satorra-Bentler chi-square difference test and the Akaike information criterion (AIC). The chi-square difference value should either be non-significant, indicating that the proposed model including our hypotheses (M 1 ) does not have a significant worse model fit than the model including only stabilities (M 0 ), or, if significant, it should be in the direction that M 1 fits the data better than M 0 . Regarding the AIC, M 1 should have a lower value than M 0 .

Table  1 displays the means, standard deviations, internal consistencies (Cronbach’s alpha), and stabilities (correlations) of all study variables. The alpha values of procrastination, perceived stress, and depression and anxiety symptoms are classified as good (> 0.80) [ 56 ]. The correlation matrix of the manifest variables used for the analyses can be found in the Additional file 1: Table  S3 .

We observed the highest test-retest reliabilities for procrastination ( r  ≥ .74). The test-retest reliabilities for depression and anxiety symptoms ( r  ≥ .64) and for perceived stress ( r  ≥ .54) were a bit lower (see Table  1 ). The pattern of correlations shows a medium to large but positive relationship between procrastination and depression and anxiety symptoms [ 57 , 58 ]. The association between procrastination and perceived stress was small, the one between perceived stress and depression and anxiety symptoms very large (see Table  1 ).

Confirmatory factor analysis showed an acceptable to good fit (x 2 (41) = 118.618, p  < .001; SRMR = 0.042; RMSEA = 0.071; TLI = 0.95; CFI = 0.97). When testing for measurement invariance over time for each construct, the residual invariance models with indicator specific factors provided good fit to the data (M RI ; see Table  2 ), suggesting that differences in the observed variables can exclusively be attributed to differences of the latent variables. We then specified and tested the measurement model of the latent constructs prior to model testing based on the items of procrastination, perceived stress, and depression and anxiety symptoms. The measurement model fitted the data well (M M ; see Table  3 ). All items loaded solidly on their respective factors (0.791 ≤ β ≤ 0.987; p  < .001).

To test our hypotheses, we analyzed the two models described in the methods section.

The fit of the stability model (M 0 ) was acceptable (see Table  3 ). Procrastination was stable over time, with stabilities above 0.82. The stabilities of perceived stress as well as depression and anxiety symptoms were somewhat lower, ranging from 0.559 (T1 -> T2) to 0.696 (T2 -> T3) for perceived stress and from 0.713 (T2 -> T3) to 0.770 (T1 -> T2) for depression and anxiety symptoms, respectively.

The autoregressive mediation model (M 1 ) fitted the data significantly better than M 0 . The direct path from procrastination (T1) to depression and anxiety symptoms (T3) was significant (β = 0.16; p  < .001), however, none of the mediated paths (from procrastination (T1) to perceived stress (T2) and from perceived stress (T2) to depression and anxiety symptoms (T3)) proved to be substantial. Also, the time-lagged paths from perceived stress (T1) to depression and anxiety symptoms (T2) and from procrastination (T2) to perceived stress (T3) were not substantial either (see Fig.  3 ).

To examine whether the hypothesized effects would occur over a one-year period rather than a six-months period, we specified an additional model with paths from procrastination (T1) to perceived stress (T3) and from perceived stress (T1) to depression and anxiety symptoms (T3), also including the stabilities of the three constructs as in the stability model M 0 . The model showed an acceptable fit (χ 2 (486) = 831.281, p  < .001; RMSEA = 0.048; SRMR = 0.091; TLI = 0.95; CFI = 0.95), but neither of the two paths were significant.

Therefore, our hypotheses, that procrastination leads to perceived stress over time (H1) and that perceived stress leads to depression and anxiety symptoms over time (H2) must be rejected. We could only partially confirm our third hypothesis, that procrastination leads to depression and anxiety over time, mediated by perceived stress (H3), since procrastination did lead to depression and anxiety symptoms over time. However, this effect was not mediated by perceived stress.

Results of the estimated model including all hypotheses (M 1 ). Note Non-significant paths are dotted. T1 = time 1; T2 = time 2; T3 = time 3. *** p  < .001

To sum up, we tried to examine the harmful consequences of procrastination on students’ stress and mental health. Hence, we selected the procrastination-health model by Sirois [ 9 ] as a theoretical foundation and tried to evaluate some of its key assumptions in a temporal perspective. The author assumes that trait procrastination leads to (chronic) disease via (chronic) stress. We chose depression and anxiety symptoms as indicators for (chronic) disease and postulated, in line with the key assumptions of the procrastination-health model, that procrastination leads to perceived stress over time (H1), that perceived stress leads to depression and anxiety symptoms over time (H2), and that procrastination leads to depression and anxiety symptoms over time, mediated by perceived stress (H3). To examine these relationships properly, we collected longitudinal data from students at three occasions over a one-year period and analyzed the data using autoregressive time-lagged panel models. Our first and second hypotheses had to be rejected: Procrastination did not lead to perceived stress over time, and perceived stress did not lead to depression and anxiety symptoms over time. However, procrastination did lead to depression and anxiety symptoms over time – which is in line with our third hypothesis – but perceived stress was not a mediator of this effect. Therefore, we could only partially confirm our third hypothesis.

Our results contradict previous studies on the stress-related pathway of the procrastination-health model, which consistently found support for the role of (chronic) stress in the relationship between trait procrastination and (chronic) disease. Since most of these studies were cross-sectional, though, the causal direction of these effects remained uncertain. There are two longitudinal studies that confirm the stress-related pathway of the procrastination-health model [ 27 , 28 ], but both studies examined short-term effects (≤ 3 months), whereas we focused on more long-term effects. Therefore, the divergent findings may indicate that there are short-term, but no long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress.

Our results especially raise the question whether trait procrastination leads to (chronic) stress in the long term. Looking at previous longitudinal studies on the effect of procrastination on stress, the following stands out: At shorter study periods of two weeks [ 27 ] and four weeks [ 28 ], the effect of procrastination on stress appears to be present. At longer study periods of seven weeks [ 59 ], three months [ 28 ], six months, and twelve months, as in our study, the effect of procrastination on stress does not appear to be present. There is one longitudinal study in which procrastination was a significant predictor of stress symptoms nine months later [ 34 ]. The results of this study should be interpreted with caution, though, because the outbreak of the COVID-19 pandemic fell within the study period, which could have contributed to increased stress symptoms [ 60 ]. Unfortunately, Johansson et al. [ 34 ] did not report whether average stress symptoms increased during their study. In one of the two studies conducted by Fincham and May [ 59 ], the COVID-19 pandemic outbreak also fell within their seven-week study period. However, they reported that in their study, average stress symptoms did not increase from baseline to follow-up. Taken together, the findings suggest that procrastination can cause acute stress in the short term, for example during times when many tasks need to be completed, such as at the end of a semester, but that procrastination does not lead to chronic stress over time. It seems possible that students are able to recover during the semester from the stress their procrastination caused at the end of the previous semester. Because of their procrastination, they may also have more time to engage in relaxing activities, which could further mitigate the effect of procrastination on stress. Our conclusions are supported by an early and well-known longitudinal study by Tice and Baumeister [ 61 ], which compared procrastinating and non-procrastinating students with regard to their health. They found that procrastinators experienced less stress than their non-procrastinating peers at the beginning of the semester, but more at the end of the semester. Additionally, our conclusions are in line with an interview study in which university students were asked about the consequences of their procrastination [ 62 ]. The students reported that, due to their procrastination, they experience high levels of stress during periods with heavy workloads (e.g., before deadlines or exams). However, the stress does not last, instead, it is relieved immediately after these periods.

Even though research indicates, in line with the assumptions of the procrastination-health model, that stress is a risk factor for physical and mental disorders [ 63 , 64 , 65 , 66 ], perceived stress did not have a significant effect on depression and anxiety symptoms in our study. The relationship between stress and mental health is complex, as people respond to stress in many different ways. While some develop stress-related mental disorders, others experience mild psychological symptoms or no symptoms at all [ 67 ]. This can be explained with the help of vulnerability-stress models. According to vulnerability-stress models, mental illnesses emerge from an interaction of vulnerabilities (e.g., genetic factors, difficult family backgrounds, or weak coping abilities) and stress (e.g., minor or major life events or daily hassles) [ 68 , 69 ]. The stress perceived by the students in our sample may not be sufficient enough on its own, without the presence of other risk factors, to cause depression and anxiety symptoms. However, since we did not assess individual vulnerability and stress factors in our study, these considerations are mere speculation.

In our study, procrastination led to depression and anxiety symptoms over time, which is consistent with the procrastination-health model as well as previous cross-sectional and longitudinal evidence [ 18 , 21 , 31 , 32 , 33 , 34 ]. However, it is still unclear by which mechanisms this effect is mediated, as perceived stress did not prove to be a substantial mediator in our study. One possible mechanism would be that procrastination impairs affective well-being [ 70 ] and creates negative feelings, such as shame, guilt, regret, and anger [ 20 , 21 , 22 , 62 , 71 ], which in turn could lead to depression and anxiety symptoms [ 23 , 24 , 25 ]. Other potential mediators of the relationship between procrastination and depression and anxiety symptoms emerge from the behavioral pathway of the procrastination-health model, suggesting that poor health-related behaviors mediate the effect of trait procrastination on (chronic) disease. Although evidence for this is still scarce, the results of one cross-sectional study, for example, indicate that poor sleep quality might mediate the effect of procrastination on depression and anxiety symptoms [ 35 ].

In summary, we found that procrastination leads to depression and anxiety symptoms over time and that perceived stress is not a mediator of this effect. We could not show that procrastination leads to perceived stress over time, nor that perceived stress leads to depression and anxiety symptoms over time. For the most part, the relationships between procrastination, perceived stress, and depression and anxiety symptoms did not match the relationships between trait procrastination, (chronic) stress, and (chronic) disease as assumed in the procrastination-health model. Explanations for this could be that procrastination might only lead to perceived stress in the short term, for example, during preparations for end-of-semester exams, and that perceived stress may not be sufficient enough on its own, without the presence of other risk factors, to cause depression and anxiety symptoms. In conclusion, we could not confirm long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, as assumed for the stress-related pathway of the procrastination-health model.

Limitations and suggestions for future research

In our study, we tried to draw causal conclusions about the harmful consequences of procrastination on students’ stress and mental health. However, since procrastination is a trait that cannot be manipulated experimentally, we have conducted an observational rather than an experimental study, which makes causal inferences more difficult. Nonetheless, a major strength of our study is that we used a longitudinal design with three waves. This made it possible to draw conclusions about the causal direction of the effects, as in hardly any other study targeting consequences of procrastination on health before [ 4 , 28 , 55 ]. Therefore, we strongly recommend using a similar longitudinal design in future studies on the procrastination-health model or on consequences of procrastination on health in general.

We chose a time lag of six months between each of the three measurement occasions to examine long-term effects of procrastination on depression and anxiety symptoms mediated by perceived stress. However, more than six months may be necessary for the hypothesized effects to occur [ 72 ]. The fact that the temporal stabilities of the examined constructs were moderate or high (0.559 ≤ β ≤ 0.854) [ 73 , 74 ] also suggests that the time lags may have been too short. The larger the time lag, the lower the temporal stabilities, as shown for depression and anxiety symptoms, for example [ 75 ]. High temporal stabilities make it more difficult to detect an effect that actually exists [ 76 ]. Nonetheless, Dormann and Griffin [ 77 ] recommend using shorter time lags of less than one year, even with high stabilities, because of other influential factors, such as unmeasured third variables. Therefore, our time lags of six months seem appropriate.

It should be discussed, though, whether it is possible to detect long-term effects of the stress-related pathway of the procrastination-health model within a total study period of one year. Sirois [ 9 ] distinguishes between short-term and long-term effects of procrastination on health mediated by stress, but does not address how long it might take for long-term effects to occur or when effects can be considered long-term instead of short-term. The fact that an effect of procrastination on stress is evident at shorter study periods of four weeks or less but in most cases not at longer study periods of seven weeks or more, as we mentioned earlier, could indicate that short-term effects occur within the time frame of one to three months, considering the entire stress-related pathway. Hence, it seems appropriate to assume that we have examined rather long-term effects, given our study period of six and twelve months. Nevertheless, it would be beneficial to use varying study periods in future studies, in order to be able to determine when effects can be considered long-term.

Concerning long-term effects of the stress-related pathway, Sirois [ 9 ] assumes that chronic procrastination causes chronic stress, which leads to chronic diseases over time. The term “chronic stress” refers to prolonged stress episodes associated with permanent tension. The instrument we used captures perceived stress over the last four weeks. Even though the perceived stress of the students in our sample was relatively stable (0.559 ≤ β ≤ 0.696), we do not know how much fluctuation occurred between each of the three occasions. However, there is some evidence suggesting that perceived stress is strongly associated with chronic stress [ 78 ]. Thus, it seems acceptable that we used perceived stress as an indicator for chronic stress in our study. For future studies, we still suggest the use of an instrument that can more accurately reflect chronic stress, for example, the Trier Inventory for Chronic Stress (TICS) [ 79 ].

It is also possible that the occasions were inconveniently chosen, as they all took place in a critical academic period near the end of the semester, just before the examination period began. We chose a similar period in the semester for each occasion for the sake of comparability. However, it is possible that, during this preparation periods, stress levels peaked and procrastinators procrastinated less because they had to catch up after delaying their work. This could have introduced bias to the data. Therefore, in future studies, investigation periods should be chosen that are closer to the beginning or in the middle of a semester.

Furthermore, Sirois [ 9 ] did not really explain her understanding of “chronic disease”. However, it seems clear that physical illnesses, such as diabetes or cardiovascular diseases, are meant. Depression and anxiety symptoms, which we chose as indicators for chronic disease, represent mental health complaints that do not have to be at the level of a major depressive disorder or an anxiety disorder, in terms of their quantity, intensity, or duration [ 40 ]. But they can be viewed as precursors to a major depressive disorder or an anxiety disorder. Therefore, given our study period of one year, it seems appropriate to use depression and anxiety symptoms as indicators for chronic disease. At longer study periods, we would expect these mental health complaints to manifest as mental disorders. Moreover, the procrastination-health model was originally designed to be applied to physical diseases [ 3 ]. Perhaps, the model assumptions are more applicable to physical diseases than to mental disorders. By applying parts of the model to mental health complaints, we have taken an important step towards finding out whether the model is applicable to mental disorders as well. Future studies should examine additional long-term health outcomes, both physical and psychological. This would help to determine whether trait procrastination has varying effects on different diseases over time. Furthermore, we suggest including individual vulnerability and stress factors in future studies in order to be able to analyze the effect of (chronic) stress on (chronic) diseases in a more differentiated way.

Regarding our sample, 3,420 students took part at the first occasion, but only 392 participated three times, which results in a dropout rate of 88.5%. At the second and third occasion, invitation e-mails were only sent to participants who had indicated at the previous occasion that they would be willing to participate in a repeat survey and provided their e-mail address. This is probably one of the main reasons for our high dropout rate. Other reasons could be that the students did not receive any incentives for participating in our study and that some may have graduated between the occasions. Selective dropout analysis revealed that the mean score of procrastination was lower in the group that participated in all three waves ( n  = 392) compared to the group that participated in the first wave ( n  = 3,420). One reason for this could be that those who have a higher tendency to procrastinate were more likely to procrastinate on filling out our survey at the second and third occasion. The findings of our dropout analysis should be kept in mind when interpreting our results, as lower levels of procrastination may have eliminated an effect on perceived stress or on depression and anxiety symptoms. Additionally, across all age groups in population-representative samples, the student age group reports having the best subjective health [ 80 ]. Therefore, it is possible that they are more resilient to stress and experience less impairment of well-being than other age groups. Hence, we recommend that future studies focus on other age groups as well.

It is generally assumed that procrastination leads to lower academic performance, health impairment, and poor health-related behavior. However, evidence for negative consequences of procrastination is still limited and it is also unclear by which mechanisms they are mediated. In consequence, the aim of our study was to examine the effect of procrastination on mental health over time and stress as a possible facilitator of this relationship. We selected the procrastination-health model as a theoretical foundation and used the stress-related pathway of the model, assuming that trait procrastination leads to (chronic) disease via (chronic) stress. We chose depression and anxiety symptoms as indicators for (chronic) disease and collected longitudinal data from students at three occasions over a one-year period. This allowed us to draw conclusions about the causal direction of the effects, as in hardly any other study examining consequences of procrastination on (mental) health before. Our results indicate that procrastination leads to depression and anxiety symptoms over time and that perceived stress is not a mediator of this effect. We could not show that procrastination leads to perceived stress over time, nor that perceived stress leads to depression and anxiety symptoms over time. Explanations for this could be that procrastination might only lead to perceived stress in the short term, for example, during preparations for end-of-semester exams, and that perceived stress may not be sufficient on its own, that is, without the presence of other risk factors, to cause depression and anxiety symptoms. Overall, we could not confirm long-term effects of trait procrastination on (chronic) disease mediated by (chronic) stress, as assumed for the stress-related pathway of the procrastination-health model. Our study emphasizes the importance of identifying the consequences procrastination can have on health and well-being and determining by which mechanisms they are mediated. Only then will it be possible to develop interventions that can prevent negative health consequences of procrastination. Further health outcomes and possible mediators should be explored in future studies, using a similar longitudinal design.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

University Health Report at Freie Universität Berlin.

Abbreviations

Comparative fit index

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Generalized Anxiety Disorder Scale-2

Heidelberger Stress Index

Hypothalamic-pituitary-adrenocortical

Robust maximum likelihood estimation

Short form of the Procrastination Questionnaire for Students

Patient Health Questionnaire-2

Patient Health Questionnaire-4

Root mean square error of approximation

Structural equation modeling

Standardized root mean square residual

Tucker-Lewis index

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Suffering in silence with high-functioning depression | The Excerpt

On a special episode (first released on May 16) of The Excerpt podcast: Many people have some experience with depression. Often the condition goes away, but what if it doesn't? What if it's something you just learn to live with? With a term like ‘high-functioning’ attached to it, it may, by its very nature, be difficult to diagnose. So what is high-functioning depression and what can be done for the people who are suffering with it? Vale Wright, the senior director of Health Care Innovation at the American Psychological Association, joins The Excerpt to help answer these questions.

Hit play on the player below to hear the podcast and follow along with the transcript beneath it.  This transcript was automatically generated, and then edited for clarity in its current form. There may be some differences between the audio and the text.

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Dana Taylor:

Hello and welcome to The Excerpt. I'm Dana Taylor. When a disorder or condition has a term like high functioning attached to it, that could mean it may, by its very nature, be difficult to diagnose at all. Many of us have some experience with depression, but what if it just didn't go away? And worse, no one could tell that's why we weren't acting like our regular selves. So what is high functioning depression and what can be done for the people who are suffering with it? To answer these questions, I'm joined by Vaile Wright, the Senior Director of Healthcare Innovation at the American Psychological Association. Thanks for joining us, Vaile.

Vaile Wright:

Thanks so much for having me.

First, what is high functioning depression?

High functioning depression, it's not an official clinical term. I think that's important for people to know. It really was coined and popularized on social media to represent a certain presentation of depression. And that presentation is somebody who seemingly seems like they have it all together on the outside. They can go to work, they have relationships, they look like they're really engaging in life, but internally they're suffering in a way that others really just can't see.

And how does high functioning depression differ from other kinds of depression?

It's not necessarily that it differs from other kinds of depression. I think what a potential benefit of this term is, is it helps people understand that depression is not a one size fits all. People can be presenting with depression with a variety of different mild or more moderate symptoms. Some people will experience sadness, whereas others experience no sadness at all. So there isn't a typical type, but we have a mental model about what we think depression looks like, and this kind of breaks that mental model a little bit.

What are some of the other conditions that can show up alongside high functioning depression? I want to know, in particular, is anxiety in the mix.

Absolutely. There's a lot of comorbid relationship, or what we mean by that is they go together, anxiety and depression, and they share a lot of the same symptoms. So it can be really hard to decide, which is it. You can have trouble concentrating with both anxiety or depression, difficulty sleeping, difficulty eating or maintaining your appetite. So a lot of overlap exists, but at the end of the day, individuals experiencing these symptoms, it interferes with their life and it often interferes with the lives of people in their homes and in their schools and in their workplaces. So it affects everybody.

What are some of the telltale signs that a person is struggling with this condition?

I think when somebody feels like they're not themselves over an extended period of time, so anybody can feel sadness or just like you're just not into it and you're just not excited about the things you used to be excited about, but when that persists and when it either starts to interfere in your life some way or others start to get worried about you and notice that something's not how it usually is, that's when we know that something's really going on that might need some help.

And what about masking?

I think there's so much stigma attached with mental health, less now maybe than 10 years ago. I think social media and celebrities coming out and being more open about their mental health has really helped. But there's still this sense of we all have to have it together all the time, or even worse that even if I'm feeling sad, I have it better than you do and so I'm not allowed to feel sad. I shouldn't even tell you I'm sad because I have so many other things going on in my life. And that's so isolating and that just perpetuates the problem.

Vaile, other than that, what are some of the barriers that people face in acknowledging their depression and getting help?

There's so much sense that this is just all on your head, and if you just sort of pick yourself up by your bootstraps and you just go to work or do what you like to do or just go out and have fun, that somehow it'll all get better. And that's not the reality. For a lot of people depression is mild and situational and it might go away. For others, it's a lifelong condition that may have periods of wellness and then have periods of debilitation again. And so, again, I think it's often a lack of understanding of how to access care and when you need it, as well as just clear systemic issues within our healthcare for actually getting the care that we need.

And then offering people some help. How is it currently being treated medically? And also is talk therapy an effective treatment here?

Talk therapy is an incredibly effective treatment for all types of depression, particularly mild and moderate forms of depression. Other often avenues for treatment include medication, but what we do know is that when people get treated early on in what's going on, they're more likely to get better quicker. And so that early recognition and then that sort of ability to say or find somebody to help you find the help you need is going to be what is most effective in the long run. It just depends a little bit on what people's preferences are, what their opportunities are, what kinds of depression and symptoms they're experiencing, and that's why working with a trained professional is really critical.

And are there any specific scientific advances that you're looking at right now that people should be watching out for in terms of treating depression?

Certainly there's been a lot of talk about the use of psychedelics and other types of treatments and innovations in that area. I think the research is still awfully early to know exactly what impacts it will have. There's also clearly, I think, a role for technology to be played in how we reach people where there are. How do we get people in their homes, how do we reach them on their phones, which they're off and on anyway. But by delivering actually evidence-based, clinically validated treatments to them, not just an app that you can get off the app store, which may be helpful but likely isn't going to really treat your depression. So I think there's lots of ways that we need to be thinking innovatively because we just can't hope that everyone's going to come into the clinical office and get the treatment that they need. We need to be thinking beyond that.

Okay. So what does a successful path to recovery look like here? Without sharing any identifying information? Can you share a real world example?

It's going to look different depending on what it is that your depression is being caused by, because we know there's a lot of causes. It can be psychological, it can be environmental, it could be biological. But if you are going to receive treatment from a trained behavioral health provider, it's going to start with an intake and some history taking and then a shared decision-making about what type of treatment makes the most sense for that individual. Often we're talking about kind of weekly treatments for maybe six to eight weeks. And over that period of time, you're working with your provider to monitor your symptoms and see if you're getting better. And then ideally, you would end treatment after that phase when you've hit this place of recovery, recognizing that at any point in time you might need a booster going forward, and that's perfectly normal. And that's the kind of discussion you might have with your provider.

Well, depression can be a lonely place for people. What's your recommendation for a patient who is looking for support from the people in their lives?

Well, one of the things to keep in mind is that if you're feeling depressed, you're likely not alone. We know that annually, 17 million Americans will experience a depressive episode. So I think even though there's so much stigma and this fear of reaching out, when we do it can be so incredibly validating. You can find somebody who has experienced what you've experienced and can really understand where you're coming from or have engaged in coping skills that have worked for them that they can share with you. We also know that just having that social connection is a huge buffer for stress. So even though it can be hard to do, reaching out to others, and even more importantly, if you're that friend who's noticing something about your friend that you think is off, take that time, take that onus to do the reaching out yourself because sometimes they just don't have it in them right now.

Vaile, how would you say high-functioning depression and the conversation around it is impacting our society at large?

I think it's increasing our health literacy, in particular our mental health literacy. And it's shining a light on the fact that even though we think depression looks one way typically, that it's a woman who is crying and can't get out of bed. And that is one way that depression manifests itself, it's not the only way. And that different groups may experiencing different symptoms, and again, that somebody might have it looking like they have it all put together on the outside, but internally you don't really know what's going on with them. And so I think it helps to ask the question of, am I reaching out enough? Am I asking the people in my lives how they're doing?

Then finally, what do people most need to know about those with high functioning depression and how to best support them?

I think what's most important is to make sure you're not unintentionally invalidating their experience, because when somebody has it all put together or it looks like they do on the outside, it can be easy to say really unhelpful things like, I don't know why you're depressed, you have a job, or you're married, or you have these great kids. And really that's not taking compassionate routes understanding what they're going through. And so just even asking that question, I'd love to know what you're going through. I can see that you're in pain. Please, let's have a conversation. Just opening that door. You don't have to solve their depression, but just letting them know that you're there and that you hear them and you see them, that's a critical way to validate their experience.

This is great information. Thank you so much for being on The Excerpt Vaile.

Thanks for having me.

Thanks to our senior producers, Shannon Rae Green and Bradley Glanzrock for their production assistance. Our executive producer is Laura Beatty. Let us know what you think of this episode by sending a note to [email protected]. Thanks for listening. I'm Dana Taylor. Taylor Wilson will be back tomorrow morning with another episode of The Excerpt.

Depression rates among US adults reach new high: Gallup

Nearly 30% of adults say they've been diagnosed with depression at some point.

Depression rates in the United States are skyrocketing, particularly among young adults and women, a new poll shows.

The survey , published by Gallup on Wednesday, found 29% of U.S. adults report being diagnosed with depression at some point during their lifetimes, an increase from 19.6% in 2015.

Meanwhile, 17.8% of those aged 18 and older either currently have or are currently being treated for depression, up from 10.5% in 2015.

According to Gallup, both rates are the highest ever recorded by the analytics company since it began tracking depression rates.

MORE: Teen girls are experiencing record-high levels of sadness and violence: CDC

"I think the results are startling," Dan Witters, research director of the Gallup National Health and Well-Being, told ABC News. "The disproportionate manner in which some groups have been affected by this makes sense to me based upon what we know about other research and those sharp increases in those depression rates among those adults under 30, women too, Blacks and Hispanics, they are really eye-popping."

Although the COVID-19 pandemic can't be blamed completely for the increasing rates, it definitely was a major factor, Witters said.

"Both of these rates had kind of been coming up over the years pre-pandemic," he said. "And you don't want to get too far out in front of your skis as far as putting all the blame on the pandemic."

He went on, "There's plenty of other big factors out there that could be relevant to these increasing rates that we've been measuring but the pandemic's a big one and indeed the rates have really come up significantly in the years since COVID hit."

More than 5,100 adults were surveyed in all 50 states and the District of Columbia during the last week of February 2023. The results are part of the larger ongoing Gallup National Health and Well-Being Index, which seeks to track and understand factors that drive well-being.

Results showed rates are rising fastest among certain groups, particularly young adults and women.

Women's rates of depression during their lifetimes climbed from 26.2% in 2017 to 36.7% in 2023. Rates of those with current depression increased from 17.6% to 23.8% over the same period.

By comparison, men with depression during their lifetimes saw a smaller increase from 17.7% in 2017 to 20.4% in 2023. Current rates for depression rose from 9.3% to 11.3%.

Witters said women have historically had higher rates of depression than men. COVID, however, may have led to a jump in these rates due to women being disproportionately forced to leave the workforce to take care of children at home and that fact that they make up a higher percentage of frontline health care workers.

MORE: Suicides rose in 2021 after 2 years of declines, CDC report finds

Breakdowns by age showed one-third of younger adults between ages 18 to 29 reported being diagnosed with depression at some point in their lives, up from 20.4% in 2017. Additionally, 24.6% said they currently have depression, an increase from 13% in 2017.

Witters pointed to other research showing a growing mental health crisis among young people in the U.S.

"Obviously social media predates 2017, but social media had the effect on a lot of kids where they feel left out, they feel compelled to look at social media, and they see people out having fun, and they're not a part of it," he said. "They can get ostracized through social media."

Adults aged 65 and older had the smallest increase for depression and were the only group that saw a decrease in rates of current depression from 2021.

When it came to breakdowns by race/ethnicity, results showed rates for Black and Hispanic adults are rising at about twice the rate of white adults.

The percentage of Black adults diagnosed with depression at some point in their lifetime rose from 20.1% to 34.4% between 2017 and 2023. For Hispanic adults, the percentage jumped from 18.4% to 31.3% over the same period.

Comparatively, white adults saw their rates increase from 22.3% in 2017 to 29% in 2023.

"For a long time, white America and white adults were reporting a clinical diagnosis of depression at rates that exceed Black and Hispanic adults," Witters said. "These big increases ... really show the strain that Black and Hispanic Americans have been under since 2017."

Black and Hispanic Americans were more likely to lose their jobs in the early days of the pandemic, he said, and events such as the death of George Floyd in May 2020 may have also contributed to depression.

"When the pandemic first hit, across all adults, negative emotional experiences [tracked by Gallup] such as sadness and anger went up a little but didn't really change that much," Witters said. "You fast forward a couple of months and you get to kind of the latter part of May and into June, anger and sadness were up over 10 percentage points."

ABC News' Dr. Amanda Kravitz contributed to this report.

Related Topics

• Mental Health

Child Tax Benefits and Labor Supply: Evidence from California

In the United States today, some of the largest social welfare programs focused on children – including the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC) – require that parents earn income from work. While intended to encourage recipients to work, tax credit work requirements may also harm the lowest-income families. In this paper, the authors study whether eliminating child tax credit work requirements affects parents’ decision to work.

The authors study this question in the context of California’s Young Child Tax Credit (YCTC), a refundable state tax credit for low-income parents with children younger than six. When the YCTC was enacted in 2019 it was available to any taxpayer with income over $1. Then, beginning in 2022, California eliminated the work requirement altogether.   Using federal administrative tax data, the authors compare the labor force participation of mothers with children who just barely qualify for the YCTC to those with children just above the age cutoff, before and after the work requirement was eliminated. They find the following:

• Eliminating the YCTC work requirement did not cause a significant number of California mothers to exit the labor force. The authors estimate that working mothers’ labor force participation fell by no more than 0.4 percentage points with the elimination of the work requirement.

The results of the study suggest that eliminating the work requirement from the federal CTC would cause fewer exits from the labor force than prior studies suggest. The results also provide new evidence for states considering adopting or reforming their own child tax benefits, as a central issue in designing such policies is whether to condition benefits on work.

More on this topic

Tax Policy and Investment in a Global Economy

The Short-Term Labor Supply Response to the Expanded Child Tax Credit

The macroeconomics of the greek depression.

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An Examination of Depression, Anxiety, and Self-Esteem in Collegiate Student-Athletes

Samantha r. weber.

1 Department of Nursing and Health Science, Limestone University, Gaffney, SC 29340, USA

Zachary K. Winkelmann

2 Department of Exercise Science, University of South Carolina, Columbia, SC 29208, USA

Eva V. Monsma

3 Department of Physical Education, University of South Carolina, Columbia, SC 29208, USA

Shawn M. Arent

Toni m. torres-mcgehee, associated data.

Not available based on Institutional Review Board policies.

Mental health research exists for student-athletes in the areas of depression, anxiety, and self-esteem prevalence. However, updated prevalence rates and assessment of risks across sports, academic status, and genders are needed. Filling the gaps in research assists in the creation of patient-centered mental health screening and interventions designed for student-athletes. Therefore, the purpose is to examine the prevalence of depression, anxiety, and self-esteem in collegiate student-athletes and differences between sex, academic status, and sport type, and identify associations for risks. Using a cross-sectional design, collegiate student-athletes were surveyed to assess for risks of depression, anxiety, and self-esteem. With the use of SPSS, Chi-square analyses and multinomial logistic regressions were used. Student-athletes (22.3%) were at risk for depression, anxiety (12.5%), and low self-esteem (8%). No significant differences were found for sex, academic status, and sport type for depression or self-esteem; however, significant differences occurred for state and trait anxiety by sex. A significant association for depression and anxiety risk was found with females at risk. Depression and anxiety are present within student-athletes, regardless of sport type. Females are at a higher risk; however, all student-athletes would benefit from the creation of validated, patient-centered mental health screenings and psychotherapeutic interventions.

1. Introduction

There are approximately a half-million collegiate student-athletes in the National Collegiate Athletic Association (NCAA), attending over 1000 colleges and universities in over 100 athletic conferences. According to the National Institute of Mental Health, approximately 8.4% of adults aged 18 or older experienced a depressive episode, and 19.1% had an anxiety disorder in the past year [ 1 ]. More specifically, within college-age students ranging from 18–25, the prevalence was highest for depression at 17.0% and 22.3% for anxiety disorders [ 1 ]. College is considered an at-risk period for the development of mental health illnesses. According to the American College Health Association, over 30% of students reported significant signs of depression [ 1 , 2 , 3 ]. College student-athletes are a subset of the young adult population and may be at risk for stressors linked to mental health issues (e.g., disordered eating, substance or alcohol abuse). With many student-athletes participating in sport, it is reasonable to believe that numerous student-athletes participate in their sport while managing the signs, symptoms, and known risk factors of depression and anxiety. With an increase in mental health visibility, an updated examination on the prevalence of depression, anxiety, and low self-esteem for this population is warranted.

Depression is characterized by mood changes, loss of interest or pleasure in daily activities, and the associated symptoms of sleep and eating problems, low energy, lack of concentration and self-worth [ 1 ]. With participation in sport, student-athletes are thought to be immune to mental health disorders like depression; however, research demonstrates that the general college student population and student-athletes are comparable [ 4 , 5 ]. Research directly investigating the prevalence and severity of depression symptoms in collegiate student-athletes varies by instruments used and by sports and sex examined. The prevalence of the risk of depression in collegiate student-athletes ranges from 15.6% to 33.2%, with first-year students and females typically reporting more symptoms [ 4 , 6 , 7 ]. When examining the depression risk prevalence in specific sports including but not limited to football, baseball, wrestling, track and field, and lacrosse, the range was from 12.1% to 35.4%, with higher rates consistent with females [ 8 , 9 , 10 ]. In the current literature, sports have been categorized as individual and team sports when examining risk of depression in collegiate student-athletes, indicating that individual sports may be at an increased risk over team sports [ 10 , 11 ]. With a younger population, a lower prevalence rate of 8% was found for depression and anxiety, and specifically 13% for individual sports and 7% for team sports, further supporting sport type as being associated with the risk of depression and anxiety in student-athletes [ 11 ]. The previous research on prevalence rates for team versus individual sports is based on a younger population, and there are different validated measures used throughout the research to assess for the presence of the risk of depression.

Anxiety is commonly known as a reaction to a perceived stressful or dangerous situation that can have debilitating effects on daily activities and performance. State anxiety refers to a temporary response to a stressful advent and trait anxiety is defined as a personality feature or predisposition [ 12 ]. Athletes often experience state anxiety during situations that create pressure, for example if a free throw determines the outcome of a basketball game. However, trait anxiety refers to characteristics of a person, where an individual is anxious about general unknown outcomes. Researchers have identified that high levels of trait anxiety may lead to an increase in state anxiety during performance [ 13 ]. However, there is limited research focusing on the examination of state and trait anxiety prevalence in student-athletes. According to current literature by Li and colleagues [ 14 ], one-third of student-athletes reported anxious symptoms prior to the season beginning with a significantly higher risk for sport injury. Furthermore, previous studies examining student-athletes primarily occurred during preseason training and did not find significance for gender, sport, or academic status differences and the state and trait anxiety scores [ 8 , 14 ]. However, both studies by Yang et. al. [ 8 ] and Li et. al. [ 14 ], indicated that the link between depression and anxiety is associated with higher levels of pain and injury incidence. Therefore, examining anxiety prevalence rates in student-athletes by sex, academic status, and sport type and determining additional risks for depression and anxiety is warranted to help clinicians prevent additional injury. Without further research on depression and anxiety prevalence, it is difficult to develop preventative mental health programs and interventions for current conditions.

Participation in sport facilitates positive mental health behaviors, including self-confidence, positive self-esteem, and social support [ 15 ]. Individuals with positive mental health behaviors may be utilizing their social support systems to cope and manage stress in helpful ways to lower risks for depression and anxiety. However, student-athletes may be more susceptible to mental health issues due to the demands of sport participation (e.g., sports injury, coach expectations) [ 9 ]. Student-athletes are thought to be protected from mental health issues because of increased self-esteem, a sense of connectedness, and social support from their teammates [ 15 ]. There is an established relationship between self-esteem and depression, indicating that self-esteem is associated with depression. In those with lower self-esteem, depression rates tend to be higher, whereas in student-athletes with a higher self-esteem a lower rate of depression was found [ 15 ]. However, this study is out of date, and updated research for student-athletes is needed.

Clinicians providing medical services within the collegiate sports setting should be mindful of comorbidities of mental illnesses and which student-athletes are at the highest risk. Additionally, being able to recognize the common mental health illnesses and risks among student-athletes can help guide clinicians to utilize validated patient-centered screenings to identify those who may need referral for psychotherapeutic intervention [ 16 ]. Early screening, identification, and intervention can allow healthcare professionals to gain more information on their patients; furthermore, this allows providers to ask in-depth questions tailored to their patients’ needs, and to develop strategies (i.e., goal setting, coping mechanisms) to support their mental and physical needs [ 17 ]. Student-athletes who have an individualized approach to their needs are more likely to communicate with their providers and trust the clinician providing healthcare [ 18 ], and with a tailored approach to healthcare, specifically mental health care, student athletes are able to receive help before signs and symptoms begin to manifest. While all student-athletes have unique personal stressors and individual experiences, understanding the associations between depression, anxiety, self-esteem, sport type, and sex may help clinicians choose to use validated screenings and further develop interventions for managing symptoms for their patients. Therefore, the purpose of this study was to examine the overall prevalence of depression, anxiety, and self-esteem in NCAA Division I and II collegiate student-athletes, with a secondary purpose to examine differences between depression and anxiety risk, and low self-esteem with demographic variables such as sex, academic status (e.g., freshman, sophomore, etc.) and sport type (e.g., power, ball sports, technical, endurance, etc.); and lastly to identify associations for depression, anxiety, and low self-esteem.

2. Materials and Methods

2.1. participants.

Participants were NCAA Division I and II student-athletes ( n = 615; age 20 ± 1 years; males: n = 233, height: 184.1 ± 0.5 cm, weight: 91.5 ± 0.15 kg; females: n = 382, height = 168.4 ± 0.39 cm, weight: 63.25 ± 19.8 kg) from across 40 institutions. To be included in the cross-sectional study, the student-athletes had to be between the ages of 18–26 and on an active roster during the time of the survey. The Institutional Review Board approved the study, and all participants consented prior to completing the survey. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the University of South Carolina (protocol code Pro00092702 and date of approval 1 November 2019).

2.2. Instruments

2.2.1. demographic information.

The demographic information collected included age, sex, self-reported height, weight, body mass index (BMI), academic status, and sport. Academic status was defined as a first-year, sophomore, junior, or senior. Participants that were considered fifth-year seniors or graduate students were coded as seniors. Sport type was classified using prior classification by Sundgot-Borgen [ 19 ], by sorting sports into groups of endurance (i.e., cross country, track, swimming), aesthetic (i.e., cheerleading, diving, dance, equestrian), power (i.e., football), ball (i.e., baseball, softball, basketball, soccer, volleyball, beach volleyball), and technical sports (i.e., golf, tennis) [ 19 ].

2.2.2. Center for Epidemiologic Studies Depression Scale

The Center for Epidemiologic Studies Depression Scale (CESD) is a self-report measure of depressive symptoms. There are eight different subscales, including sadness, loss of interest, appetite, sleep, thinking/concentration, guilt, worthlessness, being tired, fatigue, movement, and suicidal ideation over the past week. Student-athletes selected how often they have felt or behaved in a particular way on a scale of 1 (rarely or none of the time) to 4 (most or all the time) during the past week. Any scores higher than 16 indicates an individual is at risk for depression [ 20 ]. The internal consistency for the CESD is r = 0.85 to 0.90, with a test-retest reliability of r = 0.45–0.7, and r = 0.91 for this study [ 20 , 21 ].

2.2.3. State Trait Anxiety Inventory

The State Trait Anxiety Inventory (STAI) is a self-report tool that indicates anxiety and distinguishes between state and trait anxiety. The first 20 questions consist of statements examining how individuals feel “right now at this moment”, and individuals respond on a scale of 1 (not at all) to 4 (very much so). The second 20 questions examine how individuals generally feel on a scale of 1 (almost never) to 4 (almost always) [ 12 , 22 ]. State and Trait Anxiety were measured using the State-Trait Anxiety Inventory. The college student norms were used for analyses with state anxiety for females being 38.76 ± 11.96 and males at 46.47 ± 10.02, and trait anxiety for females 40.40 ± 10.15 and males 38.30 ± 9.18. For the STAI, the internal consistency coefficients range from r = 0.86 to 0.95 and the test-retest reliability ranges from r = 0.65 to 0.75 [ 12 ]. The reliability for the STAI in this study r = 0.95.

2.2.4. Rosenberg Self-Esteem Scale

The Rosenberg Self-Esteem Scale (RSES) is one of the most widely used measures of self-esteem [ 23 , 24 ]. The scale consists of 10 items that are rated on a 4-point Likert scale (strongly agree = 3, agree = 2, disagree = 1, and strongly disagree = 0), and assesses how an individual thinks and feels about themselves. Each participant’s responses are summed across the 10 items and further categorized as low self-esteem or at risk (below 15) or not at risk or high self-esteem (above 15) [ 23 , 24 ]. The scale has been validated for college populations with a test-retest reliability ranging from 0.85 to 0.88 [ 23 ], with excellent stability and a reliability of 0.90 for this study [ 24 ].

2.3. Procedures

Upon receiving approval from the University of South Carolina’s Institution Review Board, participants were recruited using a snowball sampling method. Athletic trainers who worked directly with student-athletes at NCAA Division I or II intuitions were contacted with an invitation letter and a survey link and asked to forward the invitation to their current student-athletes. There was no incentive for completion of the survey. The web-based online survey (SurveyMonkey, San Mateo, CA, USA) included an invitation/consent letter, and the demographic items were followed by the CESD, STAI, and the RSES. The survey was available for 30 days, with a follow-up reminder sent to the participant every 10 days until the window closed.

2.4. Statistical Analysis

We used SPSS statistical software (Version 27; SPSS Inc. Armonk, NY, USA) with an alpha set at p < 0.05 for all analyses. We used G*Power 3 (version 3.1.9.2., Heinrich Heine University, Dusseldorf, Germany) software to calculate power [ 25 ]. Using an alpha of 0.05 and a small effect size (0.2), our power calculation indicated that we needed a sample of 495 completed surveys to achieve an estimated power of 0.95 [ 25 , 26 ]. For sport type, power was estimated at 0.05 and large effect size (0.6), and our power calculation indicated a sample size of 46 per sport group to achieve an estimated power of 0.90 [ 25 , 26 ]. We performed basic descriptive statistics to examine the demographic information (e.g., height, weight, age, body mass index (BMI), sex, academic status, etc.) Chi-squared analyses were used to determine differences between depression, anxiety, and self-esteem risk, sex, academic status, and sport type. The results of the chi-squared tests were used to select association variables to assess each outcome using multinomial logistic regression. Education, sport, and ethnicity were not analyzed due to results from the chi-squared analyses, and sex was examined as an association variable for the outcome.

A total of 821 student-athletes initiated the survey, 675 partially completed the survey, and 615 student-athletes fully completed the survey (75% completion rate). Student-athletes included in this study were from 40 institutions across 22 teams which were categorized into endurance sports ( n = 171), aesthetic sports ( n = 102), power sports, ( n = 117), ball sports ( n = 194), and technical sports ( n = 31). Detailed demographic information can be found in Table 1 .

Participant Demographics (Mean ± SD).

3.1. Prevalence of Depression Risk

Overall, 22.3% ( n = 137/615) of student-athletes were classified as being at risk for depression. A Chi-squared analysis revealed no significant differences between the CES-D and sex (Χ 2 1,615 = 0.00, p = 0.99, with females (13.8.%) reporting the same risk as males (8.5%). Please refer to Table 2 for sex distribution. No significant differences were identified for depression risk and academic status ((Χ 2 3,615 = 6.36, p = 0.095), Table 3 ), with sophomores ( n = 45/154, 29.2%) and juniors ( n = 33/149, 22.1%) reporting the highest depression risk. A Chi-squared analysis revealed no significant differences between the CES-D and sport type (Χ 2 4,615 = 3.427, p = 0.489), with ball ( n = 48/194, 24.7%) and power ( n = 28/117, 23.9%) sports reporting the highest risk. The distribution for CES-D risk and sport type can be found in Table 3 .

Depression, Anxiety and Low Self-Esteem Prevalence Rates by Sex.

a p Values ≤ 0.05. State and trait anxiety were measured using the State-Trait Anxiety Inventory. The college student norms were used for analyses. State anxiety means and standard deviation for females was 38.76 (11.96) and for males it was 46.47 (10.02), and trait anxiety for females was 40.40 (10.15), while for males it was 38.30 (9.18).

Depression Prevalence by Academic Status and Sport.

3.2. Prevalence of Anxiety Risk

Overall, 8.5% ( n = 52/615) of student-athletes were classified as over the norm means for college-aged students for state anxiety, and 12.5% ( n = 77/615) for trait anxiety. However, most of the participants were within the norms for state (66.7%, n = 410/615) and trait (57.4%, n = 353/615) anxiety, respectively. The overall raw mean scores and standard deviations by sex are presented in Table 4 . A Chi-squared analysis revealed a significant difference for state anxiety and sex (Χ 2 2,615 = 10.46, p = 0.005), and for trait anxiety and sex (Χ 2 2,615 = 10.32, p = 0.006). Table 2 provides the distribution of state and trait anxiety by sex. There were no differences found for state and trait anxiety for academic status (Χ 2 6,615 = 3.53, p = 0.740), (Χ 2 6,615 = 4.42, p = 0.620) or for sport type (Χ 2 8,615 = 12.25, p = 0.141), (Χ 2 6,158 = 4.27, p = 0.832), as demonstrated in Table 5 .

State and Trait Anxiety Raw Scores. [M (SD)].

State and trait anxiety were measured using the State-Trait Anxiety Inventory. The college student norms were used for analyses. State anxiety means and standard deviation for females was 38.76 (11.96) and for males it was 46.47 (10.02), and trait anxiety for females was 40.40 (10.15), while for males it was 38.30 (9.18).

Anxiety Prevalence by Academic Status and Sport.

3.3. Prevalence of Low-Self Esteem

Overall, 8.0% ( n = 49/615) of student-athletes were classified as being at risk for low self-esteem. A Chi-squared analysis revealed no significant differences between the RSES and sex (Χ 2 1,615 = 1.112, p = 0.292), with females (7.1%) reporting a slightly lower risk than males (9.4%). The distribution for RSES by sex is found in Table 2 . No significant differences were identified for low self-esteem and academic status (Χ 2 3,615 = 0.394, p = 0.942), with sophomores ( n = 14/154, 9.1%) and juniors ( n = 10/125, 8.0%) reporting scores indicating low self-esteem. A Chi-squared analysis revealed no significant differences between the RSES and sport type (Χ 2 4,615 = 4.094, p = 0.393), with power ( n = 12/117, 10.3%) and endurance ( n =17/171, 9.9%) sports reporting low self-esteem. The distribution for the RSES and sport type can be found in Table 6 .

Low Self-Esteem Prevalence by Academic Status and Sport.

3.4. Multinomial Logistic Regression

Based off of the prevalence data, the results of the multinomial analysis indicated that sex is associated with depression risk, and state and trait anxiety risk ( Table 2 ). For depression risk, females are more likely to be at risk for depression when compared to males, with an odds ratio of 1.795 (CI: 1.184, 2.722). Females are more likely to be within the average college student mean for state anxiety as compared to males, with an odds ratio of 1.771 (CI: 1.214, 2.585) with an increase in odds by 77.1%. As for trait anxiety, females are more likely to be within or above the average college student mean for trait anxiety as compared to males, with an odds ratio of 1.427 (CI: 0.994, 2.048) and 2.539 (CI: 1.402, 4.596), respectively.

4. Discussion

This study examined prevalence rates for depression, anxiety, and low self-esteem risk in a large NCAA Division I and II collegiate student-athlete sample. In addition, the differences of sex, academic status and sport were explored. This study also expands on earlier research by examining sport type classifications and investigates sex and academic status for the association with depression or anxiety risk. Furthermore, this study compares findings with previous sport categorizations and provides suggestions for future interventions.

4.1. Depression

Despite increased recognition of the importance of mental health in student-athletes, prevalence rates are still high when compared with previous literature. We found an overall prevalence of 22.3% for depression risk, similar to previous research in student-athletes using the CES-D [ 7 , 8 , 14 ]. With the risk for depression at 22.3%, nearly one in every four student-athletes report signs and symptoms of depression. Collegiate student-athletes not only have an expectation of being successful athletically but are also required to succeed personally and academically. Student-athletes are required to maintain a balance between academics and specific sport requirements, placing undue stress on the student-athletes, increasing their risk of depression. While there were no significant differences for sex, this study demonstrated that more females reported signs and symptoms of depression with the CES-D. Our findings support the suggestion that females may be at a higher risk for depression than males, further reinforcing previous efforts examining depression prevalence in student-athletes [ 6 , 7 , 8 , 9 , 27 ]. When considering the distribution of sex in the sport classification, power and ball sport groups had the highest percentage for reported symptoms. For the examination of sex with depression, significant associations were found, indicating that females are more likely to report depressive symptoms than males, which is consistent with prior research [ 8 ]. Although sport type was not found to be significant, each sport type has its own associated risks.

It has been previously suggested that individual sports are at a higher risk for depression than team sports, and, furthermore, indicating that sport type is a risk for depression [ 10 , 11 ]. When examining sport in our study, we categorized our sports by the recommendations of Sundgot–Borgen [ 19 ]. With this categorization, we found no differences for sport type and depression risk; however, it is important to note that ball (basketball, soccer) and power sports (football) were the highest among sport types. Ball and power sports would fall into the category of a team sport, and while not significant, both sport groups were higher for depression risk than others that would be categorized as individual sports. The ball sport category included both females and males, while power sports only included football athletes. This finding is contrary to earlier research indicating that individual sports are more likely to report symptoms, however it should not be overlooked. The team aspect of sport is thought to be a supportive community [ 11 ], and with higher numbers from our study this could indicate possible a contention within the team community.

In addition, no significant differences were found for academic status, indicating that the risk of depression was consistent across education levels. Contrary to previous research, first-year and sophomore students have been identified to be more at risk when compared to the other education levels [ 6 , 8 ]. Our results have also indicated that academic status was not a significant factor for depression risk. While the results are insignificant, it is essential to note that mental health interventions may be beneficial for all academic levels. Each academic class experiences unique individual stressors. For example, first-year students must learn to adapt to new friends, classes, and living situations while adjusting to the new team, coach, and expectations, whereas seniors are preparing to finish their athletic careers, graduate, and become working professionals in their field of study. Mental health interventions tailored to the student-athletes’ mental and physical needs such as the instruction of coping mechanisms, time management skills, and self-care may help reduce mental health prevalence among all student-athletes regardless of academic status. In addition, to ensure appropriate patient-centered care identifying and intervening with individuals that present with symptomology early can result in appropriate referrals, improving patient relationships, and outcomes.

4.2. Anxiety

In collegiate student-athletes, there is limited research on the prevalence of state and trait anxiety [ 8 , 14 ]. Prior research has examined state and trait anxiety in student-athletes during their preseason and found no differences for sex [ 8 , 14 ] or collegiate class [ 8 ]. Our results are consistent with those of Yang and colleagues [ 8 ], and demonstrate that student-athletes’ state and trait scores are significantly lower than that of typical college students [ 22 ]. While student-athletes are reporting scores lower than regular college students, our results demonstrate that student-athletes are still demonstrating signs and symptoms of anxiety. In addition, when examining sex and anxiety, females are more likely to be at or above the average mean for both state and trait anxiety. It has been suggested that with an increase in trait anxiety, state anxiety scores may increase and affect performance [ 13 ].

In addition, no significant differences were found for state or trait anxiety scores across academic status, which is supported by Yang and colleagues [ 8 ], who revealed similar findings for anxiety scores. While not significant, it was suggested that female, freshman, or juniors had a higher tendency to report symptoms than their counterparts [ 8 ]. With increased stress to maintain academic standards, it is interesting that the scores for state anxiety were not higher. Student-athletes are required to maintain a specific grade point average each semester to maintain their scholarships and ability to participate. Similarly, a stable or general fear and worry of maintaining these requirements does not seem to be higher than that of a typical college student, which would indicate trait anxiety. Furthermore, academic status was not significant for anxiety scores in our study. Although not significant, student-athletes are still reporting anxiety symptoms. Support programs and more options for tutoring and academic success may be beneficial for all student-athletes to be successful both in the classroom and in their athletic performance.

Similar to academic status, no significant differences were found for sport type and anxiety risks. When considering state anxiety and sport, athletes would typically experience symptoms of anxiety directly after or during stressful situations [ 28 , 29 ]. The participants in our study were able to complete the survey at their convenience; therefore, it is possible that the student-athletes were completing the survey in a non-stressful environment and were truly not experiencing state anxiety. In the context of sport competition, state anxiety scores are known to increase during or directly after situations that are perceived as stressful. Therefore, future research in student-athletes may benefit from an examination of anxiety states throughout a competitive season.

4.3. Low Self-Esteem

Low self-esteem is not a mental health disorder, but rather a behavior that can be a risk for depression and anxiety [ 15 , 30 ]. Individuals experiencing low self-esteem may have an inadequate perception of their performance, possibly predisposing them to mental health problems. Our study indicated that self-esteem was above the threshold for nearly all athletes sampled (92%), reflecting prior research, indicating that student-athletes have a higher sense of self-esteem when compared to non-athletes [ 15 ]. Furthermore, in a study examining college nursing students, over 70% reported low self-esteem and high academic stress [ 31 ]. From the results of our study, more student-athletes have a higher sense of self-esteem when compared to non-athletes and college nursing students. While our sample indicated a high prevalence of high self-esteem, we still had a higher prevalence for depression risk in the same sample. This contradicts previous research that demonstrates an inverse relationship with depression and self-esteem [ 15 ]. In our study, no differences were found for academic status or sport type, while previous studies did not broadly stratify participants by sport-types when examining self-esteem. Student-athletes participating in “lean” sports tend to have lower self-esteem which becomes a predictor for other mental health issues, such as eating disorders [ 32 ]. However, in our study, power and endurance athletes reported higher scores, indicating a lower self-esteem when compared to the other sport types. Endurance athletes would fall into the category of lean sports; however, power sports would not. These results demonstrate that low self-esteem occurs in both females and males, although at a low rate. While self-esteem does not seem to be a risk for student-athletes, the prevalence rates for depression and anxiety are consistent with previous research indicating that change is not occurring.

4.4. Limitations and Future Research

The current findings emphasize the importance of investigating the prevalence of depression and anxiety risk in collegiate student-athletes. However, the study is not without limitations. First, it is important to note that the data is self-reported by the athletes and depends on the participants’ honest answers. Second, the self-report tools are not diagnostic, and instead indicate whether an individual is at risk. Additionally, when the data were categorized by sport, it is important to recognize that there were no females in the power sport category. We were also unable to examine the data by NCAA Division level due to the design of the survey and level of anonymity; an examination by division level may provide additional insight into risk differences. Lastly, as current mental health interventions are loosely focused on improving mental health awareness and decreasing stigma, future research should focus on creating mental health screenings from already validated screenings that can be tailored to the student-athlete population and on developing psychotherapeutic mental health interventions for student-athletes that reduces mental health symptomology and improves coping skills.

5. Conclusions

The present study sought to establish the prevalence of depression risk, anxiety risk, low self-esteem risk, and determine if sex, academic status, or sport type were associated. It suggests that depression and anxiety signs and symptoms are present in the student-athlete population, with females predominantly more at risk than males. Further examination into risks that may result in student-athlete mental health symptomology can help practitioners preemptively refer to mental health professionals. The student-athletes in the present sample do not appear to be at risk for low self-esteem, suggesting that other factors may be at play among the athletes that are. Furthermore, we suggest that future research create mental health screenings from validated screenings that can be tailored for the student-athlete population and the implementation of interventions to help reduce symptomology for anxiety and depression.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, S.R.W. and T.M.T.-M.; methodology, S.R.W. and T.M.T.-M.; validation, S.R.W., T.M.T.-M.; formal analysis, S.R.W.; investigation, T.M.T.-M.; data curation, S.R.W. and T.M.T.-M.; writing—original draft preparation, S.R.W.; writing—review and editing, S.R.W., Z.K.W. and T.M.T.-M.; visualization, T.M.T.-M.; supervision, Z.K.W., E.V.M., S.M.A.; T.M.T.-M.; project administration, S.R.W., Z.K.W., T.M.T.-M. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the University of South Carolina (protocol code Pro00092702 and date of approval 11/1/2019).

Informed Consent Statement

The survey contained an invitation and consent letter. Therefore, participants who completed the survey provided their consent.

Data Availability Statement

Conflicts of interest.

The authors declare that they have no conflict of interest.

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