case study about depression

Mental Health Case Study: Understanding Depression through a Real-life Example

Imagine feeling an unrelenting heaviness weighing down on your chest. Every breath becomes a struggle as a cloud of sadness engulfs your every thought. Your energy levels plummet, leaving you physically and emotionally drained. This is the reality for millions of people worldwide who suffer from depression, a complex and debilitating mental health condition.

Understanding depression is crucial in order to provide effective support and treatment for those affected. While textbooks and research papers provide valuable insights, sometimes the best way to truly comprehend the depths of this condition is through real-life case studies. These stories bring depression to life, shedding light on its impact on individuals and society as a whole.

In this article, we will delve into the world of mental health case studies, using a real-life example to explore the intricacies of depression. We will examine the symptoms, prevalence, and consequences of this all-encompassing condition. Furthermore, we will discuss the significance of case studies in mental health research, including their ability to provide detailed information about individual experiences and contribute to the development of treatment strategies.

Through an in-depth analysis of a selected case study, we will gain insight into the journey of an individual facing depression. We will explore their background, symptoms, and initial diagnosis. Additionally, we will examine the various treatment options available and assess the effectiveness of the chosen approach.

By delving into this real-life example, we will not only gain a better understanding of depression as a mental health condition, but we will also uncover valuable lessons that can aid in the treatment and support of those who are affected. So, let us embark on this enlightening journey, using the power of case studies to bring understanding and empathy to those who need it most.

Understanding Depression

Depression is a complex and multifaceted mental health condition that affects millions of people worldwide. To comprehend the impact of depression, it is essential to explore its defining characteristics, prevalence, and consequences on individuals and society as a whole.

Defining depression and its symptoms

Depression is more than just feeling sad or experiencing a low mood. It is a serious mental health disorder characterized by persistent feelings of sadness, hopelessness, and a loss of interest in activities that were once enjoyable. Individuals with depression often experience a range of symptoms that can significantly impact their daily lives. These symptoms include:

1. Persistent feelings of sadness or emptiness. 2. Fatigue and decreased energy levels. 3. Significant changes in appetite and weight. 4. Difficulty concentrating or making decisions. 5. Insomnia or excessive sleep. 6. feelings of guilt, worthlessness, or hopelessness. 7. Loss of interest or pleasure in activities.

Exploring the prevalence of depression worldwide

Depression knows no boundaries and affects individuals from all walks of life. According to the World Health Organization (WHO), an estimated 264 million people globally suffer from depression. This makes depression one of the most common mental health conditions worldwide. Additionally, the WHO highlights that depression is more prevalent among females than males.

The impact of depression is not limited to individuals alone. It also has significant social and economic consequences. Depression can lead to impaired productivity, increased healthcare costs, and strain on relationships, contributing to a significant burden on families, communities, and society at large.

The impact of depression on individuals and society

Depression can have a profound and debilitating impact on individuals’ lives, affecting their physical, emotional, and social well-being. The persistent sadness and loss of interest can lead to difficulties in maintaining relationships, pursuing education or careers, and engaging in daily activities. Furthermore, depression increases the risk of developing other mental health conditions, such as anxiety disorders or substance abuse.

On a societal level, depression poses numerous challenges. The economic burden of depression is significant, with costs associated with treatment, reduced productivity, and premature death. Moreover, the social stigma surrounding mental health can impede individuals from seeking help and accessing appropriate support systems.

Understanding the prevalence and consequences of depression is crucial for policymakers, healthcare professionals, and individuals alike. By recognizing the significant impact depression has on individuals and society, appropriate resources and interventions can be developed to mitigate its effects and improve the overall well-being of those affected.

The Significance of Case Studies in Mental Health Research

Case studies play a vital role in mental health research, providing valuable insights into individual experiences and contributing to the development of effective treatment strategies. Let us explore why case studies are considered invaluable in understanding and addressing mental health conditions.

Why case studies are valuable in mental health research

Case studies offer a unique opportunity to examine mental health conditions within the real-life context of individuals. Unlike large-scale studies that focus on statistical data, case studies provide a detailed examination of specific cases, allowing researchers to delve into the complexities of a particular condition or treatment approach. This micro-level analysis helps researchers gain a deeper understanding of the nuances and intricacies involved.

The role of case studies in providing detailed information about individual experiences

Through case studies, researchers can capture rich narratives and delve into the lived experiences of individuals facing mental health challenges. These stories help to humanize the condition and provide valuable insights that go beyond a list of symptoms or diagnostic criteria. By understanding the unique experiences, thoughts, and emotions of individuals, researchers can develop a more comprehensive understanding of mental health conditions and tailor interventions accordingly.

How case studies contribute to the development of treatment strategies

Case studies form a vital foundation for the development of effective treatment strategies. By examining a specific case in detail, researchers can identify patterns, factors influencing treatment outcomes, and areas where intervention may be particularly effective. Moreover, case studies foster an iterative approach to treatment development—an ongoing cycle of using data and experience to refine and improve interventions.

By examining multiple case studies, researchers can identify common themes and trends, leading to the development of evidence-based guidelines and best practices. This allows healthcare professionals to provide more targeted and personalized support to individuals facing mental health conditions.

Furthermore, case studies can shed light on potential limitations or challenges in existing treatment approaches. By thoroughly analyzing different cases, researchers can identify gaps in current treatments and focus on areas that require further exploration and innovation.

In summary, case studies are a vital component of mental health research, offering detailed insights into the lived experiences of individuals with mental health conditions. They provide a rich understanding of the complexities of these conditions and contribute to the development of effective treatment strategies. By leveraging the power of case studies, researchers can move closer to improving the lives of individuals facing mental health challenges.

Examining a Real-life Case Study of Depression

In order to gain a deeper understanding of depression, let us now turn our attention to a real-life case study. By exploring the journey of an individual navigating through depression, we can gain valuable insights into the complexities and challenges associated with this mental health condition.

Introduction to the selected case study

In this case study, we will focus on Jane, a 32-year-old woman who has been struggling with depression for the past two years. Jane’s case offers a compelling narrative that highlights the various aspects of depression, including its onset, symptoms, and the treatment journey.

Background information on the individual facing depression

Before the onset of depression, Jane led a fulfilling and successful life. She had a promising career, a supportive network of friends and family, and engaged in hobbies that brought her joy. However, a series of life stressors, including a demanding job, a breakup, and the loss of a loved one, began to take a toll on her mental well-being.

Jane’s background highlights a common phenomenon – depression can affect individuals from all walks of life, irrespective of their socio-economic status, age, or external circumstances. It serves as a reminder that no one is immune to mental health challenges.

Presentation of symptoms and initial diagnosis

Jane began noticing a shift in her mood, characterized by persistent feelings of sadness and a lack of interest in activities she once enjoyed. She experienced disruptions in her sleep patterns, appetite changes, and a general sense of hopelessness. Recognizing the severity of her symptoms, Jane sought help from a mental health professional who diagnosed her with major depressive disorder.

Jane’s case exemplifies the varied and complex symptoms associated with depression. While individuals may exhibit overlapping symptoms, the intensity and manifestation of those symptoms can vary greatly, underscoring the importance of personalized and tailored treatment approaches.

By examining this real-life case study of depression, we can gain an empathetic understanding of the challenges faced by individuals experiencing this mental health condition. Through Jane’s journey, we will uncover the treatment options available for depression and analyze the effectiveness of the chosen approach. The case study will allow us to explore the nuances of depression and provide valuable insights into the treatment landscape for this prevalent mental health condition.

The Treatment Journey

When it comes to treating depression, there are various options available, ranging from therapy to medication. In this section, we will provide an overview of the treatment options for depression and analyze the treatment plan implemented in the real-life case study.

Overview of the treatment options available for depression

Treatment for depression typically involves a combination of approaches tailored to the individual’s needs. The two primary treatment modalities for depression are psychotherapy (talk therapy) and medication. Psychotherapy aims to help individuals explore their thoughts, emotions, and behaviors, while medication can help alleviate symptoms by restoring chemical imbalances in the brain.

Common forms of psychotherapy used in the treatment of depression include cognitive-behavioral therapy (CBT), interpersonal therapy (IPT), and psychodynamic therapy. These therapeutic approaches focus on addressing negative thought patterns, improving relationship dynamics, and gaining insight into underlying psychological factors contributing to depression.

In cases where medication is utilized, selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed. These medications help rebalance serotonin levels in the brain, which are often disrupted in individuals with depression. Other classes of antidepressant medications, such as serotonin-norepinephrine reuptake inhibitors (SNRIs) or tricyclic antidepressants (TCAs), may be considered in specific cases.

Exploring the treatment plan implemented in the case study

In Jane’s case, a comprehensive treatment plan was developed with the intention of addressing her specific needs and symptoms. Recognizing the severity of her depression, Jane’s healthcare team recommended a combination of talk therapy and medication.

Jane began attending weekly sessions of cognitive-behavioral therapy (CBT) with a licensed therapist. This form of therapy aimed to help Jane identify and challenge negative thought patterns, develop coping strategies, and cultivate more adaptive behaviors. The therapeutic relationship provided Jane with a safe space to explore and process her emotions, ultimately helping her regain a sense of control over her life.

In conjunction with therapy, Jane’s healthcare provider prescribed an SSRI medication to assist in managing her symptoms. The medication was carefully selected based on Jane’s specific symptoms and medical history, and regular follow-up appointments were scheduled to monitor her response to the medication and adjust the dosage if necessary.

Analyzing the effectiveness of the treatment approach

The effectiveness of treatment for depression varies from person to person, and it often requires a period of trial and adjustment to find the most suitable intervention. In Jane’s case, the combination of cognitive-behavioral therapy and medication proved to be beneficial. Over time, she reported a reduction in her depressive symptoms, an improvement in her overall mood, and increased ability to engage in activities she once enjoyed.

It is important to note that the treatment journey for depression is not always linear, and setbacks and challenges may occur along the way. Each individual responds differently to treatment, and adjustments might be necessary to optimize outcomes. Continuous communication between the individual and their healthcare team is crucial to addressing any concerns, monitoring progress, and adapting the treatment plan as needed.

By analyzing the treatment approach in the real-life case study, we gain insights into the various treatment options available for depression and how they can be tailored to meet individual needs. The combination of psychotherapy and medication offers a holistic approach, addressing both psychological and biological aspects of depression.

The Outcome and Lessons Learned

After undergoing treatment for depression, it is essential to assess the outcome and draw valuable lessons from the case study. In this section, we will discuss the progress made by the individual in the case study, examine the challenges faced during the treatment process, and identify key lessons learned.

Discussing the progress made by the individual in the case study

Throughout the treatment process, Jane experienced significant progress in managing her depression. She reported a reduction in depressive symptoms, improved mood, and a renewed sense of hope and purpose in her life. Jane’s active participation in therapy, combined with the appropriate use of medication, played a crucial role in her progress.

Furthermore, Jane’s support network of family and friends played a significant role in her recovery. Their understanding, empathy, and support provided a solid foundation for her journey towards improved mental well-being. This highlights the importance of social support in the treatment and management of depression.

Examining the challenges faced during the treatment process

Despite the progress made, Jane faced several challenges during her treatment journey. Adhering to the treatment plan consistently proved to be difficult at times, as she encountered setbacks and moments of self-doubt. Additionally, managing the side effects of the medication required careful monitoring and adjustments to find the right balance.

Moreover, the stigma associated with mental health continued to be a challenge for Jane. Overcoming societal misconceptions and seeking help required courage and resilience. The case study underscores the need for increased awareness, education, and advocacy to address the stigma surrounding mental health conditions.

Identifying the key lessons learned from the case study

The case study offers valuable lessons that can inform the treatment and support of individuals with depression:

1. Holistic Approach: The combination of psychotherapy and medication proved to be effective in addressing the psychological and biological aspects of depression. This highlights the need for a holistic and personalized treatment approach.

2. Importance of Support: Having a strong support system can significantly impact an individual’s ability to navigate through depression. Family, friends, and healthcare professionals play a vital role in providing empathy, understanding, and encouragement.

3. Individualized Treatment: Depression manifests differently in each individual, emphasizing the importance of tailoring treatment plans to meet individual needs. Personalized interventions are more likely to lead to positive outcomes.

4. Overcoming Stigma: Addressing the stigma associated with mental health conditions is crucial for individuals to seek timely help and access the support they need. Educating society about mental health is essential to create a more supportive and inclusive environment.

By drawing lessons from this real-life case study, we gain insights that can improve the understanding and treatment of depression. Recognizing the progress made, understanding the challenges faced, and implementing the lessons learned can contribute to more effective interventions and support systems for individuals facing depression.In conclusion, this article has explored the significance of mental health case studies in understanding and addressing depression, focusing on a real-life example. By delving into case studies, we gain a deeper appreciation for the complexities of depression and the profound impact it has on individuals and society.

Through our examination of the selected case study, we have learned valuable lessons about the nature of depression and its treatment. We have seen how the combination of psychotherapy and medication can provide a holistic approach, addressing both psychological and biological factors. Furthermore, the importance of social support and the role of a strong network in an individual’s recovery journey cannot be overstated.

Additionally, we have identified challenges faced during the treatment process, such as adherence to the treatment plan and managing medication side effects. These challenges highlight the need for ongoing monitoring, adjustments, and open communication between individuals and their healthcare providers.

The case study has also emphasized the impact of stigma on individuals seeking help for depression. Addressing societal misconceptions and promoting mental health awareness is essential to create a more supportive environment for those affected by depression and other mental health conditions.

Overall, this article reinforces the significance of case studies in advancing our understanding of mental health conditions and developing effective treatment strategies. Through real-life examples, we gain a more comprehensive and empathetic perspective on depression, enabling us to provide better support and care for individuals facing this mental health challenge.

As we conclude, it is crucial to emphasize the importance of continued research and exploration of mental health case studies. The more we learn from individual experiences, the better equipped we become to address the diverse needs of those affected by mental health conditions. By fostering a culture of understanding, support, and advocacy, we can strive towards a future where individuals with depression receive the care and compassion they deserve.

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Patient Case Presentation

Figure 1.  Blue and silver stethoscope (Pixabay, N.D.)

Ms. S.W. is a 48-year-old white female who presented to an outpatient community mental health agency for evaluation of depressive symptoms. Over the past eight weeks she has experienced sad mood every day, which she describes as a feeling of hopelessness and emptiness. She also noticed other changes about herself, including decreased appetite, insomnia, fatigue, and poor ability to concentrate. The things that used to bring Ms. S.W. joy, such as gardening and listening to podcasts, are no longer bringing her the same happiness they used to. She became especially concerned as within the past two weeks she also started experiencing feelings of worthlessness, the perception that she is a burden to others, and fleeting thoughts of death/suicide.

Ms. S.W. acknowledges that she has numerous stressors in her life. She reports that her daughter’s grades have been steadily declining over the past two semesters and she is unsure if her daughter will be attending college anymore. Her relationship with her son is somewhat strained as she and his father are not on good terms and her son feels Ms. S.W. is at fault for this. She feels her career has been unfulfilling and though she’d like to go back to school, this isn’t possible given the family’s tight finances/the patient raising a family on a single income.

Ms. S.W. has experienced symptoms of depression previously, but she does not think the symptoms have ever been as severe as they are currently. She has taken antidepressants in the past and was generally adherent to them, but she believes that therapy was more helpful than the medications. She denies ever having history of manic or hypomanic episodes. She has been unable to connect to a mental health agency in several years due to lack of time and feeling that she could manage the symptoms on her own. She now feels that this is her last option and is looking for ongoing outpatient mental health treatment.

Past Medical History

• Hypertension, diagnosed at age 41

Past Surgical History

• Wisdom teeth extraction, age 22

Pertinent Family History

• Mother with history of Major Depressive Disorder, treated with antidepressants
• Maternal grandmother with history of Major Depressive Disorder, Generalized Anxiety Disorder
• Brother with history of suicide attempt and subsequent inpatient psychiatric hospitalization,
• Brother with history of Alcohol Use Disorder
• Father died from lung cancer (2012)

Pertinent Social History

• Works full-time as an enrollment specialist for Columbus City Schools since 2006
• Has two children, a daughter age 17 and a son age 14
• Divorced in 2015, currently single
• History of some emotional abuse and neglect from mother during childhood, otherwise denies history of trauma, including physical and sexual abuse
• Smoking 1/2 PPD of cigarettes
• Occasional alcohol use (approximately 1-2 glasses of wine 1-2 times weekly; patient had not had any alcohol consumption for the past year until two weeks ago)

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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

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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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Submitted: 4 November 2019 Revised: 24 February 2020 Accepted: 6 March 2020

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• Published: 24 April 2024

Discrimination is associated with depression, anxiety, and loneliness symptoms among Asian and Pacific Islander adults during COVID-19 Pandemic

• Cameron K. Ormiston   ORCID: orcid.org/0000-0002-3598-616X 1 , 2 ,
• Paula D. Strassle   ORCID: orcid.org/0000-0002-1072-1560 1 ,
• Eric Boyd 3 &
• Faustine Williams   ORCID: orcid.org/0000-0002-7960-2463 1  

Scientific Reports volume  14 , Article number:  9417 ( 2024 ) Cite this article

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In the United States, Asian and Pacific Islander (A/PI) communities have faced significant discrimination and stigma during the COVID-19 pandemic. We assessed the association between discrimination and depression, anxiety, and loneliness symptoms among Asian or Pacific Islander adults (n = 543) using data from a 116-item nationally distributed online survey of adults (≥ 18 years old) in the United States conducted between 5/2021–1/2022. Discrimination was assessed using the 5-item Everyday Discrimination Scale. Anxiety, depression, and loneliness symptoms were assessed using the 2-item Generalized Anxiety Disorder, 2-item Patient Health Questionnaire, and UCLA Loneliness Scale—Short form, respectively. We used multivariable logistic regression to estimate the association between discrimination and mental health. Overall, 42.7% of participants reported experiencing discrimination once a month or more. Compared with no discrimination, experiencing discrimination once a month was associated with increased odds of anxiety (Adjusted Odds Ratio [aOR] = 2.60, 95% CI = 1.38–4.77), depression (aOR = 2.58, 95% CI = 1.46–4.56), and loneliness (aOR = 2.86, 95% CI = 1.75–4.67). Experiencing discrimination once a week or more was associated with even higher odds of anxiety (aOR = 6.90, 95% CI = 3.71–12.83), depression, (aOR = 6.96, 95% CI = 3.80–12.74), and loneliness (aOR = 6.91, 95% CI = 3.38–13.00). Discrimination is detrimental to mental health, even at relatively low frequencies; however, more frequent discrimination was associated with worse mental health symptoms. Public health interventions and programs targeting anti-A/PI hate and reducing A/PI mental health burden are urgently needed.

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Introduction.

Since the start of the COVID-19 pandemic, the United States (US) has seen a dramatic rise in anti-Asian and Pacific Islander (A/PI) discrimination 1 , 2 . Within the first month of the Asian Pacific Policy and Planning Council’s public reporting center for discrimination being active, they received 1,497 reports of anti-A/PI discrimination from across the US 3 . Since the start of the pandemic, anti-Asian hate crimes have increased by 344% and over half of Asian adults report that anti-Asian discrimination is more frequent compared to before the pandemic 1 . In one nationally representative survey of US adults, 1 in 3 Asian adults reported experiencing COVID-related discrimination, and Asian adults were more likely to experience discrimination compared to Black/African American, Hawaiian/Pacific Islander, Hispanic/Latino, multiracial, and White adults, even though COVID-related discrimination was common across all racial and ethnic minoritized groups 4 . Furthermore, almost a third of US adults believe China or Chinese Americans are to blame for the COVID-19 pandemic 5 .

Experiences of discrimination can have extensive, adverse impacts on the health, including mental health, of racial and ethnic minoritized individuals 2 . For example, after the September 11, 2001 attacks, the US saw a rise in discrimination, hate crimes, and negative attitudes towards Muslim Americans, which resulted in increased depressive and post-traumatic stress disorder (PTSD) symptoms among Muslim Americans 6 , 7 , 8 . Worse mental health due to discrimination after the 9/11 attacks was also reported among other minoritized groups, including Latino adults and Asian Americans 9 , 10 . In fact, national emergencies and crises, such as 9/11 or the COVID-19 pandemic, likely provide opportunities for white supremacy and privileged groups to reassert hegemony over the country’s sociopolitical and ideological environment thereby facilitating the exclusion of non-White communities 9 .

Discrimination experiences are said to trigger stress and trauma responses that can lead to chronic mental and physical health conditions such as cardiovascular disease, PTSD, and depression 1 , 6 , 11 . Indeed, numerous studies predating the pandemic have linked discrimination with depression, suicidal ideation, loneliness, and psychological distress among A/PI adults 1 , 12 , 13 , 14 . Persistent anti-Asian rhetoric in the US news, social media, and general population, and terms such as “Kung flu,” “Chinese Virus,” and other derogatory terms toward Asian communities during the pandemic will have deleterious, far-reaching effects on A/PI mental health 2 , 6 , 15 . For example, witnessing anti-Asian discrimination in public or seeing images of discrimination towards Asian individuals on the news or social media has been linked to depressive and anxiety symptoms among Asian adults during the pandemic 16 . And although A/PI adults were less likely to report having poor mental health compared to White adults prior to the pandemic 2 , 17 , 18 , 19 , recent research has found higher levels of mental health symptoms compared with White adults during the pandemic 2 , 20 .

Presently, our knowledge on the impact of discrimination during the COVID-19 pandemic on A/PI mental health is still developing. Although depression, anxiety, and loneliness have been examined among A/PI individuals before, most studies have focused on specific populations (e.g. adolescents, older adults), predate the COVID-19 pandemic, did not control for pre-existing mental health conditions, or did not utilize a national sample 1 , 6 , 21 , 22 . Understanding this relationship is important given the drastic increase in discrimination faced by A/PI communities in the US, and the already high risk of mental health concerns during the pandemic. Thus, the purpose of this analysis was to examine the association between discrimination and depression, anxiety, and loneliness symptoms during the COVID-19 pandemic in a national sample of A/PI adults living in the United States. We hypothesized higher frequency of discrimination would confer higher odds of depression, anxiety, and loneliness.

Study data and population

We conducted a comprehensive 116-item online survey that was nationally distributed throughout the US, which focused on mental health during the COVID-19 pandemic. Qualtrics LLC, which uses a national survey panel to conduct online surveys, distributed ten thousand surveys to adults (≥ 18 years old) living in the US from May 13, 2021, to January 9, 2022. Upon completing the survey, participants were given a $5–10 gift card from Qualtrics. As we were interested in assessing mental health during the pandemic among African, Asian, Hispanic/Latino, and Middle Eastern immigrant individuals, this group was oversampled during recruitment. Low-income (< $25,000 annual household income) and rural adults were also oversampled.

Initial survey responses received by Qualtrics (n = 5938, 59.4% response rate) were assessed via Expert Review Fraud Detection to prevent multiple submissions and ensure data integrity. Participants were removed from the final survey sample if they completed < 80% of the survey after accounting for skip pattern items or if they took < 5 min to complete the survey. Overall, 5,413 surveys were ultimately included in the final sample. For this study, we restricted our cohort to participants who self-identified as Asian and/or Pacific Islander (n = 534, 9.9% of sample). Informed consent was obtained from all individual participants included in the study.

The research protocol for the study was reviewed by the National Institutes of Health (NIH) Institutional Review Board (IRB) and was approved on December 23, 2020 (IRB#000308) as an exempt study. The NIH Intramural Research Program IRB Human Research Protections Program Office of Human Subjects Research Protections determined that our protocol did not involve human subjects and was excluded from IRB review. The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The data for the study is available upon request per the new Data Management and Sharing Agreement plan.

An adapted version of the 5-item Everyday Discrimination Scale 23 was used to assess for frequency of discrimination during the COVID-19 pandemic. Participants were asked, “Since the beginning of the Coronavirus/COVID-19 pandemic, how often have any of the following things happened to you? (1) You are treated with less courtesy or respect than other people; (2) You receive worse service than other people in restaurants or stores; (3) People act as though they think you are not intelligent; (4) People act as though they are afraid of you; and (5) You are threatened or assaulted”. For each scenario, participants had five answer options (Never, About once a month, About once a week, 2–3 times a week, and Daily or almost daily). Based on the responses, discrimination frequency was classified as having felt discrimination never, once a month, or once a week or more (About once a week/2–3 times a week/daily or almost daily). Participants were further asked to give the main reasons for their discrimination experiences. They could select all that apply from the following list of reasons: People think I have Coronavirus/COVID-19, Race, Ancestry or national origin, Immigration status, Gender, Age, Religion, Height, Weight, Sexual orientation, Education or income level, None of these or not applicable. The Everyday Discrimination Scale has been validated among a wide range of racial and ethnic groups, including Asian American adults 23 , 24 , 25 , 26 , 27 , 28 , 29 .

Anxiety, depression, and loneliness symptoms were assessed using the 2-item Generalized Anxiety Disorder (GAD-2) 30 , 2-item Patient Health Questionnaire (PHQ-2) 31 , and UCLA Loneliness 3-item Scale—Short form (ULS-3) 32 , respectively. The GAD-2 asks, “Over the last 2 weeks, how often have you been bothered by the following problems? (1) Feeling nervous, anxious, or on edge. (2) Not being able to stop or control worrying.” Respondents answered, Not at all (0), Several days (1), More than half the days (2), and Nearly every day (3) for each item. Response scores were summed, and a score of ≥ 3 indicated GAD (yes/present) and < 3 no/none 33 . The PHQ-2 asked, “Over the last 2 weeks, how often have you been bothered by the following problems? (1) Feeling nervous, anxious, or on edge. (2) Not being able to stop or control worrying”. Possible responses included Not at all (0), Several days (1), More than half the days (2), and Nearly every day (3) for each item. Response scores were summed, and a score of ≥ 3 indicated yes/present depression symptoms and < 3 no/none 31 , 34 . The ULS-3 asks participants, “How often do you feel that you lack companionship?”, “How often do you feel left out?”, “How often do you feel isolated from others?”. Response options included Hardly ever (1), Some of the time (2), and Often (3) 32 . Response scores were summed for each participant and a score of 3–5 = Not Lonely (no/none) and 6–9 = Lonely (yes/present) 32 . These scale cutoffs have been validated among a diverse range of populations 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 .

Other covariates were created from single questions from the questionnaire including age (18–44, 45–54, 55–64, ≥ 65 years old), country of birth (Born outside the US or Born in the US/US-born), income ($0–24,999; $25,000–34,999; $35,000–49,999; $50,000–74,999; ≥ $74,999), education (Less than high school, High school graduate, Technical or Some college, ≥ College degree), race (Asian or Pacific Islander), ethnicity (Hispanic/Latino or not Hispanic/Latino), sexual orientation (Bisexual, Else, Gay, Heterosexual, or Lesbian), gender identity (Man, Transgender and/or Non-binary, and Woman), marital status (Divorced/Separated, Married/Living with partner, Never married, Widowed), housing stability (Stable or Unstable) and employment (Employed [full or part-time] or Not employed).

Statistical analyses

Prevalence of reasons for discrimination, anxiety, depression, and loneliness symptoms, overall and by frequency of COVID-related discrimination, were estimated using descriptive statistics. Multivariable logistic regression was used to estimate the association between discrimination (once a week or more vs. never; and monthly vs. never) and depression, anxiety, and loneliness symptoms, respectively. All models adjusted for race, ethnicity, age, gender identity, sexual orientation, income, country of birth, marital status, education, employment, housing stability, and history of mental health conditions (Anxiety disorder, Depressive disorder, Other mental health diagnosis). All analyses were performed using SAS version 9.4 (SAS Inc., Cary, NC) and SUDAAN Release 11.0.1 (Research Triangle Institute: Research Triangle Park, NC).

Descriptive statistics of study sample

The majority of participants was Asian (91.9%), aged 18–44 years (61.0%), identified as woman (65.6%), heterosexual (89.5%), were employed (56.4%), and had a college degree or more (61.0%). Approximately 56.2% of the sample was born outside of the US. In terms of pre-existing mental health conditions, 10.7% had anxiety, 7.7% had depression, and 7.6% had a mental health diagnosis that was not anxiety or depression. See Table 1 .

Overall, 42.7% of participants reported experiencing discrimination (once a month: 23.4%; once a week or more: 19.3%). Differences in discrimination frequency were seen by race, age, sexual orientation, annual household income, marital status, region of birth, history of mental health conditions (anxiety, depression, and other mental health diagnosis), and housing stability. See Table 1 . When stratifying the overall sample by race, there were differences by sexual orientation, education, region of birth, history of mental health conditions (anxiety, depression, and other mental health diagnosis), and housing status. See Table 2 .

Among participants who reported discrimination, 25.4% said the discrimination was COVID-19-related, 60.8% said it was due to race, 25.0% due to ancestry, 20.7% due immigration status, and 21.6% due to gender. See Supplemental Table 1 . Participants who experienced discrimination more frequently were more likely to report the discrimination was due to religion (19.1% vs. 4.7%, p = 0.0006). See Supplemental Table 2 and Fig.  1 A.

( A – C ) Reasons for discrimination among individuals who reported experiencing discrimination during the pandemic (n = 232, 43.4%), stratified by ( A ) Discrimination frequency, ( B ) Race, and ( C ) Country of Birth. Participants were able to select more than one reason. ( A ) Reasons for discrimination stratified by discrimination frequency. ( B ) Reasons for discrimination stratified by race. ( C ) Reasons for discrimination stratified by place of birth.

When stratifying participants who experienced discrimination by race, no differences were found between Asian and Pacific Islander respondents. See Supplemental Table 3 and Fig.  1 B. After stratifying by place of birth (born outside US and US-born), people born outside US were more likely to report the discrimination was due to race (66.9% vs. 54.1%, p = 0.04) and ancestry (30.6% vs. 18.9%, p = 0.04). See Supplemental Table 4 and Fig.  1 C.

After adjusting for sociodemographic characteristics and history of mental health, we observed a dose–response between frequency of discrimination and increased odds of poor mental health. For example, compared with those reporting no discrimination, experiencing discrimination once a month was associated with almost three times the odds of anxiety (Adjusted Odds Ratio [aOR] = 2.60, 95% Confidence Interval [CI] = 1.38–4.77) and experiencing discrimination once a week or more was associated with over six times the odds of anxiety (aOR = 6.90, 95% CI = 3.71–12.83), Supplemental Table 5 and Fig.  2 A. Similar trends were observed for both depression (once a month: aOR = 2.58, 95% CI = 1.46–4.56; once a week or more: aOR = 6.96, 95% CI = 3.80–12.74) and loneliness (once a month: aOR = 2.86, 95% CI = 1.75–4.67; aOR = 6.91, 95% CI = 3.38–13.00). See Supplemental Table 5 and Fig.  2 B,C.

( A – C ) Adjusted association between discrimination and ( A ) anxiety, ( B ) depression, and ( C ) loneliness symptoms among Asian and Pacific Islander adults. ( A ) Adjusted association between discrimination and anxiety. ( B ) Adjusted association between discrimination and depression. ( C ) Adjusted association between discrimination and depression and loneliness. All models were adjusted for race, ethnicity, age, gender identity, sexual orientation, income, country of birth, marital status, education, employment, housing stability, and history of mental health conditions (Anxiety disorder, Depressive disorder, Other mental health diagnosis). N = 499 Asian and Pacific Islander adults. See Supplemental Table 5 for the values of each aOR and 95% CI.

Using a national sample of US A/PI adults, we found that almost 50% reported experiencing discrimination, and among those who experienced discrimination, 25% reported that it was related to COVID-19. We also found that even when discrimination is experienced at relatively low frequencies (monthly), it had a substantial and detrimental impact on mental health; moreover, among individuals who experienced discrimination more frequently (once a week or more) the odds of poor mental health was even greater. Overall, this study represents one of the most recent and comprehensive assessments of the impact of discrimination on mental health in the US A/PI community during the COVID-19 pandemic.

Since the start of the pandemic, depressive symptoms among US adults and global anxiety symptoms have both tripled, and global loneliness symptoms have significantly increased 39 , 40 , 41 . These trends may be due to a multitude of reasons, including diseases-related anxiety, isolation due to quarantine and stay-at-home orders, and stress from economic and financial instability 41 . A/PI individuals, however, may be doubly burdened during the pandemic, experiencing fear, stress, and isolation due to not only the pandemic, but also due to anti-Asian discrimination, stigmatization, and violence 2 , 6 .

The present study found the total prevalence of discrimination among A/PI, Asian, and Pacific Islander adults to be 42.7%, 41.1%, and 61.4%, respectively. These findings are comparable with existing research. For example, a study utilizing COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study data found 60.7% of A/PI adults reported discrimination 42 . An online survey of Asian adults in Florida found 56.5% experienced discrimination during the pandemic 6 . Other studies report the prevalence of COVID-19-related discrimination to be 20–67% among Asian adults 1 , 2 , 4 , 43 . Among Pacific Islander adults, the prevalence of discrimination during the pandemic is estimated to be 22.8–40.5% 4 , 42 . Research prior to the pandemic show the prevalence of discrimination among Asian and Pacific Islander adults living in the US was 13–50% and 48–52%, respectively 13 , 42 . Both the present study and prior studies therefore highlight the increase in discrimination among A/PI adults and an urgent need to address this issue given discrimination’s harmful effects on mental health.

Prior research has also shown anti-Asian discrimination during the pandemic has negative effects on mental health 2 , 43 and may have led to the Asian-White mental health gap now seen in the US 2 . Our findings also mirror existing research on the link between discrimination and A/PI mental health both prior to and during the pandemic 1 , 2 , 16 , 43 , 44 , 45 , 46 . A recent study on Asian/Asian American young adults found COVID-19-related discrimination to be significantly associated with PTSD symptoms after controlling for demographics, socioeconomic status, lifetime discrimination, and pre-existing mental health conditions 1 . Furthermore, an analysis of a national survey of 245 Asian/Asian American adults found discrimination during the pandemic was significantly associated with depressive symptoms as assessed using the 20-item Center for Epidemiologic Studies of Depression Scale 43 . Given A/PI adults report lower rates of using mental health services and discrimination has been previously associated with lower mental health service utilization among Asian adults, providing community-based, accessible, anti-racist, and culturally competent services is increasingly important 2 , 3 , 12 .

There are a number of limitations to consider for our study. First, our study is cross-sectional, meaning we cannot infer any directionality or causality of our findings. While we assume discrimination leads to mental health symptoms, individuals with mental health conditions experience significant barriers and stigmatization in society and report high levels of discrimination due to their mental health status, particularly those of racial and ethnic minoritized groups 47 , 48 , 49 , 50 . Second, given small sample sizes, we aggregated the Asian and Pacific Islander samples, and were unable to perform Asian and Pacific Islander analyses separately and among subgroups. Future research should aim disaggregate data and examine the link between discrimination and mental health outcomes across Asian and Pacific Islander subgroups and other intersectional identities (e.g., generational immigration status). The heterogenous experiences between these groups therefore may not be captured in our results. Additionally, the sample size for many of our cell counts were small, which may also introduce power issues that can impact the results and are likely to be unstable in adjusted models. Fourth, this was a convenience sample, which limits statistical inference, replication, and generalization of the results. Data integrity may also be a concern of convenience sampling; however we had several safeguards in place to prevent this issue. Fourth, the survey was conducted in English, thus individuals with limited English proficiency may have been underrepresented. Finally, the survey was online and individuals with limited access to the internet may not have been captured in the results.

Conclusions

Among a national sample of A/PI adults, discrimination was associated with anxiety, depression, and loneliness symptoms. Although odds of mental health symptoms increased with increased frequency of discrimination, our results highlight the deleterious impact of discrimination even at ‘low’ levels of frequency. The pandemic and discrimination will likely have far-reaching, sustained impacts on A/PI mental and physical health. As such, health practitioners need to be educated on the unique experiences of A/PI adults, prepared to effectively screen for and treat these issues, and utilize their unique positions as leaders in health and society to stand up to racism and discrimination. Interventions that both target anti-A/PI hate and disinformation and address the growing mental health burden among A/PI in the US will be essential to mitigating potential long-term, negative effects of the pandemic among A/PI communities.

Data availability

The data are available by making a request through Dr. FW per the new Data Management and Sharing Agreement plan.

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Ormiston, C.K., Strassle, P.D., Boyd, E. et al. Discrimination is associated with depression, anxiety, and loneliness symptoms among Asian and Pacific Islander adults during COVID-19 Pandemic. Sci Rep 14 , 9417 (2024). https://doi.org/10.1038/s41598-024-59543-0

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Lu W , Bessaha M , Muñoz-Laboy M. Examination of Young US Adults’ Reasons for Not Seeking Mental Health Care for Depression, 2011-2019. JAMA Netw Open. 2022;5(5):e2211393. doi:10.1001/jamanetworkopen.2022.11393

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Examination of Young US Adults’ Reasons for Not Seeking Mental Health Care for Depression, 2011-2019

• 1 Department of Community Health and Social Medicine, School of Medicine, The City University of New York, New York
• 2 School of Social Welfare, Stony Brook University, Stony Brook, New York

Compared with any other adult age group, depression is most prevalent among young adults aged 18 to 25 years in the US. 1 Despite the increasing trajectory of depression in the past decade, young adults’ use of treatment for depression remains low. 2 Untreated depression increases young adults’ risk for substance abuse, risky sexual behaviors, unemployment, and suicide. 3 This study aimed to examine trends and patterns in young adults’ perceived reasons for not seeking treatment for depression.

This study used nationally representative data from the 2011-2019 National Survey on Drug Use and Health (NSDUH) for civilian, noninstitutionalized young adults aged 18 to 25 years. 4 Young adults with a 12-month major depressive episode (MDE) based on Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria were asked whether they had received any mental health treatment in the past year; those who responded “no” were further surveyed about reasons why they did not seek treatment. The sociodemographic variables that were examined included young adults’ age, sex, race and ethnicity, and annual household income. The institutional review board at RTI International approved the NSDUH data collection protocol, and verbal informed consent was obtained from each participant. This study followed the American Association for Public Opinion Research ( AAPOR ) reporting guideline for survey studies. 5

Bivariate logistic regression analyses were first conducted to assess time changes in annual proportions of young adults who reported specific reasons for not seeking treatment for depression (0 = no; 1 = yes); survey year was the continuous independent variable. For reasons with statistically significant time changes, interaction effects between survey year and sociodemographic variables were further examined in respective bivariate regression models. Last, a series of multivariable logistic regression analyses were conducted to examine sociodemographic differences in participants’ reported reasons for not seeking treatment for depression, controlling for survey year, participants’ MDE-related severe functional impairment, and sampling weights.

All analyses were performed using R, version 4.0.3 (R Group for Statistical Computing). For the 2011-2019 NSDUH, the annual mean weighted interview response rates for adults aged 18 to 25 years ranged between 66.4% and 80.5%. All P values were from 2-sided tests and results were deemed statistically significant at P  ≤ .05.

Between 2011 and 2019, 11 186 of 21 012 young adults with a 12-month MDE did not receive any treatment, among whom 6837 (61.1%) were women, 4349 (38.9%) were men, 4412 (39.4%) were aged 18 to 21 years, 6283 (56.2%) were White, 3309 (29.6%) had an annual household income of less than $20 000, and 6363 (56.8%) had MDE-related severe functional impairment. The sociodemographic distribution was largely consistent across survey years.

In 2019, the most-reported reasons by young adults for not seeking treatment for an MDE were cost (776 of 1552 [54.7%]; weighted percentage), not knowing where to go for services (572 of 1552 [37.8%]; weighted percentage), thought they could handle the problem without treatment (525 of 1552 [30.9%]; weighted percentage), and fear of being committed or having to take medicine (394 of 1552 [22.8%]; weighted percentage) ( Table 1 ). From 2011 to 2019, an increasing number of young adults reported not knowing where to go for services, fear of being committed or having to take medicine, having inadequate insurance coverage for treatment, fear of negative effect on jobs, and having concerns about confidentiality. No significant interaction effects were identified, suggesting that these time changes were consistent by young adults’ sociodemographic variables.

Compared with White participants, Hispanic and Asian participants were more likely to report not knowing where to go for services (Hispanic participants: adjusted odds ratio [AOR], 1.57 [95% CI, 1.21-2.03]; Asian participants: AOR, 2.63 [1.68-4.11]), whereas Native American participants were more likely to report having no insurance coverage (AOR, 3.44 [95% CI, 1.05-11.24]) ( Table 2 ). Hispanic participants were also more likely than White participants to report fear of being found out by others (AOR, 1.95 [95% CI, 1.38-2.76]). Female participants were less concerned than male participants about negative opinions of neighbors or communities (AOR, 0.65 [95% CI, 0.51-0.83]) or about being found out by others (AOR, 0.72 [95% CI, 0.54-0.96]).

Although this study is limited by potential social desirability bias based on self-reports, cost was consistently the most prominent barrier to seeking depression treatment among young adults from 2011 to 2019. In addition, young adults increasingly reported inadequate insurance coverage for mental health treatment. Since its implementation in 2014, the Medicaid expansion has reduced the rate of uninsured individuals and improved access to care for adults with depression. 6 Immediate policy actions are needed, therefore, to close the Medicaid coverage gap, especially for Native American individuals. More outreach campaigns are also warranted to increase young adults’ awareness of local mental health services, particularly among Hispanic and Asian communities. Last, destigmatizing mental health treatment should be prioritized among young adults, with gender-specific engagement interventions for men.

Accepted for Publication: March 24, 2022.

Published: May 10, 2022. doi:10.1001/jamanetworkopen.2022.11393

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2022 Lu W et al. JAMA Network Open .

Corresponding Author: Wenhua Lu, PhD, Department of Community Health and Social Medicine, School of Medicine, The City University of New York, 160 Convent Ave, New York, NY 10031 ( [email protected] ).

Author Contributions : Dr Lu had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Lu, Bessaha.

Acquisition, analysis, or interpretation of data: Lu, Muñoz-Laboy.

Drafting of the manuscript: Lu, Muñoz-Laboy.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Lu.

Administrative, technical, or material support: Lu, Bessaha.

Supervision: Muñoz-Laboy.

Conflict of Interest Disclosures: None reported.

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A New Study Is Finally Attempting to Pin Down The Root Causes of Depression

Most experts agree that depression is not one thing.

The core experiences of depression — changes in energy, activity, thinking, and mood — have been described for more than 10,000 years. The word “depression” has been used for about 350 years.

Given this long history, it may surprise you that experts don’t agree about what depression is, how to define it, or what causes it.

However, many experts do agree that depression is not one thing . It’s a large family of illnesses with different causes and mechanisms. This makes choosing the best treatment for each person challenging.

Reactive vs endogenous depression

One strategy is to search for sub-types of depression and see whether they might do better with different kinds of treatments. One example is contrasting “reactive” depression with “endogenous” depression.

Reactive depression (also thought of as social or psychological depression) is presented as being triggered by exposure to stressful life events. These might be being assaulted or losing a loved one — an understandable reaction to an outside trigger.

Endogenous depression (also thought of as biological or genetic depression) is proposed to be caused by something inside , such as genes or brain chemistry.

Many people working clinically in mental health accept this sub-typing. You might have read about this online .

But we think this approach is way too simple.

While stressful life events and genes may, individually, contribute to causing depression, they also interact to increase the risk of someone developing depression. And evidence shows that there is a genetic component to being exposed to stressors. Some genes affect things such as personality. Some affect how we interact with our environments.

What we did and what we found

Our team set out to look at the role of genes and stressors to see if classifying depression as reactive or endogenous was valid.

In the Australian Genetics of Depression Study , people with depression answered surveys about exposure to stressful life events. We analyzed DNA from their saliva samples to calculate their genetic risk for mental disorders.

Our question was simple. Does genetic risk for depression, bipolar disorder, schizophrenia, ADHD, anxiety, and neuroticism (a personality trait) influence people’s reported exposure to stressful life events?

You may be wondering why we bothered calculating the genetic risk for mental disorders in people who already have depression. Every person has genetic variants linked to mental disorders. Some people have more, some less. Even people who already have depression might have a low genetic risk for it. These people may have developed their particular depression from some other constellation of causes.

We looked at the genetic risk of conditions other than depression for a couple of reasons. First, genetic variants linked to depression overlap with those linked to other mental disorders. Second, two people with depression may have completely different genetic variants. So, we wanted to cast a wide net to look at a wider spectrum of genetic variants linked to mental disorders.

If reactive and endogenous depression sub-types are valid, we’d expect people with a lower genetic component to their depression (the reactive group) to report more stressful life events. And we’d expect those with a higher genetic component (the endogenous group) would report fewer stressful life events.

But after studying more than 14,000 people with depression, we found the opposite.

We found people at higher genetic risk for depression, anxiety, ADHD, or schizophrenia say they’ve been exposed to more stressors .

Assault with a weapon, sexual assault, accidents, legal and financial troubles, and childhood abuse and neglect were all more common in people with a higher genetic risk of depression, anxiety, ADHD, or schizophrenia.

These associations were not strongly influenced by people’s age, sex, or relationships with family. We didn’t look at other factors that may influence these associations, such as socioeconomic status. We also relied on people’s memory of past events, which may not be accurate.

How do genes play a role?

Genetic risk for mental disorders changes people’s sensitivity to the environment.

Imagine two people, one with a high genetic risk for depression and one with a low risk. They both lose their jobs. The genetically vulnerable person experiences the job loss as a threat to their self-worth and social status. There is a sense of shame and despair. They can’t bring themselves to look for another job for fear of losing it, too. For the other, the job loss feels less about them and more about the company. These two people internalize the event differently and remember it differently.

Genetic risk for mental disorders also might make it more likely people find themselves in environments where bad things happen. For example, a higher genetic risk for depression might affect self-worth, making people more likely to get into dysfunctional relationships, which then go badly.

What does our study mean for depression?

First, it confirms genes and environments are not independent. Genes influence the environments we end up in and what then happens. Genes also influence how we react to those events.

Second, our study doesn’t support a distinction between reactive and endogenous depression. Genes and environments have a complex interplay. Most cases of depression are a mix of genetics, biology, and stressors.

Third, people with depression who appear to have a stronger genetic component to their depression report their lives are punctuated by more serious stressors.

So, clinically, people with higher genetic vulnerability might benefit from learning specific techniques to manage their stress. This might help some people reduce their chance of developing depression in the first place. It might also help some people with depression reduce their ongoing exposure to stressors.

This article was originally published on The Conversation by Jacob Crouse and Ian Hickie at the University of Sydney . Read the original article here .

• Mental Health

Interleukin levels and depressive symptoms in psoriatic arthritis patients: insights from a case–control study on socio-demographic factors and disease perception

• Observational Research
• Published: 10 May 2024

Cite this article

• Marzena Waszczak-Jeka   ORCID: orcid.org/0000-0002-1496-3997 1 ,
• Paweł Żuchowski   ORCID: orcid.org/0000-0002-5605-7554 2 , 3 ,
• Marta Dura   ORCID: orcid.org/0000-0002-0210-0318 3 , 4 ,
• Agnieszka Bielewicz-Zielińska   ORCID: orcid.org/0009-0003-0948-8129 5 ,
• Michał Kułakowski   ORCID: orcid.org/0000-0003-1979-849X 3 , 6 &
• Alicja Góralczyk   ORCID: orcid.org/0009-0002-5944-0150 2  

In the course of psoriatic arthritis (PsA), depression occurs much more often than in the general population. Depression can be considered a poor prognostic factor. The aim of the study was to assess the relationships between the occurrence of depression and the levels of proinflammatory cytokines in patients with PsA. The study included 86 (47F/39M) patients with PsA. Only patients with high disease activity (DAPSA > 28) were enrolled in the study. The severity of depressive symptoms was assessed using the Beck Depression Inventory II (BDI-II) for all patients. Additionally, sociodemographic data were collected. All patients were also assessed for the levels of interleukins (IL): IL-1, IL-6, IL-17A, IL-23, and tumor necrosis factor alpha (TNF-α) using the enzyme-linked immunosorbent assay (ELISA) test. In the study group, depression (BDI-II ≥ 14) was diagnosed in 45 patients (52%). Patients with coexisting depression reported higher levels of pain and disease activity on the visual analogue scale compared to patients without depression (8.5 vs. 7.7, p < 0.001 and 9.3 vs. 8.4, p < 0.001, respectively). The mean levels of proinflammatory cytokines [pg/ml], IL-1 and IL-6, were also higher in the group of patients with depression (46.4 vs. 4.7, p < 0.001 and 10.5 vs. 4.9, p < 0.001, respectively). The coexistence of depression in the course of Psoriatic Arthritis (PsA) is associated with higher levels of IL-1 and IL-6. Depression has a negative impact on the perception of the underlying disease and is linked to reduced social and occupational activity.

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Data availiability statement

Primary data of the study are available from the corresponding author upon reasonable request.

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Marzena Waszczak-Jeka

Clinic of Rheumatology and Connective Tissue Diseases, Jan Biziel University Hospital No 2 in Bydgoszcz, Bydgoszcz, Poland

Paweł Żuchowski & Alicja Góralczyk

Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Toruń, Poland

Paweł Żuchowski, Marta Dura & Michał Kułakowski

Department of Radiology, Jan Biziel University Hospital No 2 in Bydgoszcz, Bydgoszcz, Poland

Department of Rheumatology, Voivodship Hospital in Elbląg, Elblag, Poland

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Clinical Department of Orthopaedics and Traumatology, Jan Biziel University Hospital No 2 in Bydgoszcz, Bydgoszcz, Poland

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Marzena Waszczak-Jeka—study design, data interpretation, manuscript preparation, literature search. Paweł Żuchowski—statistical analysis, data interpretation, manuscript preparation, literature search. Marta Dura—data interpretation, manuscript preparation, literature search. Agnieszka Bielewicz-Zielińska—data interpretation, manuscript preparation, literature search. Michał Kułakowski—data collenction, manuscript preparation, literature search. Alicja Góralczyk—data collection, data interpretaion, litearture search.

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Waszczak-Jeka, M., Żuchowski, P., Dura, M. et al. Interleukin levels and depressive symptoms in psoriatic arthritis patients: insights from a case–control study on socio-demographic factors and disease perception. Rheumatol Int (2024). https://doi.org/10.1007/s00296-024-05599-0

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• Published: 06 May 2024

Association between Mir-17-92 gene promoter polymorphisms and depression in a Chinese population

• Peng Liang 1 ,
• Xue Yang 2   na1 ,
• Rui Long 1 ,
• Ziling Wang 1 ,
• Pingliang Yang 3   na1 &
• Yundan Liang 1  

BMC Medical Genomics volume  17 , Article number:  123 ( 2024 ) Cite this article

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Depression is a common chronic debilitating disease with a heavy social burden. single nucleotide polymorphisms (SNPs) can affect the function of microRNAs (miRNAs), which is in turn associated with neurological diseases. However, the association between SNPs located in the promoter region of miR-17-92 and the risk of depression remains unclear. Therefore, we investigated the association between rs982873, rs9588884 and rs1813389 polymorphisms in the promoter region of miR-17-92 and the incidence of depression in a Chinese population.

we used GWAS (Genome-wide association study) and NCBI (National Center for Biotechnology Information) to screen three SNPs in the miR-17-92 cluster binding sites. A case-control study (including 555 cases and 541 controls) was conducted to investigate the relationship between the SNPs and risk of depression in different regions of China. The gene sequencing ii was used to genotype the collected blood samples.

the following genotypes were significantly associated with a reduced risk of depression: rs982873 TC (TC vs. TT: OR = 0.72, 95% CI, 0.54–0.96, P  = 0.024; TC/CC vs. TT: OR = 0.74, 95% Cl, 0.56–0.96, P  = 0.025); CG genotype of rs9588884 (CG vs. CC: OR = 0.74, 95% CI, 0.55–0.98, P  = 0.033; CG/GG vs. CC: OR = 0.75, 95% Cl, 0.57–0.98, P  = 0.036); and AG genotype of rs1813389 (AG vs. AA: OR = 0.75, 95% CI, 0.57-1.00, P  = 0.049; AG/GG vs. AA: OR = 0.76, 95% Cl, 0.59-1.00, P  = 0.047). Stratified analysis showed that there was no significant correlation between the three SNPS and variables such as family history of suicidal tendency ( P  > 0.05).

Conclusions

our findings suggest that rs982873, rs9588884, and rs1813389 polymorphisms may be associated with protective factors for depression.

Peer Review reports

Introduction

Depression is a common chronic and debilitating disorder that is characterized by affective, cognitive, and behavioral symptoms [ 1 ]. Anhedonia, a reduced ability to experience pleasure or a lack of responsiveness to hedonic stimuli, is the core symptom of depression. According to the Institute for Health Metrics and Evaluation, anhedonia affects approximately 280 million people worldwide [ 2 ]. In its most severe form, depression can lead to suicide, which is a major cause of the increasing suicide rate in the 21st century [ 3 , 4 ]. Depression is the result of a combination of social, psychological and biological factors. Although there are proven therapies for depression, more than 75% of people in low- and middle-income countries receive no treatment [ 5 ]. One factor hindering effective care is that people with depression are often not correctly diagnosed. Although there are a variety of hypotheses for the pathophysiological mechanism of depression, including inflammation [ 6 ], there is no clear mechanism that can comprehensively explain the pathogenesis. As a result, there are insufficient data to guide the diagnosis of clinical depression. Therefore, there is a need to identify markers to improve the monitoring, prognosis and therapeutic intervention for this serious global disease.

MicroRNAs (miRNAs) are a group of non-coding RNAs with a length of about 20 nucleotides encoded by the genome in cells. They negatively regulate gene expression at the post-transcriptional level by binding to the 3’-untranslated regions (3’-UTRs) of mRNA of target genes, leading to degradation or translational repression of mRNA [ 7 ]. miRNAs, which are relatively conserved in species evolution, participate in a variety of important biological processes including cell proliferation, differentiation and apoptosis [ 8 ]. Among various non-coding RNAs, miRNAs are the most studied and well characterized, and have emerged as major regulators of neuroplasticity and higher brain functions [ 9 ]. Previous studies have shown that overexpression or disorder of miRNAs is associated with the occurrence and development of many complex diseases [ 10 ], including neurological diseases such as Parkinson’s disease, Alzheimer’s disease and major depressive disorder [ 11 ]. Variations in specific miRNAs have potential as biomarkers for diagnostic or therapeutic targets in clinical practice [ 12 ]. However, the mechanisms by which miRNAs contribute to the development and progression of these neurological disorders, especially depression, remain largely unknown. Therefore, finding the specific miRNA and its potential mechanism may provide new diagnostic and therapeutic ideas for the treatment of depression.

In addition, it is worth noting that many miRNAs single nucleotide polymorphisms (SNPs) are associated with neurological diseases. For example, miR-5-2p rs41305272*T carrier frequency has been correlated with the number of anxiety and depressive disorders diagnosed per subject [ 13 ]. Another study demonstrated a significant association between miRNA-137 rs1625579 polymorphism and schizophrenia in a southern Chinese Han population [ 14 ]. Further results suggest that downregulation of miR-34b and miR-34c in the brain, and SNPs in the 3’-UTR of α-SYN, can increase α-SYN expression and may contribute to the pathogenesis of Parkinson’s disease [ 15 ]. Therefore, exploring the association between SNPs of specific miRNAs and depression is a new idea for studying the pathogenesis of depression.

Human miRNAs are characterized by clustering on chromosomes. These miRNA gene clusters are transcribed by a common promoter to generate polycistronic elements [ 16 ]. Among them, the miR-17-92 gene cluster located on chromosome 13 (13q31.3:91347820–91,354,575) encodes six mature miRNAs: namely miR-17, miR-18a, miR-19a, miR-20a, miR-19b-1 and miR-92a-1 16 . It has been found that miR-17-92 is highly expressed in the embryonic mouse brain [ 17 ] and alters the level of miR-17-92 in hippocampal neural precursor cells, which has important effects on neurogenesis and anxiety- and depression-related behaviors. Loss of miR-17-92 in neural progenitor cells results in decreased neurogenesis in the hippocampal dentate gyrus, while high expression increases neurogenesis [ 18 ]. miR-17-92 gene knockout mice show anxiety and depression-like behaviors, while miR-17-92 overexpression mice show anxiolytic and antidepressant behaviors [ 19 ]. These results suggest that the miR-17-92 cluster is a key regulator of hippocampal neurogenesis and anxiety and depressive behaviors [ 20 ], and therefore may be a new marker for the diagnosis of depressive disorders. However, the association between risk of depression and miR-17-92 SNPs, especially in the promoter region, has not been investigated.

Therefore, a case-control study was conducted to investigate the association between rs982873, rs9588884 and rs1813389 polymorphisms in the miR-17-92 promoter region and the incidence of major depressive disorder in a Chinese population; with the aim of providing a scientific basis for the prevention and treatment of depression.

Materials and methods

We conducted a case-control study involving 555 patients with depression and 541 controls. Patients with depression were recruited from Jining Mental Hospital, Yunnan Mental Health Center, Sichuan Provincial People’s Hospital and Harbin First Specialized Hospital from September 2013 to April 2022. All patients were newly diagnosed with depression using the Fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) [ 21 ] and the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) [ 22 ]. The recruited patients had a 24-item Hamilton Depression Scale (HAMD-24) total score of ≥ 24 before screening. Exclusion criteria included diagnosis of other psychiatric disorders, presence of neurological disorders, lack of signed consent, poor ability to participate in assessment, and pregnancy.

Healthy controls were randomly selected from individuals who participated in health checkups during the same period. Clinical data regarding the patient’s age, sex, pulse rate, age of onset, suicide attempt, whether the patient was the first episode, and family history were all derived from the medical record, which has been described in detail in our previous studies [ 23 , 24 ]. The exclusion criteria for healthy controls were the same as for patients, and the mean age (206 men, 335 women) was 50 ± 18.1 years (Table  1 ). Controls and cases were frequency matched according to gender, age, and region of residence. Quanto software 1.2.3 (University of Southern California, Los Angeles, CA, USA) was used to calculate the power of sample size. When the RG value was set to 1.6, the heritability of the three SNPS was greater than 80% under the dominant model.

This study was approved by the Ethics Committee of Chengdu Medical College (approval number: Chengyi Ethics [2008] No. 15), and all procedures followed the principles of the Declaration of Helsinki. Written informed consent was obtained from each participant.

SNP selection

The UCSC Genome Database [ 25 ] was searched to identify SNPs associated with depression in the 2 kb upstream of the transcription start site of the miR-17-92 promoter region. The loci with a minor allele frequency > 10% in the Asian population were selected as follows: rs982873, rs9588884 and rs1813389.

Human blood collection: we collected 2-3 ml whole blood samples from all subjects using EDTA anticoagulated tubes and stored these on ice at -20℃.

DNA extraction: DNA was extracted from each peripheral blood sample using a whole blood genomic DNA rapid extraction kit (Sangon Bioengineering (Shanghai) Co., Ltd.) according to the instructions.

Multiple amplification and high-throughput sequencing: a primer pool containing three SNP sites were designed and synthesized. The primer sequences are shown in Table  2 . The target SNP sequences were amplified, and Illumina sequencing libraries were prepared by two-step PCR. The first round PCR system was as follows: 2 µl DNA template (10 ng/µl); 1 µl upstream primer pool (10µM). The downstream primer pool (10µM) was 1 µl 2×PCR Ready Mix 15 µl (total volume 25 µl; Kapa HiFi Ready Mix). After preparation of the system, the following reaction program was performed on a PCR instrument (BIO-RAD, T100™): pre-denaturation at 98° C for 3 min, followed by eight cycles of denaturation at 98° C for 30 s, annealing at 50° C for 30 s, and extension at 72° C for 30 s. This was followed by 25 cycles of denaturation at 98° C for 30 s, annealing at 66° C for 30 s, and extension at 72° C for 30 s. The final extension was at 72° C for 5 min. After completion of the reaction, 4° C. At the end of the PCR, the correct size of the PCR products was confirmed by electrophoresis using 1% agarose gel, and the PCR products were recovered by purification using AMPure XP magnetic beads.

A second round of PCR reactions was then performed using the first round of PCR products as templates to obtain libraries with molecular tags for sequencing. The reaction system was as follows: 2 µl DNA template (10ng/µl), 1 µl universal P7 primer (containing molecular tag, 10µM); Universal P5 primer (10µM) 1 µl; 2×PCR Ready Mix 15 µl (total volume 30 µl). After the reaction system was formulated, the following PCR procedure was performed: pre-denaturation at 98° C for 5 min, followed by five cycles of denaturation at 94 °C for 30 s, annealing at 55° C for 20 s, extension at 72° C for 30 s, and final extension at 72° C for 5 min. X. The final PCR products were recovered by purification using AMPure XP magnetic beads. Individual PCR products were mixed in equal amounts and sequenced using a HiSeq XTen sequencer (Illumina, San Diego, CA).

Data quality control and genotyping analysis: data quality control was performed by the following two steps: 1) Cutadapt (v1.2.1) software was used to cut out any part of the sequence containing the sequencing adapter; 2) PRINSEQ-lite (v0.20.3) software was used to control the quality of the remaining sequences, and the bases below the quality threshold of 20 were deleted according to the sequence from 3’ to 5’ end. The remaining sequences were regarded as qualified sequences. Then BWA (v0.7.13-r1126) software was used to align the qualified sequences to the reference genome with the default parameters. Based on the results, the genotypes of the target loci were calculated by SAMtools software (v0.1.18). Finally, ANNOVAR (2018-04-16) software was used for gene annotation. In addition, 5% of the samples were randomly selected for repeat genotyping for quality control, with 100% agreement for each SNP.

Statistical analysis

All statistical analyses were performed using SPSS 25.0 (Chicago, IL, USA) and GraphPad Prism 5.0 (GraphPad Software, San Diego, CA, USA). The genotype frequencies of rs982873, rs9588884 and rs1813389 were calculated by direct counting. Hardy-Weinberg equilibrium was assessed by X [ 2 ] test. The distribution of rs982873, rs9588884 and rs1813389 genotypes in cases and controls was analyzed by X [ 2 ] test; and the association between the three polymorphisms and the risk of depression was evaluated by odds ratio (OR) and 95% confidence interval (Cl). A P value of < 0.05 was considered statistically significant.

The genotype frequencies of the three polymorphisms in controls and participants are shown in Table  3 . The distribution of genotypes in the control group did not deviate from Hardy-Weinberg equilibrium (rs982873: P  = 0.29; rs9588884: P  = 0.33; rs1813389: P  = 0.72). eQTL [ 26 ] query results showed no effect of rs982873, rs9588884 or rs1813389 polymorphism loci on the expression of miR-17-92. There was a significant difference between cases and controls in the following: the distribution of TC genotype of rs982873 (TC vs. TT: OR = 0.72, 95% CI, 0.54–0.96, P  = 0.024; TC/CC vs. TT: OR = 0.74, 95% Cl, 0.56–0.96, P  = 0.025); the distribution of rs9588884 CG genotype (CG vs. CC: OR = 0.74, 95% CI, 0.55–0.98, P  = 0.033; CG/GG vs. CC: OR = 0.75, 95% Cl, 0.57–0.98, P  = 0.036); the distribution of rs1813389 AG genotype (AG vs. AA: OR = 0.75, 95% CI, 0.57-1.00, P  = 0.049; AG/GG vs. AA: OR = 0.76, 95% Cl, 0.59-1.00, P  = 0.047).

No significant association was found between rs982873, rs9588884 and rs1813389 polymorphisms and the following variables ( P  > 0.05; Table  4 ): depressive episode (severe vs. mild/moderate), family history (yes vs. no), first episode (yes vs. no).

The haplotype analysis of rs982873, rs9588884 and rs1813389 polymorphism sites showed that rs982873, rs9588884 and rs1813389 had strong linkage disequilibrium (Fig.  1 ), and no significant difference was found between patients and healthy controls with different haplotype types (Table  5 ).

Genetic variants, such as miRNAs or SNPs in miRNA promoter regions, can affect the regulation of miRNA-dependent gene expression. This is associated with a variety of diseases, including depression, and can alter an individual’s susceptibility to the disease; for examples microRNA processing genes DGCR8 rs3757 and AGO1 rs636832 are significantly associated with depression [ 27 ]. In our work, we used a case-control study design to investigate the relationship between miR-17-92 polymorphism and the risk of depression in a Chinese population for the first time. We found that the rs982873 TC, rs9588884 CG and rs1813389 AG genotypes were significantly associated with a reduced risk of depression. Our results suggest that the rs982873, rs9588884, and rs1813389 polymorphisms may be associated with protective factors for depression in this population. Since genetic polymorphisms rarely determine disease development, we can therefore only indicate changes in susceptibility or resistance to factors that contribute to the occurrence of the disease and/or the severity of its course [ 28 ]. This is because the phenotype depends not only on the genotype but also on its interaction with the environment. We also know that the interaction between genes and the environment is very complex. Because our bodies are exposed to many positive and negative factors [ 29 ], these can have an impact on the development of depression. However, we did not find an association between depressive symptoms and the studied polymorphisms, which may be due to individual differences.

There is growing evidence that depression is a complex and widespread disorder that affects thought, mood, and physical health. It is characterized by low mood, low energy, sadness, insomnia and an inability to enjoy life. However, it is often difficult to diagnose, especially in primary medical care [ 30 ]. At present, the incidence of depression in students is increasing year by year, and the incidence is high in young group [ 31 ]. Depression can also be misdiagnosed and, in addition, detection of mild depression is difficult because symptoms can be confused with symptoms of nervousness under stress [ 31 ]. Therefore, finding rapid tests to assess the risk of depression is necessary to complement a medical diagnosis. Biomarkers such as gene mutations, neurotransmitters and cytokines have been widely used in clinical practice to identify diseases. Our study showed that rs982873, rs9588884 and rs1813389 polymorphisms in the miR-17-92 promoter region were associated with the risk of depression and therefore may be potential biomarkers for a diagnosis.

The genetic variation of miRNA is closely related to various human diseases, and may lead to the risk of diseases in different systems. The miR-17-92 cluster is known to play an important role in multiple systems such as digestion, circulation and immunity. The miR-17-92 cluster has been found to affect nervous system development, and is associated with a variety of neurological diseases. One study suggested that the miR-17-92 cluster could enhance neuroplasticity and functional recovery after stroke in rats [ 32 ]. Another paper found that it can regulate neural and vascular regeneration in the adult CNS [ 33 ]. A further study demonstrated that it regulates multiple functionally relevant voltage-gated potassium channels in chronic neuropathic pain [ 34 ], and another showed that miR-19 plays an important role in glioma pathogenesis [ 20 ]. One other study found that downregulation of miR-17-5p expression contributes to PQ-induced dopaminergic neurodegeneration [ 35 ]. The results of the above studies all play a guiding role in our study. However, to the best of our knowledge, genetic variation in miR-92-17 has not been investigated in depression. In this study, we evaluated the association between SNPs located in the promoter region of the miR-17-92 cluster and depression in a Chinese population. Our results showed that rs982873 TC, rs9588884 CG and rs1813389 AG genotypes were significantly associated with reduced risk of depression.

Previous studies on genetic polymorphism and depression mostly focused on the coding region of genes, and there are relatively few studies on the non-coding region. Our study is a pioneering exploration since it includes a relatively large sample from different regions of China, which increases the accuracy of our results. However, our study also has some limitations. We cannot explain the effects of rs982873, rs9588884 and rs1813389 polymorphisms on gene expression and function. In this study, the whole genomic DNA of peripheral blood was extracted for the study, and the influence of other components of blood on the results was not considered. These questions will be refined in future experiments.

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Data availability

The datasets generated and/or analyzed in the current study are not publicly available due to authors’ concerns about leaking data from the paper, but are available to the corresponding authors upon reasonable request.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (grant number 81901379) and the Natural Science Foundation of Sichuan, China (grant number 2022NSFSC0778). Chengdu Medical College graduate student innovation fund project(YCX2022-01-05).

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Xue Yang, Pingliang Yang authors contributed equally to this work.

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Department of Pathology and Pathophysiology, School of Basic Medical Sciences, Chengdu Medical College, Chengdu, 610500, Sichuan, P.R. China

Peng Liang, Rui Long, Yue Li, Ziling Wang & Yundan Liang

Department of Geriatric psychiatry, the First Special Hospital in Harbin, Harbin, P.R. China

Department of Anesthesiology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, P.R. China

Pingliang Yang

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PL, XY, YL, RL, ZLW and YDL contributed to conception and design of the study. XY organized the database. PL performed the statistical analysis. PL wrote the first draft of the manuscript. YDL and XY collect patient information. XY, YL, and ZLW wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

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Correspondence to Pingliang Yang or Yundan Liang .

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Liang, P., Yang, X., Long, R. et al. Association between Mir-17-92 gene promoter polymorphisms and depression in a Chinese population. BMC Med Genomics 17 , 123 (2024). https://doi.org/10.1186/s12920-024-01894-8

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Received : 25 October 2023

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DOI : https://doi.org/10.1186/s12920-024-01894-8

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