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Patient Case Presentation

a case study about depression

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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Psychiatry Online

  • March 01, 2024 | VOL. 181, NO. 3 CURRENT ISSUE pp.171-254
  • February 01, 2024 | VOL. 181, NO. 2 pp.83-170
  • January 01, 2024 | VOL. 181, NO. 1 pp.1-82

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The Critical Relationship Between Anxiety and Depression

  • Ned H. Kalin , M.D.

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Anxiety and depressive disorders are among the most common psychiatric illnesses; they are highly comorbid with each other, and together they are considered to belong to the broader category of internalizing disorders. Based on statistics from the Substance Abuse and Mental Health Services Administration, the 12-month prevalence of major depressive disorder in 2017 was estimated to be 7.1% for adults and 13.3% for adolescents ( 1 ). Data for anxiety disorders are less current, but in 2001–2003, their 12-month prevalence was estimated to be 19.1% in adults, and 2001–2004 data estimated that the lifetime prevalence in adolescents was 31.9% ( 2 , 3 ). Both anxiety and depressive disorders are more prevalent in women, with an approximate 2:1 ratio in women compared with men during women’s reproductive years ( 1 , 2 ).

Across all psychiatric disorders, comorbidity is the rule ( 4 ), which is definitely the case for anxiety and depressive disorders, as well as their symptoms. With respect to major depression, a worldwide survey reported that 45.7% of individuals with lifetime major depressive disorder had a lifetime history of one or more anxiety disorder ( 5 ). These disorders also commonly coexist during the same time frame, as 41.6% of individuals with 12-month major depression also had one or more anxiety disorder over the same 12-month period. From the perspective of anxiety disorders, the lifetime comorbidity with depression is estimated to range from 20% to 70% for patients with social anxiety disorder ( 6 ), 50% for patients with panic disorder ( 6 ), 48% for patients with posttraumatic stress disorder (PTSD) ( 7 ), and 43% for patients with generalized anxiety disorder ( 8 ). Data from the well-known Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study demonstrate comorbidity at the symptom level, as 53% of the patients with major depression had significant anxiety and were considered to have an anxious depression ( 9 ).

Anxiety and depressive disorders are moderately heritable (approximately 40%), and evidence suggests shared genetic risk across the internalizing disorders ( 10 ). Among internalizing disorders, the highest level of shared genetic risk appears to be between major depressive disorder and generalized anxiety disorder. Neuroticism is a personality trait or temperamental characteristic that is associated with the development of both anxiety and depression, and the genetic risk for developing neuroticism also appears to be shared with that of the internalizing disorders ( 11 ). Common nongenetic risk factors associated with the development of anxiety and depression include earlier life adversity, such as trauma or neglect, as well as parenting style and current stress exposure. At the level of neural circuits, alterations in prefrontal-limbic pathways that mediate emotion regulatory processes are common to anxiety and depressive disorders ( 12 , 13 ). These findings are consistent with meta-analyses that reveal shared structural and functional brain alterations across various psychiatric illnesses, including anxiety and major depression, in circuits involving emotion regulation ( 13 ), executive function ( 14 ), and cognitive control ( 15 ).

Anxiety disorders and major depression occur during development, with anxiety disorders commonly beginning during preadolescence and early adolescence and major depression tending to emerge during adolescence and early to mid-adulthood ( 16 – 18 ). In relation to the evolution of their comorbidity, studies demonstrate that anxiety disorders generally precede the presentation of major depressive disorder ( 17 ). A European community-based study revealed, beginning at age 15, the developmental relation between comorbid anxiety and major depression by specifically focusing on social phobia (based on DSM-IV criteria) and then asking the question regarding concurrent major depressive disorder ( 18 ). The findings revealed a 19% concurrent comorbidity between these disorders, and in 65% of the cases, social phobia preceded major depressive disorder by at least 2 years. In addition, initial presentation with social phobia was associated with a 5.7-fold increased risk of developing major depressive disorder. These associations between anxiety and depression can be traced back even earlier in life. For example, childhood behavioral inhibition in response to novelty or strangers, or an extreme anxious temperament, is associated with a three- to fourfold increase in the likelihood of developing social anxiety disorder, which in turn is associated with an increased risk to develop major depressive disorder and substance abuse ( 19 ).

It is important to emphasize that the presence of comor‐bid anxiety symptoms and disorders matters in relation to treatment. Across psychiatric disorders, the presence of significant anxiety symptoms generally predicts worse outcomes, and this has been well demonstrated for depression. In the STAR*D study, patients with anxious major depressive disorder were more likely to be severely depressed and to have more suicidal ideation ( 9 ). This is consistent with the study by Kessler and colleagues ( 5 ), in which patients with anxious major depressive disorder, compared with patients with nonanxious major depressive disorder, were found to have more severe role impairment and more suicidal ideation. Data from level 1 of the STAR*D study (citalopram treatment) nicely illustrate the impact of comorbid anxiety symptoms on treatment. Compared with patients with nonanxious major depressive disorder, those 53% of patients with an anxious depression were less likely to remit and also had a greater side effect burden ( 20 ). Other data examining patients with major depressive disorder and comorbid anxiety disorders support the greater difficulty and challenge in treating patients with these comorbidities ( 21 ).

This issue of the Journal presents new findings relevant to the issues discussed above in relation to understanding and treating anxiety and depressive disorders. Drs. Conor Liston and Timothy Spellman, from Weill Cornell Medicine, provide an overview for this issue ( 22 ) that is focused on understanding mechanisms at the neural circuit level that underlie the pathophysiology of depression. Their piece nicely integrates human neuroimaging studies with complementary data from animal models that allow for the manipulation of selective circuits to test hypotheses generated from the human data. Also included in this issue is a review of the data addressing the reemergence of the use of psychedelic drugs in psychiatry, particularly for the treatment of depression, anxiety, and PTSD ( 23 ). This timely piece, authored by Dr. Collin Reiff along with a subgroup from the APA Council of Research, provides the current state of evidence supporting the further exploration of these interventions. Dr. Alan Schatzberg, from Stanford University, contributes an editorial in which he comments on where the field is in relation to clinical trials with psychedelics and to some of the difficulties, such as adequate blinding, in reliably studying the efficacy of these drugs ( 24 ).

In an article by McTeague et al. ( 25 ), the authors use meta-analytic strategies to understand the neural alterations that are related to aberrant emotion processing that are shared across psychiatric disorders. Findings support alterations in the salience, reward, and lateral orbital nonreward networks as common across disorders, including anxiety and depressive disorders. These findings add to the growing body of work that supports the concept that there are common underlying factors across all types of psychopathology that include internalizing, externalizing, and thought disorder dimensions ( 26 ). Dr. Deanna Barch, from Washington University in St. Louis, writes an editorial commenting on these findings and, importantly, discusses criteria that should be met when we consider whether the findings are actually transdiagnostic ( 27 ).

Another article, from Gray and colleagues ( 28 ), addresses whether there is a convergence of findings, specifically in major depression, when examining data from different structural and functional neuroimaging modalities. The authors report that, consistent with what we know about regions involved in emotion processing, the subgenual anterior cingulate cortex, hippocampus, and amygdala were among the regions that showed convergence across multimodal imaging modalities.

In relation to treatment and building on our understanding of neural circuit alterations, Siddiqi et al. ( 29 ) present data suggesting that transcranial magnetic stimulation (TMS) targeting can be linked to symptom-specific treatments. Their findings identify different TMS targets in the left dorsolateral prefrontal cortex that modulate different downstream networks. The modulation of these different networks appears to be associated with a reduction in different types of symptoms. In an editorial, Drs. Sean Nestor and Daniel Blumberger, from the University of Toronto ( 30 ), comment on the novel approach used in this study to link the TMS-related engagement of circuits with symptom improvement. They also provide a perspective on how we can view these and other circuit-based findings in relation to conceptualizing personalized treatment approaches.

Kendler et al. ( 31 ), in this issue, contribute an article that demonstrates the important role of the rearing environment in the risk to develop major depression. Using a unique design from a Swedish sample, the analytic strategy involves comparing outcomes from high-risk full sibships and high-risk half sibships where at least one of the siblings was home reared and one was adopted out of the home. The findings support the importance of the quality of the rearing environment as well as the presence of parental depression in mitigating or enhancing the likelihood of developing major depression. In an accompanying editorial ( 32 ), Dr. Myrna Weissman, from Columbia University, reviews the methods and findings of the Kendler et al. article and also emphasizes the critical significance of the early nurturing environment in relation to general health.

This issue concludes with an intriguing article on anxiety disorders, by Gold and colleagues ( 33 ), that demonstrates neural alterations during extinction recall that differ in children relative to adults. With increasing age, and in relation to fear and safety cues, nonanxious adults demonstrated greater connectivity between the amygdala and the ventromedial prefrontal cortex compared with anxious adults, as the cues were being perceived as safer. In contrast, neural differences between anxious and nonanxious youths were more robust when rating the memory of faces that were associated with threat. Specifically, these differences were observed in the activation of the inferior temporal cortex. In their editorial ( 34 ), Dr. Dylan Gee and Sahana Kribakaran, from Yale University, emphasize the importance of developmental work in relation to understanding anxiety disorders, place these findings into the context of other work, and suggest the possibility that these and other data point to neuroscientifically informed age-specific interventions.

Taken together, the papers in this issue of the Journal present new findings that shed light onto alterations in neural function that underlie major depressive disorder and anxiety disorders. It is important to remember that these disorders are highly comorbid and that their symptoms are frequently not separable. The papers in this issue also provide a developmental perspective emphasizing the importance of early rearing in the risk to develop depression and age-related findings important for understanding threat processing in patients with anxiety disorders. From a treatment perspective, the papers introduce data supporting more selective prefrontal cortical TMS targeting in relation to different symptoms, address the potential and drawbacks for considering the future use of psychedelics in our treatments, and present new ideas supporting age-specific interventions for youths and adults with anxiety disorders.

Disclosures of Editors’ financial relationships appear in the April 2020 issue of the Journal .

1 Substance Abuse and Mental Health Services Administration (SAMHSA): Key substance use and mental health indicators in the United States: results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068, NSDUH Series H-53). Rockville, Md, Center for Behavioral Health Statistics and Quality, SAMHSA, 2018. https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/NSDUHFFR2017/NSDUHFFR2017.htm Google Scholar

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6 Dunner DL : Management of anxiety disorders: the added challenge of comorbidity . Depress Anxiety 2001 ; 13:57–71 Crossref , Medline ,  Google Scholar

7 Kessler RC, Sonnega A, Bromet E, et al. : Posttraumatic stress disorder in the National Comorbidity Survey . Arch Gen Psychiatry 1995 ; 52:1048–1060 Crossref , Medline ,  Google Scholar

8 Brawman-Mintzer O, Lydiard RB, Emmanuel N, et al. : Psychiatric comorbidity in patients with generalized anxiety disorder . Am J Psychiatry 1993 ; 150:1216–1218 Link ,  Google Scholar

9 Fava M, Alpert JE, Carmin CN, et al. : Clinical correlates and symptom patterns of anxious depression among patients with major depressive disorder in STAR*D . Psychol Med 2004 ; 34:1299–1308 Crossref , Medline ,  Google Scholar

10 Hettema JM : What is the genetic relationship between anxiety and depression? Am J Med Genet C Semin Med Genet 2008 ; 148C:140–146 Crossref , Medline ,  Google Scholar

11 Hettema JM, Neale MC, Myers JM, et al. : A population-based twin study of the relationship between neuroticism and internalizing disorders . Am J Psychiatry 2006 ; 163:857–864 Link ,  Google Scholar

12 Kovner R, Oler JA, Kalin NH : Cortico-limbic interactions mediate adaptive and maladaptive responses relevant to psychopathology . Am J Psychiatry 2019 ; 176:987–999 Link ,  Google Scholar

13 Etkin A, Schatzberg AF : Common abnormalities and disorder-specific compensation during implicit regulation of emotional processing in generalized anxiety and major depressive disorders . Am J Psychiatry 2011 ; 168:968–978 Link ,  Google Scholar

14 Goodkind M, Eickhoff SB, Oathes DJ, et al. : Identification of a common neurobiological substrate for mental illness . JAMA Psychiatry 2015 ; 72:305–315 Crossref , Medline ,  Google Scholar

15 McTeague LM, Huemer J, Carreon DM, et al. : Identification of common neural circuit disruptions in cognitive control across psychiatric disorders . Am J Psychiatry 2017 ; 174:676–685 Link ,  Google Scholar

16 Beesdo K, Knappe S, Pine DS : Anxiety and anxiety disorders in children and adolescents: developmental issues and implications for DSM-V . Psychiatr Clin North Am 2009 ; 32:483–524 Crossref , Medline ,  Google Scholar

17 Kessler RC, Wang PS : The descriptive epidemiology of commonly occurring mental disorders in the United States . Annu Rev Public Health 2008 ; 29:115–129 Crossref , Medline ,  Google Scholar

18 Ohayon MM, Schatzberg AF : Social phobia and depression: prevalence and comorbidity . J Psychosom Res 2010 ; 68:235–243 Crossref , Medline ,  Google Scholar

19 Clauss JA, Blackford JU : Behavioral inhibition and risk for developing social anxiety disorder: a meta-analytic study . J Am Acad Child Adolesc Psychiatry 2012 ; 51:1066–1075 Crossref , Medline ,  Google Scholar

20 Fava M, Rush AJ, Alpert JE, et al. : Difference in treatment outcome in outpatients with anxious versus nonanxious depression: a STAR*D report . Am J Psychiatry 2008 ; 165:342–351 Link ,  Google Scholar

21 Dold M, Bartova L, Souery D, et al. : Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders: results from a European multicenter study . J Psychiatr Res 2017 ; 91:1–13 Crossref , Medline ,  Google Scholar

22 Spellman T, Liston C : Toward circuit mechanisms of pathophysiology in depression . Am J Psychiatry 2020 ; 177:381–390 Link ,  Google Scholar

23 Reiff CM, Richman EE, Nemeroff CB, et al. : Psychedelics and psychedelic-assisted psychotherapy . Am J Psychiatry 2020 ; 177:391–410 Link ,  Google Scholar

24 Schatzberg AF : Some comments on psychedelic research (editorial). Am J Psychiatry 2020 ; 177:368–369 Link ,  Google Scholar

25 McTeague LM, Rosenberg BM, Lopez JW, et al. : Identification of common neural circuit disruptions in emotional processing across psychiatric disorders . Am J Psychiatry 2020 ; 177:411–421 Link ,  Google Scholar

26 Caspi A, Moffitt TE : All for one and one for all: mental disorders in one dimension . Am J Psychiatry 2018 ; 175:831–844 Link ,  Google Scholar

27 Barch DM : What does it mean to be transdiagnostic and how would we know? (editorial). Am J Psychiatry 2020 ; 177:370–372 Abstract ,  Google Scholar

28 Gray JP, Müller VI, Eickhoff SB, et al. : Multimodal abnormalities of brain structure and function in major depressive disorder: a meta-analysis of neuroimaging studies . Am J Psychiatry 2020 ; 177:422–434 Link ,  Google Scholar

29 Siddiqi SH, Taylor SF, Cooke D, et al. : Distinct symptom-specific treatment targets for circuit-based neuromodulation . Am J Psychiatry 2020 ; 177:435–446 Link ,  Google Scholar

30 Nestor SM, Blumberger DM : Mapping symptom clusters to circuits: toward personalizing TMS targets to improve treatment outcomes in depression (editorial). Am J Psychiatry 2020 ; 177:373–375 Abstract ,  Google Scholar

31 Kendler KS, Ohlsson H, Sundquist J, et al. : The rearing environment and risk for major depression: a Swedish national high-risk home-reared and adopted-away co-sibling control study . Am J Psychiatry 2020 ; 177:447–453 Abstract ,  Google Scholar

32 Weissman MM : Is depression nature or nurture? Yes (editorial). Am J Psychiatry 2020 ; 177:376–377 Abstract ,  Google Scholar

33 Gold AL, Abend R, Britton JC, et al. : Age differences in the neural correlates of anxiety disorders: an fMRI study of response to learned threat . Am J Psychiatry 2020 ; 177:454–463 Link ,  Google Scholar

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a case study about depression

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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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a case study about depression

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

© 2020 K. M. Cooper, L. E. Gin, et al. CBE—Life Sciences Education © 2020 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Bella DePaulo Ph.D.

Scaremongering About Living Alone: A Case Study

People who live alone are very unlikely to be depressed..

Posted February 27, 2024 | Reviewed by Michelle Quirk

  • What Is Depression?
  • Find a therapist to overcome depression
  • A misleading NPR headline implied that people living alone are especially likely to be depressed.
  • In a CDC study, people living alone had significantly higher rates of depression only if living in poverty.
  • Negative portrayals in the media can make people who love living alone doubt themselves.

An article on the NPR website, about a segment on Morning Edition, came with this headline: “Americans who live alone report depression at higher rates, but social support helps.” What were those “higher rates”? Just guessing, maybe about 70 percent? Surely more than half?

In the Facebook group, The Community of Single People, Monica Pignotti flagged that article. Wisely, she did not stop at the headline. She looked for the actual percentage of people living alone who feel depressed. The answer: 6 percent! A more accurate headline would be something like, “Americans who live alone report very low rates of depression.”

The actual headline referred to “higher rates,” a comparative claim. People living alone, we are led to believe, are more likely to be depressed than people living with others. But the rates of depression for people not living alone were 4 percent. With the large number of people in the study (nearly 30,000), that was a statistically significant difference from 6 percent, but as Monica suggested, it may not be a meaningful difference. I doubt that anyone reading just the headline would guess that the difference was just two percentage points.

People Living Alone Are More Depressed Only if They Get Almost No Social Support

The headline does include the qualifier that “social support helps.” I went to the original research report from the Centers for Disease Control and Prevention (CDC) to see the numbers. Participants—a nationally representative sample of adults in the United States aged 18 years and older—were asked, “How often do you get the social and emotional support you need?” They could answer rarely or never, sometimes, usually, or always. Only if the participants rarely or never got the emotional support they needed were the people living alone more likely to be depressed than the people living with others (20 percent vs. 12 percent).

People Living Alone Are More Depressed Only if They Are Impoverished

The CDC study also reported rates of depression by four levels of income: below the federal poverty level, up to twice the poverty level, from twice to four times the poverty level, and the highest level of income, more than four times the poverty level. The people living alone reported significantly higher rates of depression than those living with others only if they were living in poverty, 14 percent versus 9 percent.

Income also mattered in a previous study of loneliness among more than 16,000 Germans ranging in age from 18 to 103 years. When the researchers simply compared all the people living alone with all the people living with others, the people living alone were lonelier. But when they matched people on income so that they were comparing people living alone with people living with others when both groups had the same income, then they found that the people living alone were actually less lonely. (I discussed those findings in greater detail here at Living Single.)

Older People Are Very Unlikely to Be Depressed When Living Alone

The stereotype of old people living alone is that they are sad and lonely. But, according to the CDC study, that caricature may be exactly wrong. Among those 65 and older who were living alone, only 5 percent reported feeling depressed. People between the ages of 45 and 64 had the highest rate of depression when living alone, though at 9 percent, even that wasn’t very high. (For the other two age groups, 18-29 and 30-44, the rate was 6 percent, close to the rate for the oldest group.)

Why This Matters

Media messages matter. We should be able to trust in what we read, even if we read no more than a headline, especially from prestige media such as NPR. Typically, we can. But when it comes to matters such as living alone, we are at greater risk of scaremongering.

Unjustifiably negative portrayals of solo living, or of being single, are evident in other domains, too, such as popular culture and even in reports of scientific research . The cumulative effect is that people who love living alone, or love being single (such as the single at heart ), come to doubt themselves. Or worse—they worry that something is wrong with them. Think about that: They have what we all want, a life that they love. But instead of feeling encouraged to embrace their most fulfilling and authentic way of living, they wonder whether they should instead live the way they are expected to live. That’s unfair to them, especially when the actual findings are not at all what they have been led to believe. It undermines their potential to fully flourish.

Rhitu Chatterjee. Americans who live alone report depression at higher rates, but social support helps . NPR. February 15, 2024.

Bella DePaulo Ph.D.

Bella DePaulo, Ph.D. , an expert on single people, is the author of Single at Heart and other books. She is an Academic Affiliate in Psychological & Brain Sciences, UCSB.

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This figure shows the proportion of respondents in each 10-year age group whose scores exceed thresholds for clinically significant (A) anxiety, (B) depression, or (C) both anxiety and depression. Plots reflect population-weighted descriptive statistics (not regression-adjusted values). Calculations were conducted using data from Household Pulse Surveys April 2020 to August 2022. 21

Calculations were conducted using data from Household Pulse Surveys April 2020 to August 2022. 21 This figure shows that White respondents exhibit a larger spread in anxiety and depression than individuals from racially and ethnically minoritized groups, with the highest levels of anxiety and depression among White respondents aged 18 to 39 years and the lowest levels among White respondents aged 40 to 59 years (whereas prevalence for individuals from racially and ethnically minoritized groups tends to fall between these extremes for both age groups). Plots reflect population-weighted descriptive statistics (not regression-adjusted values). Minority group indicates individuals from racially and ethnically minoritzed groups.

This figure shows the proportion of respondents with clinically elevated (A) anxiety and (B) depression over the pandemic period, grouped by annual household income level. Plots reflect population-weighted descriptive statistics (not regression-adjusted values). Calculations were conducted using data from Household Pulse Surveys April 2020 to August 2022. 21

This figure depicts the proportion of respondents with clinically elevated (A) anxiety and (B) depression over the pandemic period. The thicker lines correspond to the time period before vaccination was available in the US. The finer lines distinguish between survey respondents who indicated that they have received at least 1 dose of a vaccine (dashed line) or have not yet been vaccinated (solid line). Plots reflect population-weighted descriptive statistics (not regression-adjusted values). Calculations were conducted using data from Household Pulse Surveys April 2020 to August 2022. 21

eFigure 1. Prepandemic Trends in Depressive Symptoms

eTable 1. Household Pulse Survey Administration Dates

eTable 2. Descriptive Statistics—Exposures and Covariates

eTable 3. Descriptive Statistics—Outcome Variables

eTable 4. Detailed Regression Results

eFigure 2. Co-occurrence of Anxiety and Depression

eFigure 3. Anxiety and Depression for White Respondents and Individuals From Racially and Ethnically Minoritzed Groups, by Age Group, Annotated With Current Events

eTable 5. Impacts of Pandemic Burden on Anxiety and Depression, Overall and for Ages 18 to 39 Years vs Ages 40 Years and Older

eTable 6. Impacts of Prior COVID-19 Diagnosis and Vaccine Receipt

eFigure 4. Anxiety and Depression by Economic Precarity Score and Age Group

eTable 7. Prevalence of Anxiety and Depression by Economic Precarity

eTable 8. Proportion of Age Disparity Accounted for by Exposure Effect

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Collier Villaume S , Chen S , Adam EK. Age Disparities in Prevalence of Anxiety and Depression Among US Adults During the COVID-19 Pandemic. JAMA Netw Open. 2023;6(11):e2345073. doi:10.1001/jamanetworkopen.2023.45073

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Age Disparities in Prevalence of Anxiety and Depression Among US Adults During the COVID-19 Pandemic

  • 1 School of Education and Social Policy, Northwestern University, Evanston, Illinois
  • 2 Institute for Policy Research, Northwestern University, Evanston, Illinois
  • 3 Department of Psychology, University of Florida, Gainesville

Question   Were there age disparities in anxiety and depression during the COVID-19 pandemic?

Findings   In this cross-sectional study of 3 028 923 US adults, anxiety and depression were significantly higher among adults aged 18 to 39 years (40% and 33%, respectively) compared with adults aged 40 years and older (31% and 24%, respectively). Greater economic precarity and greater reactivity to changing case counts among younger adults were associated with this age disparity.

Meaning   These findings suggest that more than one-third of young adults had anxiety or depression during the COVID-19 pandemic; less favorable economic conditions and responses to social upheaval may have contributed to young adults’ worse mental well-being.

Importance   High levels of anxiety and depression were documented shortly after the arrival of the COVID-19 pandemic and were more prevalent in younger adults than in older adults. Knowing whether these age disparities persisted throughout multiple years of the COVID-19 pandemic and identifying associated factors will help guide health policy.

Objective   To investigate age disparities in anxiety and depression during the COVID-19 pandemic.

Design, Setting, and Participants   This cross-sectional study consisted of a nationally representative online survey administered between April 2020 and August 2022 and included US adults who were not incarcerated. Data were analyzed between March and September 2022.

Exposures   The first 27 months of the COVID-19 pandemic included wide variation in infection rates, turbulence in US political and social life, and geopolitical instability. Primary exposures include individuals’ age and economic precarity and pandemic-related events (eg, weekly state-level case counts and individual vaccination status).

Main outcomes and measures   Symptoms of anxiety and depression were assessed via responses to 2-item screeners (Generalized Anxiety Disorder 2-item for anxiety and Patient Health Questionnaire-2 for depression). An individual’s symptoms were identified as clinically elevated if scores exceeded validated thresholds.

Results   This study included 3 028 923 respondents (mean [SD] age, 48.9 [17.0] years; 1 567 603 [51.8%] female). In multiple regression analyses that include state fixed effects and survey-week fixed effects, likely anxiety and depressive disorders among 291 382 (40%) and 238 505 (33%) of adults aged 18 to 39 years, respectively, compared with 357 820 (31%) and 274 534 (24%) of adults aged 40 to 59 years and 225 295 (20%) and 183 695 (16%) adults aged 60 years and older. Levels declined throughout the pandemic period for those aged 40 years and older but remained elevated for younger adults. Analyses identified several associated factors of these age disparities. Younger adults’ anxiety and depression increased more than older adults’ after surges in COVID-19 case counts but decreased less following vaccination against the virus. Additionally, approximately one third of the age gap among individuals with depression and anxiety was attributed to economic precarity, to which younger adults are disproportionately exposed.

Conclusions and relevance   In this cross-sectional study of anxiety and depression during the COVID-19 pandemic, economic precarity was associated with high anxiety and depression among younger adults in the US compared with older adults in the US. These findings suggest a need for greater mental health care and economic policies targeted toward younger adults.

The years from 2020 through 2022 were difficult, due to the combination of the COVID-19 pandemic and a series of national and global events that impacted people in the US and around the world. From waves of COVID-19 morbidity and mortality to protests against police violence, climate catastrophes, and mass shooting events, the COVID-19 pandemic era can be thought of as a period of chronic stress, punctuated with acute stressors. Both chronic and recent stress exposure are known factors of anxiety and depression symptoms and disorders. 1 - 3 Indeed, high levels of anxiety and depression were identified early in the COVID-19 pandemic, with reports of up to 6-fold 4 - 8 increase from prior-year levels. Most published studies focused on the initial months after the pandemic’s onset; more recent data allows us to examine whether high levels of depression and anxiety persisted across multiple years of the COVID-19 pandemic.

A concerning age disparity in symptoms and disorders of depression and anxiety emerged in the decade prior to the COVID-19 pandemic, with adolescents and young adults showing higher levels of depression and anxiety than older adults. 9 - 11 However, it is not clear whether mental health worsened early in the pandemic primarily among younger adults or throughout the adult age distribution 12 (eFigure 1 in Supplement 1 ). It is also unclear whether the age disparity widened or narrowed throughout the pandemic period and what factors might account for the age disparity or time trends.

The present study examines age disparities in symptoms of anxiety and depression across the first 2 years of the COVID-19 pandemic. To our knowledge, it is the first to examine symptoms of anxiety and depression in nationally representative data collected more recently than June 2021. We analyzed more than 3 million responses to the Household Pulse Survey (HPS) from April 2020 through August 2022, alongside weekly state-level data on COVID-19 cases and deaths. 13

Our objective was to examine whether levels of depression and anxiety in younger adults are higher than for those in middle and older adulthood and to determine whether this disparity spanned the first 2 years of the pandemic period. We investigated whether pandemic- and nonpandemic-related stress exposures measured in the HPS differed by age group and were associated with the age disparities in mental health observed. Exposures included younger adults’ economic circumstances and responses to pandemic case counts and vaccine availability. Finally, we used a decomposition analysis to quantify the proportion of the age disparity that is explained, statistically, by differences in stress exposure between age groups, vs differences in their responses (vulnerability) to these stressors. We hypothesized that anxiety and depression prevalence would be higher for younger adults than their older counterparts at the beginning of the pandemic and would fall for all age groups as vaccines became available.

This cross-sectional study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. The institutional review board at Northwestern University confirmed this study is not human participant research and waived the need for informed consent and review.

The US Census Bureau developed the HPS early in the COVID-19 pandemic. Forty-eight surveys were administered online to a mean (SD) of approximately 63 000 (13 551) respondents per survey between April 2020 and August 2022 (mean [SD], 18 [11] days) (eTable 1 in Supplement 1 ). The median (IQR) response rate was 6.4% (4.3%-7.2%) and increased slightly in later surveys. We excluded any response missing both anxiety and depression data (474 826 [13%]). While the HPS surveyed a small proportion of respondents (158 644 [5%]) multiple times, our analytic sample included only 1 response per person, retaining the first response with complete anxiety or depression data.

Respondents completed 2-item screeners, the Generalized Anxiety Disorder Screener (GAD-2) 14 for anxiety and the Patient Health Questionnaire (PHQ-2) 15 for depression. Items index how often symptoms were experienced in the past 2 weeks (0, not at all; 3, nearly every day). Responses were summed to create an anxiety score and a depression score, with totals of 3 or greater interpreted as clinically significant. 14 - 16 Analyses adjusted for respondent sex, age, race or ethnicity, education level, and income (eTable 2 in Supplement 1 ). Survey respondents were asked to self-identify their ethnicity and race, and responses were then aggregated and recoded into a combined ethnicity and race variable (White or racial and ethnic minority). This study investigated factors of inequality in Americans’ experiences of the COVID-19 pandemic. Given the US history of chattel slavery and the ongoing harms perpetuated against members of ethnically and racially minoritized groups—and their implications for health and well-being—we had reason to hypothesize that group membership might be associated with other factors examined in this study.

COVID-19 cases and deaths at the state level were obtained from the US Department of Disease Control and Prevention Case Surveillance data set. 13 Prior-week counts were computed by subtracting each state’s cumulative cases (deaths) from its prior-week figure. Values are expressed in terms of cases per 100 and deaths per 1000 residents, with state population obtained from the 2020 census. All subsequent exposures were measured at the individual level.

COVID-19–related HPS survey measures included 2 questions asking if they had ever been diagnosed with COVID-19 (1, yes; 0, no) and if they had received at least 1 dose of a vaccination against COVID-19 (1, yes; 0, no). Both questions were added to the HPS in January of 2021 (eTable 1 in Supplement 1 ).

Several variables were used to assess the extent to which a respondent is economically precarious. We use this term to refer to the uncertainty of a person’s position, which may predispose them to greater risk exposure during turbulent times. Among potential sources of precarity assessed in the HPS, an indicator variable was created to capture whether a respondent resides in a home that is owned rather than rented. An item that asked whether respondents worked for pay in the past 7 days was used as a measure of recent employment. A question about income loss initially referred to income loss experienced since the start of the COVID-19 pandemic and was updated in April 2021 to refer to the past 4 weeks. Models included a separate indicator variable for each version of this question. An alternative approach to measuring economic precarity used a composite measure (a risk score) that assigned a score of 1 for each source of precarity a respondent reported: educational attainment below a bachelor’s degree, annual household income below $35 000, living in a home that is not owned, or any income loss.

This data set was analyzed as panel data with state fixed effects and survey-week fixed effects. 17 Regression models first examined demographic differences in the prevalence of anxiety and depression. Our second set of analyses asked whether younger adults experienced more stressful conditions than those in middle or older adulthood. Here, we estimated each stressor of interest from age category in a separate regression model. The stressors examined were directly associated with the pandemic as well as economic precarity or household composition.

Next, we considered whether such stressors might be more strongly associated with anxiety or depression for young adults vs middle adults. Regression models estimated anxiety or depression from each stress exposure of interest (eg, home ownership) and the interaction between that stressor and a variable for young adulthood (home ownership under age 40 years).

Finally, we used the Blinder-Oaxaca decomposition to quantify how explanatory variables account for anxiety and depression differently between adults aged 18 to 39 years and aged 40 to 59 years. This method fits a regression model separately for each group and then separates the difference in average levels of the outcome into 2 components. The first, the endowment effect, reflects the change in the outcome that would, statistically, be expected if the 2 groups were exposed to the same conditions (ie, if 1 group took on the covariate distribution of the other). 18 The second, the coefficient effect, captures differences in the association of explanatory variables. This portion is attributed to age group differences in vulnerability to stressful conditions (and unmeasured variance, including error). 19

Analyses were conducted using Stata/MP version 17.0 (StataCorp), with sampling weights that adjust for nonresponse and yield nationally representative estimates. 20 An a priori threshold of P  <.05 was set for statistical significance. All tests were 2-sided.

We analyzed data from 3 028 923 respondents (mean [SD] age, 48.9 [17.0] years; 1 567 603 [51.8%] female; 1 926 300[63.6%] non-Hispanic White; 498 145 [16.4%] Hispanic or Latino; and 333 805 [11.0%] non-Hispanic Black). Descriptive statistics appear in eTables 2 to 3 in Supplement 1 .

Anxiety and depression were high throughout the study period, especially for young adults ( Figure 1 ). On average throughout the pandemic, clinically significant anxiety was exhibited by 40.4% (95% CI, 39.5%-41.3%) (eTable 4 in Supplement 1 ) and clinically significant depression by 36.3% (95% CI, 35.4% to 37.1%) of respondents aged 18 to 29 years. The prevalence of anxiety was approximately 4 percentage points lower for each 10-year age group ( P  <.001); depression prevalence was also lower for older age groups, with smaller gaps observed between some age categories ( Figure 1 ).

The remainder of this article presents results by 20-year age category, comparing young adults (aged 18 to 39 years) to those in middle adulthood (aged 40 to 59 years). Respondents aged 60 years and older were excluded because many are not among the working age population and likely experienced pandemic-related income disruptions differently than younger US adults.

Anxiety and depression scores and prevalence appear by 20-year age category in eTable 3 in Supplement 1 . Scores were higher for anxiety and depression among those in young adulthood compared with middle adulthood (mean [SD] anxiety score: 2.44 [2.11] vs 2.00 [2.06] and mean [SD] depression score, 2.05 [2.00] vs 1.62 [1.87], respectively; P <.001) (eTable 3 in Supplement 1 ).

Anxiety and depression were significantly more prevalent among females than males (eTable 4 in Supplement 1 ). Figure 2 shows that the age disparity in anxiety and depression was present for both White individuals and individuals from racially and ethnically minoritized groups; it was significant for both groups but larger for White individuals (eTable 4 in Supplement 1 ). Individuals with below a bachelor’s degree (BA) had significantly higher levels of anxiety and depression than those with a BA or above (eTable 4 in Supplement 1 ). Anxiety and depression prevalence also followed an income gradient. As Figure 3 shows, lower household incomes were associated with significantly greater prevalence of anxiety and depression (eTable 4 in Supplement 1 ).

Anxiety and depression are often comorbid conditions. 22 In this sample, more than half of respondents with high anxiety scores also had high depression scores (380 820 of 634 204 [60.1%] of those with any anxiety have both anxiety and depression) and more than 80% of those with high depression scores also had high anxiety scores (380 820 of 457 836 [83.2%] of those with any depression had both anxiety and depression). Figure 1 and eFigure 2 in Supplement 1 depict patterns of cooccurrence by 10-year and 20-year age groups, respectively.

The highest levels of anxiety and depression were observed early in the pandemic, with a peak in late 2020 and a pronounced decline in anxiety (and, to a lesser degree, depression) beginning in early 2021. The peak roughly coincided with the fall 2020 surge in COVID-19 cases—and the decline followed the availability COVID-19 vaccination ( Figure 2 and eFigure 3 in Supplement 1 ). This early 2021 decline was more pronounced for respondents in middle adulthood than for young adults, who exhibited persistently high levels of anxiety and depression. As a result, the age gap widened. For anxiety, it increased approximately 33% from the April 2020 to January 2021 period to the January 2021 to August 2022 period from 7.0 (95% CI, 6.51-7.46) percentage points to 9.3 (95% CI, 8.91-9.72) percentage points. For depression, it increased more than 20%, from 7.5 (95% CI, 7.08-8.00) percentage points to 9.1 (95% CI, 8.74-9.53) percentage points, throughout the same period.

Adults aged 18 to 39 years reported lower household incomes (60% the odds of earning $100 000 or more) (eTable 2 in Supplement 1 ) and lower rates of living alone than those in middle adulthood. They had approximately half the odds of residing in an owned home compared with those aged 40 to 59 years. Younger adults also had higher scores on the economic risk composite. However, the 2 groups reported similar rates of pandemic-related income loss and recent employment. Regarding COVID-19 exposure, adults aged 18 to 39 years were more likely than those aged 40 to 59 years to report that they have been diagnosed with COVID-19 (OR, 1.04; 95% CI, 1.02-1.06) and less likely to report vaccination against it (OR, 0.76; 95% CI, 0.74-0.77).

COVID-19 case counts were more strongly associated with anxiety and depression for younger adults than for older adults (eTable 5 in Supplement 1 ). However, vaccination against the virus was associated with greater improvements in mental well-being of adults aged 40 years or older compared with those aged 18 to 39 years ( Figure 4 and eTable 6 in Supplement 1 ).

Individuals who were high on the economic risk score in both age groups exhibited high levels of anxiety and depression (eFigure 4 in Supplement 1 ). There was little age-related difference in mental health among adults experiencing high levels of economic precarity (eTable 7 in Supplement 1 ).

Several additional specifications were tested to ensure our measurement of economic precarity were not associated with instability with household composition. Results confirmed that mental health was not worse among respondents who live alone or who report residing with children.

Our final analysis separates the age disparity in anxiety and depression into 2 components: the portion that can be attributed to differences that would, statistically, be estimated to disappear if the younger group had the same observable characteristics as their older counterparts, and the portion that would not. 19 Results indicate that differences in demographic characteristics, including income, accounted for approximately 20% of the age disparity in anxiety and depression (estimated separately) (eTable 8 in Supplement 1 ). This estimate would translate to an estimated 1.8 million fewer young adults in the US exhibiting clinically meaningful symptoms of anxiety or depression. In subsequent models, accounting for home ownership or the economic risk score each increased the proportion explained to more than 30%. In contrast, no reduction in anxiety or depression was estimated if younger adults took on the response of their older counterparts to infection with or vaccination against COVID-19 (eTable 8 in Supplement 1 ).

Survey responses from more than 3 million US adults suggest that high levels of anxiety and depression among young adults, which were reported in the pandemic’s first year, 4 - 6 , 8 , 23 persisted throughout the years since the onset of the COVID-19 pandemic. We observed the highest levels of anxiety and depression among adults under the age of 40 years. Our analyses offer key insights into factors of this disparity.

Additionally, we found that young adults experience more economic precarity than older adults, including lower household income and lower odds of homeownership. 24 These types of precarity are not specifically related to the COVID-19 pandemic and, for many young adults, likely predated the pandemic period. 10

Younger adults showed greater sensitivity to fluctuations in COVID-19 case counts than those aged 40 years and older. This vulnerability may be consistent with a heightened responsivity to stressors that is characteristic of adolescents and young adults. 25 This predisposition may be accentuated by the chronic and repeated episodic stressors of the pandemic. In contrast, middle adulthood was associated with vulnerability to several other exposures we examined. For instance, greater responsiveness to vaccination against the COVID-19 may help to explain the reduction in anxiety and depression that adults aged 40 years and older experienced beginning in early 2021, 6 a shift that began around when vaccines became available and persisted through 2022 but was not shared by adults aged 18 to 39 years.

Exposure to economic precarity also accounted for a substantial portion of the age disparity in anxiety and depression. In fact, adults aged 40 years and older who are economically precarious look quite similar to adults aged 18 to 39 years. This tells us that lower levels of anxiety and depression among adults aged 40 years or older may partially reflect the higher levels of economic privilege they have, on average, compared with their younger counterparts.

Decomposition analysis estimated that differences in the demographic and economic conditions to which young adults vs middle adults are exposed account for approximately one third of the age disparity in anxiety and depression. This is the portion of the age disparity that could, in theory, be reduced if younger adults instead experienced the material conditions of their older counterparts. These analyses indicate that approximately one third of the age disparity can be attributed to younger adults’ greater exposure to stressors that undermine their stability.

Across these research questions, we examined a range of potential factors that may be associated with anxiety and depression symptoms observed. We regarded certain stress exposures, like COVID-19 case counts and vaccination, as explicitly pandemic-related and others as more related to economic precarity. This categorization may imply a separation between 2 types of stress that, in reality, would be expected to influence one another. Social and economic privilege would be expected to affect a person’s odds of contracting the virus as well as their access to paid sick days or the ability to work remotely. Accordingly, our interpretation of a result like younger adults’ greater responsiveness to COVID-19 case counts (vs those aged 40 to 59 years) should reflect a possible association with concerns about the virus and concerns about economic stability (for instance, worrying that a virus surge might lead to loss of income). Moreover, even if their own risk of infection was not the primary driver of young adults’ concerns, their symptoms of anxiety and depression could stem from risks the virus poses to other loved ones. Alternatively, their symptoms may follow from other ways that pandemic surges disrupt economic activity or our social fabric (eg, increases in social isolation and the disruption of holiday gatherings or other celebrations). Finally, we cannot rule out the possibility that current events or social stressors contributed to the persistently elevated anxiety and depression observed among young adults. Data were collected across a period that included racial justice protests, mass shootings, the Russian invasion of Ukraine, decades-high inflation, and recurrent climate catastrophes, to name just a few of the period’s destabilizing events. In fact, according to the 2022 Stress in America Survey, many US adults describe a profound sense of loss and grief regarding the COVID-19 pandemic, 26 alongside worries about household finances and the economy and feelings of unease about the geopolitical events in Ukraine. 26 These sentiments suggest this period is marked by a sense of upheaval that has left a lasting impact on young adult well-being.

This study has limitations. While repeated cross-sectional surveys can provide a view on population trends throughout the pandemic, they do not follow the same set of individuals over time. This prohibits drawing conclusions about the causal impact of a change in stress exposure over time on an individual’s mental well-being. It is also worth noting that the 2 age groups we compare were surveyed simultaneously; we do not draw conclusions about how the mental health of today’s young adults will change as they get older or even as the COVID-19 pandemic period transitions into a new normal with fewer public health guidelines in place. Our comparisons concern only group differences observed during the COVID-19 pandemic period.

Online surveys like the HPS tend to have lower response rates than telephone surveys, which raises concerns that the people choosing to respond to survey invitations differ meaningfully from those who are recruited but do not respond. This type of measurement error cannot be eliminated with sampling weights. 20 We recommend relying on the HPS for the types of insights to which it is well-suited; for instance, it offers a large sample size and good temporal resolution across the pandemic. We echo the US Census Bureau’s caution that, as an experimental data product, the HPS should not be compared directly with nationwide prevalence estimates that are derived from other well-established surveys. 20 Finally, our outcome variables come from screening questions that assess symptoms of anxiety and depression for potential clinical significance; they should not be conflated with the clinical diagnosis of an anxiety or depressive disorder.

In this cross-sectional study, we document concerning levels of anxiety and depression among young adults that persisted throughout the first 2 years of the COVID-19 pandemic. More than one third of the age-related gap in anxiety and depression was attributed to differences in demographic and economic conditions between young and middle adults in the US. We find that younger adults are sensitive to fluctuations in COVID-19 case levels and speculate that they may show heightened responsiveness to other societal events that have occurred during the pandemic period. While there is more to learn about the factors that contribute to the experience younger US adult have with anxiety and depression in the current context, our findings point to a need for mental health care and economic policies that target the needs of young adults.

Accepted for Publication: October 16, 2023.

Published: November 30, 2023. doi:10.1001/jamanetworkopen.2023.45073

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Collier Villaume S et al. JAMA Network Open .

Corresponding Author: Sarah Collier Villaume, PhD, Northwestern University, 2120 Campus Dr, Annenberg Hall, Evanston, IL 60208 ( [email protected] ).

Author Contributions: Dr Collier Villaume 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: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Collier Villaume.

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

Statistical analysis: All authors.

Administrative, technical, or material support: Adam.

Supervision: Chen, Adam.

Conflict of Interest Disclosures: None reported.

Data Sharing Statement: See Supplement 2 .

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Computer Science > Computation and Language

Title: your model is not predicting depression well and that is why: a case study of primate dataset.

Abstract: This paper addresses the quality of annotations in mental health datasets used for NLP-based depression level estimation from social media texts. While previous research relies on social media-based datasets annotated with binary categories, i.e. depressed or non-depressed, recent datasets such as D2S and PRIMATE aim for nuanced annotations using PHQ-9 symptoms. However, most of these datasets rely on crowd workers without the domain knowledge for annotation. Focusing on the PRIMATE dataset, our study reveals concerns regarding annotation validity, particularly for the lack of interest or pleasure symptom. Through reannotation by a mental health professional, we introduce finer labels and textual spans as evidence, identifying a notable number of false positives. Our refined annotations, to be released under a Data Use Agreement, offer a higher-quality test set for anhedonia detection. This study underscores the necessity of addressing annotation quality issues in mental health datasets, advocating for improved methodologies to enhance NLP model reliability in mental health assessments.

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  • Published: 01 March 2024

Adherence to the nordic diet is associated with anxiety, stress, and depression in recovered COVID-19 patients, a case-control study

  • Asie Araste 1 , 2 ,
  • Mohammad Reza Shadmand Foumani Moghadam 3 ,
  • Kimia Mohammadhasani 4 ,
  • Mohammad Vahedi Fard 4 ,
  • Zahra Khorasanchi 1 ,
  • MohammadReza Latifi 5 ,
  • Elahe Hasanzadeh 5 ,
  • Nasrin Talkhi 6 ,
  • Payam Sharifan 1 ,
  • Parisa Asadiyan-Sohan 7 ,
  • Marjan Khayati Bidokhti 5 ,
  • Arezoo Ghassemi 5 ,
  • Reza Assaran Darban 7 ,
  • Gordon Ferns 8 &
  • Majid Ghayour-Mobarhan 1 , 5  

BMC Nutrition volume  10 , Article number:  38 ( 2024 ) Cite this article

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Follow-up of COVID-19 recovered patients to discover important adverse effects on other organs is required. The psychological health of COVID-19 patients may be affected after recovery.

We aimed to evaluate the association between adherence to the Nordic diet (ND) and psychological symptoms caused by COVID-19 after recovery.

Dietary data on 246 qualified adults (123 cases and 123 controls). The dietary intake in this case-control study was calculated by a reliable and valid food frequency questionnaire (FFQ). Depression Anxiety Stress Scale (DASS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Short-Form Health Survey (SF-36) were used to analyze participant’s anxiety, stress, depression, sleep quality, insomnia, and quality of life of participants.

There was a significant inverse relationship between total anxiety, stress, and depression scores and the intake of whole grains ( P  < 0.05). Furthermore, there was a significant inverse association between depression and fruit intake ( P  < 0.05). A significant negative correlation was found between insomnia and sleep quality and the intake of root vegetables ( P  < 0.05). In the multinomial-regression model, a significant association between the Nordic diet and anxiety, stress, and depression was found only in the case group (OR = 0.719, 95% CI 0.563–0.918, p-value = 0.008; OR = 0.755, 95% CI 0.609–0.934, P-value = 0.010, and, OR = 0.759, 95% CI 0.602–0.956, P-value = 0.019 respectively).

Adherence to the Nordic diet might reduce anxiety, stress, and depression in recovered COVID-19 patients.

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Introduction

Coronavirus disease 2019 (COVID-19) is an infectious disease that caused patients a wide range of physical and psychological problems [ 1 ]. Some studies noticed COVID-19 patients experience psychological and psychiatric problems after infection such as insomnia, anxiety, depression, delirium, memory loss, and loss of concentration [ 2 , 3 ]. These psychological symptoms may continue after convalescence from COVID-19 and harm the mental health of recovered patients. Impaired mental health reduces the quality of life [ 4 ], so it should be considered during hospitalization and recovery. These patients suffer from psychological sequelae after COVID-19, so it is essential to follow up patients that recovered from COVID-19 [ 5 ]. Li et al. reported that 35% of COVID-19 patients have severe to moderate psychological symptoms [ 6 ]. A systematic review found anxiety and insomnia to occurred in 35.7% and 41.9% of patients with acute SARS, falling to 12.3% and 12.1% at follow-up [ 4 ].

Dietary interventions with relatively moderate effect sizes can significantly reduce the mental and neurological disease burden through food and nutrient-based approaches [ 7 , 8 ]. ND is a “plant-based” dietary pattern that recommends protein intake from plant sources. It also recommends consumption of fruits and vegetables, whole grains, seeds, and nuts [ 9 ]. To increase protein intake, ND recommends increased the consumption of legumes and fish [ 9 ]. Along with all these recommendations, there is a limit on the use of red meat and processed foods [ 10 ]. Some studies have shown that ND has beneficial effects on psychological symptoms [ 10 , 11 ]. Therefore, it is essential to assess the diet of COVID − 19 recovered patients based on their symptoms. Nutraceutical interventions are increasingly being used in psychiatric practice [ 5 ]. Jacka et al. demonstrated impressive effects of a 3-month dietary intervention on moderate-to-severe depression with a 32% remission in the intervention group [ 12 ]. Another study of the Nordic diet reported better improvement in depression in the ND group compared to the control group [ 13 ].

Recovered COVID-19 patients faced a severely stressful experience that challenged their psychological health. It is necessary to follow up these people and control their diet to improve their impaired mental health. Considering a healthy diet can improve psychological symptoms after COVID-19. Few studies have been performed to analyse the Nordic diet on psychological disorders. In this case-control study, we attempted to investigate the association between adherence to the ND and psychological responsibility in both recovered COVID-19 patients and healthy people.

Study design

The present case-control study was performed between November 2020 to January 2021 at the clinic of Qaem Hospital, Mashhad, Iran. Adult subjects aged ≥ 30 years old who were affected by COVID-19 within the last 1 month. Participants had a negative CT scan or PCR test for COVID-19 when the interview was started. Also, we randomly selected the control group from adults > 30 years who did not have a COVID-19 history. These participants were referred to the nutrition clinic of the Qaem Hospital. Subjects who had a history of depression treatment in the last 6 months, autoimmune diseases, cancer, renal or hepatic failure, and metabolic bone disease were excluded. Adherence to a special dietary pattern such as a vegetarian diet was another exclusion criteria.

In the control group, subjects with a history of COVID-19 according to CT scan or PCR test, renal or hepatic failure, autoimmune diseases, having a history of depression treatment in the last 6 months, cancer, and adherence to a special diet were excluded. We enrolled one matched control subject for every case. Also, the case and control groups corresponded according to age and gender (± 5 years). In the present study, 246 subjects who had the eligibility criteria were recruited, of which a total of 240 subjects (120 cases and 120 controls) were encompassed in the last analysis. The mean energy of two cases and four controls were outside ± 3 standard deviation (SD), so they were excluded. All cases and control filled out noticed written agreement, and all methods were performed based on related guidelines and regulations or the Helsinki affirmation.

General and anthropometric characteristics

Demographic and anthropometric features, such as age, gender, height, weight, and education level were carried out by an expert nurse. Weight was measured by a calibrated personal scale. the fixed measuring tape was used to find out the height. Body weight (kg)/ (body height (m)) 2 was applied for calculating body mass index (BMI).

Dietary intake assessment

The food intake of patients was determined by a reliable and valid 68-item semi-quantitative food frequency questionnaire (FFQ) [ 14 , 15 ]. The FFQ was completed through face-to-face interviews. Food analysis was undertaken using Nutritionist IV software (N-Squared Computing, Cincinnati, OH, USA). Healthy Nordic Food Index (HNFI) scores were assessed based on the method of Olsen et al. [ 16 ]. To calculate the HNFI, we consider six groups with the same micronutrient amount. Daneshzad et al. [ 17 ] validated the modified ND score for the Iranian population, including (a) fish (fish conserved in oil and salt and other fish), (b) legumes (soybeans, beans, and lentils), (c) whole grains, (d) fruit (fresh and dried fruits, fruit juice) (e) root vegetables (onion, garlic, and potato) and (f) cabbages and vegetables (lettuce, tomato, cucumber, spinach, and leafy vegetables), We calculated below- and above-average intake for every item. Each group was classified based on the score obtained (scoring 0–1 points shows “low adherence”, scoring 2–3 points “medium adherence”, and scoring 4–6 points “high adherence”). ND was not given to any individuals and agreement to ND was assessed.

Depression anxiety stress scales (DASS)

Depression anxiety stress scales (DASS) are among the most valid and exact tools to analyze mental conditions [ 18 ]. It is a questionnaire that generally includes three subscales, seven questions, and 21 items. Each question score ranges from 0 to 3 on a four-point scale to recognize the severity of mental disorders, consisting of depression, anxiety, and stress. In DASS, a lower score reveals a lower degree of negative mood, and a higher score indicates a more severe degree of negative emotion. In the Iranian population, the validity and reliability of the used version of DASS in this study, have been reported formerly [ 19 ]. The anxiety, stress, and depression scores were separated into two categories: No or minimal scores and some degree of mental disorder. According to the scores obtained from each item decided as follows: (≤ 7, No), (> 7, some degree of anxiety), (≤ 14, No), (> 14 some degree of stress), (≤ 9, No), (> 9, some degree of depression)

Pittsburgh sleep quality index (PSQI)

The sleep quality of the patients was analyzed using a 19-item self-reported PSQI questionnaire that evaluates sleep quality during the last 30 days [ 20 ]. It consists of 19 objects combined for 7 component scores, containing sleep duration, sleep latency, subjective sleep quality, sleep disturbances, use of sleep medication, daytime dysfunction, and habitual sleep competence. The responses are scored on a 3-point scale, ranging from 0 to 3. The total score for sleep quality is measured by combining the 7 component scores, which range from 0 to 21. Subjects were categorized into two groups according to their PSQI score: the good-sleeper group (PSQI ≤ 5) and the poor-sleeper group (PSQI > 5). Also, the validity of the PSQI Persian version has been confirmed in 2012 [ 21 ].

Insomnia severity index (ISI)

The Insomnia Severity Index (ISI) is a seven-item self-report tool for determining patients’ insomnia symptoms and their outcomes. The aspects measured included severeness of sleep onset, interference of sleep difficulties with daytime functioning, sleep dissatisfaction, early morning awakening problems, sleep preservation, distress caused by sleep difficulties, and noticeability of sleep problems by others [ 22 ]. According to severeness, each item scored on a 0–4 scale with a full scale ranging from 0 to 28. The scoring system reports as follows: severe insomnia [ 22 , 23 , 24 , 25 , 26 , 27 , 28 ], mild insomnia [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ], sub-threshold insomnia [ 8 , 9 , 10 , 11 , 12 , 13 , 14 ], and no insomnia (0–7). In the Iranian population the reliability and validity of the Persian version of this questionnaire have been confirmed (Cronbach’s a > 0.8 and intra-class correlation coefficient > 0.7) [ 23 ].

Quality of life questionnaire

We used the Short-Form Health Survey (SF-36) validated questionnaire to analyze the general quality of life. SF-36 calculated the overall healthy quality of life based on Mental Health, General Health, Vitality, Role Emotional, Social Functioning, Body Pain, Role Physical, and Physical Functioning. Scores of this questionnaire range from 0 to 100 and the higher score shows a higher quality of life. The SF-36 was assessed in the Iranian population in a prior study and revealed construct validity and good reliability [ 24 ].

Statistical analysis

The Kolmogorov-Smirnov test was used to analyze the normality of variables. Descriptive statistics, such as SD and mean, were determined for all variables and expressed as mean ± SD for normally distributed variables and median and interquartile range (IQR) for non-normally distributed variables. Also, categorical indices were indicated by percent. We used Chi-square test and independent sample t-test to compare variables between case and control groups. For food intake comparison among two groups besides tertiles of HNFI score, a Multivariate Analysis of Variance (MANOVA) test was performed. Pearson correlation test was used to show an association between components of the Nordic diet and psychological scores. Eventually, we used multinomial logistic regression to evaluate the correlation between the classification of the adherence ND and psychological scores. Statistical package for social sciences (SPSS) version 18 (IBM Inc. Chicago, IL, USA) was used to perform statistical analyses, and rpart package in R version 4.1.2 (R Core Team. 2020). Statistical significance was considered as p-value < 0.05.

Demographic and anthropometric characteristics of the participants in case and control groups are shown in Fig.  1 . The case and control group mean age was 60.38 ± 13.61 and 57.43 ± 7.71 years, respectively (Fig.  1 c). The case group had 45% females and the control group had 45.6% females (Fig.  1 a). There were no significant differences in gender, age, weight, and BMI between case and control groups ( p  > 0.05). Nevertheless, there was a significant difference in educational level and height between the two groups ( p  < 0.05) (Fig.  1 b).

figure 1

Demographic and clinical characteristics of the participants between groups. (a) Gender, (b) Education, (c) Age, (d) Anthropometric measurements

Table  1 . demonstrates the comparison of the mean energy, macronutrients, and components of the HNFI score in classification of adherence ND between both groups. There was a significant difference in energy consumption between the case and control groups ( p  = 0.036). Regarding components of the HNFI score, there were significant differences between fruits, legumes, cabbage and vegetables, fish intakes, and classification of HNFI score in both groups ( p  < 0.05). There was a significant difference in carbohydrate and whole grain intakes between classification of adherence HNFI score in case subjects ( p  < 0.05).

Heat map (Fig.  2 ) demonstrates that there was a significant opposite association between total anxiety, stress, and depression scores and the consumption of whole grains ( r  = − 0.35; P  < 0.05, r  = − 0.36; P  < 0.05, r  = − 0.33; P  < 0.05 respectively). Furthermore, there was a significant opposite relation between depression and fruit intake ( r = -0.29; P  < 0.05). A significant negative association was observed between insomnia and sleep quality and the consumption of root vegetables ( r  = − 0.26; P  < 0.05, r  = − 0.28; P  < 0.05, respectively).

figure 2

Correlation between components of Nordic diet and psychological tests in case and control groups

Multinomial logistic regression analyses were applied to evaluate the relationship between psychological function and the Nordic diet in crude and adjusted models. As observed in Table  2 , the odds ratio was adjusted for gender, age, educational levels, and energy intake in the adjusted model. High adherence to the ND was significantly related to anxiety, stress, and depression in the adjusted model (OR = 0.759, 95% CI 0.602–0.956, P-value = 0.019; OR = 0.719, 95% CI 0.563–0.918, p-value = 0.008; OR = 0.755, 95% CI 0.609–0.934, P-value = 0.010, respectively) only in the case group.

This case-control study evaluated the relationship between adherence to the ND and psychological role in 240 adults aged ≥ 30 years old who were healthy and recovered from COVID-19. In this study, we found that more adherence to ND was related to lower odds of anxiety, stress, and depression in recovered COVID-19 patients. Regarding components of the Nordic style, only in the case group, we found a significant opposite correlation between total anxiety, stress, and depression scores and the consumption of whole grains. Also, there was a significant opposite relation between depression and fruit consumption in this group.

The relationship between dietary patterns and psychological health has been considered an important issue [ 25 ]. Multiple studies recommended consuming food sources of vitamins and fibre during COVID-19, that are rich in the Nordic diet [ 26 , 27 , 28 ]. Choosing food like fruits, vegetables, and whole grains which are rich in fibre, antioxidant, and anti-inflammatory constituents might be important in COVID-19 [ 29 ]. Brown et al. found that a diet containing mostly whole grains, vegetables, and fruits with low amounts of foods with animal sources decreased the severity of COVID-19 [ 30 ]. Another study showed that increasing the intake of fruits, vegetables, and whole grains and decreasing the consumption of red meat, processed meat, sweets, refined cereals, fried food, and sugary drinks have antidepressant effects [ 31 ]. In line with our study, a randomized controlled trial performed in 2021 showed that a healthy Nordic diet improves depressive symptoms [ 13 ]. Also, a cross-sectional study with 181 subjects, aged between 18 and 25 years old, showed that adherence to a Nordic diet with a high intake of fruits and vegetables reduces stress and anxiety scores [ 11 ]. A plant-based diet rich in fibre, resistant starch, and carbohydrates appears to be advantageous because it fills the host’s intestinal with beneficial microbes that have health benefits for COVID-19 patients [ 29 ]. Enhancing diet quality improved mood. Dietary patterns rich in omega-3 and fibre may be related to decreased symptoms of anxiety, stress, and depression [ 32 ].

People suffer from mental problems after contracting COVID-19 due to the fear of losing people and social rejection. A dietary pattern rich in vegetables and fruits plays a role in improving mental distress [ 33 ]. In this study, we revealed that more adherence to ND was associated with less odds of anxiety, stress, and depression score through recovered COVID-19 patients. Our results were in line with the findings of prior studies [ 11 , 13 ]. We concluded that depression scores were inversely associated with the consumption of fruit. Also, root vegetable consumption was correlated with insomnia and sleep quality among recovered COVID-19 patients. Root vegetable and Fruit intake improve life satisfaction and mental health. A meta-analysis consisting of 446,551 subjects, revealed that vegetable and fruit intake may play an essential function in reducing the depression risk [ 34 ]. Some studies estimated that the consumption of fruits can negatively affect mental health [ 35 , 36 ]. Liu et al. in their meta-analysis indicated that fruit intake lowered depression and anxiety symptoms [ 37 ]. Various possible mechanisms could link fruit and vegetable intake with psychological symptoms. Oxidative stress has negative effects on mental health. A large number of antioxidants in vegetables and fruits, such as beta-carotene, folic acid, vitamin E, and vitamin C reduce the harmful oxidative stress effects on mental well-being and improve depression [ 38 ]. Fruits and vegetables are rich in different minerals and vitamins like folate. Folate and vitamin B12 deficiency increase the levels of homocysteine and the risk of depression [ 39 ]. Also, magnesium deficiency may increase inflammatory factors like C-reactive protein which helps the development of depression [ 40 ].

A healthy diet and lifestyle could affect symptoms of mood disorder in recovered COVID-19 patients [ 5 , 41 ]. Inflammation caused by COVID-19 can affect neurological mechanisms, so having a healthy diet should be prioritized to prevent long-term neurological symptoms from COVID-19 [ 11 ]. Therefore, consumption of fibre and whole grains is recommended [ 42 ]. Our results revealed a significant relationship between whole grains anxiety, stress, and depression which confirms previous studies [ 43 , 44 , 45 ]. A cohort study found that regular consumption of whole grains, fruits, and vegetables is inversely related to anxiety and depression risk in elderly persons [ 6 ]. Mohammadi et al. in their randomized clinical trial study recognized a positive association between stress and anxiety and whole grains [ 44 ]. A previous study revealed that a greater intake of non-refined grains concluded to decrease depression and anxiety severeness [ 45 ]. A dietary pattern identified by high whole grain consumption was significantly connected with decreased depression risk [ 46 ]. In contrast, high consumption of refined grains was related to more depression risk [ 47 ]. Nutritional factors also have a direct and potent effect on neurophysiology [ 48 , 49 ]. Berk et al. recognized inflammation as a mediating pathway for the development of depression [ 50 ]. Evidence suggests that frequent consumption of magnesium-rich foods may improve COVID-induced inflammation. A healthy diet provides sources of magnesium. For example, whole grains are identified as one of the best sources of food due to their magnesium content [ 51 , 52 , 53 ]. Also, a previous study revealed that a dietary pattern with higher intake of whole grains, fruits, and vegetables reduces inflammation by decreasing IL-6 and CRP in plasma [ 3 ]. Whole grains are a rich source of B vitamins like Thiamine, nicotinic acid, pyridoxine, and pantothenic acid but they are not rich in folates unless fortified with folic acid. These vitamins can positively affect mental health [ 54 ]. For instance, folate and pyridoxine deficiency are effective in mental health due to their function in the synthesis of neurotransmitters for example serotonin, as well as their coenzyme role in one-carbon metabolism pathways [ 55 ].

Our study suggests that adherence to the ND may reduce anxiety, stress, and depression in patients recovered from COVID-19. A dietary pattern rich in fruit and whole grains might be beneficial in treating depressive symptoms in patients who have recovered from COVID-19. Additional large-scale longitudinal studies are essential to substantiate.

Data availability

The datasets collected and/or analyzed during the present study are not publicly accessible due to ethical concerns but the corresponding author may provide datasets upon request.

Abbreviations

  • Nordic diet

food frequency questionnaire

Depression anxiety stress scales

Pittsburgh Sleep Quality Index

Insomnia Severity Index

Short-Form Health Survey

Coronavirus disease 2019

standard deviation

body mass index

Healthy Nordic Food Index

interquartile range

Multivariate Analysis of Variance

Statistical package for social sciences

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Acknowledgements

We sincerely thank all patients participating in this study.

This study is supported by Mashhad University of Medical Sciences (grant nu: 981873).

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MGH, and ZKH initially conceptualized and designed the study. MGH contributed to obtaining the initial funding. The manuscript was written by AA, ZKH, KMH, and MVF and was reviewed by all members. PSH, NT and RAD were responsible for the design optimization and statistical analysis. EH, ML, PAS, MKHB, MSHFM, and AGH contribute sampling. GF performed English editing. All authors read and approved the final manuscript.

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Araste, A., Moghadam, M.R.S.F., Mohammadhasani, K. et al. Adherence to the nordic diet is associated with anxiety, stress, and depression in recovered COVID-19 patients, a case-control study. BMC Nutr 10 , 38 (2024). https://doi.org/10.1186/s40795-024-00845-x

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COVID-19 and Depression: Understanding the Connection

  • COVID and Depression
  • Long COVID and Depression
  • Depression After COVID
  • Other Mental Health Effects

Even after your other symptoms from COVID-19 have gone away, you might experience sadness, fatigue, and other signs of depression . Scientists are still studying how COVID can affect the brain in some people and why this may put them at greater risk of depression.  

Depression is one of the most common issues some people experience after a COVID infection, as part of long COVID —sometimes referred to as PASC (post-acute sequelae of COVID-19). According to one analysis, roughly 10% to 30% of people may still experience depression symptoms three months later, which may be severe in 3% to 12% of people.

This article explains more about the link between depression and COVID. It discusses how the virus that causes COVID directly affects the brain, other mental health effects of the pandemic, and tips on how to cope with depression after COVID.  

FG Trade / Getty Images

Is There a Link Between COVID-19 and Depression?

Although scientists were initially most concerned about COVID-19 symptoms such as shortness of breath from lung infection, the virus causing COVID-19 (SARS-CoV-2) can also affect other body systems, including your brain.  

People who have COVID have a higher rate of depression than people in the general population. You might be more prone to getting depression even after your other symptoms from COVID, like sore throat, are gone, and you no longer have an active viral infection.

People with severe COVID symptoms seem to have a greater risk of initial depressive symptoms. However, some studies have shown that people with mild COVID symptoms have a similar risk of post-COVID depression as people who had more severe infections that required hospitalization.

What’s the Link Between Long COVID and Depression? 

Long COVID broadly refers to symptoms still present at least three months after a COVID-19 infection.  

Not everyone with long COVID has the same symptoms. Some people have shortness of breath, dizziness, or pain without a clear cause. However, others have symptoms that are very common in clinical depression . Others might have mild depressive symptoms.

For example, many people with long COVID have fatigue, apathy (lack of interest), sleep problems (too much or too little), or decreased mental sharpness ( brain fog ). Many people also experience increased anxiety or sadness. In some cases, depression might be part of a long COVID syndrome, with or without additional symptoms.  

What Causes Depression in People Who Have Had COVID-19?

Scientists are still learning about what causes depression in people who’ve had COVID-19. They do know that circumstances contribute to COVID-related depression. For example, if you’ve lost income or have to cancel plans due to a COVID infection, you may naturally feel some sadness.

However, the virus that causes COVID also seems to directly affect the brain in ways scientists don’t fully understand. Other infections may also trigger syndromes that can cause symptoms like depression, like the original SARS virus or Lyme disease .

Scientists theorize that inflammation plays a role in the development of depression with COVID-19. The virus that causes COVID can trigger immune-signaling molecules that can enter the brain and affect your mood, sleep, sense of motivation, and enjoyment. Scientists think inflammation plays a role in depression, even in people who have never had COVID.

However, the link between COVID and depression is complex. The virus that causes COVID binds to specific receptors in your brain, which might worsen depression. Some scientists speculate that low levels of the virus might be present in some people with long COVID, which could contribute to depression symptoms.

Alterations in the normal immune response ( autoimmune disease ) may also play a role, but more research on the relationship between autoimmune disease, COVID, and depression is needed.  

Risk Factors

Some people seem to be at greater risk of depression after COVID. For example, women have an increased risk compared to men—which is true for depression in general, as well. People with a history of depression or other mental health issues also have an increased risk.   

Other Mental Health Effects of the Pandemic

The pandemic significantly increased rates of anxiety and depression overall, even in people who didn’t have the COVID-19. This was especially true early in the pandemic before vaccines and targeted treatments were available. Uncertainty about the virus was particularly stressful and profoundly affected people’s lives.  

The pandemic also had broader effects, which varied based on individual circumstances. Some people were grieving from losing a loved one or managing the physical challenges of regaining their health, including from long COVID.

People were also dealing with the indirect impacts of the virus, such as job and income loss, social isolation, and burnout from increased responsibilities at home and/or work. Alcohol-related deaths and rates of suicide also increased.  

Many of these trends improved as the impact of COVID lessened and disease outcomes became more predictable. Some scientists believe the overall effects on people’s mental health have been overestimated.

However, some people are still struggling with mental health issues that might have been triggered or worsened by circumstances related to the pandemic. 

How to Cope With Depression After COVID-19

Depression after COVID-19 is relatively common, and symptoms decrease with time in most people.  

If your depression is severely interfering with your life, reach out to a healthcare provider or mental health professional. It’s especially critical to do so if you are having thoughts of self-harm or suicide. They can help you determine how to best navigate this time.

If you're experiencing suicidal thoughts, call or text 988  to contact the  988 Suicide & Crisis Lifeline  and connect with a trained counselor. If you or a loved one is in immediate danger, call  911 . For more mental health resources, see the  National Helpline Database .

Even if your symptoms are less severe, getting some input from a mental health provider is often helpful. Depending on your situation and personal preferences, you might consider drug treatments for depression or therapy such as cognitive behavioral therapy (CBT).

Many people benefit from a holistic, multifaceted approach to depression treatment. Some considerations to help you cope include the following:

  • Decrease stressors : Scale back responsibilities in a way that’s practical for you (when possible).
  • Lean on your personal support network : Find ways to connect with others, even if you mostly feel like withdrawing.
  • Exercise regularly : Try to exercise in ways you enjoy, but pace yourself and don’t overdo it. It can be beneficial to get out in nature. 
  • Pay attention to your diet : Make sure you are eating enough. Try to emphasize whole foods with protein, fiber, vitamins, and minerals over heavily processed foods with lots of sugar. 
  • Prioritize sleep : If you are sleeping too much, make small goals to help get you out of bed and engaged in a task.
  • Find time for your favorite activities : Even if you don’t feel like pursuing your hobbies, sometimes the enjoyment comes back once you get started. 
  • Try mind-body or stress-reduction techniques : Approaches like tai chi, yoga, meditation, massage, guided imagery, or prayer may help. Some people report improvement from alternative approaches like acupuncture.
  • Be kind to yourself : Practice self-compassion and remind yourself that it isn’t your fault you are having a tough time. 

A holistic approach may also work best if you have depression in the context of other symptoms from long COVID. You may want to connect with a long COVID clinic (facilities specializing in long COVID care), where they can provide additional expertise and treatment approaches.  

COVID-19 causes an increased risk of depression, both during active infection and for months following. Sometimes, this is part of a broader long COVID syndrome, which might include additional symptoms like pain, light-headedness, brain fog, and fatigue. 

Social isolation and other factors surrounding COVID negatively affect many people’s mental health. But infection with the virus itself also seems to leave you more prone to depression, whether by inflammation or other unclear brain changes.

A holistic approach may work best in managing symptoms of depression related to COVID. Often, a combination of psychological therapy, medication, mind/body approaches, solid nutrition, and other lifestyle changes are needed. 

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By Ruth Jessen Hickman, MD Ruth Jessen Hickman, MD, is a freelance medical and health writer and published book author.

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A Case Study of Depression in High Achieving Students Associated With Moral Incongruence, Spiritual Distress, and Feelings of Guilt

Bahjat najeeb.

1 Institute of Psychiatry, Rawalpindi Medical University, Rawalpindi, PAK

Muhammad Faisal Amir Malik

Asad t nizami, sadia yasir.

Psychosocial and cultural factors play an important, but often neglected, role in depression in young individuals. In this article, we present two cases of young, educated males with major depressive disorder and prominent themes of guilt and spiritual distress. We explore the relationship between moral incongruence, spiritual distress, and feelings of guilt with major depressive episodes by presenting two cases of depression in young individuals who were high-achieving students. Both cases presented with low mood, psychomotor slowing, and selective mutism. Upon detailed history, spiritual distress and feelings of guilt due to internet pornographic use (IPU) and the resulting self-perceived addiction and moral incongruence were linked to the initiation and progression of major depressive episodes. The severity of the depressive episode was measured using the Hamilton Depression Scale (HAM-D). Themes of guilt and shame were measured using the State of Guilt and Shame Scale (SSGS). High expectations from the family were also a source of stress. Hence, it is important to keep these factors in mind while managing mental health problems in young individuals. Late adolescence and early adulthood are periods of high stress and vulnerabe to mental illness. Psychosocial determinants of depression in this age group generally go unexplored and unaddressed leading to suboptimal treatment, particularly in developing countries. Further research is needed to assess the importance of these factors and to determine ways to mitigate them.

Introduction

More attention needs to be paid to the psychological and societal factors which precipitate, prolong, and cause a relapse of depression in high-achieving young individuals. A young, bright individual has to contend with the pressures of -- often quite strenuous -- moral and financial expectations from the family, moral incongruence, spiritual distress, and feelings of guilt.

Moral incongruence is the distress that develops when a person continues to behave in a manner that is at odds with their beliefs. It may be associated with self-perceptions of addictions, including, for example, to pornographic viewing, social networking, and online gaming [ 1 ]. Perceived addiction to pornographic use rather than use is related to the high incidence of feelings of guilt and shame and predicts religious and spiritual struggle [ 2 - 3 ]. Guilt is a negative emotional and cognitive experience that occurs when a person believes that they have negated a standard of conduct or morals. It is a part of the diagnostic criteria for depression and various rating scales for depressive disorders [ 4 ]. Generalized guilt has a direct relationship with major depressive episodes. Guilt can be a possible target for preventive as well as therapeutic interventions in patients who experience major depressive episodes [ 5 ].

We explored the relationship between moral incongruence, spiritual distress, and feelings of guilt with major depressive episodes in high-achieving students. Both patients presented with symptoms of low mood, extreme psychomotor slowing, decreased oral intake, decreased sleep, and mutism. The medical evaluation and lab results were unremarkable. The severity of depressive episodes was measured using the Hamilton Depression Scale (HAM-D). Themes of guilt and shame were measured by using the State of Guilt and Shame Scale (SSGS). This case study was presented as a poster abstract at the ‘RCPsych Faculty of General Adult Psychiatry Annual Conference 2021.’

Case presentation

A 25-year-old Sunni Muslim, Punjabi male educated till Bachelors presented with a one-month history of fearfulness, weeping spells during prolonged prostration, social withdrawal, complaints of progressively decreasing verbal communication to the extent of giving nods and one-word answers, and decreased oral intake. His family believed that the patient's symptoms were the result of ‘Djinn’ possession. This was the patient’s second episode. The first episode was a year ago with similar symptoms of lesser severity that resolved on its own. Before being brought to us, he had been taken to multiple faith healers. No history of substance use was reported. Psychosexual history could not be explored at the time of admission. His pre-morbid personality was significant for anxious and avoidant traits. 

On mental state examination (MSE), the patient had psychomotor retardation. He responded non-verbally, and that too slowly. Once, he wept excessively and said that he feels guilt over some grave sin. He refused to explain further, saying only that ‘I am afraid of myself.’ All baseline investigations returned normal. His score on the Hamilton Depression Rating Scale (HAM-D) was 28 (Very Severe). A diagnosis of major depressive disorder was made. The patient was started on tab sertraline 50 mg per day and tab olanzapine 5 mg per day. After the second electroconvulsive therapy (ECT), his psychomotor retardation improved and he began to open up about his stressors. His HAM-D score at this time was 17 (moderate). He revealed distress due to feelings of excessive guilt and shame due to moral incongruence secondary to internet pornography use (IPU). The frequency and duration of IPU increased during the last six months preceding current illness. That, according to him, led him to withdraw socially and be fearful. He felt the burden of the high financial and moral expectations of the family. He complained that his parents were overbearing and overinvolved in his life. His family lacked insight into the cause of his illness and had difficulty accepting his current state. All these factors, particularly spiritual distress, were important in precipitating his illness. He scored high on both the shame and guilt domains (14/25, and 20/25, respectively) of the State of Shame and Guilt Scale (SSGS).

He was discharged after three weeks following a cycle of four ECTs, psychotherapy, and psychoeducation of the patient and family. At the time of discharge, his HAM-D score was 10 (mild) and he reported no distress due to guilt or feeling of shame. He has been doing well for the past 5 months on outpatient follow-up.

A 21-year-old Sunni Muslim, Punjabi male, high-achieving student of high school presented with low mood, low energy, anhedonia, weeping spells, decreased oral intake, decreased talk, and impaired biological functions. His illness was insidious in onset and progressively worsened over the last 4 months. This was his first episode. He was brought to a psychiatric facility after being taken to multiple faith healers. Positive findings on the MSE included psychomotor slowing, and while he followed commands, he remained mute throughout the interview. Neurological examination and laboratory findings were normal. His score on HAM-D was 24 (very severe). He was diagnosed with major depressive disorder and started on tab lorazepam 1 mg twice daily with tab mirtazapine 15 mg which was built up to 30 mg once daily. He steadily improved, and two weeks later his score on HAM-D was 17 (moderate). His scores on SSGS signified excessive shame and guilt (16/25, and 21/25; respectively). He communicated his stressors which pertained to the psychosexual domain: he started masturbating at the age of 15, and he felt guilt following that but continued to do so putting him in a state of moral incongruence. He perceived his IPU as ‘an addiction’ and considered it a ‘gunahe kabira’ (major sin) and reported increased IPU in the months leading to the current depressive episode leading to him feeling guilt and anguish. Initially, during his illness, he was taken to multiple faith healers as the family struggled to recognize the true nature of the disease. Their understanding of the illness was of him being under the influence of ‘Kala Jadu’ (black magic). His parents had high expectations of him due to him being their only male child. After 3 weeks of treatment and psychotherapy, his condition improved and his HAM-D score came out to be 08 (mild). He was discharged on 30 mg mirtazapine HS and seen on fortnightly visits. His guilt and shame resolved with time after the resolution of depressive symptoms and counseling. We lost the follow-up after 6 months.

Late adolescence and young adulthood can be considered a unique and distinct period in the development of an individual [ 6 ]. It is a period of transition marked by new opportunities for development, growth, and evolution, as well as bringing new freedom and responsibilities. At the same time, this period brings interpersonal conflicts and an increased vulnerability to mental health disorders such as depression and suicidality. Biological, social, and psychological factors should all be explored in the etiology of mental health problems presenting at this age [ 6 ].

Socio-cultural factors played a significant role in the development and course of disease in our patients, and these included the authoritarian parenting style, initial lack of awareness about psychiatric illnesses causing a delay in seeking treatment, high expressed emotions in the family, and the burden of expectations from the family and the peer group. The strict and often quite unreasonable societal and family expectations in terms of what to achieve and how to behave and the resultant onus on a high-scoring, bright young individual make for a highly stressful mental state. 

We used the ICD-10 criteria to diagnose depression clinically in our patients and the HAMD-17 to measure the severity of symptoms [ 7 ]. Both our patients had scores signifying severe depression initially. Psychomotor retardation was a prominent and shared clinical feature. Psychomotor retardation is the slowing of cognitive and motor functioning, as seen in slowed speech, thought processes, and motor movements [ 8 - 9 ]. The prevalence of psychomotor retardation in major depressive disorder ranges from 60% to 70% [ 10 ]. While psychomotor retardation often responds poorly to selective serotonin reuptake inhibitors (SSRI), both tricyclic antidepressants (TCAs) and noradrenergic and specific serotonergic antidepressants (NaSSA) produce a better response [ 9 , 11 ]. In addition, ECT shows a high treatment response in cases with significant psychomotor retardation [ 11 - 12 ].

A growing body of evidence shows that shame and guilt are features of numerous mental health problems. Guilt is the negative emotional and cognitive experience that follows the perception of negating or repudiating a set of deeply held morals [ 4 ]. Guilt can be generalized as well as contextual and is distinct from shame [ 13 ]. The distinction between guilt and shame allows for an independent assessment of the association of both guilt and shame with depressive disorder. As an example, a meta-analysis of 108 studies including 22,411 individuals measuring the association of shame and guilt in patients with depressive disorder found both shame and guilt to have a positive association with depressive symptoms. This association was stronger for shame (r=0.43) than for guilt (r=0.28) [ 14 ]. In our study, we used the State of Shame and Guilt Scale (SSGS), to measure the feelings of guilt and shame [ 15 ]. The SSGS is a self-reported measure and consists of 5 items each for subsets of guilt and shame. SSGS scores showed high levels of guilt and shame in both of our patients.

During the course of treatment, we paid special attention to the psychological, cultural, and social factors that likely contributed to the genesis of the illness, delayed presentation to seek professional help, and could explain the recurrence of the depressive episodes. In particular, we observe the importance, particularly in this age group, of family and societal pressure, spiritual distress, moral incongruence, and feelings of guilt and shame. Moral incongruence is when a person feels that his behavior and his values or judgments about that behavior are not aligned. It can cause a person to more negatively perceive a behavior. As an example, the presence of moral congruence in an individual is a stronger contributor to perceiving internet pornographic use (IPU) as addictive than the actual use itself [ 16 ]. Therefore, moral congruence has a significant association with increased distress about IPU, enhanced psychological distress in general, and a greater incidence of perceived addiction to IPU [ 16 ].

Self-perceived addiction is an individual’s self-judgment that he or she belongs to the group of addicts. The pornography problems due to moral incongruence (PPMI) model is one framework that predicts the factors linking problematic pornographic use with self-perceived addiction. This model associates moral incongruence with self-perceived addiction to problematic pornographic use [ 17 ]. A recent study on the US adult population also showed a high association of guilt and shame with moral incongruence regarding IPU [ 18 ]. Another factor of importance in our patients was spiritual distress, which is the internal strain, tension, and conflict with what people hold sacred [ 19 ]. Spiritual distress can be intrapersonal, interpersonal, or supernatural [ 20 ]. Research indicates that IPU causes people to develop spiritual distress that can ultimately lead to depression [ 16 - 17 ].

Conclusions

In both our cases the initial presentation was that of psychomotor slowing, selective mutism, and affective symptoms of low mood, therefore, a diagnosis of depressive illness was made. One week into treatment, improvement was noted both clinically as well as on the psychometric scales. Upon engaging the patients to give an elaborate psychosexual history, moral incongruence, spiritual distress, and feelings of guilt, linked particularly to self-perceived addiction to IPU were found. Sensitivity to the expectations of the parents, the cognizance of failing them because of illness, and their own and family’s lack of understanding of the situation were additional sources of stress. Hence, it is imperative to note how these factors play an important role in the initiation, progression, and relapse of mental health problems in young individuals. 

Acknowledgments

We are thankful to the participants of this study for their cooperation.

The authors have declared that no competing interests exist.

Human Ethics

Consent was obtained or waived by all participants in this study

COMMENTS

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