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An Exploratory Study of Students with Depression in Undergraduate Research Experiences

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

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

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

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

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

INTRODUCTION

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

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

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

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

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

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

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

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

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

Student Interviews

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

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

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

Personal, Research, and Depression Demographics

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

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

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

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

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

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

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

f Staff members included lab coordinators or lab managers.

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

Interview Analysis

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

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

The Effect of Depressive Symptoms on Undergraduate Research

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

The Effect of Undergraduate Research Experiences on Student Depression

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

Lab Environment: Relationships with Others in the Lab.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Recognize student depression as a valid illness..

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

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

Foster a Positive Lab Environment.

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

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

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

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

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

Treat Undergraduates with Respect and Remember to Praise Them.

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

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

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

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

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

Limitations and Future Directions

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

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

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

Important note

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

ACKNOWLEDGMENTS

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

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

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• Published: 13 July 2021

Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students

• Emily N. Satinsky 1 ,
• Tomoki Kimura 2 ,
• Mathew V. Kiang 3 , 4 ,
• Rediet Abebe 5 , 6 ,
• Scott Cunningham 7 ,
• Hedwig Lee 8 ,
• Xiaofei Lin 9 ,
• Cindy H. Liu 10 , 11 ,
• Igor Rudan 12 ,
• Srijan Sen 13 ,
• Mark Tomlinson 14 , 15 ,
• Miranda Yaver 16 &
• Alexander C. Tsai 1 , 11 , 17  

Scientific Reports volume  11 , Article number:  14370 ( 2021 ) Cite this article

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• Epidemiology
• Health policy
• Quality of life

University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I 2  = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I 2  = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of Ph.D. students are urgently needed.

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Introduction

Mental health problems among graduate students in doctoral degree programs have received increasing attention 1 , 2 , 3 , 4 . Ph.D. students (and students completing equivalent degrees, such as the Sc.D.) face training periods of unpredictable duration, financial insecurity and food insecurity, competitive markets for tenure-track positions, and unsparing publishing and funding models 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 —all of which may have greater adverse impacts on students from marginalized and underrepresented populations 13 , 14 , 15 . Ph.D. students’ mental health problems may negatively affect their physical health 16 , interpersonal relationships 17 , academic output, and work performance 18 , 19 , and may also contribute to program attrition 20 , 21 , 22 . As many as 30 to 50% of Ph.D. students drop out of their programs, depending on the country and discipline 23 , 24 , 25 , 26 , 27 . Further, while mental health problems among Ph.D. students raise concerns for the wellbeing of the individuals themselves and their personal networks, they also have broader repercussions for their institutions and academia as a whole 22 .

Despite the potential public health significance of this problem, most evidence syntheses on student mental health have focused on undergraduate students 28 , 29 or graduate students in professional degree programs (e.g., medical students) 30 . In non-systematic summaries, estimates of the prevalence of clinically significant depressive symptoms among Ph.D. students vary considerably 31 , 32 , 33 . Reliable estimates of depression and other mental health problems among Ph.D. students are needed to inform preventive, screening, or treatment efforts. To address this gap in the literature, we conducted a systematic review and meta-analysis to explore patterns of depression, anxiety, and suicidal ideation among Ph.D. students.

Flowchart of included articles.

The evidence search yielded 886 articles, of which 286 were excluded as duplicates (Fig.  1 ). An additional nine articles were identified through reference lists or grey literature reports published on university websites. Following a title/abstract review and subsequent full-text review, 520 additional articles were excluded.

Of the 89 remaining articles, 74 were unclear about their definition of graduate students or grouped Ph.D. and non-Ph.D. students without disaggregating the estimates by degree level. We obtained contact information for the authors of most of these articles (69 [93%]), requesting additional data. Three authors clarified that their study samples only included Ph.D. students 34 , 35 , 36 . Fourteen authors confirmed that their study samples included both Ph.D. and non-Ph.D. students but provided us with data on the subsample of Ph.D. students 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 . Where authors clarified that the sample was limited to graduate students in non-doctoral degree programs, did not provide additional data on the subsample of Ph.D. students, or did not reply to our information requests, we excluded the studies due to insufficient information (Supplementary Table S1 ).

Ultimately, 32 articles describing the findings of 29 unique studies were identified and included in the review 16 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 (Table 1 ). Overall, 26 studies measured depression, 19 studies measured anxiety, and six studies measured suicidal ideation. Three pairs of articles reported data on the same sample of Ph.D. students 33 , 38 , 45 , 51 , 53 , 56 and were therefore grouped in Table 1 and reported as three studies. Publication dates ranged from 1979 to 2019, but most articles (22/32 [69%]) were published after 2015. Most studies were conducted in the United States (20/29 [69%]), with additional studies conducted in Australia, Belgium, China, Iran, Mexico, and South Korea. Two studies were conducted in cross-national settings representing 48 additional countries. None were conducted in sub-Saharan Africa or South America. Most studies included students completing their degrees in a mix of disciplines (17/29 [59%]), while 12 studies were limited to students in a specific field (e.g., biomedicine, education). The median sample size was 172 students (interquartile range [IQR], 68–654; range, 6–6405). Seven studies focused on mental health outcomes in demographic subgroups, including ethnic or racialized minority students 37 , 41 , 43 , international students 47 , 50 , and sexual and gender minority students 42 , 54 .

In all, 16 studies reported the prevalence of depression among a total of 23,469 Ph.D. students (Fig.  2 ; range, 10–47%). Of these, the most widely used depression scales were the PHQ-9 (9 studies) and variants of the Center for Epidemiologic Studies-Depression scale (CES-D, 4 studies) 63 , and all studies assessed clinically significant symptoms of depression over the past one to two weeks. Three of these studies reported findings based on data from different survey years of the same parent study (the Healthy Minds Study) 40 , 42 , 43 , but due to overlap in the survey years reported across articles, these data were pooled. Most of these studies were based on data collected through online surveys (13/16 [81%]). Ten studies (63%) used random or systematic sampling, four studies (25%) used convenience sampling, and two studies (13%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of depression.

The estimated proportion of Ph.D. students assessed as having clinically significant symptoms of depression was 0.24 (95% confidence interval [CI], 0.18–0.31; 95% predictive interval [PI], 0.04–0.54), with significant evidence of between-study heterogeneity (I 2  = 98.75%). A subgroup analysis restricted to the twelve studies conducted in the United States yielded similar findings (pooled estimate [ES] = 0.23; 95% CI, 0.15–0.32; 95% PI, 0.01–0.60), with no appreciable difference in heterogeneity (I 2  = 98.91%). A subgroup analysis restricted to the studies that used the PHQ-9 to assess depression yielded a slightly lower prevalence estimate and a slight reduction in heterogeneity (ES = 0.18; 95% CI, 0.14–0.22; 95% PI, 0.07–0.34; I 2  = 90.59%).

Nine studies reported the prevalence of clinically significant symptoms of anxiety among a total of 15,626 Ph.D. students (Fig.  3 ; range 4–49%). Of these, the most widely used anxiety scale was the 7-item Generalized Anxiety Disorder scale (GAD-7, 5 studies) 64 . Data from three of the Healthy Minds Study articles were pooled into two estimates, because the scale used to measure anxiety changed midway through the parent study (i.e., the Patient Health Questionnaire-Generalized Anxiety Disorder [PHQ-GAD] scale was used from 2007 to 2012 and then switched to the GAD-7 in 2013 40 ). Most studies (8/9 [89%]) assessed clinically significant symptoms of anxiety over the past two to four weeks, with the one remaining study measuring anxiety over the past year. Again, most of these studies were based on data collected through online surveys (7/9 [78%]). Five studies (56%) used random or systematic sampling, two studies (22%) used convenience sampling, and two studies (22%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of anxiety.

The estimated proportion of Ph.D. students assessed as having anxiety was 0.17 (95% CI, 0.12–0.23; 95% PI, 0.02–0.41), with significant evidence of between-study heterogeneity (I 2  = 98.05%). The subgroup analysis restricted to the five studies conducted in the United States yielded a slightly lower proportion of students assessed as having anxiety (ES = 0.14; 95% CI, 0.08–0.20; 95% PI, 0.00–0.43), with no appreciable difference in heterogeneity (I 2  = 98.54%).

Six studies reported the prevalence of suicidal ideation (range, 2–12%), but the recall windows varied greatly (e.g., ideation within the past 2 weeks vs. past year), precluding pooled estimation.

Additional stratified pooled estimates could not be obtained. One study of Ph.D. students across 54 countries found that phase of study was a significant moderator of mental health, with students in the comprehensive examination and dissertation phases more likely to experience distress compared with students primarily engaged in coursework 59 . Other studies identified a higher prevalence of mental ill-health among women 54 ; lesbian, gay, bisexual, transgender, and queer (LGBTQ) students 42 , 54 , 60 ; and students with multiple intersecting identities 54 .

Several studies identified correlates of mental health problems including: project- and supervisor-related issues, stress about productivity, and self-doubt 53 , 62 ; uncertain career prospects, poor living conditions, financial stressors, lack of sleep, feeling devalued, social isolation, and advisor relationships 61 ; financial challenges 38 ; difficulties with work-life balance 58 ; and feelings of isolation and loneliness 52 . Despite these challenges, help-seeking appeared to be limited, with only about one-quarter of Ph.D. students reporting mental health problems also reporting that they were receiving treatment 40 , 52 .

Risk of bias

Twenty-one of 32 articles were assessed as having low risk of bias (Supplementary Table S2 ). Five articles received one point for all five categories on the risk of bias assessment (lowest risk of bias), and one article received no points (highest risk). The mean risk of bias score was 3.22 (standard deviation, 1.34; median, 4; IQR, 2–4). Restricting the estimation sample to 12 studies assessed as having low risk of bias, the estimated proportion of Ph.D. students with depression was 0.25 (95% CI, 0.18–0.33; 95% PI, 0.04–0.57; I 2  = 99.11%), nearly identical to the primary estimate, with no reduction in heterogeneity. The estimated proportion of Ph.D. students with anxiety, among the 7 studies assessed as having low risk of bias, was 0.12 (95% CI, 0.07–0.17; 95% PI, 0.01–0.34; I 2  = 98.17%), again with no appreciable reduction in heterogeneity.

In our meta-analysis of 16 studies representing 23,469 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of depression was 24%. This estimate is consistent with estimated prevalence rates in other high-stress biomedical trainee populations, including medical students (27%) 30 , resident physicians (29%) 65 , and postdoctoral research fellows (29%) 66 . In the sample of nine studies representing 15,626 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of anxiety was 17%. While validated screening instruments tend to over-identify cases of depression (relative to structured clinical interviews) by approximately a factor of two 67 , 68 , our findings nonetheless point to a major public health problem among Ph.D. students. Available data suggest that the prevalence of depressive and anxiety disorders in the general population ranges from 5 to 7% worldwide 69 , 70 . In contrast, prevalence estimates of major depressive disorder among young adults have ranged from 13% (for young adults between the ages of 18 and 29 years in the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions III 71 ) to 15% (for young adults between the ages of 18 and 25 in the 2019 U.S. National Survey on Drug Use and Health 72 ). Likewise, the prevalence of generalized anxiety disorder was estimated at 4% among young adults between the ages of 18 and 29 in the 2001–03 U.S. National Comorbidity Survey Replication 73 . Thus, even accounting for potential upward bias inherent in these studies’ use of screening instruments, our estimates suggest that the rates of recent clinically significant symptoms of depression and anxiety are greater among Ph.D. students compared with young adults in the general population.

Further underscoring the importance of this public health issue, Ph.D. students face unique stressors and uncertainties that may put them at increased risk for mental health and substance use problems. Students grapple with competing responsibilities, including coursework, teaching, and research, while also managing interpersonal relationships, social isolation, caregiving, and financial insecurity 3 , 10 . Increasing enrollment in doctoral degree programs has not been matched with a commensurate increase in tenure-track academic job opportunities, intensifying competition and pressure to find employment post-graduation 5 . Advisor-student power relations rarely offer options for recourse if and when such relationships become strained, particularly in the setting of sexual harassment, unwanted sexual attention, sexual coercion, and rape 74 , 75 , 76 , 77 , 78 . All of these stressors may be magnified—and compounded by stressors unrelated to graduate school—for subgroups of students who are underrepresented in doctoral degree programs and among whom mental health problems are either more prevalent and/or undertreated compared with the general population, including Black, indigenous, and other people of color 13 , 79 , 80 ; women 81 , 82 ; first-generation students 14 , 15 ; people who identify as LGBTQ 83 , 84 , 85 ; people with disabilities; and people with multiple intersecting identities.

Structural- and individual-level interventions will be needed to reduce the burden of mental ill-health among Ph.D. students worldwide 31 , 86 . Despite the high prevalence of mental health and substance use problems 87 , Ph.D. students demonstrate low rates of help-seeking 40 , 52 , 88 . Common barriers to help-seeking include fears of harming one’s academic career, financial insecurity, lack of time, and lack of awareness 89 , 90 , 91 , as well as health care systems-related barriers, including insufficient numbers of culturally competent counseling staff, limited access to psychological services beyond time-limited psychotherapies, and lack of programs that address the specific needs either of Ph.D. students in general 92 or of Ph.D. students belonging to marginalized groups 93 , 94 . Structural interventions focused solely on enhancing student resilience might include programs aimed at reducing stigma, fostering social cohesion, and reducing social isolation, while changing norms around help-seeking behavior 95 , 96 . However, structural interventions focused on changing stressogenic aspects of the graduate student environment itself are also needed 97 , beyond any enhancements to Ph.D. student resilience, including: undercutting power differentials between graduate students and individual faculty advisors, e.g., by diffusing power among multiple faculty advisors; eliminating racist, sexist, and other discriminatory behaviors by faculty advisors 74 , 75 , 98 ; valuing mentorship and other aspects of “invisible work” that are often disproportionately borne by women faculty and faculty of color 99 , 100 ; and training faculty members to emphasize the dignity of, and adequately prepare Ph.D. students for, non-academic careers 101 , 102 .

Our findings should be interpreted with several limitations in mind. First, the pooled estimates are characterized by a high degree of heterogeneity, similar to meta-analyses of depression prevalence in other populations 30 , 65 , 103 , 104 , 105 . Second, we were only able to aggregate depression prevalence across 16 studies and anxiety prevalence across nine studies (the majority of which were conducted in the U.S.) – far fewer than the 183 studies included in a meta-analysis of depression prevalence among medical students 30 and the 54 studies included in a meta-analysis of resident physicians 65 . These differences underscore the need for more rigorous study in this critical area. Many articles were either excluded from the review or from the meta-analyses for not meeting inclusion criteria or not reporting relevant statistics. Future research in this area should ensure the systematic collection of high-quality, clinically relevant data from a comprehensive set of institutions, across disciplines and countries, and disaggregated by graduate student type. As part of conducting research and addressing student mental health and wellbeing, university deans, provosts, and chancellors should partner with national survey and program institutions (e.g., Graduate Student Experience in the Research University [gradSERU] 106 , the American College Health Association National College Health Assessment [ACHA-NCHA], and HealthyMinds). Furthermore, federal agencies that oversee health and higher education should provide resources for these efforts, and accreditation agencies should require monitoring of mental health and programmatic responses to stressors among Ph.D. students.

Third, heterogeneity in reporting precluded a meta-analysis of the suicidality outcomes among the few studies that reported such data. While reducing the burden of mental health problems among graduate students is an important public health aim in itself, more research into understanding non-suicidal self-injurious behavior, suicide attempts, and completed suicide among Ph.D. students is warranted. Fourth, it is possible that the grey literature reports included in our meta-analysis are more likely to be undertaken at research-intensive institutions 52 , 60 , 61 . However, the direction of bias is unpredictable: mental health problems among Ph.D. students in research-intensive environments may be more prevalent due to detection bias, but such institutions may also have more resources devoted to preventive, screening, or treatment efforts 92 . Fifth, inclusion in this meta-analysis and systematic review was limited to those based on community samples. Inclusion of clinic-based samples, or of studies conducted before or after specific milestones (e.g., the qualifying examination or dissertation prospectus defense), likely would have yielded even higher pooled prevalence estimates of mental health problems. And finally, few studies provided disaggregated data according to sociodemographic factors, stage of training (e.g., first year, pre-prospectus defense, all-but-dissertation), or discipline of study. These factors might be investigated further for differences in mental health outcomes.

Clinically significant symptoms of depression and anxiety are pervasive among graduate students in doctoral degree programs, but these are understudied relative to other trainee populations. Structural and clinical interventions to systematically monitor and promote the mental health and wellbeing of Ph.D. students are urgently needed.

This systematic review and meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach (Supplementary Table S3 ) 107 . This study was based on data collected from publicly available bibliometric databases and did not require ethical approval from our institutional review boards.

Eligibility criteria

Studies were included if they provided data on either: (a) the number or proportion of Ph.D. students with clinically significant symptoms of depression or anxiety, ascertained using a validated scale; or (b) the mean depression or anxiety symptom severity score and its standard deviation among Ph.D. students. Suicidal ideation was examined as a secondary outcome.

We excluded studies that focused on graduate students in non-doctoral degree programs (e.g., Master of Public Health) or professional degree programs (e.g., Doctor of Medicine, Juris Doctor) because more is known about mental health problems in these populations 30 , 108 , 109 , 110 and because Ph.D. students face unique uncertainties. To minimize the potential for upward bias in our pooled prevalence estimates, we excluded studies that recruited students from campus counseling centers or other clinic-based settings. Studies that measured affective states, or state anxiety, before or after specific events (e.g., terrorist attacks, qualifying examinations) were also excluded.

If articles described the study sample in general terms (i.e., without clarifying the degree level of the participants), we contacted the authors by email for clarification. Similarly, if articles pooled results across graduate students in doctoral and non-doctoral degree programs (e.g., reporting a single estimate for a mixed sample of graduate students), we contacted the authors by email to request disaggregated data on the subsample of Ph.D. students. If authors did not reply after two contact attempts spaced over 2 months, or were unable to provide these data, we excluded these studies from further consideration.

Search strategy and data extraction

PubMed, Embase, PsycINFO, ERIC, and Business Source Complete were searched from inception of each database to November 5, 2019. The search strategy included terms related to mental health symptoms (e.g., depression, anxiety, suicide), the study population (e.g., graduate, doctoral), and measurement category (e.g., depression, Columbia-Suicide Severity Rating Scale) (Supplementary Table S4 ). In addition, we searched the reference lists and the grey literature.

After duplicates were removed, we screened the remaining titles and abstracts, followed by a full-text review. We excluded articles following the eligibility criteria listed above (i.e., those that were not focused on Ph.D. students; those that did not assess depression and/or anxiety using a validated screening tool; those that did not report relevant statistics of depression and/or anxiety; and those that recruited students from clinic-based settings). Reasons for exclusion were tracked at each stage. Following selection of included articles, two members of the research team extracted data and conducted risk of bias assessments. Discrepancies were discussed with a third member of the research team. Key extraction variables included: study design, geographic region, sample size, response rate, demographic characteristics of the sample, screening instrument(s) used for assessment, mean depression or anxiety symptom severity score (and its standard deviation), and the number (or proportion) of students experiencing clinically significant symptoms of depression or anxiety.

Risk of bias assessment

Following prior work 30 , 65 , the Newcastle–Ottawa Scale 111 was adapted and used to assess risk of bias in the included studies. Each study was assessed across 5 categories: sample representativeness, sample size, non-respondents, ascertainment of outcomes, and quality of descriptive statistics reporting (Supplementary Information S5 ). Studies were judged as having either low risk of bias (≥ 3 points) or high risk of bias (< 3 points).

Analysis and synthesis

Before pooling the estimated prevalence rates across studies, we first transformed the proportions using a variance-stabilizing double arcsine transformation 112 . We then computed pooled estimates of prevalence using a random effects model 113 . Study specific confidence intervals were estimated using the score method 114 , 115 . We estimated between-study heterogeneity using the I 2 statistic 116 . In an attempt to reduce the extent of heterogeneity, we re-estimated pooled prevalence restricting the analysis to studies conducted in the United States and to studies in which depression assessment was based on the 9-item Patient Health Questionnaire (PHQ-9) 117 . All analyses were conducted using Stata (version 16; StataCorp LP, College Station, Tex.). Where heterogeneity limited our ability to summarize the findings using meta-analysis, we synthesized the data using narrative review.

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Acknowledgements

We thank the following investigators for generously sharing their time and/or data: Gordon J. G. Asmundson, Ph.D., Amy J. L. Baker, Ph.D., Hillel W. Cohen, Dr.P.H., Alcir L. Dafre, Ph.D., Deborah Danoff, M.D., Daniel Eisenberg, Ph.D., Lou Farrer, Ph.D., Christy B. Fraenza, Ph.D., Patricia A. Frazier, Ph.D., Nadia Corral-Frías, Ph.D., Hanga Galfalvy, Ph.D., Edward E. Goldenberg, Ph.D., Robert K. Hindman, Ph.D., Jürgen Hoyer, Ph.D., Ayako Isato, Ph.D., Azharul Islam, Ph.D., Shanna E. Smith Jaggars, Ph.D., Bumseok Jeong, M.D., Ph.D., Ju R. Joeng, Nadine J. Kaslow, Ph.D., Rukhsana Kausar, Ph.D., Flavius R. W. Lilly, Ph.D., Sarah K. Lipson, Ph.D., Frances Meeten, D.Phil., D.Clin.Psy., Dhara T. Meghani, Ph.D., Sterett H. Mercer, Ph.D., Masaki Mori, Ph.D., Arif Musa, M.D., Shizar Nahidi, M.D., Ph.D., Arthur M. Nezu, Ph.D., D.H.L., Angelo Picardi, M.D., Nicole E. Rossi, Ph.D., Denise M. Saint Arnault, Ph.D., Sagar Sharma, Ph.D., Bryony Sheaves, D.Clin.Psy., Kennon M. Sheldon, Ph.D., Daniel Shepherd, Ph.D., Keisuke Takano, Ph.D., Sara Tement, Ph.D., Sherri Turner, Ph.D., Shawn O. Utsey, Ph.D., Ron Valle, Ph.D., Caleb Wang, B.S., Pengju Wang, Katsuyuki Yamasaki, Ph.D.

A.C.T. acknowledges funding from the Sullivan Family Foundation. This paper does not reflect an official statement or opinion from the County of San Mateo.  

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A.C.T. conceptualized the study and provided supervision. T.K. conducted the search. E.N.S. contacted authors for additional information not reported in published articles. E.N.S. and T.K. extracted data and performed the quality assessment appraisal. E.N.S. and A.C.T. conducted the statistical analysis and drafted the manuscript. T.K., M.V.K., R.A., S.C., H.L., X.L., C.H.L., I.R., S.S., M.T. and M.Y. contributed to the interpretation of the results. All authors provided critical feedback on drafts and approved the final manuscript.

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Satinsky, E.N., Kimura, T., Kiang, M.V. et al. Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students. Sci Rep 11 , 14370 (2021). https://doi.org/10.1038/s41598-021-93687-7

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Assessing the role of depression-related stigma in depression care in Malawi

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• Affiliation: Gillings School of Global Public Health, Department of Epidemiology
• Globally, depression is prevalent and burdensome. People with depression that hold stigmatizing beliefs related to their condition are at higher risk of never seeking treatment and/or falling out of treatment after initial engagement, posing significant risks to depression recovery. Research in the U.S. found a reduction in stigma after patients engaged in supportive counseling compared to other treatment methods for depression. There has not been much research on mental health stigma in Malawi. Therefore, using data from the Sub-Saharan Africa Regional Partnership (SHARP) for Mental Health Capacity Building scale-up trial, this dissertation expands upon ongoing depression-related implementation science research efforts in the region by exploring the role of stigma during depression care. Patients in the cohort (N=743) were largely treatment-naïve and had depressive symptoms indicated by the Patient Health Questionnaire-9. This dissertation aimed to 1) estimate the effect of baseline anticipated treatment-related stigma on the 3-month probability of depression remission and 2) estimate the association between referral to clinically appropriate problem-solving based therapy and internalized depression stigma three months later. We found that the probability of achieving depression remission at the 3-month interview among participants with high anticipated treatment-related stigma (0.31; 95% Confidence Interval [CI]: 0.23, 0.39)) was 10 percentage points lower than among patients who had low or neutral levels of anticipated treatment-related stigma (risk: 0.41; 95% CI: 0.36, 0.45; RD: -0.10; 95% CI: -0.19, -0.003). In our analysis of the effect of counseling referral on 3-month probability of having high internalized depression stigma, we found that the probability of high internalized stigma was 33 percentage points greater (95% Confidence Interval [CI]: 0.16, 0.50) among patients who were referred to counseling (0.43; 95% CI: 0.32, 0.55) compared to those who were not referred to counseling (0.10; 95% CI: -0.10, 0.30). Taken together, the results from this dissertation highlight 1) the critical role that treatment-related stigma plays in the path to depression recovery, 2) the lack of adequate solutions currently being implemented to address internalized stigma during depression treatment, and 3) the potential impact of an intervention targeting depression-related stigma among patients receiving depression care in Malawi.
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Recognizing Depression in the Elderly: Practical Guidance and Challenges for Clinical Management

Maria devita.

1 Department of General Psychology (DPG), University of Padua, Padua, Italy

2 Geriatrics Division, Department of Medicine (DIMED), University of Padua, Padua, Italy

Rossella De Salvo

Adele ravelli, marina de rui, alessandra coin, giuseppe sergi, daniela mapelli.

Depression is one of the most common mood disorders in the late-life population and is associated with poor quality of life and increased morbidity, disability and mortality. Nevertheless, in older adults, it often remains undetected and untreated. This narrative review aims at giving an overview on the main definitions, clinical manifestations, risk and protective factors for depression in the elderly, and at discussing the main reasons for its under/misdiagnosis, such as cognitive decline and their overlapping symptomatology. A practical approach for the global and multidisciplinary care of the older adult with depression, derived from cross-checking evidence emerging from the literature with everyday clinical experience, is thus provided, as a short and flexible “pocket” guide to orient clinicians in recognizing, diagnosing and treating depression in the elderly.

Introduction

Depression is one of the most common mood disorders in the late-life population. 1 , 2 The prevalence of depressive disorder in the over 60 years old population is about 5.7%. 3 However, it increases with age, to reach the peak of 27% in over-85 individuals. 1 Interestingly, the prevalence still increases and reaches the 49% in those living in communities or nursing homes, 4 , 5 regardless of the severity or the definition of depression considered. 1

Late-life depression (LLD) can be distinguished according to the age at which the first depression occurred. Early-onset depression (EOD) identifies the persistence or recurrence in old age of a depression previously diagnosed throughout adulthood, while late-onset depression (LOD) represents a depressive disorder developed de novo in old age. 6

DSM 5 identifies a cluster of depressive symptoms, namely depressed mood, loss of interest and pleasure, weight loss or gain, fatigue, insomnia or hypersomnia, psychomotor agitation or retardation, decreased concentration, thoughts of death and/or suicide and worthlessness. 3

However, LLD is characterized by an atypical cluster of symptoms, ie somatic symptoms which are predominant compared to mood symptoms, so it is important to be aware of this particular clinical presentation in order to not underestimate LLD.

Moreover, the complex spectrum of Late-Life Depression (LLD) goes beyond the main diagnostic entities of unipolar depressive disorders, such as Major Depressive Disorder (MDD) and persistent depressive disorder. 7 Relevant depressive symptoms which do not fulfill the criteria for a diagnosis of depression have nevertheless a significant clinical relevance, because of their association with poorer quality of life and increased disability; however, they are often undetected and untreated, despite a very small chance of spontaneous remission. 8

Depressive symptoms produce clinically significant distress and impairment in daily life, notching social, familiar, and occupational areas of functioning. Depression is entangled in a bidirectional relationship with somatic morbidity finally resulting in an increase in patients’ burden of disability and frailty and augmenting mortality. 9 In fact, besides being a risk factor and a predictor of poor prognosis for many conditions, like diabetes, cancer, cardiovascular diseases, dementia, 10–12 depression can be precipitated and perpetuated by chronic medical conditions typical of the aging process. A longitudinal study of 3214 healthy elderly individuals proved that Mild Cognitive Impairment (MCI), as well as smoking and mobility, vision, and subjective memory impairments, can significantly increase the risk of depression. 13

Thus, the diagnosis of depression is challenging in elderly people, since it often presents with multifaceted and more somatic symptoms compared to adults, 14 thus resembling a “real” medical organic disease. 5

Also, treatment is demanding, because of the complexity of older patients, who more frequently have a pharmacological-resistant depression and require a multidimensional and, possibly, a multi-professional equipe taking charge.

The objective of this review is, on the one hand, to explain the strong impact of geriatric depression on individual and caregivers’ quality of life and the difficulties in recognizing and prescribing the adequate treatment and, on the other hand, to propose a practical approach for the global and multi-disciplinary care of the older adult with depression, from diagnosis up to the definition of a customized treatment. In order to do so, a short and flexible “pocket” guide is here proposed as a tool to orient clinicians in recognizing, diagnosing and treating depression in the elderly. To the best of our knowledge, there is no tool currently available, such as the here proposed pocket guide, thought to be flexible and easily adaptable to the most disparate clinical contexts.

Reviewing the Literature on Geriatric Depression: Definitions, Risk and Protective Factors, Symptomatology and Clinical Variants

Geriatric depression syndrome: characterization and symptomatology.

While the depression severity appears to remain stable across the lifespan, what really differentiates depression in middle and old age concerns qualitative differences in the clinical presentation of the symptomatology ( Table 1 ).

Depression Symptoms in Younger and Older Adults: Typical and Atypical Presentation

Abbreviations : *DSM, Diagnostic and Statistical Manual of Mental disorders; **GI, gastrointestinal.

As an example, considering depressed mood (sadness or dysphoria) and loss of interest (anhedonia), which are the two core symptoms of Major Depressive Disorder (MDD) according to the DSM 5, they can be manifested differently in older adults compared younger people, 15 as well as inappropriate guilt or feelings of worthlessness. 16 Notably, regarding the first of these two core symptoms (ie depressed mood), feelings of dysphoria or sadness are frequently absent in older adults, 7 underlying a specific variant of geriatric depression indicated as “depression without sadness”, 17 characterized by lack of interest, sleep difficulties, lack of hope, loss of appetite and thoughts of death.

On the contrary, symptoms like lack of vigor and withdrawal, which are referred to the second core symptom of MDD, are usually more pronounced. In fact, “loss of interest” is usually pronounced, since older adults tend to be more apathetic. 18 Suicidal thoughts are frequent in LLD, together with state of anxiety, especially in the morning. 19

What characterizes even more LLD is a shift towards somatic symptoms, 18 which become prominent and vary in their manifestations compared to early onset depression, although the criteria symptoms remain the same. For example, while increased appetite and overeating may frequently occur in younger individuals, loss of appetite and weight are more common in late life. 20 Similarly, considering that sleep duration declines with age, decreased sleep is more common in LLD compared to hypersomnia, which is more typically experienced by younger depressed adults. 18 Fatigue is expressed both as physical tiring and lack of energy rather than a mental symptom, while the “poor concentration” symptom could be manifested more as a broader cognitive impairment where memory loss is related to executive dysfunction. 21 In general, older people manifest more vague and gastrointestinal somatic complaints, together with hypochondriasis. 22 Lastly, psychomotor retardation is more common in LLD than agitation, leading to disturbances in speech, facial expression, fine motor behavior, and gross locomotor activity, which exceed the general slowdown observed in normal aging. 23

It is therefore clear that one of the main challenges in recognizing the diagnostic features of geriatric depression is the overlap of its typical symptoms with those of other comorbid physical or neurologic conditions and, in general, with the typical signs of frailty (ie, weight loss, psychomotor slowing and exhaustion).

In fact, the somatic symptoms that in younger adults are indicative of depression, in the elderly may be correlated with aging and may not be indicative of a specific pathology, as well as could be due to other comorbid conditions. Thus, while including somatic symptoms in geriatric screening for depression regardless of their etiology (inclusive approach) may lead to false positives, 24 it remains true that they cannot be completely excluded from the diagnostic framework (as the exclusive approach, instead, proposes), as aging and its associated conditions do not necessarily justify all these aspects. An alternative is represented by the aetiological approach, in which somatic symptoms are considered only if they are not primarily due to another medical condition. 25 In general, a good clinical practice is to ask people about their mood when they refer to non-specific physical complaints, as to assess the presence of mood problems that older adults tend not to autonomously express, as previously stated.

Geriatric Depression Syndromes

Because of its peculiar features and complexity, different specific variants of geriatric depression have been proposed to better frame its presentations.

Among these, the “depletion syndrome”, 26 characterized by lack of interest, sleep difficulties, lack of hope, loss of appetite and thoughts of death, described the common condition of “depression without sadness” seen in older adults.

Another condition is referred to as “reversible dementia”. In some cases, in fact, older patients suffering from a severe depression development with marked cognitive impairment can induce the clinicians to misdiagnose dementia. 27 However, in these patients, the cognitive symptomatology recedes with the remission of depression, even if a part of them subsequently develops a proper dementia. 28 The label of “pseudodementia” this condition was addressed as, is no longer used, because of the complex relationship between depression and dementia, which represents an interaction between pathological processes, with more than one illness masquerading as another. 29

In fact, the complex entanglement involving aging-related processes, network dysfunction and depressive symptoms is also supported by the fact that two distinct syndromes regarding LOD can be recognized, ie the “depression-executive dysfunction syndrome” (DED) and vascular depression. DED 30 develops in patients whose fronto-striatal pathways are affected by aging-related or pathological changes. It is marked by psychomotor retardation, loss of interest, suspiciousness, lack of insight and pronounced disability, but rather mild vegetative symptoms and less prominent depressive ideation. 31 Moreover, individuals affected by this syndrome have impaired performance in tests of executive functioning (namely verbal fluency, response inhibition, problem solving, cognitive flexibility, working memory and ideomotor planning). 32 Vascular depression, instead, is characterized by psychomotor slowing, lack of initiative and apathy, and it is typically observed in patients with a medical history of hypertension and cognitive impairment. 31 The “vascular depression” hypothesis postulates that cerebrovascular disease may predispose, precipitate, or perpetuate some geriatric depressive disorders, 31 disrupting networks supporting affective and cognitive functions. 32

Risk and Protective Factors

The identification of factors that can increase or protect from the risk of developing depression in the elderly population is crucial in order to promote prevention strategies, but also for the best comprehensive approach to this disease. The literature has shown that suffering from a chronic disorder 4 , 33–35 or cognitive impairment, 36 having a weak social, emotional and supportive network, 5 , 37 living isolated, taking care of relatives with chronic disease, 38 losing a partner, 39 can facilitate the rising of depressive symptoms. Furthermore, gender differences, well known in younger patients, persists also into late life, so being a woman can represent a risk factor. 40 On the other hand, having a high level of self-esteem, 41 resilience 42 and sense of control, 41 keeping a healthy lifestyle 43 and having a medium/high level of cognitive reserve 44 represent protective factors for the rising of depression in elderly age. Table 2 provides a detailed overview of the main risk and protective factors involved in geriatric depression.

Risk and Protective Factors for Depression in Elderly

Recognizing Geriatric Depression in the Elderly: A Current Challenge

Depression in older adults is often under- or misdiagnosed and thus undertreated or inappropriately treated. Reasons for underdiagnosis are several and include psychosocial factors too. The first issue concerns the prejudice that depression is a normal phase of aging, because of the medical and situational conditions typical of older age, such as the limitations imposed by functional disability, health concerns and psychological stressors as decreasing social contacts, transitions in key social roles (ie, retirement) and grief. 15 Although, mood deflection is certainly understandable, it does not imply that it should be neglected, nor that it is not treatable, especially when it is a source of suffering and impairs functioning. Another barrier for depression recognition involves stigmatization. In fact, some individuals are reluctant to accept a diagnosis of depression, and often both patients and clinicians may hope to find a “medical illness” in order to avoid the stigma of a psychiatric diagnosis. 20 Moreover, older adults are less likely to express mood problems, like dysphoria or worthlessness, and may describe their symptoms in a more “somatic” way. 7 In general, older adults often find physical illness to be more acceptable than psychiatric illness. 45 At the same time, physicians may lack screening for depression because of more urgent physical problems or because they wrongly attribute depressive symptoms to comorbid medical illness. 46

In addition to underdiagnosis, another factor that contributes to undertreatment is misdiagnosis. As previously stated ( Table 1 ), in the elderly depression has an atypical presentation, including persistent complaints of pain, headache, fatigue, apathy, agitation, insomnia, weight loss, low attention and other nonspecific symptoms which can overlap with or be confused with other physical illnesses and dementia. This can lead clinicians to pursue an expensive medical workup, when they may not be able to recognize these problems as being part of a depressive episode. At the same time, older adults may relate their symptoms to a medical condition, thus not seeking the proper help. 18 Thus, it is necessary to gain insight on variability in the presentation of specific depressive symptoms across the lifespan.

Confounding Factors: Cognitive Impairment and Depression in Older Adults

Another specific challenge in the accurate diagnosis of depression concerns its entanglement with cognitive impairment and dementia. In fact, there is a substantial overlapping in the clinical presentation of late-life depression and early-stage dementia: a subjective perception of memory loss, as well as psychomotor retardation and a lack of motivation in answering at cognitive tests are typically observed in depressed older adults, and can be interpreted as signs of dementia. 47 Moreover, in older adults, depression is commonly accompanied by cognitive deficits, which are present in 20 to 50% of cases. 48 , 49 On the other hand, depressive symptoms are a common neuropsychiatric symptom of Alzheimer’s Disease (AD). 50 Still, given the prevalence of both syndromes in the older population, they can also independently co-occur, and the two diagnoses are not mutually exclusive. 36

Geriatric depression is characterized by cognitive deficits involving executive functions, such as problem solving, planning, decision-making and inhibition, along with selective and sustained attention and working memory impairment. 51 Other deficits, involving some aspects of episodic memory and visuospatial functions, may be secondary to executive dysfunction. 28 These symptoms remain significant even after the remission of the depressive symptomatology. 52 In a 10-year longitudinal study, Ly et al 53 have shown that depressed older adults perform worse than compared healthy controls in cognitive tasks, maybe for the neurotoxic effects of depression and reduced cognitive reserve.

The relationship between late-life depression and cognitive decline is even more complex, considering that, besides mimicking each other, they also can coexist and be mutually a risk factor.

On the one hand, in fact, older adults with dementia can develop pure depressive symptoms. Clinical depression in these cases can be either reactive to the diagnosis or a relapse of a previously diagnosed depression. 54 Olin et al proposed diagnostic criteria for “depression of Alzheimer’s disease”, including the presence of at least three significant depressive symptoms during the same two-week period that represents a significant perturbation from previous functioning, when all the criteria of AD are fulfilled. 55

On the other hand, Ly et al 53 found that late-onset depression, but not EOD, was associated with a more rapid cognitive decline over time. These findings suggest that EOD, whose symptoms are persistent or recurrent in old age, is a vulnerability factor that alters cognitive abilities even in healthy aging, representing a risk factor for dementia. 21 On the contrary, LOD could be a real harbinger of dementia. In particular, highly educated people are more likely to show depressive symptoms as initial presentation of dementia, probably because cognitive reserve may delay the onset of cognitive, but not depressive, symptomatology. 56

Reviewing the Literature on Therapeutic Approaches to Depression in the Elderly

The effective management of geriatric depression builds upon different strategies, involving both pharmacological and non-pharmacological options that have to be considered based on the patient’s characteristics and psychosocial environment, in order to shape a tailored and comprehensive intervention. In fact, the most effective approach is the biopsychosocial one, combining pharmacotherapy, psychotherapy and an array of lifestyle and social environment’s personalized modifications. These therapies and good practices have shown to be effective, resulting in improved quality of life, enhanced functional capacity, possible improvement in medical health status, increased longevity, and lower health care costs. 14

Pharmacological Treatment of Depression in Older Adults

Late-life depression compared with that of younger patients shows a lower response rate to antidepressants, nonetheless several treatment options exist.

When prescribing drugs, including psychotropic drugs, to older adults’ attention should be paid to pharmacokinetic and pharmacodynamic changes associated with aging. In fact, drug distribution varies, due to the increase in body fat that leads to an increasing distribution volume and elimination of half-life for lipophilic drugs. Renal filtration rate decrease enhances the problem of drug elimination. In addition, hepatic metabolism, besides being affected by aging, is also influenced by other concomitant drugs that induce or inhibit cytochrome P-450 metabolic enzymes.

In the choice of antidepressant treatment, the patient’s previous response to treatment should be considered, as well as his/her other comorbidities and medications, in order to minimize the risk of side effects and drug–drug interactions. In addition, somatic symptoms associated with depression like anxiety, psychotic symptoms, insomnia/hypersomnia, hyperphagia/poor nutrition should be considered.

The second-generation antidepressants, ie Selective Serotonin Reuptake Inhibitors (SSRIs) and Selective Norepinephrine Reuptake Inhibitors (SNRIs), are considered the first-line treatment options for depression in the elderly, because of their efficacy, 57 tolerability and safety profile. Except for paroxetine, they have lower anticholinergic effects than older antidepressants (ie tricyclics) and are thus well tolerated by patients with cognitive impairment or cardiovascular disease. SSRIs are also good for improving cognition, 58 while SNRIs are a good first choice in comorbid neuropathic pain. Most frequent SSRIs and SNRIs side effects include hyponatremia, 59 nausea and gastro-intestinal bleeding, 60 so periodic blood exams are recommended. Another second-generation antidepressant is mirtazapine that improves appetite being useful for anorexia, 61 and whose sedative side effect can be useful for insomnia. 62 A novel antidepressant, vortioxetine, a multimodal serotonin modulator, seems to be promising for elderly people since it also has a positive effect on cognition, independently of the improvement in depression. 63

When psychotic symptoms coexist, the addition of antipsychotics to antidepressants may be more effective than antipsychotics or antidepressants monotherapy, as reported by Meyers et al, 64 who found that the combination treatment of olanzapine plus sertraline was not only more effective than monotherapy but also equally tolerated.

Psychotherapy in Geriatric Depression

As for younger adults, also for older people psychotherapeutic approaches are to be encouraged, even in the presence of cognitive decline, since that treatment’s versatility gives the therapist the opportunity to adapt it to the patient’s needs and characteristics and to his/her physical and emotional environment.

In the following paragraphs a brief overview of the principal psychotherapy approaches available for older persons with depression is shortly provided.

Problem Adaptation Therapy (PATH)

PATH is a home-delivered psychosocial intervention, which has shown to lead to significant positive results in elderly with depression, by providing help in emotional regulation. 65 , 66 This kind of therapy puts the focus on strategies personalized on each patient’s needs (ie memory and organizational deficits, behavioral/functional limitations, interpersonal tension, social isolation and anhedonia). 65 PATH looks to lessen the negative impact of emotions by improving pleasurable activities, using a problem-solving approach and integrating environmental adaptations and compensatory strategies, for instance using calendars, checklists and strategies to sustain or shift attention.

Engage Therapy

This stepped therapy targets behavioral domains grounded on neurobiological constructs using simple and efficient behavioral techniques. 31 The intervention aims at modulating patient’s response using the “reward exposure” strategy, working on three main behavioral domains, ie “negativity bias” (negative valence system dysfunction), “apathy” (arousal system dysfunction), and “emotional dysregulation” (cognitive control dysfunction), and add strategies targeting these domains.

Problem Solving Therapy (PST)

PST is an 8-week intervention that consists in a seven-step process to solve problems, including problem orientation that directs patient attention to one problem at a time, problem definition that helps patients select relevant information to determine what the root problem is, goal setting that focuses attention to the desired outcome, brainstorming that helps patients consider different ways for reaching the goal, decision-making, to evaluate the alternative solutions likelihood and picking the best choice, and action planning that involves a step-by-step plan for the patient to implement his/her solution. 67

Supportive Therapy

This home-delivered psychotherapy focuses on nonspecific therapeutic factors as facilitating expression of affect, conveying empathy, highlighting successful experiences, and imparting optimism. Supportive Therapy reduces depression and disability in older patients with major depression, cognitive impairment, and disability. 65

Interpersonal Therapy

Interpersonal Therapy is a psychodynamic therapy that focuses on complicated grief, role transition, role dispute/interpersonal conflicts, and interpersonal deficits. 68 During the first phase of treatment, therapists help patients to explore and understand depressive symptoms through a psychoeducational approach. In later phases, problems are identified and understood in the interpersonal context. In the final phase, the therapist focuses on the gains and limitations of therapy and the prevention of relapses. 68

Computerized Cognitive Remediation (CCR)

CCR has demonstrated improvements in mood and self-reported function in depressed patients similar to those obtained through the Problem Solving Therapy. 81 CCR is suitable for patients with an MMSE score of at least 24/30. 68 It makes use of a video game to treat depression (EVO), personalized, self-administered and continuously adapted to the patients’ aptitude both at baseline and progress in treatment. 67 Unlike Problem Solving Therapy, the EVO participants showed generalization to untrained measures of working memory and attention, as well as negativity bias. CCR is relatively inexpensive and can be used at the patients’ homes, thus minimizing barriers to access of care, common in older adults. 31

Electroconvulsive Therapy (ECT)

An effective treatment for depression in elderly population, available from mental health specialists, is electroconvulsive therapy (ECT). 69 In ECT, an electrical stimulus is given for a brief period to produce a generalized seizure. The treatment is effective especially for psychotic depression, severe suicidality, treatment-refractory depression, catatonia, and depression with severe weight loss and anorexia, moreover, is indicated for older old (≥80 years). 70 A meta-analysis of the cognitive effects of ECT suggests its relative safety and the transient character of its effects on cognition. 71 Compared to antidepressants, ECT induces a higher speed of remission. 72

Practical Guidance for Depression Diagnosis and Treatment in the Elderly: A Pocket Guide for the Daily Clinical Management

If the proper recognition of geriatric depression remains at current challenge, the key aspects and main evidence presented here, along with a long interdisciplinary team clinical experience, lead to the identification of some guidelines to optimize the recognition and the adequate differential diagnosis of depression in the elderly. All the contents discussed below are summarized in the pocket guide, as a practical reference for a comprehensive diagnostic procedure in everyday clinical practice (see Figure 1 ).

Pocket guide for the assessment and management of geriatric depression in everyday clinical practice.

Clinicians should carefully consider depression among possible differential diagnosis, particularly when: patients refer to their attention with vague complaints as pain, fatigue and diffuse symptoms and/or suffer from anxiety or sleep disturbances; some clues are evident, such as poor personal hygiene, flat affect and slumped posture; the patient tends to frequently use healthcare resources, as calls or visits to practitioners. 46 , 48

In these cases, an accurate screening for the underlying risk factors and a collection of anamnestic data, which include medical, psychological and cognitive remote and recent history, is crucial to evaluate all potential contributing or protecting factors. Furthermore, to assess the individual’s protective factors (that mainly deal with aspects related to social network, hobbies, physical activity or personal interests) will also have a positive clinical implication in the management and treatment of depressive symptoms from a non-pharmacological point of view, by knowing the activities that could be pleasant and stimulating, as well as his or her personal resources.

Moreover, caregivers and families can be helpful, since they may provide information about the patient’s mood, behavior and general functioning. In fact, they could notice relevant changes that are not reported by the patient, especially if she or he has poor insight, as in the case of the co-occurrence of cognitive impairment.

When talking to patients, instead, it is important to adequate to the social and cultural background of older adults. As discussed in the previous sections, they are not used to deal with mental health issues and to verbally express concerns about their mood. Thus, the clinician should prefer to use expressions such as “Are you feeling low/down?” instead of directly asking “Are you depressed?” in order to address the stigma, and discuss mental health referral in the broader context of other medical conditions to increase the acceptability. 38 At the same time, all the healthcare professionals should promote the sensitization of the elderly to mood disorders and more generally to mental health, so that they can themselves become more attentive and aware in recognizing their emotional and psychological difficulties.

Clinicians can count on several validated tools to quantitatively assess the presence and severity of depression, namely self-report scales, clinician rating scales and structured interviews. Despite their popularity and their clear advantages, some considerations have to be taken into account when dealing with older adults. First of all, these tools were mostly developed for young adults, so they do not always catch the appropriate features for the elderly. 73 This also falls on their validity and reliability, which are strictly related to the population they are based on. 74 Self-reports are widely used because of their quickness and ease of administration. However, they are susceptible to some respondent’s characteristics, such as low educational attainment or cognitive impairment, which can influence the true comprehension of questions or of the response format. 75 In general, in the case of older adults with cognitive impairment, it is preferable to avoid self-reports and use alternative assessment methods that include direct observation and family reports. 7 Moreover, especially for patients with comorbidities, items with somatic content may need further clarifications, since somatic symptoms could be misattributed to depression. 76 Lastly, visual impairment can obstacle the completion of self-report scales: in these cases, the clinician can either propose an enlarged copy of the scale or administrate it orally. The use of clinician rating scales overcomes some of these issues, since they are based on the direct observation of a trained professional. If clinician rating scales offer a more accurate measurement of depression, it has been found that they are less sensitive in detecting changes in mild forms of depression. 77 Structured interviews offer the possibility to facilitate the comprehension of questions, as well as to deeper investigate aspects that need to be better clarified, as the nature of somatic symptoms; however, because of the time and skills requested for their administration, their utility is limited. 78 Overall, there is no single superior assessment method; rather, it is important that clinicians are aware of their strengths and shortcomings and informed about the psychometric properties of the main tools, so that they can choose the most appropriate instrument depending on the characteristics of the individuals. Moreover, using multiple methods and sources of information (ie, multidimensional assessment) has been shown to be the most effective approach. 78

When depressive symptoms are detected and a diagnosis of LLD is probable, among all the other factors, also the domestic and family context has to be looked at, that is, whether there are dynamics that can exacerbate the depressive symptomatology of the patient. This could be the case, for example, of a dysfunctional interaction in the patient-caregiver dyad or of some psycho-affective characteristics of the caregiver himself (for example, if he or her is depressed as well), likewise tensions in family relationships or other health or financial issue of relevant psychological impact.

Lastly, it is important to exclude somatic causes of depression and to characterize a depressive episode or symptoms through patient history, clinical examination, laboratory tests, and/or imaging. In fact, LLD can per se be distinguished into a proper LOD or the recurrence of an EOD and, as stated, this has some clinical implications. Alternatively, depression can be secondary to a general medical condition or to a substance or medication use, considering that multimorbidity and polypharmacy are extremely common conditions among older adults. 79 Moreover, depressive symptoms could be the manifestation of a cerebrovascular disease or of a prodromal stage of AD, thus having a primarily organic origin. It is also important, in any case, to repeat when possible both the instrumental examinations (namely imaging techniques for the investigation of regional brain glucose metabolism, as FDG-PET) and the administration of cognitive and/or psychological screening tools in order to re-evaluate the overall diagnosis at a follow-up after 6–9 months. In fact, since LLD is a treatable and reversible condition, when a diagnosis of depression is made and a pharmacological or non-pharmacological treatment has been proposed, there should be evidence of efficacy. Otherwise, the question arises if the depressive symptoms observed were secondary to another cause (so, the diagnosis was incorrect) or the therapeutic approach chosen was not the most suitable one.

Depression and Cognitive Impairment: How to Address Differential Diagnosis?

Whereas depressive and cognitive disorders often coexist in the elderly, it is crucial to distinguish a geriatric depression that includes cognitive deficits from a mild dementia with depressive symptoms. What needs to be determined from a clinical point of view, in particular, is whether or not the picture observed will evolve into dementia.

Time is a first important criterion: while in the case of dementia symptoms will develop with a slow progression over several years, depressive symptomatology onset can be dated with more precision and the progression of symptoms is more rapid. 48 , 80 Another relevant cue concerns awareness. Patients with reversible dementia complain more about their cognitive disturbances, highlighting their failures and disability and precisely describing the pattern of their deficits; older adults with dementia, on the contrary, usually lack insight and their description of cognitive loss is vague. 80

From a neuropsychological point of view, evidence has been described about a different characterization of cognitive profiles of patients with AD and depression that can be striking in the differential diagnosis.

First of all, patients with LLD show a prominent dysexecutive profile, with a slight impairment in global cognition. 21 Conversely, a broader cognitive impairment, with significant deficits of orientation, language, praxis and memory is typical of AD. 81 Secondly, although a memory disturbance is visible in both AD and LLD, they have a different functional origin. The episodic memory impairment of AD, due to hippocampal damage, is defined by a recall deficit that does not improve with cueing or recognition testing, since storage processes are primarily affected. 82 Depression, instead, leads to an insufficient allocation of attentional resources and executive dysfunction that affect encoding or retrieval strategies, 83 without a pure storage deficit. Thus, a differential diagnosis can be made with specific memory testing based on effective and specific encoding of information and retrieval facilitation with cueing. 82 Inefficacy of cueing and a flat learning curve despite exposure is typical of AD, while an improvement with exposure and a normal recall with retrieval cues are distinctive features of depression. 36

In general, patients with depression have a suboptimal cognitive performance due to poor motivation that leads them to give up the task more easily, not pay enough attention and use ineffective strategies, so their overall performance is more influenced by the cognitive load of the task and the extent to which it relies on executive functions. 83

In addition to all the steps that have to be gone through, and the factors that have to be taken into account for a comprehensive assessment that includes depression among the differential hypothesis, some general guidelines are here suggested about organizational aspects that can be implemented to improve the detection of depressive symptoms in the elderly.

First, given the predominance of somatic symptoms in late-life depression, as well as their tendency to focus more on their physical (rather than mental) issues, it is plausible that older adults who suffer from depression do not spontaneously refer to a mental health professional at first, but to other figures, such as general practitioners, physicians or other health professionals. For this reason, it would be important to improve the knowledge about late-life depression presentation, as well as the capacity to carry out screening activities, of specialists of other disciplines. In fact, although a formal diagnosis of depression is not part of their role, they could improve the detection of potential cases because of their position, as it is the case of occupational and physical therapists, nurses or general practitioners. 45

Furthermore, different professional figures, as psychiatrists, geriatricians, psychologists and neuropsychologists, often have to interface with older adults’ depressive symptoms in the presence of multimorbidity and/or cognitive deficits, and thus answer questions concerning the differential diagnosis of depression. It is of paramount importance for each specialist to evaluate individuals in their whole complexity. In this regard, a multidimensional assessment should always be provided, in order to take into account all the aspects discussed above, such as risk and protective factors, medical and psychological history, social context and recent life events. Moreover, when appropriate, specialists should choose a multidisciplinary approach, referring patients to other professionals that can have a role in the differential diagnosis or in identifying the most appropriate therapeutic option. When possible, it would be a valuable resource for figures with different and complementary competences to work together.

For example, in the specific case of older adults with depressive symptoms with a subjective perception or signs of cognitive impairment, geriatricians and neuropsychologists could manage outpatient visits and consultations in wards together, considering the tangled characteristics of LLD discussed above. In this way, these professional figures can provide a first screening of cognitive functioning and the characterization of some deficits that will help in the differential diagnosis between depression and dementia. Moreover, this synergy can help to consciously investigate the presence of a mood disorder and, where necessary, to offer to the patient a more accurate psychological and cognitive assessment, targeted medical investigations and therefore a tailored treatment.

In case older adults are aware of having a mood problem, they mainly refer to the psychiatrist. Notwithstanding the crucial role and competence of psychiatrists in this context, it is still important for them to consider older adults in their whole complexity. In this regard, they should provide a multidimensional assessment that takes into account all the aspects previously stated (ie, risk and protective factor, medical and psychological history, social context, recent life events…) and, when appropriate, have a multidisciplinary approach, referring patients to other professionals that can have a role in the differential diagnosis or in identifying the most appropriate therapeutic approach.

Another professional figure that frequently has to cope with the differential diagnosis of depression are geriatricians, since in their clinical practice they consult with patients who show signs or have a subjective perception of cognitive or neuropsychiatric problems. Both in outpatient visits and in consultations in wards, it could be a valuable resource for the geriatricians to be assisted by a neuropsychologist. For the characteristics of LLD discussed above, it would be beneficial for patients if the geriatrician and the psychologist/neuropsychologist could work together in the assessment of older adults, both for the outpatient visits and for the consultation inwards.

In this way, these professional figures can synergistically provide a first screening of cognitive functioning and the characterization of some deficits that will help in the differential diagnosis between depression and dementia. Moreover, it can help to consciously investigate the presence of a mood disorder and, where necessary, to offer the patient a more accurate psychological and cognitive assessment, targeted medical investigations and therefore a tailored treatment.

In conclusion, as a general indication, it is overall important to periodically screen older adults for depression. Furthermore, patients who already are in treatment for depression need to be periodically re-evaluated, since the persistence of a depressive symptomatology suggests that the therapeutic approach chosen (pharmacological or not) should be revised.

Conclusions

This review, beyond reviewing depression, its clinical main characterizations and current challenges had the goal to propose a few guidelines born from the “every-day” clinical activity carried-out on this population. A “pocket guide” has been produced in order to hopefully orient clinicians in their daily clinical management of depression and in sensitizing different professionals to a comprehensive, global and multidisciplinary assessment of a complex disorder affecting complex individuals such as the elderly are. Shortly, after a first multidimensional assessment, clinicians are provided with clinical cues orienting their diagnostic process. Whereas the diagnosis of depression is confirmed, by also excluding other co-occurrent/different pathologies (ie cognitive decline), a first- and second-line therapeutic approaches are suggested, including both pharmacological and non-pharmacological options. Lastly, follow-ups and periodic clinical assessments are strongly recommended to monitor individuals over time.

Finally, by considering not only the risk, but also the protective factors that may help people in facing depression along late life, this review also indirectly encourages clinicians in promoting active social, cognitive and psycho-affective lifestyles in the elderly, as crucial, modifiable factors that may significantly influence the natural course of their aging.

The authors report no conflicts of interest in this work.

Psychische Spät- und Langzeitfolgen einer Krebserkrankung

Psychological late and long-term effects of cancer

• Published: 02 March 2021
• Volume 27 , pages 753–758, ( 2021 )

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• Heide Götze 1  

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Zusammenfassung

Hintergrund.

Viele langzeitüberlebende Krebspatienten leiden auch mehrere Jahre nach Abschluss der Akutbehandlung unter psychischen Belastungen.

Ziel der Arbeit

Der Beitrag gibt einen Überblick zu den psychischen Spät- und Langzeitfolgen nach Krebs und dem bisherigen Forschungsstand. Ergebnisse einer Befragung von 1000 langzeitüberlebenden Krebspatienten werden vorgestellt und diskutiert.

Material und Methoden

In einer registerbasierten Kohortenstudie an der Medizinischen Fakultät der Universität Leipzig wurden etwa 1000 Menschen hinsichtlich Depressions- und Angstsymptomatik (Patient Health Questionnaire, PHQ-9/General Anxiety Disorder, GAD-7) sowie Progredienzangst (Fear of Progression Questionnaire, FoP-SF) befragt, bei denen die Krebsdiagnose 5 bzw. 10 Jahre zurücklag.

Mittlere bis starke depressive bzw. Angstsymptomatik zeigten 17 % bzw. 9 % der langzeitüberlebenden Krebspatienten. Folgende Faktoren waren am stärksten mit Depressivität und Ängstlichkeit assoziiert: jüngeres Alter, weibliches Geschlecht, finanzielle Probleme, geringe Lebensqualität und kognitive Defizite. Vor allem Patienten, die jünger als 70 Jahre alt waren, waren depressiver und ängstlicher als die Vergleichsgruppe der Allgemeinbevölkerung. Eine hohe Progredienzangst gaben 17 % der langzeitüberlebenden Krebspatienten an. Die größten Sorgen betrafen die Zukunft der Familie und bevorstehende Arzttermine.

Schlussfolgerung

Die psychischen Spät- und Langzeitfolgen einer Krebserkrankung und -behandlung bedeuten nicht nur persönliches Leid für die betroffene Person, sondern sind auch für unser Gesundheitssystem von enormer Bedeutung. Es ist wichtig, betroffene Patienten frühzeitig zu identifizieren und ihnen angemessene Unterstützung anzubieten.

Many long-term cancer survivors suffer from psychological distress even several years after completing acute treatment.

The article gives an overview of the psychological late and long-term consequences after cancer and the current state of research. Results of a survey of 1000 long-term cancer survivors are presented and discussed.

Materials and methods

In a register-based cohort study at the Medical Faculty of the University of Leipzig, around 1000 people were asked about symptoms of depression and anxiety (Patient Health Questionnaire, PHQ-9/General Anxiety Disorder, GAD-7) and fear of cancer recurrence (Fear of Progression Questionnaire, FoP-SF), who were diagnosed for cancer 5 and 10 years ago.

In all, 17 and 9% of long-term cancer survivors showed moderate to severe depressive or anxiety symptoms. The following factors were most strongly associated with depression and anxiety: younger age, female gender, financial problems, limited quality of life and cognitive deficits. In particular, patients younger than 70 years of age were more depressed and anxious than the comparison group in the general population. A high fear of cancer recurrence was reported by 17% of long-term cancer survivors. The main concerns were about the family’s future and upcoming doctor’s appointments.

Conclusions

The psychological late and long-term consequences of cancer not only mean personal suffering for the individual, but are also of great importance for our healthcare system. It is important to identify patients at high risk early and offer them adequate support.

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Götze, H. Psychische Spät- und Langzeitfolgen einer Krebserkrankung. Onkologe 27 , 753–758 (2021). https://doi.org/10.1007/s00761-021-00924-9

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Accepted : 08 February 2021

Published : 02 March 2021

Issue Date : August 2021

DOI : https://doi.org/10.1007/s00761-021-00924-9

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