Department of Psychology
Department of Psychology

Christopher G Beevers


ProfessorPh.D., University of Miami

Professor and Director of the Institute for Mental Health Research
Christopher G Beevers

Contact

  • Phone: (512) 232-3706
  • Office: RLP (formerly CLA) 4.528
  • Campus Mail Code: E9000

Interests


Etiology, maintenance, and treatment of unipolar depression in adults

Biography


Christopher Beevers is the Wayne H. Holtzman Regents Chair in Psychology. Dr. Beevers received his doctorate in adult clinical psychology from the University of Miami in 2002. His clinical internship and postdoctoral fellowship were completed in the Department of Psychiatry and Human Behavior at Brown University. Dr. Beevers' primary research interest focuses on the cognitive etiology and treatment of major unipolar depression. He believes that understanding normal cognitive processes provides an important foundation for identifying how these processes go awry in clinical depression. Further, he is very interested in using experimental psychopathology methods to understand why treatments work and translating these same methods into effective interventions for depression and related psychopathology (e.g., anhedonia, negative affect). Dr. Beevers is particularly interested in the interplay between biology and cognitive risk and maintaining factors for depression. Current projects utilize behavioral, eye tracking, and EEG methodologies to measure cognitive bias combined with smartphone methods to measure affect and behavior in its natural environment. He collaborates with numerous faculty at UT, nationally, and internationally. He is also an award-winning teacher, as he received the Silver Spurs Centennial Teaching Fellowship (2018) and the Raymond Dickson Centennial Endowed Teaching Award (2017) from the University of Texas at Austin. He also occasionally boasts about himself in the third person on his faculty profile page. Please see this brief video for more information about Dr. Beevers' work. 

See his Google Scholar or ORCID profiles for more information about his work.

Dr. Beevers does not plan to review graduate student applications to his laboratory for admission in Fall of 2020. See Info for Prospective Students for further detail.

Courses


PSY 352 • Abnormal Psychology

42010 • Spring 2020
Meets TTH 11:00AM-12:30PM

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

42570 • Spring 2019
Meets TTH 2:00PM-3:30PM JES A121A

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

42774 • Spring 2018
Meets TTH 11:00AM-12:30PM RLM 5.104

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

42330 • Fall 2015
Meets MWF 11:00AM-12:00PM NOA 1.126

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

42710 • Spring 2015
Meets TTH 12:30PM-2:00PM CLA 0.126

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

44100 • Spring 2014
Meets TTH 3:30PM-5:00PM CLA 0.130

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

43355 • Fall 2012
Meets TTH 11:00AM-12:30PM NOA 1.124

The main goal for this course is to provide broad exposure to descriptive psychopathology (i.e., the symptoms, signs, and clinical course) and treatment of the major psychiatric disorders. A scientific and empirical approach to this material is emphasized.

PSY 352 • Abnormal Psychology

43310 • Spring 2012
Meets TTH 11:00AM-12:30PM NOA 1.124

The main goal for this course is to provide broad exposure to descriptive psychopathology (i.e., the symptoms, signs, and clinical course) and treatment of the major psychiatric disorders. A scientific and empirical approach to this material is emphasized.

PSY 352 • Abnormal Psychology

43235 • Fall 2011
Meets TTH 11:00AM-12:30PM NOA 1.124

The main goal for this course is to provide broad exposure to descriptive psychopathology (i.e., the symptoms, signs, and clinical course) and treatment of the major psychiatric disorders. A scientific and empirical approach to this material is emphasized.

PSY 352 • Abnormal Psychology

43195 • Fall 2010
Meets TTH 11:00AM-12:30PM WEL 1.308

Prerequisites

Upper-division standing required. PSY 301 and PSY 418 or an equivalent with a grade a grade of at least C in both.

Course Description

The main goal for this course is to provide broad exposure to descriptive psychopathology (i.e., the symptoms, signs, and clinical course) and treatment of the major psychiatric disorders. A scientific and empirical approach to this material is emphasized.

Grading Policy

Three (3) exams will be given during the semester. Each exam will contribute to 30% of your final grade. Exams thus make up 90% of your grade. Each exam will consist of approximately 60 multiple choice and/or matching questions. An optional, cumulative final exam will be offered during the final exam period. The optional final exam will include material that is covered throughout the semester. The optional final exam can be substituted for one (1) exam during the semester.

There will also be one required writing assignment. For this assignment, you will write about a specific issue/controversy in an area of clinical psychology. You will be given a list of writing assignments and reference material to choose from at the beginning of the semester. This writing assignment counts toward 10% of your grade.

Texts

Barlow, D. H., Writing & Durand, V. M. (2005). Abnormal Psychology: An integrative approach. 4th edition. Wadsworth: Belmont, CA.

PSY 352 • Abnormal Psychology

44285 • Fall 2008
Meets TTH 9:30AM-11:00AM BUR 208

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

45130 • Fall 2007
Meets TTH 9:30AM-11:00AM ECJ 1.202

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

44895 • Fall 2006
Meets TTH 9:30AM-11:00AM ECJ 1.202

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 352 • Abnormal Psychology

43070 • Spring 2006
Meets TTH 9:30AM-11:00AM BUR 108

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 394Q • Research Meths In Clinical Psy

43245 • Spring 2006
Meets TH 2:00PM-5:00PM SEA 5.106

Seminars in Clinical Psychology. One or three lecture hours a wekk for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

PSY 352 • Abnormal Psychology

43050 • Fall 2005
Meets TTH 9:30AM-11:00AM GRG 102

Biological and social factors in the development and treatment of psychopathology. Three lecture hours a week for one semester. Prerequisite: For psychology majors, upper-division standing and Psychology 301 and 418 with a grade of at least C in each; for nonmajors, upper-division standing, Psychology 301 with a grade of at least C, and one of the following with a grade of at least C: Biology 318M, Civil Engineering 311S, Economics 329, Educational Psychology 371, Electrical Engineering 351K, Government 350K, Mathematics 316, 362K, Mechanical Engineering 335, Psychology 317, Sociology 317L, Social Work 318, Statistics 309, Statistics and Scientific Computation 302, 303, 304, 305, 306, 318.

PSY 394Q • Research Meths In Clinical Psy

41740 • Spring 2005
Meets TH 2:00PM-5:00PM SEA 3.250

Seminars in Clinical Psychology. One or three lecture hours a wekk for one semester. May be repeated for credit when the topics vary. Prerequisite: Graduate standing and consent of instructor.

Teaching Statement


Statement of Teaching Philosophy

October 1, 2018

My overarching goal for teaching is to engage students in their coursework so that they can become well-informed consumers of psychological science who are able to think critically and independently about the material. To meet this goal, I keep my lectures up-to-date and supplement textbook material with the latest research findings. I focus on material that is firmly grounded in theory and challenge students to identify the strengths and weaknesses of the evidence that supports or opposes each theory. When weaknesses are identified, I ask students how they would improve upon existing work and we share our views on important next steps for the field. Based on these discussions, I strongly encourage students to develop hypotheses and to empirically pursue their ideas by developing their own research projects whenever possible.

I use several methods to engage students in their coursework. First, I strive to present material in an organized and clear manner. To accomplish this, I prepare extensively and offer clear definitions with concrete examples. I frequently use film clips to illustrate my points and to emphasize the clinical presentation of disorders we cover in class. I also provide students with all the PowerPoint slides I use in class. In my undergraduate class, I use lecture capture software to record my lectures and make them available to students to review. This way, I hope students are better able to think about the material that is being presented in class rather than frantically writing down everything that I say during the lecture.

Second, my lectures are grounded in the science of psychology. During class, I attempt to excite students about topics, issues, and questions at the cutting edge of our science. This often involves a thorough examination of particularly influential classic and contemporary research. Furthermore, when discussing the treatment of psychiatric disorders, I adopt a scientist-practitioner perspective and demonstrate how psychological science can inform our understanding of mental disorders. 

Third, I encourage students to engage with class material in a manner that promotes critical thinking about assigned topics. For instance, in the graduate research methods class, I start most classes with a group discussion about assigned readings. I also encourage students to relate the material to their own research and experiences. Prior to the class, I provide students with target questions specifically designed to facilitate critical thinking. In my undergraduate abnormal psychology class, I quiz students frequently to further reinforce learning. Students are also required to diagnose and develop a treatment plan for fictional case studies based on material presented in class. I believe applying information learned in class to new contexts strongly facilitates learning.

Fourth, I strongly encourage students to become involved in psychological research at all levels, from participating in experiments, as well as conducting and designing them, to writing up and publishing new findings. This is particularly relevant for the doctoral students that I advise; however, I encourage undergraduate students to get involved in research as well. This is one reason why approximately 5 - 10 undergraduates volunteer in my laboratory in any given semester.

Finally, I take mentoring of students (both graduate and undergraduate) in my lab very seriously. I work hard to cultivate similar levels of enthusiasm I have for research in those that I advise. I believe it is critically important that students are excited about research questions they investigate; otherwise, research can become very tedious. Therefore, I try to be as flexible as possible when students pursue projects that are not directly related to my own research interests. This philosophy has allowed me to learn about areas of research that I would not have otherwise been exposed to. I also adapt my mentoring style to each student, providing as much structure and supervision as needed. I meet with some students on a weekly basis, whereas others need far less direct supervision. I have high expectations for my students but at the same time, I try to provide them with opportunities and support needed to be successful. I aim to do this in a nurturing and collaborative way, treating them as junior colleagues when appropriate. Throughout this process, I work with students to clarify their goals so they can leave our program as accomplished and successful researchers of the human condition.

In recognition of my teaching, I was recently awarded the Raymond Dickson Centennial Endowed Teaching Award from the College of Liberal Arts. This award recognizes sustained teaching excellence at the undergraduate level among faculty within the College of Liberal Arts. I was one of two faculty members selected from within the college to receive this honor. This year I have been nominated by the college for a university-wide teaching award, the President's Associates Teaching Excellence Award. Even if I do not go on to win this latter teaching award, it is humbling to receive this recognition, as I know firsthand that our college is filled with many outstanding faculty and teachers.

Research Statement


Statement of Research Interests

October 1, 2018

My primary research interest involves testing cognitive theories of depression, often leveraging models and methods from studies of normal behavior to understand how these processes go awry in clinical depression. I also believe that to develop comprehensive etiological models of depression, it is necessary to incorporate multiple perspectives. By studying mechanisms across units of analyses (genetic, neural, cognitive, environmental), we may be able to develop more comprehensive models of depression and significantly enhance our understanding of this debilitating disorder. To this end, I use experimental psychopathology methods to manipulate cognitive biases thought to maintain depression. Such work holds the promise to identify causal mechanisms and simultaneously point to interventions that can improve depression. Finally, I am also interested in identifying who is most likely to respond to treatments so that we can begin to move towards personalized treatment algorithms. Below I describe my research interests in more detail, briefly highlighting findings and emphasizing near-term future directions for my work.

Cognitive theories of depression posit that cognitive biases are a causal agent in the disorder (1,2). However, relatively few strong empirical tests of this claim have been completed leading some to speculate that negative cognition is an epiphenomenon of the disorder. My research suggests that dysfunctional thinking does indeed fluctuate with mood state, but also remains relatively stable over long periods of time (3). Further, our taxometric work suggests that cognitive vulnerability should be conceptualized as dimensional rather than categorical (4). In other words, dysfunctional thinking is present to a greater or lesser extent in all individuals. In longitudinal studies, we have documented that negative cognitive bias is present before an episode of depression (5,6) and predicts who is likely to remain depressed (7). Negative cognitive biases can remain elevated following symptomatic recovery (8), increasing the risk for future episodes (9).

Further, most prior work in the area of depression and negative cognition has been correlational. Although this provides an important and valuable foundation, I think a critical future direction is to develop interventions that precisely target and reverse negative cognitive biases and improve subsequent symptoms (10). Examples of this work include our effort to reverse negative attention bias with attention bias modification (11). In a recent study, we demonstrated that attention bias modification reduced negative attention bias, improved resting state connectivity in brain regions shown to support negative attention bias, and improved subsequent depression symptoms (12). With support from the NIMH, we are now following up on this initial finding with a larger clinical trial. We are also developing other cognitive bias manipulations and brief interventions that specifically target other important cognitive mechanisms (e.g., negative self-referent processing, self-dislike).

I have recently developed a strong interest in identifying who is most likely to respond to interventions for depression. Statistical prediction has dramatically improved with the development of new approaches, such as machine learning. These approaches are now routinely used by the tech industry and many for-profit companies to predict what goods consumers are likely to purchase or what movies individuals would prefer to watch. These same methods can now be applied to intervention research to determine who is most likely to respond to which interventions. A major advantage of machine learning approaches is that we can use multiple weak predictors to develop algorithms that robustly predict response to treatment. These treatment algorithms can then be used to predict the probability that a new patient will respond to a given treatment. With support from the NIMH, we are currently testing these ideas in several large datasets involving pharmacological and psychological interventions (13).

Finally, over 10 years ago, my collaborators and I started to examine the genetic etiology of several negative cognitive biases. Consistent with the zeitgeist of the time, we examined associations between candidate genetic variants (e.g., serotonin transporter promoter polymorphism; 5-HTTLPR) and negative cognitive biases. In a series of studies, we found that variation within the 5-HTTLPR polymorphism was associated with an attentional bias for negative information (e.g., 14,15). Several other research groups around the world replicated this finding (16); however, we now know that these results are very likely false positives (or grossly overestimate the variance explained by a single genetic variant). More recently, we have moved towards using genome-wide methods (polygenic risk scores; genome-wide complex trait analyses) to quantify the additive genetic contribution to depression symptom dimensions and treatment response (17,18). I hope to do something similar with cognitive phenotypes as well, as doing so will help us understand the degree to which negative cognitive biases are influenced by genetic variation (if at all).

Summary

My work suggests that negative cognitive bias is not simply an epiphenomenon of depression. Negative cognitive bias predicts increases in depression, is apparent before depression onset and persists after depression remits. Manipulating negative cognitive bias, such as biased attention, can improve symptoms of depression. Negative cognitive bias appears to have a genetic origin, although much more work is needed to firmly establish this possibility. I believe that experimental psychopathology methods have the promise to help identify the most important mechanisms that maintain depression. Further, new statistical methods may help uncover who will respond well to current treatments and who will not. This could help narrow our focus towards developing interventions for individuals who are least likely to respond to traditional treatments.

Although I have made significant steps towards improving our understanding of depression, I look forward to the continued evolution of my research. I have a strong sense of where my work is headed, but I am also influenced by important findings and new methodological developments. For instance, I think a critically important development is the renewed focus on the (often ignored) psychometrics of task-based measurements (19) and whether we should use sum scores to measure depression severity (spoiler alert: we shouldn’t in many instances, 20). Many fascinating questions remain unanswered and I look forward to studying these questions for many years to come. I also look forward to mentoring students and helping them to develop their own research questions, so they too can learn how exciting and rewarding the science of clinical psychology can be.

References

  1. Beevers CG. Cognitive vulnerability to depression: A dual process model. Clin Psychol Rev. 2005 Nov 1;25(7):975–1002.
  2. Disner SG, Beevers CG, Haigh EAP, Beck AT. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci. 2011 Aug;12(8):467–77.
  3. Beevers CG, Miller IW. Depression-related negative cognition: Mood-state and trait dependent properties. Cogn Ther Res. 2003;28(3):293–307.
  4. Gibb BE, Alloy LB, Abramson LY, Beevers CG, Miller IW. Cognitive vulnerability to depression: a taxometric analysis. J Abnorm Psychol. 2004 Feb;113(1):81–9.
  5. Beevers CG, Lee H-J, Wells TT, Ellis AJ, Telch MJ. Association of predeployment gaze bias for emotion stimuli with later symptoms of PTSD and depression in soldiers deployed in Iraq. American Journal of Psychiatry. 2011 Jul;168(7):735–41.
  6. Beevers CG, Carver CS. Attentional bias and mood persistence as prospective predictors of dysphoria. Cogn Ther Res. Springer; 2003;27(6):619–37.
  7. Disner SG, Shumake JD, Beevers CG. Self-referential schemas and attentional bias predict severity and naturalistic course of depression symptoms. Cogn Emot. 2016 Feb 22;:1–13.
  8. Beevers CG, Rohde P, Stice E, Nolen-Hoeksema S. Recovery from major depressive disorder among female adolescents: a prospective test of the scar hypothesis. J Consult Clin Psychol. 2007 Dec 1;75(6):888–900.
  9. Beevers CG, Keitner GI, Ryan CE, Miller IW. Cognitive predictors of symptom return following depression treatment. J Abnorm Psychol. 2003 Aug;112(3):488–96.
  10. Gibb BE, McGeary JE, Beevers CG. Attentional biases to emotional stimuli: Key components of the RDoC constructs of sustained threat and loss. Glatt SJ, editor. Am J Med Genet B Neuropsychiatr Genet. 2nd ed. 2016 Jan;171B(1):65–80.
  11. Wells TT, Beevers CG. Biased attention and dysphoria: Manipulating selective attention reduces subsequent depressive symptoms. Cogn Emot. 2010;24(4):719–28.
  12. Beevers CG, Clasen PC, Enock PM, Schnyer DM. Attention bias modification for major depressive disorder: Effects on attention bias, resting state connectivity, and symptom change. J Abnorm Psychol. 2015 Aug;124(3):463–75.
  13. Pearson R, Pisner D, Meyer B, Shumake JD, Beevers CG. A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression. Psychol Med. 2018.
  14. Beevers CG, Wells TT, Ellis AJ, McGeary JE. Association of the serotonin transporter gene promoter region (5-HTTLPR) polymorphism with biased attention for emotional stimuli. J Abnorm Psychol. 2009 Aug;118(3):670–81.
  15. Beevers CG, Marti CN, Lee H-J, Stote DL, Ferrell RE, Hariri AR, et al. Associations between serotonin transporter gene promoter region (5-HTTLPR) polymorphism and gaze bias for emotional information. 2011 Feb;120(1):187–97.
  16. Pergamin-Hight L, Bakermans-Kranenburg MJ, Van Ijzendoorn MH, Bar-Haim Y. Variations in the promoter region of the serotonin transporter gene and biased attention for emotional information: A meta-analysis. Biol Psychiatry. 2012 Feb 15;71(4):373–9.
  17. Palmer RHC, Beevers CG, McGeary JE, Brick LA, Knopik VS. A preliminary study of genetic variation in the dopaminergic and serotonergic systems and genome-wide additive genetic effects on depression severity and treatment response. Clin Psychol Sci. 2017 Jan;5(1):158–65.
  18. Pearson R, Palmer RHC, Brick LA, McGeary JE, Knopik VS, Beevers CG. Additive genetic contribution to symptom dimensions in major depressive disorder. J Abnorm Psychol. 2016 May;125(4):495–501.
  19. Dainer-Best J, Lee HY, Shumake JD, Yeager DS, Beevers CG. Determining optimal parameters of the self-referent encoding task: A large-scale examination of self-referent cognition and depression. Psychol Assess. 2018 Jun 7.
  20. Beevers CG, Mullarkey MC, Dainer-Best J, Stewart RA, Labrada J, McGeary JE, et al. Association between negative cognitive bias and depression: A symptom-level approach. Manuscript under review. 2018.

Diversity Statement


Statement of Contributions to Equity, Diversity, and Inclusion

October 1, 2018

I am strongly committed to increasing diversity and inclusiveness in clinical science. I believe my actions and contributions throughout my career support this statement. Below I outline some of the ways I have tried to make a difference in this area while acknowledging that there is likely much more that I could have done in the past and much more that I can do in the future to increase inclusiveness and diversity.

The primary way I have tried to increase diversity in clinical science is through mentorship of undergraduate and graduate students from groups that are traditionally underrepresented in academia. There is ample opportunity to do this at the University of Texas at Austin, as there is substantial racial and ethnic diversity among undergraduates. The most recent freshman class is 40% White, 22% Asian/Asian American, 5% Black/African American, 25% Hispanic/Latino, 0.2% American Indian/Alaskan, 0.1% Native Hawaiian/Pacific Islander, and 1% unreported/unknown. Thus, our student body is diverse and I actively work to ensure that student volunteer research assistants (about 8 – 10 per year) in my lab mirror this diversity.

Further, every year that I am asked, I serve as a faculty mentor for the Summer Undergraduate Research Experience (SURE) program. SURE is a summer internship program for undergraduate students interested in research in psychology and who are currently attending a college or university in the state of Texas. The program provides hands-on training and close mentorship in order to make students from underrepresented backgrounds (racial/ethnic/SES) more competitive for top doctoral training programs. These students receive a stipend, housing, and research mentorship during their two-month summer internship. Once the summer internship has finished, we typically stay in touch and I (along with students in my lab) help support them through the application process to graduate school. I believe supporting students from underrepresented groups is critical for the long-term goal of increasing diversity and inclusiveness in clinical science graduate training programs.

In a similar fashion, I have tried to increase equity and diversity among the graduate students I have mentored. To help facilitate recruitment, I have applied for competitive fellowships offered by the Provost at the University of Texas, designed to increase graduate student diversity. These mentoring awards support outstanding students who add to the diversity of our graduate programs. I have mentored graduate students, post-doctoral fellows, and research scientists who increase the racial, sexual orientation, and socioeconomic status diversity within clinical science. I then strongly believe it is critical to continue to support these students as they move towards developing their careers as independent clinical scientists.

Finally, I have also chaired (and been members of) a number of faculty search committees. For hiring at the Institute for Mental Health Research (the organized research unit that I direct at the University of Texas), I worked to incorporate several approaches to our searches to help increase the likelihood that our search would reach individuals from all backgrounds. Specifically, on each search committee, we included a member of the Department of Psychology’s diversity committee. This person served as an advocate for diverse applicants and when we interviewed applicants, assessed how applicants may be able to contribute to the department’s diversity mission. We also made sure that we advertised positions broadly, specifically sending the job ads to listserves and research networks that were more likely to be inclusive. We also reached out to colleagues who worked in areas related to ethnic and cultural diversity and specifically asked for candidates that we could contact directly, in an effort to increase our inclusiveness. We were not always successful in hiring diverse faculty members (indeed, some candidates had concerns about the perceived limited inclusiveness and diversity); however, I believe it is critically important that we keep trying, as this sort of change takes time and sustained effort to reverse.

I have tried to highlight some of the ways in which I tried to address diversity and inclusiveness. I wish I could say that all of these efforts have resulted in a highly diverse and equitable student body and faculty. It hasn’t. We have much more work to do in this area. Having grown up in a fairly diverse community (Toronto, Ontario, Canada), I am committed to helping develop a more inclusive clinical science community. Indeed, one trend that I and others have noted, is that many of the individuals who are leading the charge for more diversity, tend to be diverse in some way themselves. While this is very honorable and important, those of us whose racial or economic attributes do not necessarily enhance diversity (privileged, white males, like myself) need to do more. We need to take on more of this burden than we have in the past, as everyone benefits from a more diverse and inclusive community.

Current Projects


My laboratory conducts translational research on the etiology and treatment of depression. We are particularly interested in the intersection between cognitive models of depression, genetics, and neuroscience. The Mood Disorders Lab focuses primarily on the collection of phenotypic data, such as cognitive vulnerability to depression, measured with a variety of different approaches. Central techniques include behavioral reaction time tasks and psychophysiology, including eye-tracking and more recently electroencephalography. In close collaboration with geneticists, we are then able to explore the genetic underpinnings of vulnerability to depression and its correlates. We are particularly interested in whole genome approaches and epigenetics.

We have numerous ongoing projects within the lab. Here is a current sampling of projects:

  • We are just about to complete a therapygenetics study, which examines whether polygenic scores can predict response to internet delivered psychotherapy. This project is funded by the Brain and Behavior Foundation and is being conducted in collaboration with colleagues at Brown University (J. McGeary).
  • Related to the idea above, we are also exploring novel analytic approaches (e.g., machine learning) to identify who is most likely to respond to various forms of depression treatment. This project if funded by the National Institute of Mental Health (NIMH).   
  • We are exploring different approaches to cognitive training, in an effort to reverse the cognitive biases that are believed to maintain the disorder. This work falls under the umbrella of Cognitive Bias Modification. This is an exciting new area of research that promises to merge basic psychopathology research with treatment development.
  • We are also conducting research that examines decision making in healthy and depressed individuals. This work is funded by the National Institute on Drug Abuse (NIDA).   

Info for Prospective Students


Frequently Asked Questions

Will you be taking a graduate student into your lab this year? 

I am planning on admitting a graduate student in the Fall of 2019 into my laboratory.  

Are there any particular experiences that I should emphasize in my application this year?

I am very interested in recruiting motivated and talented students into the lab. It is a plus (but certainly not required) if applicants have interests and experience with programming and coding (e.g., Python, Matlab, etc.). If you have experience programming in Python and/or Java, please make that apparent in your application materials. Although this topic is of interest, any student with outstanding potential to be successful in graduate school and beyond will be considered.   

What other attributes to do you look for in graduate students?

First and foremost, good graduate students are passionate about their work. This is important because the research process can take a long time from start to finish, there is often not much positive reinforcement along the way, and it can be easy to get distracted. Passion for what they do helps sustain students through this process. Good students are also highly motivated to succeed and willing to work very hard. Being smart, curious, a good writer, and having good quantitative skills also helps.

What are your top tips for students interested in applying to a psychology graduate program?

  1. Fit between your research interests and those of the advisor you are applying to work with is probably the most important aspect of your application. Not just in terms of your stated interests, but also in terms of your experiences. For instance, if someone is interested in studying alcohol disorders in graduate school, the most competitive students often have worked in an alcohol research laboratory as an undergraduate.
  2. I would also recommend doing as well as possible on the GREs, particularly the verbal section. This is one of the few ways faculty can compare students across a level playing field.
  3. Remember that most people do not get into graduate school the first time they apply. Our doctoral program in clinical psychology only accepts 3-5 students from approximately 350 applications every year.
  4. I would also recommend verifying that the faculty member you would like to work with plans to accept a graduate student that year.

Do you take people straight out of undergrad?

It is somewhat unusual for me to take someone who just received their undergraduate degree. I like to admit people who have worked as post-bac RAs for a year or two because if they still want to do research after working full time for a couple of years, that is a good sign.  

When (if ever) is the best time to get an email from an applicant asking: 1) if you are taking students next year; and 2) just expressing interest in your work as a way to say please look at my application?

A month or two into the fall semester. Too early and faculty won't know if they are able to admit a student. I think it is OK to express interest in my work--just try to be concise. It is useful to say specifically why you are interested, rather than just saying you admire it etc. I also think it is a great idea to attach a CV, as that is a good way for me to quickly see what sorts of experiences a student has had.  

Do you hate these emails? Do you like them?

I don't mind them. 

When (if ever) is the best time to get an email from a faculty mentor suggesting that I should look at a particular applicant closely?

Probably right around the application deadline. Much earlier than that, and I would likely forget! So, best to catch the advisor near the time when he/she starts looking at applications. And, at least at Texas, we don't start looking at applications until after the deadline (which is usually early to mid Dec, which means I usually don't look at them until after Christmas early Jan). 

Other useful resources:

Media Coverage


Translational Research Helps Understand and Treat Mental Health Disorders

Understanding Mental Health Disorders
Almost one in two people in the United States will experience a mental health disorder in their lifetime. Despite this fact, there are relatively few effective behavioral treatments that provide long-lasting relief from problems like depression and anxiety. Dr. Christopher Beevers, a professor at the University of Texas at Austin and director of the Institute for Mental Health Research, is trying to change this. The institute's mission is, "to transform the understanding and treatment of mental illness through basic and clinical research, paving the way for prevention, recovery, and cure."


To Treat Depression, a New Approach Tries Training the Brain

Published in the Wall Street Journal on June 1, 2015

Computer games, chirping birds and electrical stimulation in studies to change how depressed people think


The Attention Machine

Published in the Atlantic on February 9, 2015.

A new brain-scanning technique could change the way scientists think about human focus.


Psychologists Use Machine Learning to Help Diagnose Depression

Published by the Texas Advanced Computing Center on March 22, 2017.

University of Texas researchers use Stampede supercomputer to identify patterns in neuroimaging data that are predictive for mental disorders.


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