Get Involved! Become a Research Intern at CARE!

There are ample opportunities for undergraduate students to become involved in my research and I enjoy working with students to help them reach their career goals. Past undergraduate students who have worked as research assistants under my supervision have gotten into top clinical psychology, counseling psychology, and neuroscience graduate schools including: Northwestern University, University of Missouri – Kansas City, University of Iowa, University of Toronto, Loyola University, University of Illinois – Urbana-Champaign, Brandeis University, and the University of Chicago.

Currently research internships are for credit through PSYC 480 or PSYC 580. Interns can expect to devote 3 semester hours per week (which amounts to 9 hours of lab work, plus one-hour lab meeting or 10 hours total per week). Lab tasks/duties include: data entry, telephone screening of participants, scheduling, collection and preparation of biological samples, data management, and assisting with manuscript and grant preparation. Depending on the studies, interest, and training there are also opportunities to work directly with research participants.


Why Should You Care about CARE Research?

Imagine you or a loved one was diagnosed with cancer. You would work with an oncologist to diagnose the type of cancer, identify the stage of the cancer (e.g., Stage I to Stage IV), and your diagnosis and stage-of-cancer would lead your doctor to develop the most effective treatment possible to improve your health.

Now, imagine you or a loved one was diagnosed with an eating disorder. Sadly, there are few treatment centers for eating disorders – particularly in rural areas or mid-sized cities – and there is a lack-of-training, which means that many doctors and psychologists are not able to make accurate diagnoses. Even if your diagnosis was accurate, the current diagnostic system for eating disorders does not inform prognosis (treatment outcomes). One of the only prognostic indicators is how well you or your loved one respond to treatment in the first four weeks. Yet, there are few assessment tools to help your doctor monitor your progress in treatment, particularly for men, youth, and racial or ethnic minorities. Our current work is largely focused on addressing these issues. Ultimately, the critical question that drives our assessment and classification work is: Can we develop improved diagnostic systems and assessments to better predict important clinical outcomes and match patients to the best treatments?

Diagnosis and assessment often seem “dry” or boring, but they are the foundation for effective intervention! As you will see from the descriptions of our studies, we have several local and national partnerships that are helping us rapidly translate our findings into clinical practice.

Diagnosis and Classification of Eating Disorders

Problem: Eating disorders (EDs) are associated with substantial psychiatric and medical morbidity and sequelae. Once present, EDs are extremely difficult to treat and, treatments for EDs often do not work for more than half of patients. Even when treatments do lead to successful recovery from an ED, 65-80% of these patients will continue to suffer from (or develop) an internalizing disorder (i.e., mood or anxiety disorder) at follow-up. Despite decades of research showing strong associations of EDs with mood and anxiety disorders, the majority of treatment and longitudinal studies for EDs have focused primarily (or exclusively) on ED-specific processes. Thus, little is known about specific aspects of internalizing psychopathology that lead to poor treatment response, course, and outcome among individuals with EDs.

Goal: To use empirical methods to better identify how eating disorder symptoms cluster together to form dimensional syndromes, and to understand what drives comorbidity of EDs with mood and anxiety.

Measures: SCID, EPSI-Self-Report and EPSI-CR, NEO-PI-3 (personality), ADIS Phobia Module, IDAS-CR and IDAS-Self-Report, select EDE interview subscales, and self-reports of substance abuse, treatment course, clinical impairment, and negative urgency (impulsivity).

Participants: Persons aged 18 and older with an eating disorder recruited from the community. All participants have a DSM-5 eating disorder.

Design: Participants are screened to determine if they have a clinically significant eating disorder (of any type), then come into the lab to complete measures. Participants complete a six-month online follow-up, and then re-visit the lab annually over a three-year period. We have recruited slightly over 250 participants, to date, for this study. We aim to recruit a total of 280 participants from the community to account for attrition.

For More Information: See Forbush et al., 2010 Journal of Abnormal Psychology; Forbush and Watson, 2013 Psychological Medicine. These initial studies include over 16,000 participants and have shown that eating disorders fit better within a spectrum of mood and anxiety disorders, rather than their own separate class of “eating disorders.” Our recent work from this dataset showed that a dimensional model was nearly six times more predictive of impairment at baseline vs. all DSM eating, mood, and anxiety disorders combined (Forbush et al., 2017 Comprehensive Psychiatry) and predicted 60% of six-month outcomes (Forbush et al., under review).

Future Directions: We are testing the biometric structure of eating, mood, and anxiety disorders using behavior-genetic modeling in collaboration with the University of Minnesota. We also plan to use fMRI to better characterize neural circuitry in response to select laboratory-based tasks that have been shown in other studies to be robust predictors of depression in a sub-set of women participants with bulimia nervosa.

Assessment of Disordered Eating

Problem: Current measures of disordered eating are either very narrow in scope (e.g., assess only one aspect of disordered eating, such as disinhibited eating) or have serious limitations, such as gender biases, inconsistent factor structures, and poor discriminant validity. To address this problem, my laboratory developed the Eating Pathology Symptoms Inventory (EPSI; pronounced ‘ep-see’), which has demonstrated strong evidence for test retest reliability, internal consistency, and convergent/discriminant validity. The measure has been tested in over 2,000 subjects and results have been very promising. For example, the EPSI has less gender and weight category bias, a more replicable factor structure, and stronger criterion-related validity for distinguishing among individuals with different types of eating disorders compared to other established measures of eating pathology.

Goal: We are working on several studies designed to further validate and extend our work on the EPSI. This includes: Project 1) validating an interview version of the EPSI in a large sample of individuals with bulimic syndromes recruited from the community; Project 2) developing a week-to-week version of the EPSI (called the Eating Pathology Clinical Outcomes Tracker or “EPCOT”) in collaboration with Recovery Record, Inc. to be used in psychotherapy randomized clinical trials and in routine clinical practice to enable improved therapy outcomes tracking; Project 3) developing and validating a version of the EPSI (called the EPSI Child and Teen Version, or “EPSI CHaT”) for children and adolescents age 10 through 18 in collaboration with two major eating disorder centers; and Project 4) developing and validating a computerized adaptive test that will work on a mobile phone to reduce administration length and provide therapists with “signal alarms” when their client’s scores indicate that they are making less than adequate progress. Project 4 is funded by the National Eating Disorders Association.

Measures: EPSI-Self-Report and EPSI-CR, various measures of personality, Inventory of Depression and Anxiety-Self-Report, Eating Disorder Examination interview sections, and childhood eating disorder measures for Project 3. Project 4 also includes measures to assess therapist impressions of the app.

Participants: Project 1 participants are described above in the Diagnosis and Classification of Eating Disorders section. Project 2 will recruit individuals from: PSYC 104 (general sample), Amazon’s MTurk (community sample), and users of Recovery Record (patients with eating disorders). Project 3 will recruit children and adolescents with an eating or feeding disorder from Children’s Mercy Hospital in Kansas City, the Eating Disorder Recovery Center [MOU1] (multiple USA locations), and from schools in the Lawrence, Kansas area to test the measure in community children and adolescents. Project 4 will recruit persons who are age 14 and older at the start of treatment for an eating disorder. We have partnered with local treatment providers in the Kansas City metro area to recruit participants.

Design: Project 1 uses the same design described in the Diagnosis and Classification of Eating Disorders study. Project 2 aims to test the structure of the new week-to-week version of the EPSI in a variety of samples to characterize the structure of the measure, test for validity and reliability, and develop norms. Project 3 involves revising the measure to make it applicable to children and adolescents. Project 4 will include weekly assessment using the mobile app for 16 weeks, starting at the beginning of therapy (admission). Clients and therapists will also fill out separate baseline and end-of-study assessments to validate the measure.

For More Information: See Forbush et al. (2013) Psychological Assessment; Forbush, Wildes, & Hunt (2014) International Journal of Eating Disorders. My honors student and I published a paper in which we translated the EPSI self-report measure into Mandarin and Cantonese (see Tang, Forbush, & Liu, 2015 International Journal of Eating Disorders).

Future Directions: In the future, we would like to validate the Excessive Exercise, Restricting, and Binge Eating scales with the 24-HR (an online dietary recall measure) and a wearable device to track and energy expenditure.

Graduate Student Independent Research Studies

Ms. Brittany Bohrer, M.A. (Ph.D. Candidate)

  • Predictors of eating disorders treatment seeking using a nationally representative dataset (Bohrer, Carroll, & Forbush, 2017 in International Journal of Eating Disorders).
  • Differences among individuals with purging and non-purging bulimia nervosa.
  • Reliability and validity of measures of restraint and disinhibited eating in normal weight, overweight, and obese individuals recruited from the community (Bohrer, Forbush, & Hunt, 2015 Appetite).
  • Clinical utility and stability of the Eating Pathology Symptoms Inventory over time.
  • Treatment of eating disorders in persons with type I diabetes mellitus (dissertation).


Ms. Danielle Chapa, M.A.

  • Differences between sub-threshold and full-threshold bulimia nervosa (Chapa, Bohrer, & Forbush, 2017 in Eating Behaviors).
  • Temporal definitions of dietary restricting in predicting clinical impairment and binge eating.
  • Trajectory of eating disorder symptoms over time.


Ms. Alexis Exum, B. A.

  • Using item-response theory to test the information value of DSM-5 eating disorder symptoms
  • Review paper of the Strong Black Woman Ideal with Dr. Tamara Baker


Ms. Kelsey Hagan, M.A. (Ph.D. Candidate; Internship in 2018-2019 at Stanford University)

  • Meta-analysis of the efficacy of cognitive remediation therapy in anorexia nervosa.
  • Empirical test of Lowe’s Three-Factor Model of Dieting.
  • Novel application of a model of imbalanced reward processing and inhibitory control in substance use disorders to bulimia nervosa (dissertation).
  • Development of a model to identify sub-components of dietary restraint (Hagan, Forbush, & Chen, 2017 Psychological Assessment).
  •  “Weight suppression” as a potential predictor of clinical impairment in bulimic syndromes (Hagan, Clark, & Forbush, 2017 International Journal of Eating Disorders).


Ms. Victoria Perko, B.A.

  • Network analysis comparing eating disorder symptomology of men and women
  • Comparison of diagnostic migration across DSM-IV and DSM-5

Ms. Brianne Richson, B.S.

  • Testing the predictive validity of the DSM-5 severity indices for bulimia nervosa
  • Identifying improved outcome definitions for understanding eating-disorder recovery


Additional Active Collaborative Research Projects

Dr. Joseph Donnelly, University of Kansas Medical Center

  • Predictors of diet quality and weight gain in adolescents.

Dr. Laura Martin, Hoglund Brain Imaging Center

  • Pilot test of reward and stress response using fMRI in women with bulimia nervosa.

Dr. Sara Gould

  • Dr. Gould works at Children’s Mercy. We collaborate on almost all the project that are listed above!

Dr. Christopher Cushing

  • Development of the mobile phone app (Assessment Project 4)

Dr. Michael Vitevitch, University of Kansas

  • Application of network analysis to eating disorders

Dr. Tera Fazzino, University of Kansas

  • Dr. Fazzino is Associate Director of the new KU Addictions Center. She studies food addiction.

  Additional Clinical-Research Resources!

The Lawrence and Kansas City metro-areas provide unparalleled access to a rich array of resources that set us apart from many other graduate programs.

Patient Recruitment. We are close partners with Children’s Mercy, which provides outstanding access to child and adolescent outpatient clients with eating issues through the Eating Disorder. Dr. Gould and I coordinate a consortium of treatment providers who have agreed to allow us to recruit through their clinics. The consortium provides combined access to over 600 patients per year with an eating disorder. We are also close partners with Recovery Record, Inc. which has administered the EPSI and other eating-disorder measures to over 65,000 users with an eating disorder and the Eating Recovery Center’s 23 eating-disorder units across the USA.

Hoglund Brain Imaging Center (HBIC). The brain imaging resources at HBIC in Kansas City provides students with equipment and facilities that are not available at many other imaging centers. HBIC is the only center in the world with capabilities for whole-cortex adult magnetoencephalography (cMEG) and high-density fetal MEG. For more info, see:

Center for Research Methods and Data Analysis (CRMDA). CRMDA provides consultation to graduate students, as well as monthly workshops, and summer “stats camp.” Most graduate students in the laboratory have benefited greatly from the statistical resources here on campus. For more info, see:

Practica Opportunities. CARE has an assessment practicum (PSYC 977) for graduate students that counts toward the in-house clinical hours requirement. In addition to my assessment practicum, there are numerous additional practicum opportunities, including neuropsychological assessment; in-patient psychiatry; VA hospitals; Children’s Mercy rotations (including research and clinical rotations at the ED unit); and opportunities to learn intensive Dialectical Behavior Therapy through the Bert Nash Community Mental Health Center in Lawrence, KS. See the list of opportunities in the Clinic Lounge.