Dr. Meredith Lotz Wallace's long-term research goal is to become a psychiatric biostatistician who develops and applies novel methods to aid researchers in attaining the goals of the NIMH Research Domain Criteria (RDoC) project. The RDoC project suggests that mental disorders may be ideally characterized by multiple dimensions of signs and symptoms (e.g., brain circuitry, physiology, behavior, and self-report); however, this new paradigm poses substantial challenges because most existing statistical methods were not designed to accommodate the resulting mixture of data types. Dr. Wallace's proposed Mentored Research Scientist Development (K01) award is the first step towards her long-term research goal; it will provide the training and support she needs to develop statistical methods that will make the RDoC project a more viable research framework. The overall aim of Dr. Wallace's K01 is to develop and apply novel clustering methods that incorporate multiple types of intensively measured data.
In Aim 1, Dr. Wallace will develop clustering methods that incorporate intensively measured data captured through polysomnography, actigraphy, and daily self-report measures. These methods will be developed under two different theoretical frameworks to enhance their generalizability to applications beyond those addressed specifically in the K01.
In Aim 2, Dr. Wallace will apply her methods to a data base containing multiple dimensions of observations from over 1000 individuals with a variety of levels of disturbances related to loss, anxiety, and sleep/wake regulation. The methods' application will reveal multidimensional profiles that may cut across the current DSM-based diagnoses. A study of these profiles will clarify the extent to which the multiple dimensions of signs and symptoms lie on a true continuum or separate into discrete classes. Although the candidate's background in biostatistics has primed her to begin this research, its successful completion ultimately hinges on additional training in three areas: 1) mathematical foundations of methods for clustering and intensively measured data, 2) negative valence systems (e.g., loss and anxiety), and 3) sleep/wake regulation. This training will be achieved through tutorials, directed readings, formal coursework, hands-on clinical work, and professional conferences. To achieve her training goals, Dr. Wallace has assembled a strong team of clinical and methodological mentors and consultants. The clinical mentoring team is led by Dr. Ellen Frank, an internationally recognized expert in mood-related disorders. The methodological mentoring team is led by Dr. Satish Iyengar, a leader the field of psychiatric statistics with expertise in clustering and modeling intensively measured data. The training and research resulting from this project will provide Dr. Wallace with the experience and skills she needs to submit an R01 in the fourth year of the K01. This R01 will allow Dr. Wallace to expand on her proposed methods and apply them to develop RDoC-based multidimensional profiles based on additional dimensions and domains of study.
Recent developments in neuroscience and psychology have led researchers to endeavor to characterize mental disorders based multiple dimensions of signs and symptoms (e.g., neurobiological, physiological, behavioral, and self-report). The proposed work will (1) develop new clustering methods that can incorporate the variety of types of intensively measured data that result from observing multiple dimensions of signs and symptoms, and (2) apply the methods to reveal multidimensional profiles that may cut across current categorical diagnoses, thereby suggesting innovative ways of characterizing mental disorders that may eventually lead to more specific and effective treatments.
|Wallace, Meredith L; Stone, Katie; Smagula, Stephen F et al. (2018) Which Sleep Health Characteristics Predict All-Cause Mortality in Older Men? An Application of Flexible Multivariable Approaches. Sleep 41:|
|Price, Rebecca B; Kuckertz, Jennie M; Amir, Nader et al. (2017) Less is more: Patient-level meta-analysis reveals paradoxical dose-response effects of a computer-based social anxiety intervention targeting attentional bias. Depress Anxiety 34:1106-1115|
|Banihashemi, Layla; Wallace, Meredith L; Sheu, Lei K et al. (2017) Childhood maltreatment moderates the effect of combat exposure on cingulum structural integrity. Dev Psychopathol 29:1735-1747|
|Wallace, Meredith L; McMakin, Dana L; Tan, Patricia Z et al. (2017) The role of day-to-day emotions, sleep, and social interactions in pediatric anxiety treatment. Behav Res Ther 90:87-95|
|Wallace, Meredith L; Simsek, Burcin; Kupfer, David J et al. (2016) An approach to revealing clinically relevant subgroups across the mood spectrum. J Affect Disord 203:265-274|
|Price, Rebecca B; Wallace, Meredith; Kuckertz, Jennie M et al. (2016) Pooled patient-level meta-analysis of children and adults completing a computer-based anxiety intervention targeting attentional bias. Clin Psychol Rev 50:37-49|
|Levenson, Jessica C; Wallace, Meredith L; Anderson, Barbara P et al. (2015) Social rhythm disrupting events increase the risk of recurrence among individuals with bipolar disorder. Bipolar Disord 17:869-79|
|Hopkins, Emily E; Wallace, Meredith L; Conley, Yvette P et al. (2015) Symptoms of attention-deficit hyperactivity disorder, nonsyndromic orofacial cleft children, and dopamine polymorphisms: a pilot study. Biol Res Nurs 17:257-62|
|Wallace, Meredith L; Iyengar, Satish; Bramoweth, Adam D et al. (2015) Clarifying Heterogeneity of Daytime and Nighttime Symptoms of Post-traumatic Stress in Combat Veterans with Insomnia. Mil Psychol 27:212-222|
|Frank, Ellen; Wallace, Meredith L; Hall, Martica et al. (2015) An Integrated Risk Reduction Intervention can reduce body mass index in individuals being treated for bipolar I disorder: results from a randomized trial. Bipolar Disord 17:424-37|
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