Trauma and Stressor Related Disorders and Disasters
An Examination of Trauma Symptom Networks in Treatment Responders versus Non-Responders
Alexa Skolnik, B.A.
Graduate Student
University of Toledo
Ottawa Hills, Ohio
Kailyn Fan, B.A. (she/her/hers)
Clinical Research Coordinator
McLean Hospital
Belmont, Massachusetts
Clarissa Ong, Ph.D.
Assistant Professor & Clinic Director
University of Toledo
Toledo, Ohio
Thröstur Björgvinsson, ABPP, Ph.D. (he/him/his)
Director, Behavioral Health Partial Hospital Program
McLean Hospital
Belmont, Massachusetts
Courtney Beard, Ph.D.
Associate Professor
McLean Hospital/Harvard Medical School
Belmont, Massachusetts
Treatment non-response is of great concern to our field—it is widely known that not all patients will respond to a given treatment, yet no consistent demographic or clinical factors have emerged as predictors of treatment response. An oft-overlooked and potentially critical factor in treatment response is trauma. Posttraumatic stress disorder (PTSD) symptoms are correlated with poor clinical outcomes as well as decreased quality of life and functioning. Such clinical outcomes (e.g., depression, anxiety) likely interfere with treatment engagement or may themselves be the focus of treatment, rather than the underlying trauma that maintains them. A potential method to gain insight into how to best help treatment non-responders is to examine connections among psychiatric symptoms. Through the framework of network analysis, psychiatric symptoms can be conceptualized as relating to each other, such that one symptom influences the other, driving psychological disorders in a self-sustaining manner. In theory, if we understand these symptom connections for a given individual, we can optimally tailor treatments to individuals to disrupt these maladaptive connections, thereby increasing the likelihood of treatment response. While the use of network analysis has grown exponentially over the past several years, the use of network analysis to examine differences between those who do and do not respond to treatment has been limited. The current study aims to examine PTSD symptom networks in treatment responders and non-responders—defined by changes in self-reported quality of life—among patients with transdiagnostic presentations in an intensive partial hospitalization program. We hypothesize that networks will differ between the two groups, though analyses about exactly how networks vary are largely exploratory due to the dearth of literature in this domain. Participants will be categorized as responders or non-responders based on self-reported changes in quality of life from pre- to posttreatment. To examine the main research question, cross-sectional partial correlation networks of baseline PTSD symptoms will be estimated for each group. These PTSD symptom networks will then be compared to examine any potential differences. Examining differences in trauma symptom relationships across treatment responders and non-responders is critical for understanding variables underlying treatment response and highlights potential treatment targets for those likely to be non-responders.