A Novel Approach to Integrating Event-Related Potentials and Self-Report Indices of Transdiagnostic Risk Factors of Emotional Distress - PROJECT SUMMARY
Emotional distress disorders are both common (lifetime prevalence rates ranging from 18-32%) and costly
(global economic cost of $1.15 trillion dollars annually). Despite an increased focus on defining the
mechanisms of psychopathology within a psychobiological framework, distinct biological processes have yet to
be identified specific to individual emotional distress disorders. These limitations are, in part, responsible for
the current paradigm shift in research on psychopathology, embodied by the Research Domain Criteria
(RDoC). RDoC has proposed a shift to focus on narrow, dimensional, psychological constructs associated with
biological processes and behaviors. The limitations of the current diagnostic system also have led to the
hierarchical taxonomy of psychopathology (HiTOP), evidence from which supports dividing emotional distress
disorders into distress and fear clusters of disorders. Focusing on constructs that operate as risk factors across
multiple emotional distress disorders could integrate these two approaches. Anxiety sensitivity (AS), or the fear
of anxious arousal as likely catastrophic, and intolerance of uncertainty (IU), or maladaptive emotional arousal
when confronted with potentially negative unknown events, are two such risk factors. However, to unite these
two disparate approaches, it must be demonstrated that AS and IU can be considered psychobiological
constructs that each uniquely relate to RDoC and HiTOP domains. When conducting research aimed at
establishing psychobiological understanding, it is important to consider measurement error at the biological
level and the increased likelihood of successful cross-unit integration with more proximal units of analysis. We
propose an innovative, scientifically rigorous quantitative approach to integrate event-related potentials (ERPs;
time-locked neural responding to cognitive-behavioral tasks) with self-reports of AS and IU. Specifically,
confirmatory factor analysis (CFA) will be used to create psychoneurometric (PN) bifactor models of AS and
IU. We further propose that these PN bifactor models will demonstrate unique relations with RDoC and HiTOP
domains. Specific Aim 1 will validate PN bifactor models of AS and IU. It is posited that the PN bifactor
solutions will fit the data better than uni- and multi-dimensional models (H1). AS and IU can be linked to RDoC
constructs (acute threat and potential threat, respectively) and emotional distress clusters of disorders (fear-
based and distress-based, respectively). Specific Aim 2 will demonstrate convergent and discriminant validity
for the PN bifactor models of AS and IU with RDoC constructs and emotional distress disorder clusters. It is
posited that the AS factors will be most related to acute threat and fear-based disorders and IU will be most
related to potential threat and distress-based disorders (H2). The proposed project will 1) establish an
approach for linking units of analysis consistent with a psychobiological model and 2) demonstrate convergent
and discriminant validity for AS and IU in relation to the RDoC and HiTOP approaches, thus providing a bridge
between the two systems of assessing psychopathology.
