Startle Habituation and Latent Growth Curve Modeling: Moving Away From Means-Based Analyses (2011)

Undergraduates: Stephanie Lane, Joseph Franklin

Faculty Advisor: Patrick Curran
Department: Psychology & Neuroscience

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Startle methodology is a useful mechanism through which to view a variety of disorders, as previous research has found that individuals with certain psychopathologies modulate responses differently to acoustic startle stimuli. Almost all studies involving acoustic startle stimuli present a block of habituation stimuli to participants; the goal of this habituation block is to detect whether or not an individual has reached his or her baseline level before continuing on to further experimental tasks. Currently, this block of habituation data is examined using means-based procedures that require the artificial division of data; therefore, these means-based techniques are limited. It has been documented in the literature that the rate at which an individual habituates to external stimuli can be informative with respect to a wide range of traits, from psychopathy to personality; however, the methods with which this rate of change is determined are limited. Latent curve models may be a more suitable fit to the data given its pattern of nonlinear change over time. The current study substantively examined the clinical implications of individual variability in startle habituation and quantitatively investigated the methodological challenges of this data in a sample of approximately 100 college students. It was found that a quadratic growth curve most optimally fit the pattern of startle habituation, offering a framework for more valid inferences with respect to psychopathology.