Work

Modeling BAS Dysregulation in Bipolar Disorder

Year: 2016

Type: article

Abstract: Time series analysis is a technique that can be used to analyze the data from a single subject and has great potential to investigate clinically relevant processes like affect regulation. This article uses time series models to investigate the assumed dysregulation of affect that is associated with bipolar disorder. By formulating a number of alternative models that capture different kinds of theoretically predicted dysregulation, and by comparing these in both bipolar patients and controls, we aim to illustrate the heuristic potential this method of analysis has for clinical psychology. We argue that, not only can time series analysis elucidate specific maladaptive dynamics associated with psychopathology, it may also be clinically applied in symptom monitoring and the evaluation of therapeutic interventions.

Source: Assessment

DOI: 10.1177/1073191116632339

Authors: Ellen L. Hamaker, Raoul P. P. P. Grasman, Jan Henk Kamphuis

Institutions: Utrecht University, University of Amsterdam

Language: English

Topic: Mental Health Research Topics

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funder: Princeton University