An affective space view on depression and anxiety. Issue 4 (18th October 2018)

• Record Type: Journal Article
• Authors: Xu, Meng Lin; De Boeck, Paul; Strunk, Daniel
• Is Part Of: International journal of methods in psychiatric research. Volume 27:Issue 4(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-18
• Subjects: affective disorders -- Bayesian approach -- measurement -- patient reported outcome; Psychiatry -- Research -- Methodology -- Periodicals; Psychiatry -- Periodicals; 616.890072
• DOI: 10.1002/mpr.1747
• Languages: English
• ISSNs: 1049-8931

Abstract

Abstract: The circumplex model for core affect is among the most prominent characterizations of emotion and has received extensive empirical support. However, no prior study exists that connects the measurement of depression and anxiety with the core affect structure and the bipolar dimensions of arousal and valence it includes. Objectives: This study aims to investigate the reconcilability between a continuous model based on Russell's core affect system and a discrete entity view on depression and anxiety. Methods: The data were drawn from the anxiety and depression short forms in the Patient‐Reported Outcomes Measurement Information System ( N = 763). It consists of 15 items with a 5‐point Likert scale. Ratings of the items in terms of distress and arousal were obtained from experts in emotion research. An approach based on Russell's core affect theory was compared with the common type of factor models in which the items are lined up on clearly separated depression and anxiety dimensions with an empty space in between, as if they are separate and discrete entities. Our alternative model works with a continuous space instead. Results: The core affect theory‐based method exhibits a goodness of fit that is comparable with the conventional models. Conclusions: Depression and anxiety can be understood in terms of Russell's bipolar core affect model; the core affect‐based model leaves room for symptoms in the space between dimensions.