Exploring dynamics in mood regulation--mixture latent Markov modeling of ambulatory assessment data

Psychosomatic Medicine
Claudia CrayenJeroen K Vermunt

Abstract

To illustrate how fluctuation patterns in ambulatory assessment data with features such as few categorical items, measurement error, and heterogeneity in the change pattern can adequately be analyzed with mixture latent Markov models. The identification of fluctuation patterns can be of great value to psychosomatic research concerned with dysfunctional behavior or cognitions, such as addictive behavior or noncompliance. In our application, unobserved subgroups of individuals who differ with regard to their mood regulation processes, such as mood maintenance and mood repair, are identified. In an ambulatory assessment study, mood ratings were collected 56 times during 1 week from 164 students. The pleasant-unpleasant mood dimension was assessed by the two ordered categorical items unwell-well and bad-good. Mixture latent Markov models with different number of states, classes, and degrees of invariance were tested, and the best model according to information criteria was interpreted. Two latent classes that differed in their mood regulation pattern during the day were identified. Mean classification probabilities were high (>0.88) for this model. The larger class showed a tendency to stay in and return to a moderately pleasant mo...Continue Reading

Citations

Nov 20, 2012·Annual Review of Clinical Psychology·Timothy J Trull, Ulrich Ebner-Priemer
Sep 29, 2017·Multivariate Behavioral Research·S de Haan-RietdijkE L Hamaker
May 15, 2012·Psychosomatic Medicine·Thomas Kubiak, Arthur A Stone
Jun 2, 2018·World Psychiatry : Official Journal of the World Psychiatric Association (WPA)·Inez Myin-GermeysUlrich Reininghaus

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