Structure and Variation of Mood in Individuals with Parkinson's Disease: a Dynamic Factor Analysis

Mood structure was examined among individuals diagnosed with Parkinson's disease. Twelve individuals completed a measure of positive and negative affect for 70 consecutive days. Mood structure was determined by using dynamic factor analysis (DFA) models that account for both concurrent and lagged relationships in repeated measurements. Five individuals had sufficient variability in positive and negative affect to conduct DFA on both sets of variables. Results showed the presence of 2 2-factor 1-lag models, 2 1-factor 1-lag models, and a P-technique model. There was sufficient variability in positive affect to conduct DFA on positive affect for the entire sample. Two individuals displayed 2-factor 1-lag models, 6 individuals had 1-factor 1-lag models, and 4 individuals showed P-technique models. Implications of lagged relationships are discussed from substantive and methodological perspectives.