Dynamic Structure of Emotions Among Individuals with Parkinson's Disease

With few exceptions, the dynamics underlying the mood structures of individuals with Parkinson's Disease have consistently been overlooked. Based on 12 participants' daily self-reports over 72 days, we identified 10 participants whose covariance matrices for positive and negative affect were similar enough to warrant pooling. Dynamic factor models that included factor autoregression and cross-regressions were fitted to the pooled, lagged covariance matrix representing approximately 700 occasions of measurement. Although results from the pooled data indicated that both positive and negative affect had a strong lag-1 autoregressive impact on current positive and negative affect, most individuals showed stronger autoregressive effects for positive than negative affect when examined individually. There was also a weak cross-regression effect of positive affect on negative affect, but the reverse was not true. Through model fitting, we demonstrated that failure to incorporate lagged relations among factors could lead to an overestimation of concurrent correlations among latent factors. Implications of the findings in relation to the orthogonality of positive and negative affect are discussed.