A hierarchical latent stochastic differential equation model for affective dynamics

In this article a continuous-time stochastic model (the Ornstein-Uhlenbeck process) is presented to model the perpetually altering states of the core affect, which is a 2-dimensional concept underlying all our affective experiences. The process model that we propose can account for the temporal changes in core affect on the latent level. The key parameters of the model are the average position (also called home base), the variances and covariances of the process, and the regulatory mechanisms that keep the process in the vicinity of the average position. To account for individual differences, the model is extended hierarchically. A particularly novel contribution is that in principle all parameters of the stochastic process (not only the mean but also its variance and the regulatory parameters) are allowed to differ between individuals. In this way, the aim is to understand the affective dynamics of single individuals and at the same time investigate how these individuals differ from one another. The final model is a continuous-time state-space model for repeated measurement data taken at possibly irregular time points. Both time-invariant and time-varying covariates can be included to investigate sources of individual differences. As an illustration, the model is applied to a diary study measuring core affect repeatedly for several individuals (thereby generating intensive longitudinal data).     

Adherence as a determinant of effectiveness of internet cognitive behavioural therapy for anxiety and depressive disorders

Since 2009, the Clinical Research Unit for Anxiety and Depression (CRUfAD) has been providing primary care clinicians with internet cognitive behaviour therapy (iCBT) courses to prescribe to patients. Although these courses have demonstrated efficacy in research trials, adherence in primary care is less than half that of the research trials. The present studies pose three questions: first, do course non-completers drop out because of lack of efficacy? Second, can changes in delivery (e.g. adding choice, reminders and financial cost) improve adherence? Last, does clinician contact improve adherence? The results showed that non-completers derive benefit before dropping out; that adding reminders, choice of course and timing, and financial cost can significantly improve adherence; and that clinician contact during the course is associated with increased adherence. It is concluded that improved adherence is an important determinant of effectiveness.