Computational Modeling and Analysis of Therapeutical Interventions for Depression

Abstract

Abstract. Depressions impose a huge burden on both the patient suffering from a depression as well as society in general. In order to make interventions for a depressed patient during a therapy more personalized and effective, a supporting personal software agent can be useful. Such an agent should then have a good idea of the current state of the person. A computational model for human mood regulation and depression has been developed in previous work, but in order for the agent to give optimal support during an intervention, it should also have knowledge on the precise functioning of the intervention in relation with the mood regulation and depression. This paper therefore presents computational models for these interventions for different types of therapy. Simulation results are presented showing that the mood regulation and depression indeed follow the expected patterns when applying these therapies. The intervention models have been evaluated for a variety of patient types by simulation experiments and formal verification. IntroductionMajor depression is currently the fourth disorder worldwide in terms of disease burden, and is expected to be the disorder with the highest disease burden in highincome countries by the year 2030 (cf. [14]). Effective interventions for treating depressions are of utmost importance for both the patients suffering from a depression as well as for society in general. Supporting software agents can be very helpful in effectively treating a depression by providing personalized support for patients. Thereby, the agent can for example provide feedback on the current situation, give tips, and give certain tasks or assignments. In order for such a personal assistant agents to function effectively, it requires a detailed computational model on the relevant human states and their interrelationship regarding regulation of mood and depression. Such a model can also help to understand and analyze the basics behind a depression better. In [5] an example was shown of a computational model for mood regulation and depression based on literature on emotion and mood regulation. This model however does not explicitly address the functioning of interventions, such as activity scheduling [13] and cognitive restructuring [3]. Particularly for the domain of a personal assistant agent that supports patients during a major depression, knowledge

Computational Modeling and Analysis of the Role of Physical Activity in Mood Regulation and Depression

“…Such a model can be used to analyse how, and to which extent different therapies can achieve a desired effect, as was shown in [7]. However, physical activity and its effect on mood and depression is not addressed this model.…”

“…In the figure, the states and lines that are depicted in grey represent states from the original model from [6]. States and dashed lines in black have been added to model the points of impact of the interventions as described in [7]. The thick black states and solid black lines represent the additional physical states.…”

“…Finally, world event indicates an external situation which is imposed on the human (e.g., losing your job). In addition to the states mentioned above, in [7] a number of states have been added to the model in [6] that relate to therapeutical interventions. First, a state representing the intervention (i.e., intervention) expressing that an intervention is taking place.…”

Utilization of a Virtual Patient Model to Enable Tailored Therapy for Depressed Patients

“…In [6] and [7], therapies are described in terms of a computational mood model [5]. In Figure 1, the mood model is shown in gray.…”

“…In extensions of the model (see [6]; [7]), the influence of various therapies upon these states of the patient have been included, which enables predictions on the effectiveness of the therapy for the patient.…”