My research

My research focuses on understanding psychological resilience from a complex systems perspective. Psychological resilience refers to the ability to maintain or quickly recover good mental health despite experiencing adversity. In my research, I have expanded upon existing complex models of psychopathology, particularly network models of psychiatric symptoms, to explore their behavior under various simulated perturbations or clinical interventions. For example, I have developed a method to compute the stability landscapes of these network models, allowing us to evaluate the likelihood of individuals becoming 'stuck' in a dysfunctional phase.

Currently, I am working as a postdoctoral researcher at the Department of Epidemiology & Data Science in Amsterdam UMC. My work involves investigating how this simulation-based complexity approach can be effectively applied to different types of public health data. I aim to broaden the scope of my research beyond solely examining psychological variables. Instead, I intend to incorporate relevant variables from diverse domains, such as social functioning, cognitive health, and physical health, into the models. By doing so, I hope to gain a more comprehensive understanding of resilience and its implications for public health.

IAS fellowship

During my research fellowship at the IAS, my central research question will focus on identifying the adverse events that lead to declines in multiple domains of functioning among older adults, as well as exploring potential interventions or preventive measures that can interrupt these detrimental cycles and enhance resilience.

The aging population in the Netherlands is growing rapidly, and by 2040, there is a projected 151% increase in individuals over 90 years old compared to 2019. Aging often comes with a diminished resilience to adverse events across various functional domains. These events can range from limitations in daily activities and physical health issues like hip fractures, to social challenges like bereavement, cognitive difficulties such as memory complaints, and emotional struggles like depression or apathy. When these events occur, they can trigger a cascading effect, causing losses in other domains and ultimately leading to complex care demands.

By utilizing simulations and network analysis, I will investigate how adverse events can initiate cascades of loss across different functional domains. Building upon methods I developed during my PhD research, I aim to apply these approaches to analyze existing longitudinal data from the Longitudinal Aging Study Amsterdam (LASA). LASA has been collecting comprehensive information on physical, cognitive, emotional, and social factors from thousands of older adults since 1992.

Through this research, I aim to achieve a methodological goal of exploring the optimal application of these methods to longitudinal population data. Furthermore, I hope to gain insights into the mechanisms through which adverse events impact multiple domains of functioning in old age and identify potential strategies to disrupt these detrimental cycles.