Developed by scientists at Michigan State University and Massachusetts Institute of Technology, and funded by the National Institute of Mental Health, the model provides a better understanding of depression and the foundation for creating a pioneering tool to attack the complex disorder.
A paper outlining the research team's findings is published online in the journal Psychological Medicine.
"Clinicians who treat depression tend to work on a trial-and-error basis, whereas this model could give them a more systematic and effective method for making decisions about treatment," said Andrea K. Wittenborn, associate professor in MSU's Department of Human Development and Family Studies and lead investigator on the study. "Most importantly, this model provides a method for personalizing treatment to each unique patient."
Depression is likely caused by multiple biological, psychological, social and environmental drivers, and these factors often overlap, such as cortisol hormone levels going up in response to stress from troubled relationships or economic hardship. Yet most previous research on depression focused on only one or two factors, and not how the many factors intersect and unfold over time.
Wittenborn and colleagues analyzed nearly 600 scientific articles on depression and incorporated the major drivers of depression discussed in the research into a complex model that essentially diagrams how one driver affects another. Depression drivers range from sleep problems to social isolation to inflammation of the brain.
Study co-author Hazhir Rahmandad, an MIT scholar, is an expert in a process called system dynamics that's more common to engineering and business. The team used this approach to create a comprehensive model of depression. While future research is needed to further validate the model, it's a vital first step in better understanding depression and potentially improving care for the illness.