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Software Model Predicts Risk of Depression Relapse

Software Model Predicts Risk of Depression Relapse

German neuroscientists have written a software program that they believe can calculate the risk for experiencing a major depression relapse.

For the project, Selver Demic, M.D., of the Ruhr University Bochum and his colleagues from the Mercator Research Group examined a variety of factors that influence depression.

“Approximately 20 percent of the population will suffer a depressive episode in the course of their lives,” said Demic. “This cohort of 20 percent includes people who will never again experience any problems after that one-time episode is over.

“The others, however, will suffer repeatedly or chronically under the disorder, despite taking appropriate medication. We want to use our model to explain the occurrence and recurrence rates.”

The model includes factors such as rate of memory lapses, cognitive bias, and activity levels of the mood-related neurochemical serotonin.

Some of the variables such as serotonin are well-recognized as being associated with depression while other items include social factors such as family demographics and job situation. A unique aspect of the research is the inclusion of all factors into one model.

After using the model for analysis, Demic discovered the observed patterns of depression could only be explained by a division into two distinct patient groups: A high-risk group whose parameters are so unfortunately aligned that they will always suffer from recurring depressions; another group in which depression will only occur by chance.

The scientists also wanted to compile a systematic definition for the individual disease states based on objective facts, moving beyond the existing classification system that has some degree of subjectivity.

Currently, psychologists and doctors use a system based on:

  • the depressive episode, diagnosed after characteristic symptoms such as lack of motivation and sadness have lasted for minimum of 14 days;
  • the recovery phase, which applies when the patient has not presented any symptoms for a period of at least six months;
  • and the remission phase, if the period between two depressive episodes is shorter than six months.

“When assessing which phase the patient is currently undergoing, psychologists and doctors will also always rely on their intuition and experience.

“Often, it is not clear if a patient is going through the remission or the recovery phase when he shows depressive symptoms for a few days during the six-month period,” said Demic.

Consequently, the neuroscientist developed a mathematical model, a so-called finite state machine (FSM).

This tool is fed data regarding a patient’s state every day. Based on those data and as result of the time course, the FSM calculates the disease state that the patient is currently undergoing.

“Our approach to understand depression is entirely novel,” said Demic. “Therefore, we expect animated debates with doctors, psychologists, and other scientists.

“What’s important is that we have demonstrated the potential computer-based models offer with regard to research into depression.”

Source: Ruhr-University Bochum

Software Model Predicts Risk of Depression Relapse

Rick Nauert PhD

Rick Nauert, PhDDr. Rick Nauert has over 25 years experience in clinical, administrative and academic healthcare. He is currently an associate professor for Rocky Mountain University of Health Professionals doctoral program in health promotion and wellness. Dr. Nauert began his career as a clinical physical therapist and served as a regional manager for a publicly traded multidisciplinary rehabilitation agency for 12 years. He has masters degrees in health-fitness management and healthcare administration and a doctoral degree from The University of Texas at Austin focused on health care informatics, health administration, health education and health policy. His research efforts included the area of telehealth with a specialty in disease management.

APA Reference
Nauert PhD, R. (2018). Software Model Predicts Risk of Depression Relapse. Psych Central. Retrieved on November 29, 2020, from
Scientifically Reviewed
Last updated: 8 Aug 2018 (Originally: 23 Oct 2014)
Last reviewed: By a member of our scientific advisory board on 8 Aug 2018
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