Depression is a deeply complex condition, shaped by a mix of emotional patterns, biological factors, and life stresses. This complexity also makes treating it especially challenging. What works for one person may not work for another, and finding the right treatment can take time.
To address this, researchers from the University of Alberta (U of A) and Radboud University in the Netherlands have developed a new, more personalized way to treat depression. Their work, recently published in PLOS ONE, could mark a turning point in how doctors choose the best treatment for each individual patient.
Currently, treating depression is often a matter of trial and error. A person might try one antidepressant or therapy, and if it doesn’t help, they’ll try another. Zachary Cohen, one of the lead researchers and an assistant professor at U of A, explains that about half of all patients don’t respond to the first treatment they’re given.
This “one-size-fits-all” approach doesn’t account for how differently people experience depression—and how differently they respond to treatments.
To fix this, the researchers spent ten years developing a precision treatment model. They gathered data from more than 60 clinical trials involving nearly 10,000 patients from around the world.
These trials had studied five of the most common treatments for depression: antidepressant medications, cognitive therapy, behavioral therapy, interpersonal therapy, and short-term psychodynamic therapy (a deeper form of talk therapy). Each trial provided valuable information about which treatments worked best for which types of patients.
Before starting treatment, patients in these trials were evaluated for various factors, including age, gender, and whether they had other mental health conditions like anxiety or personality disorders.
Ellen Driessen, the study’s lead researcher and a clinical psychology professor at Radboud University, noted that patients with certain features responded better to some treatments than others. For example, someone with both depression and anxiety might benefit more from one type of therapy than someone with only depression.
The goal is to use this information to build a tool that can help doctors quickly identify the best treatment for each individual. The tool would be a type of clinical decision support system—essentially, a computer program or web application that takes in patient information and produces a clear treatment recommendation.
Unlike general guidelines that give a list of options, this tool would deliver a specific suggestion tailored to each person’s unique profile.
Cohen and Driessen explain that the paper they just published outlines their plan and approach, but the tool itself is still in development. The team is now working on building the model based on the massive dataset they’ve collected. Once complete, they plan to test the tool in a clinical setting to see if it actually improves treatment outcomes in the real world.
If the tool works as expected, it could be rolled out more widely to clinics and hospitals. Importantly, it’s designed to be low-cost and easy to use. Most of the information it needs can be collected from basic clinical records or simple self-report questionnaires. This means it could be used not just in well-funded health systems, but also in places with fewer resources.
Ultimately, the researchers hope this tool will help doctors make more informed treatment decisions, shorten the time it takes for patients to find the right care, and reduce the emotional and economic toll of depression. By matching patients to the treatment that fits them best right from the start, this new approach could bring hope to millions of people around the world.
If you care about mental health, please read studies about 6 foods you can eat to improve mental health, and B vitamins could help prevent depression and anxiety.
For more health information, please see recent studies about how dairy foods may influence depression risk, and results showing Omega-3 fats may help reduce depression.
The research findings can be found in PLOS ONE.
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