Research Summary Archive
This archive includes earlier research summaries, offering plain-language translations of our research findings. It provides access to previously published summaries for those interested in exploring prior work.
Explore our earlier summaries using the links below.
- Can blood samples help predict how well someone will respond to antidepressant medications?
- Can brain activity predict responses to medication and therapy for depression?
- Can genetic risk scores help explain how people with depression respond to antidepressants?
- Do insomnia symptoms affect antidepressant treatment in depression?
- Can interactions between depression symptoms help predict relapse?
- Is depression associated with changes in brain connections?
- Could childhood experiences and brain patterns predict depression outcomes?
- Can sleep and activity patterns help predict relapse in depression?
- Can machine learning be used as a tool to predict depression treatment outcomes using brain activity?
- Wellness Under Watch: Using Wearables and Data to Catch Depression Early
- Predicting Antidepressant Response with Brain Scans and Artificial Intelligence
- Deciphering the Relationship Between Brain Structure and Epigenetics in Depression
- CHOICE‑D: Empowering Patients with a Plain-Language Guide to Depression Treatment
- Mid-study report on the CAN-BIND-1 study for personalizing depression treatment
- Hippocampal tail volume as a predictive biomarker of antidepressant treatment
- Childhood Maltreatment and Cognitive Functioning in Patients with Major Depression