We are seeking volunteers who have never had depression

 << Click here to sign up via our pre-screening form >>

 What is the study about?

After recovering from depression, it is currently difficult to advise on the risk of future recurring episodes. The aim of this study is to find better ways to predict the risk of future depressive episodes for a particular person. We have previously found some psychological tests and brain scans that could be useful in predicting risk of recurrence. Here, our aim is to replicate and extend our previous work.

What would you have to do?

Help us as a control participant for comparison with our depression group by taking part in an initial clinical and neurocognitive assessment, including a virtual reality task followed by a magnetic resonance imaging (MRI) session. Optionally, you can also take part in an electroencephalogram session.

What are the benefits for you?

There are no direct benefits for you. It is you who will benefit the progress of medical research. You can make an important contribution to a better understanding of depression and its treatment by participating in our research project. However, we can pay some compensation in shopping vouchers and we will give you access to the results of all tests performed, including an electronic copy of your MRI scan if you wish.

If you are interested in participating, then you can read full details about the study in our participant information sheet and sign-up via our pre-screening form.

You need to:

• not be currently taking antidepressant medications
• be fluent in English
• able to travel to Denmark Hill Campus, King’s College London in about two hours
• have no personal or first-degree family history of depression, bipolar or psychotic disorders
• have no history of neurological disorders
• not misusing substances or alcohol
• be 18 years or older

Self-Blame Virtual Reality Task

Watch interview with Dr Zahn about his research at Cambridge University:

Podcast where Dr Zahn explains his research on guilt and depression.

Press coverage of our previous research on predicting recurrence of depression on which this study builds.