Measurement of symptom severity and related treatment effectiveness
Our research involves investigating:
- the relationship between symptom severity and recognition and treatment of depression.
- the psychometric properties of commonly used depression severity scales
- data driven approaches to classifying depressive disorders
- the relationship between depression severity and treatment efficacy and tolerability
To find out more contact Isobel Cameron (firstname.lastname@example.org)
Efficacy and outcomes related to ECT
A major research focus is on electroconvulsive therapy, including clinical and bioscience investigations. A clinical trial (KANECT) explored the use of ketamine in ECT and is now complete. The KANECT trial’s latest protocol is available here: Earlier versions and a summary of amendments are available on request from Daniel Bennett.
A recent BBC documentary featured our clinical and research teams:
To find out more contact Daniel Bennett (email@example.com)
Management of depression with mobile phones
Through an EPSRC-funded, international, multidisciplinary project (http://www.trump-india-uk.org/) we are:
- employing qualitative research methods to explore the use of mobile phone technology to support the management of chronic depression in rural areas
- reviewing the research literature regarding telephone technology in the management and treatment of depression
- collaborating with computing scientists, designers, anthropologists and public health clinicians in India and UK in the design and delivery of a mobile phone intervention
- utilising case studies to initially assess the feasibility of the mobile phone intervention
To find out more contact Dr Isobel Cameron (firstname.lastname@example.org) or Dr Sinead Sheehan (email@example.com).
Measurement of facial expression using computerised methods
We are investigating facial imitation in mood disorder by measuring the capacity to:
- encode information from facial expression, and
- expressively and accurately imitate another facial expression.
Using computer vision and machine learning techniques we aim to identify behavioural signatures which are unique to mood disorder.
To find out more contact James Cusack (firstname.lastname@example.org) or Justin Williams (email@example.com)
Media portrayal of antidepressant drugs
Through an interdisciplinary CSO-funded doctoral fellowship, Nooreen Akhtar is:
- conducting sentiment analysis, involving the application of natural language processing (NLP), computational linguistics and text analysis to investigate newspaper articles covering topics related to anti-depressant medication.
- conducting interviews and focus groups with patient, public and stakeholder groups to gain insight into beliefs and attitudes relating to a range of articles on anti-depressant drugs in the treatment of depression.
To find out more contact Nooreen Akhtar (firstname.lastname@example.org) or Isobel Cameron (email@example.com)