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Active Assistance for Psychological Therapy (Actissist): A digital intervention for co-producing care in psychosis

Published on: 21st December 2016

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Case Study 24
Citizen Driven Health

Principal Investigator: Dr Sandra Bucci, The University of Manchester, Technical Leads: Prof. John Ainsworth and Mr Matthew Machin, The University of Manchester

The Challenge

Severe mental health problems such as schizophrenia affect 24 million people worldwide. Psychosis typically develops in early adulthood and up to 80% of patients relapse within 5-years.

Treating psychosis effectively is a complex process that takes time and requires a lot of resource. If the symptoms of psychosis are not addressed quickly then treatment can be challenging and ultimately lead to worse outcomes for patients and their families.

There is an increasing need to develop innovative solutions that improve the speed and quality of recovery in psychosis beyond those offered by conventional treatments. The challenge is to:

  1. Deliver more effective, efficient psychological treatments at the point-of-need to overcome limitations in existing practice and improve the speed and quality of recovery over and above existing drug treatments.
  2. Increase access to psychological therapies that encourage patients to better self-manage their symptoms and ensure early signs of relapse are identified and treated in a timely manner.

The Research

A team of researchers at The University of Manchester worked with service users and other stakeholders to co-design a smartphone app that uses academic theory to help support patients. The 12-week digital intervention works by:

  • helping patients better identify the early warning signs of psychosis;
  • delivering treatment at the point that it is needed most;
  • improving the patient’s ability to function day-to-day;
  • enhancing the patients overall quality of life; and
  • potentially reducing demand on NHS services.

By applying a patient-centred approach Actissist delivers timely, personalised care that reduces the risk of distressing psychotic experiences.

The Results

Actissist was used in a small study with 24 patients to make sure that it is safe, practical and accepted by patients as an effective way to treat psychotic and other distressing experiences.

The research showed that patients were comfortable with using Actissist to the extent that uptake of the app was higher and drop-out rates lower than face-to-face and other computerized psychological packages.

In addition, the research team found the app led to statistically significant improvements in patient outcomes at the end of treatment, in comparison with a control group of patients who used a symptom-monitoring app. When looked at in detail, researchers found high rates of acceptability and other individual benefits for patients as a result of the intervention.

The Impact

This research has the potential for broad-ranging impact with benefits to patients, the NHS, healthcare professionals, the national and international scientific communities, and government policies.

As Actissist is a platform technology that can be applied to a range of both mental and physical health problems, this research is of keen interest to healthcare academics as well as computer scientists and informaticians across institutions worldwide.

Furthermore, this research helps further advance and understand how technology can help deliver new health and care treatments. Actissist is unique in applying comprehensive and theory-driven clinical techniques to digital treatments, delivered in real-time, to patients with severe mental health problems. By using rigorous scientific methods, the app allows other innovators to develop further mental health interventions using the Actissist model.

Finally, as self-management is a cornerstone of NHS policy, this research addresses established NHS England priorities in the area of severe mental health treatment policy.

Find out more: www.research.bmh.manchester.ac.uk/actissist

Enquiries to Stephen Melia, Communication Lead, Health eResearch Centre, stephen.melia@manchester.ac.uk

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