Detecting relapse in schizophrenia using remote sleep monitoring.
Research type
Research Study
Full title
Detecting relapse in schizophrenia using remote sleep monitoring - a feasibility and acceptability study.
IRAS ID
168023
Contact name
James MacCabe
Contact email
Sponsor organisation
King's College London
Duration of Study in the UK
0 years, 8 months, 30 days
Research summary
Around 80% of individuals who develop schizophrenia will experience at least one further episode within five years of the first episode. Each episode of relapse carries serious implications for the sufferer and their carers. Early detection and prevention are therefore important goals in reducing the burden associated with schizophrenia, however no clinically useful, objective methods of detecting relapse exist.
There is clinical consensus that sleep disturbance is commonly observed in relapse, and monitoring of sleep-wake activity may therefore serve as an effective early warning sign. Unobtrusive sensors that are worn on the body are becoming increasingly cost-effective and widely available, and show promise in being able to detect dynamic changes in behaviours such as sleep. Together with a smartphone, data can be transmitted to the care team from the patient’s home, on a real-time basis, raising the possibility of timely interventions that prevent further deterioration.
We will monitor sleep-wake patterns using a proprietary, commercially available wrist-worn activity tracker (a Fitbit) communicating wirelessly with a smartphone. We have developed a software application on the smartphone consisting of a sleep diary and symptom diary. Data will be uploaded automatically and securely via the smartphone to the research team. Sixteen consenting patients with stable schizophrenia who are living in their homes will be asked use the system continuously for two months. The primary objectives are to test the feasibility and acceptability of the technology in patients, and to improve the system such that it can be used in a larger scale study sleep monitoring in detecting relapse. The secondary objectives are to investigate how sleep-wake patterns are associated with clinical variables such as severity of symptoms and medication. The present study does not seek to capture relapse, and is not powered to do so.
REC name
London - Dulwich Research Ethics Committee
REC reference
15/LO/0673
Date of REC Opinion
26 May 2015
REC opinion
Further Information Favourable Opinion