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TechCare: Mobile-assessment and therapy for psychosis: An intervention for clients within the early intervention service

Published online by Cambridge University Press:  23 March 2020

N. Gire*
Affiliation:
University of Central Lancashire, School of Health, Preston, United Kingdom
I.B. Chaudhry
Affiliation:
The University of Manchester, Institute of Brain Behaviour and Mental Health, Manchester, United Kingdom
F. Naeem
Affiliation:
Queens University, Psychiatry, Kingston, Canada
J. Duxbury
Affiliation:
University of Central Lancashire, School of Health, Preston, United Kingdom
M. Riley
Affiliation:
Lancashire Care NHS Foundation Trust, Early Intervention Service, Preston, United Kingdom
M. McKeown
Affiliation:
University of Central Lancashire, School of Health, Preston, United Kingdom
C.D. Taylor
Affiliation:
The University of Manchester, School of Psychology, Manchester, United Kingdom
P.J. Taylor
Affiliation:
University of Liverpool, Institute of Psychology, Health & Society, Liverpool, United Kingdom
R. Emsley
Affiliation:
The University of Manchester, Institute of Population Health, Manchester, United Kingdom
N. Caton
Affiliation:
Lancashire Care NHS Foundation Trust, Early Intervention Service, Preston, United Kingdom
J. Kelly
Affiliation:
Lancashire Care NHS Foundation Trust, Early Intervention Service, Preston, United Kingdom
D. Kingdon
Affiliation:
University of Southampton, Psychiatry, Southampton, United Kingdom
N. Husain
Affiliation:
The University of Manchester, Institute of Brain Behaviour and Mental Health, Manchester, United Kingdom
*
*Corresponding author.

Abstract

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Introduction

In the UK, mental illness is a major source of disease burden costing in the region of £105 billion pounds. mHealth is a novel and emerging field in psychiatric and psychological care for the treatment of mental health difficulties such as psychosis.

Objective

To develop an intelligent real-time therapy (iRTT) mobile intervention (TechCare) which assesses participant's symptoms in real-time and responds with a personalised self-help based psychological intervention, with the aim of reducing participant's symptoms. The system will utilise intelligence at two levels:

– intelligently increasing the frequency of assessment notifications if low mood/paranoia is detected;

– an intelligent machine learning algorithm which provides interventions in real-time and also provides recommendations on the most popular selected interventions.

Aim

The aim of the current project is to develop a mobile phone intervention for people with psychosis, and to conduct a feasibility study of the TechCare App.

Methods

The study consists of both qualitative and quantitative components. The study will be run across three strands:

– qualitative work;

– test run and intervention refinement;

– feasibility trial.

Results

Preliminary analysis of qualitative data from Strand 2 (test run and intervention refinement) in-depth interviews with service users (n = 2) and focus group with health professionals (n = 1), highlighted main themes around security of the device, multimedia and the acceptability of psychological interventions being delivered via the TechCare App.

Conclusions

Research in this area can be potentially helpful in addressing the demand on mental health services globally, particularly improving access to psychological interventions.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Type
EV1289
Copyright
Copyright © European Psychiatric Association 2016
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