Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT.
Health Technol Assess
; 26(27): 1-174, 2022 05.
Article
in En
| MEDLINE
| ID: mdl-35639493
ABSTRACT
WHAT WAS THE PROBLEM?: Relapse is a considerable problem for people with a diagnosis of schizophrenia. Relapse can be predicted by early warning signs that are unique to the person. They include withdrawal, fear and paranoia. WHAT WAS THE QUESTION?: Is it possible to investigate the effectiveness of an intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? WHAT DID WE DO?: We spoke with 88 mental health staff, 40 carers and 21 service users before we designed a system that used a mobile phone to help people monitor early warning signs. We included peer support to help people using the system reflect on their experiences. We hoped the overall system, called EMPOWER, would help people to be more in charge of their mental health. After consenting 86 people to the study, we were able to randomly assign 73 people either to use the EMPOWER system (42 people) or to receive their normal treatment alone (31 people). We used research measures over 1 year to help us better understand people's experiences. We also involved carers (for example family or friends) and mental health service providers in the research. WHAT DID WE FIND?: We found that it was possible to recruit people to the study and to gather research data. We also found that people used the EMPOWER system and found it acceptable. We found that those who used EMPOWER had a lower rate of relapse over 12 months than people who did not. They were also less likely to be fearful of relapse. We found that EMPOWER was likely to be cost-effective. WHAT DOES THIS MEAN?: This means that a study to investigate the effectiveness of a system to recognise and respond to early warning signs of relapse in schizophrenia is possible.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Psychotic Disorders
/
Schizophrenia
Type of study:
Clinical_trials
/
Diagnostic_studies
/
Etiology_studies
/
Health_technology_assessment
/
Prognostic_studies
Aspects:
Patient_preference
Limits:
Humans
Language:
En
Journal:
Health Technol Assess
Journal subject:
PESQUISA EM SERVICOS DE SAUDE
/
TECNOLOGIA MEDICA
Year:
2022
Document type:
Article
Affiliation country:
Country of publication: