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Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support

Authors :
Gumley, Andrew
Bradstreet, Simon
Ainsworth, John
Allan, Stephanie
Alvarez-Jimenez, Mario
Beattie, Louise
Bell, Imogen
Birchwood, Max
Briggs, Andrew
Bucci, Sandra
Castagnini, Emily
Clark, Andrea
Cotton, Sue M
Engel, Lidia
French, Paul
Lederman, Reeva
Lewis, Shon
Machin, Matthew
MacLennan, Graeme
Matrunola, Claire
McLeod, Hamish
McMeekin, Nicola
Mihalopoulos, Cathrine
Morton, Emma
Norrie, John
Reilly, Frank
Schwannauer, Matthias
Singh, Swaran P
Smith, Lesley
Sundram, Suresh
Thomson, David
Thompson, Andrew
Whitehill, Helen
Wilson-Kay, Alison
Williams, Christopher
Yung, Alison
Farhall, John
Gleeson, John
Source :
JMIR Research Protocols, Vol 9, Iss 1, p e15058 (2020)
Publication Year :
2020
Publisher :
JMIR Publications, 2020.

Abstract

BackgroundRelapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions. ObjectiveThis study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial. MethodsWe will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support. ResultsRecruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation. ConclusionsThe knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial. Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 99559262; http://isrctn.com/ISRCTN99559262 International Registered Report Identifier (IRRID)DERR1-10.2196/15058

Details

Language :
English
ISSN :
19290748
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
JMIR Research Protocols
Publication Type :
Academic Journal
Accession number :
edsdoj.bc867fcf959b4d56a70b15f0cfbe2ca6
Document Type :
article
Full Text :
https://doi.org/10.2196/15058