Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT

Author:

Gumley Andrew I1ORCID,Bradstreet Simon1ORCID,Ainsworth John2ORCID,Allan Stephanie1ORCID,Alvarez-Jimenez Mario34ORCID,Birchwood Maximillian5ORCID,Briggs Andrew6ORCID,Bucci Sandra27ORCID,Cotton Sue3ORCID,Engel Lidia8ORCID,French Paul9ORCID,Lederman Reeva10ORCID,Lewis Shôn27ORCID,Machin Matthew11ORCID,MacLennan Graeme12ORCID,McLeod Hamish1ORCID,McMeekin Nicola1ORCID,Mihalopoulos Cathy8ORCID,Morton Emma13ORCID,Norrie John14ORCID,Reilly Frank15ORCID,Schwannauer Matthias16ORCID,Singh Swaran P5ORCID,Sundram Suresh17ORCID,Thompson Andrew35ORCID,Williams Chris1ORCID,Yung Alison2ORCID,Aucott Lorna12ORCID,Farhall John1819ORCID,Gleeson John20ORCID

Affiliation:

1. Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK

2. Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

3. Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia

4. Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia

5. Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK

6. Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK

7. Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK

8. School of Health and Social Development, Deakin University, Melbourne, VIC, Australia

9. Department of Nursing, Manchester Metropolitan University, Manchester, UK

10. School of Computing and Information Systems, Melbourne School of Engineering, University of Melbourne, Melbourne, VIC, Australia

11. Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

12. Health Services Research Unit, University of Aberdeen, Aberdeen, UK

13. Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada

14. Usher Institute, University of Edinburgh, Edinburgh, UK

15. Scottish Recovery Network, Glasgow, UK

16. School of Health in Social Science, University of Edinburgh, Edinburgh, UK

17. Department of Psychiatry, Monash University, Melbourne, VIC, Australia

18. Department of Psychology and Counselling, La Trobe University, Melbourne, VIC, Australia

19. NorthWestern Mental Health, Melbourne, VIC, Australia

20. Healthy Brain and Mind Research Centre, Australian Catholic University, Melbourne, VIC, Australia

Abstract

Background Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse. Objective How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? Design A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up. Settings Glasgow, UK, and Melbourne, Australia. Participants Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user. Interventions The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted. Main outcome measures The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse. Results We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference –4.29, 95% confidence interval –7.29 to –1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained. Limitations This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness. Conclusions A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible. Future work A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3–0.4). Trial registration This trial is registered as ISRCTN99559262. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879).

Funder

Health Technology Assessment programme

National Health and Medical Research Council

Publisher

National Institute for Health and Care Research (NIHR)

Subject

Health Policy

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