Trial reportHealth technology assessment (Winchester, England)2022
Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT.
Trial report in Health technology assessment (Winchester, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 5 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Digital Therapeutics for People with Schizophrenia Spectrum Disorders: A Systematic Literature Review of Their Effect on Symptoms and Functioning.Schizophrenia bulletin · 2026Pooled it
- Digital phenotyping and digital monitoring technologies for relapse detection in mental health: a systematic review.BMC psychiatry · 2026Pooled it
- Efficacy of User Self-Led and Human-Supported Digital Health Interventions for People With Schizophrenia: A Systematic Review and Meta-Analysis.Schizophrenia bulletin · 2025Pooled it
- The impact of mobile health interventions on patients with schizophrenia: a meta-analysis.Frontiers in psychiatry · 2025Pooled it
- Characteristics and Outcomes of mHealth Interventions in Psychosis: Systematic Mapping Review.Journal of medical Internet research · 2024Pooled it
- Response to Lewis et al. (2026): Clarifying the comparative characterization of EMPOWER in the ILIA study protocol.European archives of psychiatry and clinical neuroscience · 2026Article
- Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study.JMIR research protocols · 2026Article
- Explainable artificial intelligence (XAI) in schizophrenia: enhancing transparency in clinical decision-making.Frontiers in systems biology · 2026Review
- Schizophrenia.Nature reviews. Disease primers · 2025Review
- Active remote monitoring of long-term conditions with mobile devices: a systematic review of cost-effectiveness analyses.NPJ digital medicine · 2025Article
- Effects of motivational and early warning nursing on wound healing and socio-psychological adaptability in hepatobiliary surgical patients.World journal of gastrointestinal surgery · 2025Article
- Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review.JMIR mental health · 2024Article
- Potential Increasing Trend in Schizophrenia Relapse Prevention in the Past 40 Years: A Bibliometric Analysis.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024Review
- Co-Production of a Flexibly Delivered Relapse Prevention Tool to Support the Self-Management of Long-Term Mental Health Conditions: Co-Design and User Testing Study.JMIR formative research · 2024Article
- The Impact of Intervention Design on User Engagement in Digital Therapeutics Research: Factorial Experiment With a Mixed Methods Study.JMIR formative research · 2024Article
- The Safety of Digital Mental Health Interventions: Systematic Review and Recommendations.JMIR mental health · 2023Review
- Digital tools to support mental health: a survey study in psychosis.BMC psychiatry · 2023Article
- Perception of risk of relapse among patients with first episode and recurrent schizophrenia: a descriptive phenomenological study.BMC psychiatry · 2023Article
- Identifying and Categorizing Adverse Events in Trials of Digital Mental Health Interventions: Narrative Scoping Review of Trials in the International Standard Randomized Controlled Trial Number Registry.JMIR mental health · 2023Article
- PERCEPTIONS AND EXPERIENCES OF M-HEALTH TECHNOLOGIES AND SOCIAL MEDIA: A QUALITATIVE STUDY IN PATIENTS WITH SCHIZOPHRENIA.Health psychology research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
30 authors at 15 institutions in 3 countries.
Funding
Abstract
backgroundRelapse 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.
objectiveHow 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?
designA 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.
participantsService 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.
interventionsThe 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 measuresThe 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.
resultsWe 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.
conclusionsA 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 registrationThis trial is registered as ISRCTN99559262.
fundingThis project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in
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