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A randomised controlled trial of smartphone active symptom monitoring in psychosis

  • Shôn Lewis
  • , Paolo Fraccaro
  • , John Ainsworth
  • , Matthew Machin
  • , Caroline Sanders
  • , Zhimin He
  • , Pauline Whelan
  • , Charlotte Stockton-Powdrell
  • , Richard Hopkins
  • , Til Wykes

    Research output: Contribution to Journal › Article › peer-review

    Abstract

    Background: We developed a smartphone-based personalised technology to
    monitor symptoms in real time and showed good acceptability, reliability
    and validity for active remote monitoring of symptoms in previous published studies (www.clintouch.com). We report a randomised trial testing
    its efficacy in improving psychotic symptom control, and its potential as
    an early warning system for relapse when embedded into the ICT systems
    of mental health provider organisations, and as a tool for identifying new
    phenotypes for precision medicine.
    Methods: Participants with SMI receive a semi-random beep 2–4 times
    per day on their smartphone app and answer 14 key symptom rating items
    using a touchscreen slider. Responses are uploaded wirelessly in real time
    to a central server and build into a graphical readout on the handset, allowing active symptom monitoring and attempts at self-management. We built
    this into an end-to-end system in two NHS Hospital Trusts (Manchester
    and South London) to stream data into electronic care records and enable
    detection by the clinical team of early signs of relapse in people with SMI
    when key symptoms exceeded a personalised severity threshold. We conducted an open randomised controlled trial of this active symptom monitoring (ASM) using the smartphone app compared to usual management
    with the aim of assessing: (i) acceptability of continuous monitoring over
    3 months; (ii) impact of active self-monitoring on PANSS positive symptoms and Empowerment Rating Scale score assessed at 6 and 12 weeks; (iii)
    efficiency of detecting early warning signs of relapse. Eligible participants
    with a DSM5 diagnosis of schizophrenia and related disorders and a history of relapse within the previous two years were included from an early
    intervention team (early psychosis group) and a community team (chronic
    psychosis group).
    Results: Of 181 eligible, 81 were randomised to either active symptom
    monitoring or management as usual. 90% stayed in the trial for 12 weeks.
    Of the 38 in the ASM arm who completed 12-week follow up, adherence
    defined as responding to >33% of alerts was 84%, >50% of alerts was 60%.
    At 12 weeks, ASM compared to usual management was associated with no
    difference on empowerment scale. PANSS positive subscale score showed
    a significant mean reduction in the ASM group over 12 weeks in the early
    psychosis group (n= 22, planned ANCOVA p<0.02), but no effect in the
    chronic psychosis group (n=19). Early warning sign alerts generated by the
    system occurred in 92% of cases and blind comparison with electronic case
    record data suggested good sensitivity and lower specificity, but with clear
    indications of how to adjust the gain of the system to improve future eventdetection efficiency. Multivariate analyses pointed to the ability of the system to identify clinical subtypes.
    Discussion: The active smartphone monitoring system is feasible and
    acceptable over three months in people with schizophrenia and related disorders. It was associated with psychotic symptom improvement in recent
    onset participants, supporting the notion of improved self-management.
    When built into clinical management workflows to enable personalised
    alerts of symptom deterioration, it was shown to have potential use in promoting earlier intervention for relapse.
    Original languageEnglish
    Pages (from-to)S106
    JournalSchizophrenia Bulletin
    Volume44
    Issue numbersuppl_1
    DOIs
    Publication statusPublished - 1 Apr 2018

    Keywords

    • Psychosis
    • mHealth
    • RCT

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