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 JournalArticlepeer-review


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
Issue numbersuppl_1
Publication statusPublished - 1 Apr 2018


  • Psychosis
  • mHealth
  • RCT


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