SlowMo, a digital therapy targeting reasoning in paranoia, versus treatment as usual in the treatment of people who fear harm from others: study protocol for a randomised controlled trial
Garety et al. Trials
SlowMo, a digital therapy targeting reasoning in paranoia, versus treatment as usual in the treatment of people who fear harm from others: study protocol for a randomised controlled trial
Philippa A. Garety 0 1 3
Thomas Ward 0 1 3
Daniel Freeman 2
David Fowler 6 7
Richard Emsley 5
Graham Dunn 5
Elizabeth Kuipers 1 3
Paul Bebbington 4
Helen Waller 0 1 3
Kathryn Greenwood 6 7
Mar Rus-Calafell 2 8
Alison McGourty 6
Amy Hardy 0 1 3
0 South London and Maudsley NHS Foundation Trust , London , UK
1 Department of Psychology, King's College London, Institute of Psychiatry, Psychology and Neuroscience , P077 Henry Wellcome Building, De Crespigny Park, London SE5 8AF , UK
2 Department of Psychiatry, Oxford University , Oxford , UK
3 Department of Psychology, King's College London, Institute of Psychiatry, Psychology and Neuroscience , P077 Henry Wellcome Building, De Crespigny Park, London SE5 8AF , UK
4 Division of Psychiatry, University College London , London , UK
5 Centre for Biostatistics, School of Health Sciences, The University of Manchester, Manchester Academic Health Science Centre , Manchester , UK
6 Sussex Partnership NHS Foundation Trust , Worthing , UK
7 School of Psychology, University of Sussex , Brighton , UK
8 Oxford Health NHS Foundation Trust , Oxford , UK
Background: Paranoia is one of the most common symptoms of schizophrenia-spectrum disorders, and is associated with significant distress and disruption to the person's life. Developing more effective and accessible psychological interventions for paranoia is a clinical priority. Our research team has approached this challenge in two main ways: firstly, by adopting an interventionist causal approach to increase effectiveness and secondly, by incorporating user-centred inclusive design methods to enhance accessibility and usability. Our resultant new digital intervention, SlowMo, intensively targets a reasoning style associated with paranoia, fast thinking, characterised by jumping to conclusions and belief inflexibility. It consists of an easy-to-use, enjoyable and memorable digital interface. An interactive web-based app facilitates delivery of face-to-face meetings which is then synchronised with an innovative mobile app for use in daily life. Methods/Design: We aim to test the clinical efficacy of SlowMo over 24 weeks to determine the mechanisms through which it reduces paranoia, and to identify participant characteristics that moderate its effectiveness. In a parallel-group randomised controlled trial, with 1:1 allocation, 360 participants with distressing persecutory beliefs will be independently randomised to receive either the SlowMo intervention added to treatment as usual (TAU) or TAU, using randomly varying permuted blocks, stratified by paranoia severity and site. Research workers will be blind to therapy allocation. The primary outcome is paranoia severity over 24 weeks; our hypothesised mechanism of change is reasoning; moderators include negative symptoms and working memory; and secondary outcomes include wellbeing, quality of life, and service use. The accessibility, usability and acceptability of the digital platform will be assessed. (Continued on next page)
(Continued from previous page)
Discussion: SlowMo has been developed as the first blended digital therapy to target fears of harm from others through
an inclusive design approach. In addition to testing its efficacy, this trial will add to our understanding of
psychological mechanisms in paranoia. The study will examine the usability and adherence of a novel digital
therapy, including an app for self-management, in a large sample of people affected by severe mental health
Trial registration: ISRCTN registry, ID: ISRCTN32448671. Registered prospectively on 30 January 2017. Date
assigned 2 February 2017.
People often experience distressing fears about other
people intentionally causing them harm: this is known as
]. The severity of paranoia lies on a continuum,
ranging from fleeting ideas that someone on the street
might be laughing at us, to more elaborate and persistent
beliefs (sometimes called persecutory delusions) such as
that the secret services are trying to have us killed.
Paranoia is one of the most common symptoms of
schizophrenia-spectrum disorders, and is associated with
significant distress and disruption to the person’s life [
This results in increased use of services, including
inpatient admissions, and high costs to mental health care
providers. Developing effective interventions for paranoia
is, therefore, a clinical priority. The National Institute for
Health and Care Excellence (NICE; 2014) recommends
cognitive-behavioural therapy for psychosis (CBTp),
including paranoia [
]. However, there are significant
challenges to access, engagement, adherence and effectiveness
]. CBTp has relatively high training and delivery costs,
which limits availability. Even when it is offered, people
may be reluctant to engage in therapy, and can struggle to
remember what is discussed or apply new learning to daily
life. Recent meta-analytical studies of CBTp have found
small- to medium-sized beneficial effects on paranoia, and
a pressing need to improve outcomes has been identified
]. Our research team has approached this challenge in
two main ways: firstly by adopting an interventionist
causal approach [
] to increase CBTp effectiveness and
secondly by incorporating user-centred inclusive design
methods to enhance accessibility and usability. Our
resultant new digital intervention, SlowMo, aims to improve the
appeal, ease of use, memorability and clinical effectiveness
of psychological therapy for people who fear harm from
The interventionist causal approach to improving
therapy effectiveness involves first identifying mechanisms
that play a causal role in paranoia (e.g. reasoning, worry,
negative self-beliefs, safety behaviours and sleep
dysfunction) and then developing tailored interventions to target
these causal processes [
]. These targeted interventions
are anticipated to reduce paranoia severity through
different pathways given the multifactorial causality of paranoia.
For example, a recent randomised controlled trial of a
brief intervention focussed on worry processes
demonstrated that reductions in this mechanism accounted for
improvements in paranoia . In contrast, SlowMo
works by intensively targeting a certain type of thinking
associated with paranoia, which can be thought of as fast
]. Fast thinking is characterised by
focussing on too little information (‘jumping to conclusions’)
and belief inflexibility (high conviction in thoughts and a
lack of consideration of alternative ideas [
]). It has been
robustly linked to paranoia [
attempts to modify this style of reasoning include
groupbased, metacognitive training (MCT) and, more recently,
individual training (MCT+) developed by Moritz and
]. Whilst earlier findings for MCT were
promising, more robust designs have not shown consistent
improvements in reasoning, or paranoia at long-term
follow-up, particularly for those with more severe
The SlowMo intervention builds on the important
work of Moritz and colleagues and is the endpoint of a
decade of development and testing in four studies
targeting fast thinking in paranoia [
]. The first
versions of the intervention were tested iteratively, in three
randomised studies and one case series, with
developments over time in intervention content, duration and
name, whilst always targeting aspects of fast thinking
and paranoia [
]. We found reductions in
unhelpful fast thinking and improvements in paranoia
severity. In an experimental study [
] designed to
examine mediation, we found preliminary evidence that
changes in belief flexibility mediated improvements in
paranoia. Most recently, in a feasibility randomised
controlled trial, 31 participants with paranoia were recruited
and randomly allocated 2:1 to the Thinking Well
intervention or treatment as usual (TAU) [
intervention involved face-to-face sessions with a therapist,
initially working on a brief computer-based programme
targeting reasoning biases [
] followed by four additional
therapy sessions (with no additional digital component)
aimed at generalising the learning to real-world situations.
We found reductions in fast thinking (belief flexibility and
jumping to conclusions) and promisingly large effects
(effect size d = 1.1) on paranoia severity. However,
assessments were not blinded and the sample size was small.
Further, whilst the acceptability of the intervention was
high, participants suggested ways in which the
intervention could be made more personalised, enjoyable and
applicable to daily life. Our experimental work also indicated
that people with more working memory difficulties and
negative symptoms benefitted less from the therapy. This
current iteration (SlowMo) shares the focus on reasoning
of its predecessors (Maudsley Review Training
] and Thinking Well [
]). However, whilst
previous versions of the intervention relied on verbal
presentation of material using PowerPoint and pen-and-paper
tools, SlowMo uses a website and app for interactive,
multimodal communication of information, together with
consistent use of normalising (everyday) language.
Incorporating digital technologies into psychological
interventions presents unique opportunities for
improving outcomes, understanding mechanisms of change and
reducing costs [
]. However, to deliver meaningful
change in health care, digital solutions need to be
tailored to meet the specific needs of their users and to be
trustworthy with regard to safety, privacy and
]. To meet this challenge, the development
of SlowMo therapy has involved a user-centred inclusive
design approach. Inclusive design aims to address the
needs of the broadest range of users possible, a crucial
issue given the heterogeneity of psychosis. Our design
approach was informed by the Design Council’s double
diamond method , which comprises the following
phases: discover, define, develop and deliver.
Importantly, stakeholders (service users, clinicians, researchers,
technologists, innovation design engineers), including
sampling of ‘extreme’ users [
], were involved from the
outset, with iterative exploration, prototype testing and
feedback informing the design and development of
SlowMo aims to assist people with paranoia by
supporting them to notice their upsetting concerns and
fast-thinking habits, and then providing them with
strategies to slow down for a moment in order to focus on
new information and develop safer thoughts [
consists of an easy-to-use, enjoyable and memorable digital
interface. Thoughts are visualised as bubbles, with
different speeds, sizes and colours reflecting different thinking
habits, intensities of emotion and coping tips. This
simple visual metaphor aims to help people to understand
that thoughts are transient, and that we can modify
them by using coping strategies. Based on session
content from earlier work, an interactive web-based app
facilitates the delivery of face-to-face meetings. This is
then synchronised with an innovative, mobile app for
use in daily life, which is ‘native’ (i.e. one that runs on
the phone and can work offline). Feasibility testing of an
early prototype has been conducted with acceptability,
usability and enjoyment assessed through a self-report
10-item User Experience Survey, adapted from use in a
previous study examining the feasibility of a mobile app
for the management of psychosis [
]. The measure
generates a mean percentage for each dimension of user
experience, ranging from 0 (totally disagree) to 100 (totally
agree). Results were extremely positive, with high rates
of acceptability, usability and enjoyment (>75%).
Participants indicated that they significantly preferred the
digital interface to conventional therapy materials. This
is particularly encouraging in the context of digital
interventions given recent evidence that overall uptake of a
therapeutic app for psychosis delivered in a naturalistic
setting was low [
]. Given these data on the digital
interface, together with the proof-of-concept, feasibility
and acceptability evidence from our four preliminary
], we are now well placed to test the
SlowMo intervention in a fully powered, larger,
methodically rigorous, multisite randomised controlled trial.
We aim to test the clinical efficacy of SlowMo over
24 weeks compared to TAU to determine the
mechanisms through which it reduces paranoia, and to identify
participant characteristics that moderate its effectiveness
(either by moderating the degree of change in the
mechanism, or by influencing adherence to the intervention).
We will test the hypothesis that changes in fast thinking
mediate changes in our primary outcome of paranoia
severity. Consistent with our interventionist causal
approach, we do not hypothesise that worry is a mediator,
as it is not targeted in the SlowMo intervention, even
though changes in worry did mediate changes in
paranoia in a recent trial, when it was the treatment target
]. However, we will examine any observed effects. In
addition, we have preliminary evidence of modifiers of
treatment effects that we will also take the opportunity
to investigate. Using a randomised controlled trial
design, we have selected TAU as the comparator condition.
This is because there is a very low penetration of
evidence-based psychological treatment in the NHS, and
thus the key efficacy question to address at this stage is
whether SlowMo confers benefits over and above
standard care. An important secondary goal is to evaluate
mechanisms of action; the trial hypotheses concern
reasoning, and are best tested where the control
condition is inactive with respect to the targeted
The main research questions are as follows:
1. Is SlowMo efficacious in reducing paranoia severity
over 24 weeks, when added to TAU, in comparison
to TAU alone?
2. Does SlowMo reduce paranoia severity by improving
fast thinking (reducing belief inflexibility and
jumping to conclusions)?
3. Do participant characteristics (i.e. their cognitive
capacities, specifically working memory and thinking
habits; and their symptoms, specifically negative
symptoms) moderate the effects of the intervention?
4. Does outcome differ by adherence to the
intervention and is adherence predicted by the
participants’ beliefs about their illness and about the
5. Does the SlowMo digital therapy platform have
acceptable rates of usability, acceptability and
6. Does SlowMo lead to changes in the following
secondary outcomes: other delusional symptoms,
wellbeing, quality of life, self and others schemas,
service use and worry
1. The intervention will reduce paranoia severity over
2. Fast thinking (belief inflexibility and jumping to
conclusions) will improve in response to the
3. Reductions in fast thinking will mediate positive
change in paranoia severity
4. Poorer working memory and more severe negative
symptoms will negatively moderate treatment effects
5. Therapy adherence will moderate the effects of
treatment on outcome and adherence will be
predicted by beliefs about mental health problems
6. Worry will not mediate reductions in paranoia
The study design is a parallel-group randomised
controlled trial, with 1:1 allocation. Participants with
distressing persecutory beliefs who meet the inclusion
criteria (see below) will be independently randomised to
receive either the SlowMo intervention added to TAU,
or TAU. Independent randomisation (centrally
administered independently of the trial team by the King’s
Clinical Trials Unit (CTU)) will use an online system
generating randomly varying permuted blocks, stratified
by site and baseline paranoia severity. Stratification by
paranoia severity will use a median split of ≥ 62 (Green
Paranoid Thoughts Scale (GPTS) part B [
] based on
data from [
]). Research workers will be blind to
therapy allocation, to facilitate completion of unbiased and
objective assessments. Adherence to the blindness
procedure will be supported by the research coordinator
and therapists having responsibility for the
randomisation process and informing participants of
randomisation outcome. Further, the blinding procedure will be
explained to participants and they will be reminded not
to inform research workers of therapy allocation. Breaks
in blinding will be monitored and recorded. Embedded
within the design will be measures to elucidate how the
treatment works. For reporting the trial, the CONSORT
(Consolidated Standards of Reporting Trials; http://
www.consort-statement.org/) Statement will be followed,
with consideration of the mHealth evidence reporting
and assessment (mERA) [
] and CONSORT-EHEALTH
]. For the protocol, the SPIRIT (Standard
Protocol Items: Recommendations for Interventional
]) Checklist and Figure are provided in this
paper see: Additional file 1.
The inclusion criteria are as follows: aged 18 years and
over; persistent (3 + months) distressing paranoia (as
assessed using the Schedules for Clinical Assessment in
Neuropsychiatry (SCAN, [
]) and scoring > 29 on the
GPTS, part B, persecutory subscale [
]; diagnosis of
schizophrenia-spectrum psychosis (F20-29, ICD-10
]); capacity to provide informed consent; sufficient
grasp of English to participate in informed consent
process, assessments and interventions.
Criteria for exclusion are as follows: profound visual
and/or hearing impairment; inability to engage in the
assessment procedure; currently in receipt of other
psychological therapy for paranoia; primary diagnosis of
substance abuse disorder, personality disorder, organic
syndrome or learning disability.
Mobile ownership is not a criterion for participation,
as android smartphones with the SlowMo mobile app
will be provided.
Participants will be recruited from mental health
services across three main trial sites in England with the
same procedures followed at each site: South London
and Maudsley NHS Foundation Trust, Sussex
Partnership NHS Foundation Trust and Oxford Health NHS
Foundation Trust. Up to six additional Patient
Identification Centres, comprising NHS trusts
geographically near to the main recruitment trust sites, will be
used as required.
Figure 1 illustrates the trial/recruitment flowchart.
Planned trial interventions
SlowMo therapy consists of eight individual, face-to-face
sessions, of 60–90 min, delivered by trained therapists
within a 12-week timeframe, assisted by a web-based
app hosted on a touchscreen laptop, with interactive
personal accounts and tasks. Initial sessions involve
building the meta-cognitive skill of noticing thoughts
and thinking habits (visualised as bubbles spinning faster
or more slowly). People learn that everyone thinks fast
at times, and this can be useful. However, thinking
slowly can be helpful in dealing with stress and fears
about other people. This key principle frames the
sessions in which people are supported to try out tips to
slow down for a moment, e.g. by considering the impact
of mood and past experiences on concerns and by
looking for safer alternative explanations. There is an
emphasis throughout the intervention on practising the
skills inside and outside sessions. Participants build
confidence in managing paranoia, feeling safer in their daily
life and working towards a valued goal. The overall
session structure is fixed, but individual content is
personalised throughout as participants record their
individual worries, ways of feeling safer, key learning from
each session, and a message for the week ahead. All of
the personalised session content is synchronised with a
native mobile app installed on a standard android
smartphone to assist therapy generalisation into daily life. This
allows people to notice their fears and thinking habits,
and supports them to slow down for a moment, by
providing strategies, encouraging them to audio- or
textrecord helpful new information and to generate safer
thoughts. Recorded information is stored in a format
whereby, when experiencing recurrent concerns, people
can readily access what was previously useful. Optional
notifications are available if people wish the app to
check-in with them. The app is specifically designed for
offline use, to minimise concerns about privacy and
security. Participants are not given standardised
instructions about when to use the app, rather the emphasis is
on tailoring usage according to what is most helpful for
the individual. Use of the app is monitored objectively
through data input and system analytics. Please see Fig. 2
for an overview of the main SlowMo screens.
Referral identified & screened
Client agrees to meet
Assess eligibility and capacity to consent, complete
Client does not agree to meet
Consent not given
Baseline assessments completed
Randomised to intervention group
(SlowMo + TAU) (n = 180)
Randomised to control group
(TAU) (n = 180)
Receive 8 session SlowMo
followup assessment at 12 weeks
followup assessment at 24 weeks
Control group follow-up
assessment at 12 weeks
Control group follow-up
assessment at 24 weeks
Fig. 1 SlowMo trial design and recruitment flowchart
The development work has been done by Evolyst
Ltd., a user-centred and evidence-based health care
software development company. The design and
development of the app has been informed by the
British Standards Institute quality criteria and code of
practice for health care apps (BSI; [
]). SlowMo uses
a proprietary software platform developed using an
Azure-based WCF (Windows Communication
Foundation) Web Service, acting as an Application
Programming Interface (API) to a Model View Controller
(MVC) Asp.Net Web application; and a
Xamarin.Android-based mobile application, allowing for use of
the full Microsoft Stack and negating interoperability
issues. SlowMo has currently been developed as a
standalone product, given the lack of consensus on
operating systems across the NHS trusts, and current
TAU is care delivered to both randomised groups,
according to national and local service protocols and
best practice guidelines (specifically, NICE guidance
on community mental health treatment for people
with psychosis and the standards of community care
required by the national regulators). Participation will
not alter usual treatment decisions about medication
and additional psychosocial interventions which
remain the responsibility of the clinical team. A
modified version of the Client Service Receipt
] will be used to measure service use.
Antipsychotic medication data will be extracted from
medical records and dosages converted into
Assessments and follow-up
Assessment of efficacy
Participants will complete a range of self-report and
interview-based measures to assess the impact of the
interventions on primary and secondary outcomes, the
hypothesised mediators, and other key processes
implicated in paranoia and response to therapy. Assessments
will be completed at baseline, 12 and 24 weeks. Every
effort will be made to ensure that data collection and
completeness is optimised throughout the trial, and to
minimise attrition/loss to follow-up. Please refer to Fig. 3
(SPIRIT Figure) for details of assessment at each visit.
Assessments will be audio-taped (after first establishing
consent) to allow evaluation of adherence to the
research protocol and assessment ratings.
The primary outcome is paranoia severity measured
by the GPTS [
] over 24 weeks. The GPTS comprises
two scales assessing thinking relevant to paranoia: ideas
of social reference and persecution, rated over the
preceding month. Each item is scored on a five-point Likert
scale from 1 (‘not at all’) to 5 (‘totally’). A total score can
be calculated ranging from 32 to 160, with higher scores
reflecting higher levels of paranoia. Two 16-item
subscales assess ideas of social reference (part A) and
persecution (part B) relevant to paranoia.
Other paranoia outcomes:
Fig. 3 Standard Protocol Items: Recommendations for Interventional Trial (SPIRIT) Figure. A digital therapy for people who fear harm from others
(SlowMo): schedule of enrolment, interventions and assessments
1. The Psychotic Symptom Rating Scales-Delusions
]), consisting of six items
which assess the following dimensions of delusions:
amount of preoccupation with delusions, duration of
preoccupation with delusions, conviction, amount of
distress, intensity of distress and disruption to life
caused by beliefs
2. The persecutory delusions and ideas of reference
items from the Scales for Assessment of Positive
Symptoms (SAPS; [
]), a semi-structured interview
designed to assess the positive symptoms of psychosis
Hypothesised mediators are measured by changes in
fast thinking assessed by:
1. Possibility of Being Mistaken (taken from the
Maudsley Assessment of Delusions Schedule
]); Alternative Explanations from the
Explanations of Experiences interview [
are commonly used published methods of assessing
lack of belief flexibility relating to delusional beliefs
2. Jumping to Conclusions (JTC) Beads Data-gathering
] versions 85:15 and 60:40.
Please refer to Fig. 3 for details of secondary outcomes
and other key processes hypothesised as moderators;
these include published and established measures of
], quality of life [
], self and other schemas
], service use [
], worry [
], cognitive tests [
other paranoia measures  and measures of beliefs
about mental health problems and perceived relationship
with carers [
Safety and adverse event assessment and monitoring and stopping rules
The occurrence of adverse events (AEs) will be
monitored actively and systematically, following SPIRIT
guidance for reporting of harms. AEs include: deaths;
selfharm; serious violent incidents; complaints about
therapy; and referrals to crisis care or admission to
psychiatric hospital during therapy. A standard method of
reporting will be employed, categorising events by
severity (five grades, A–E). Subject to the approval by the
independent chairperson of the Data Monitoring and
Ethics Committee (DMEC, see below, ‘Research
governance’), investigators will also determine whether an event
is temporally related to the intervention, and whether it
is unexpected or unexplained given the participant’s
clinical course, previous conditions and history, and
concomitant treatments. Following [
], the event will then
be rated within five categories from ‘not related’ to
‘related’. Any associations between AEs and the SlowMo
hardware or software will also be recorded. At each
meeting of the DMEC, or at any time at the request of
the DMEC chairperson, a full report of AEs will be
reviewed. The DMEC will be responsible for
investigating further, if there are concerns about unexpectedly
high rates of AEs. This may involve the DMEC members
being unblinded to the trial condition or seeking further
data on AEs. If there are any ethical or safety reasons
why the trial should be prematurely ended, they will
advise the Trial Steering Committee (TSC) accordingly.
Individual participants will have the right to withdraw
from the trial at any time. In addition the therapist, in
collaboration with the participant and relevant clinical
team, may decide to stop the therapy if it is directly
associated with a worsening of mental state. Reasons for
withdrawal from the study will be recorded. For the final
reports of the trial, the numbers, types and severity of
AEs by trial condition, as well as discontinuations, will
be reported, using descriptive statistics (since there are
no pre-specified hypotheses concerning AEs or harms,
and, given the expected low frequency of AEs, the data
will not be suitable for an intention-to-treat (ITT)
The trial may be prematurely discontinued by the
sponsor or chief investigator on the basis of new safety
information or for other reasons given by the DMEC,
the TSC, the regulatory authority or the Ethics
Committee concerned. The trial may also be prematurely
discontinued due to lack of recruitment or upon advice from
the TSC, which will advise on whether to continue or
discontinue the study and make a recommendation to
the sponsor. If the study is prematurely discontinued,
active participants will be informed and no further
participant data will be collected.
Accessibility, usability and acceptability assessments
Given the novelty of the digital therapy platform, its
accessibility, usability and acceptability will be assessed in
the SlowMo arm. This will be done through assessment
of current mobile use and confidence at the beginning of
therapy, monitoring of connectivity for the web app,
system analytics data on the use of the platform, the User
Experience Survey (adapted from [
]), and a
serviceuser led qualitative interview with a sub-sample of those
receiving SlowMo (n = 20).
Therapy adherence assessments
In the SlowMo arm, therapy adherence will be assessed
from the number and duration of sessions attended, and
system analytics data on mobile app use. Therapy
delivery will be evaluated in terms of fidelity to the treatment
Data management and security
All data will be anonymised at source. All personal data
will be kept in a locked filing cabinet in a locked office
and will be kept separate from all the research data.
Therapy files will be kept in a secure office in the clinic
and will not be accessible to the staff collecting the
research outcome data. Data will be entered on a
computerised database, held centrally and managed by King’s
College London CTU, by research assistants using a
secure network connection. Audio-recording equipment
will be used to record assessments to check fidelity to
assessment protocols and to ensure interrater reliability.
The therapy sessions will be audio-recorded (with
participant consent) for monitoring the intervention in
terms of fidelity and competence. These audio files,
named with a unique participant identifier, will be stored
as computer files on secure NHS/university servers.
Security and privacy of information stored on the app
has been considered throughout its development. If
informed consent is provided, app data will only be
synched during therapy sessions, over secure
connections and stored on a password-protected, secure
database. Data transferred will only contain a name (chosen
by the person) and a Unique Device Identifier (UDID)
which is generated automatically by the therapy
platform, and will match the anonymised participant
number. Participants can also opt to use the app in a fully
offline mode. Participants will have the opportunity, if
they wish, to password protect the handset with a pin
number or password. During the informed consent
process potential participants will be made fully aware of
the data collected by the platform, and how data will be
stored and used. Access to this privacy and security
information is also available from the settings menu of the
app, which consenting participants can access at any
Data quality will be ensured by close monitoring and
routine auditing for accuracy throughout the data
collection period. In order to ensure the accuracy of the data
entered into the database, the main outcome measure
entry will be checked for every participant by comparing
the paper record with that on the database. An error
rate of no more than 5% is acceptable. This will be done
once all possible assessments for each time point have
been completed. If the error rate is higher than 5%,
advice will be sought from the trial statistician and
methodologist regarding further data checking.
Recruitment of 360 participants will be split equally
across sites. We have powered the study conservatively
to detect a clinically meaningful 10-point reduction in
the primary outcome measure (GTPS [
]); based on a
standard deviation of 25, this is a 0.4 effect size [
account for: clustering in the SlowMo arm with an
intraclass correlation coefficient (ICC) = 0.01 with 10
therapists (no clustering in the TAU arm), 1:1 allocation,
0.05 significance level. Calculations used Clsampsi in
Stata. A simple two-tailed t test with 150 people per
group gives 90% power to detect an effect size of 0.4,
and 80% for 0.35. In practice, power will be increased by
using multiple regression. To allow for conservatively
high 20% attrition we will recruit 360 patients at baseline
split equally across three sites (120 per site, 60 per arm
per site). For the mediational analyses, a sample of N =
300 has > 80% power to detect a proportion mediated of
40%, and > 70% power to detect a proportion mediated
of 30%, corresponding to findings in our pilot work [
(calculated using PowerMediation in R).
We will report all participant flow, and analyses will be
conducted on the ITT population: all participants will
be randomised regardless of non-compliance with
protocol or withdrawal from the study. Analyses will
postdate final follow-up assessments, with due consideration
of potential biases from loss to follow-up. The primary
analysis will test for a treatment effect on the primary
and secondary clinical outcomes. Random effects
regression models allowing for clustering by both participants
and therapists will be fitted to the repeated measures,
controlling for treatment site, baseline paranoia severity
and the corresponding baseline assessment for the
outcome under investigation. We will allow for missing
outcome data under the Missing At Random assumption
]; we may also use inverse probability weighting to
adjust for non-adherence to allocated treatment and
other intermediate outcomes as predictors of future loss
to follow-up [
]. Secondary analyses will test
treatment-effect mechanisms, moderation and process/
adherence effects using modern causal inference
]. The trial outcomes will comprise two
parallel series of longitudinal data: one for the putative
mediators (M) and one for the clinical outcomes (Y).
For the mechanistic analysis, to test for a treatment
effect on the putative mediator, we will replace the
clinical outcome with the mechanistic variable as the
dependent variable in the random-effect models. If we
separately demonstrate a treatment effect on both the
putative mediator and on the clinical outcome, we will
evaluate mediation in these parallel longitudinal data
sets through the use of parallel growth curve and latent
change models [
]. These models preserve the basic
mediation model by replacing observed variables with
latent constructs – the growth factors driving the
temporal responses, M1 to Mp and Y1 to Yp. Importantly,
the mediational structure only applies to the slope
growth or change factors since randomised treatments
are independent of the intercept growth factors (baseline
values). Growth curve and latent change models can be
estimated by maximum likelihood and other methods
using the software package Mplus . The application
of these methods to mechanism evaluation within EME
(Efficacy and Mechanism Evaluation) trials is illustrated
The aim of these analyses is to demonstrate that the
effect of treatment on the growth (change) in the clinical
outcome (Y) is explained (caused) by its effect on the
growth (change) in the mediator. The major challenge to
a valid inference is that there may be confounding of the
mediator and outcome. We will begin by allowing for
baseline values of the mediator and of the clinical
outcome, as in the analyses of the successful EME Worry
Intervention Trial [
]. We will then check the
sensitivity of the results to the possibility of hidden confounding
(unmeasured variables) through the use of instrumental
variable methods [
Research governance and patient and public involvement (PPI)
King’s College London is the research sponsor and the
South London and Maudsley NHS Foundations Trust is
co-sponsor. The trial has received a favourable ethical
opinion from Camberwell St. Giles Research Ethics
Committee (REC) (REC Reference: 16/LO/1862; IRAS:
206680). Any changes to the study protocol will be
submitted to the REC and then communicated to all
relevant parties (including the DMEC, TSC and study
funders). The trial will be conducted in compliance with
the principles of the Declaration of Helsinki [
Medical Research Council Guidelines for Good Clinical
] and in accordance with all applicable
regulatory requirements including but not limited to the
Research Governance Framework and the Mental Capacity
Act 2005 [
]. The chief investigator (CI) will have
overall responsibility for the trial data set and will permit
trial-related monitoring, audits and REC review by
providing the sponsor(s), and REC direct access to source
data and other documents as required. A dedicated trial
coordinator post will assist in the day-to-day
management of the project reporting to the CI. A Trial
Management Committee (TMC) will meet monthly: its
membership will include the investigators and the trial
coordinator and site coordinators. It will be chaired by
the CI and will manage the day-to-day running of the
study and oversee the preparation of reports to the TSC
and DMEC. The TSC will meet at least annually and will
include in its membership a lay member and access to
consultation with a patient and public involvement (PPI)
advisory group. The TSC’s purpose is to provide
independent overall supervision of the trial, approving the
protocol and amendments, and monitoring progress,
through audits of recruitment and data completion rates
and adherence to the protocol. It will provide
independent advice on all aspects of the trial. A DMEC will be
convened and will meet at least annually and report to
the TSC. It will have access to all trial data and will
receive regular reports on AEs. Membership of the DMEC
will be fully independent of the trial team and will
comprise two independent clinician researchers, one of
whom will act as chair, and a statistician who will be
independent of the applicants and of the TSC. The DMEC
chair will be notified of any serious AEs as they occur,
and with the DMEC will consider whether any interim
analyses are warranted, review data and advise the TSC
on any ethical or safety reasons why the trial should be
prematurely ended. The PPI Advisory Group will advise
on and contribute to recruitment, qualitative data
collection and dissemination activities throughout the trial.
SlowMo has been developed as the first blended digital
therapy to target fears of harm from others through an
inclusive design approach. Improving the effectiveness
and accessibility of psychological treatments for paranoia
is a clinical health priority [
]. The current trial aims to
achieve this in two ways. Firstly, adopting an
interventionist causal treatment approach, SlowMo therapy
tackles fast thinking, which research has shown to play a
key role in the development and maintenance of
distressing paranoia. Secondly, incorporating digital
technologies into psychological interventions presents unique
opportunities for developing effective and accessible
treatments. However, the adoption of digital technology
cannot of itself guarantee effective therapy. We therefore
used an inclusive design approach in the development of
SlowMo therapy, with stakeholder involvement at each
stage and a clear focus on addressing the needs of the
broadest possible range of users, including sampling of
‘extreme’ users [
Given the strong evidence for targeting reasoning as a
treatment for paranoia [
], our encouraging pilot
data, and its inclusive user-centred design, SlowMo is
expected to be highly acceptable and to lead to clinically
worthwhile improvements in paranoia severity, working
by supporting people to ‘slow down for a moment’ and
reduce their reliance on fast thinking. The data from this
study will also add significantly to our understanding of
psychological mechanisms and change processes in
paranoia. As well as providing valuable information for
treatment development, evidence of mechanisms of action
will inform the theoretical understanding of paranoia in
a way that may itself shape future therapeutic initiatives.
The trial will provide data on whether characteristics of
participants (including working memory and negative
symptoms) moderate the effects of the intervention on
fast thinking, and also the effect on outcome of an
adequate dose of treatment and therapy adherence.
From the perspective of digital health, we will examine
the usability and adherence of a novel digital therapy,
including an app for self-management in daily life in a
large sample of people affected by severe mental health
difficulties. Uniquely, the mobile app allows for
monitoring of fast and slow thinking in real time and is,
therefore, well placed to advance our understanding of its
role in paranoia .
In summary, the SlowMo trial has the potential to
inform future stratified medicine approaches, the
development of more targeted therapies and the applicability of
digital health innovations with this population. The trial
is funded for 31 months and began in February 2017.
Final outcome assessments will be completed by
summer 2019, and outcome results will become available in
2020. They will then be written up by the trial team and
published in peer-reviewed journals. Participants will
receive a summary of the results, and we will also
disseminate findings more broadly through public engagement
Recruitment of participants commenced in May 2017
and will be open until spring 2019. The date of first
enrolment is May 2017.
Professor Philippa Garety (CI) and Dr. Thomas Ward
can be contacted for scientific queries.
Dr. Thomas Ward (trial coordinator) is the main
contact for general trial-related queries.
Chief investigator: Professor Philippa Garety
PO Box 77, Henry Wellcome Building, The Institute of
Psychiatry, Psychology and Neuroscience, King’s College
London, De Crespigny Park, London SE5 8AF, UK
Tel: +44 (0)20 7848 5046; Fax: +44 (0)20 7848 5006
Trial coordinator: Dr. Thomas Ward:
Psychology, PO77, HWB, King’s College London,
Institute of Psychiatry, Psychology and Neuroscience, De
Crespigny Park, London SE5 8AF, UK
Tel: +44 (0) 207 848 0594; Fax: +44 (0) 207 848 5006
Additional file 1: SPIRIT 2013 Checklist: recommended items to address
in a clinical trial protocol and related documents. (DOC 122 kb)
AE: Adverse event; API: Application Programming Interface; BCSS: Brief Core
Schema Scales; BSI: British Standards Institute; CBTp: Cognitive-behavioural
therapy for psychosis; CONSORT: Consolidated Standards of Reporting Trials;
CTU: Clinical Trials Unit; DMEC: Data Monitoring and Ethics Committee;
EME: Efficacy and Mechanism Evaluation; GPTS: Green Paranoid Thoughts
Scale; ICC: Intraclass correlation coefficient; ICD: International Classification of
Diseases; IRAS: Integrated Research Application System; ITT: Intention-
totreat; JTC: Jumping to Conclusions; KCL: King’s College London;
MADS: Maudsley Assessment of Delusions Schedule; MANSA: Manchester
Short Assessment of Quality of Life; MCT: Metacognitive training; MVC: Model
View Controller; NICE: National Institute of Health and Clinical Excellence;
NIHR: National Institute for Health Research; PPI: Patient and public
involvement; PSYRATS: Psychotic Symptoms Rating Scales; R&D: Research
and Development; RCT: Randomised controlled trial; REC: Research Ethics
Committee; SAPS: Scale for the Assessment of Positive Symptoms;
SLaM: South London and Maudsley NHS Foundation Trust;
TAU: Treatment as usual; TMC: Trial Management Committee; TSC: Trial
Steering Committee; UDID: Unique Device Identifier; WCF: Windows
PAG and EK acknowledge support from the National Institute for Health
Research (NIHR) Biomedical Research Centre of the South London and
Maudsley NHS Foundation Trust and King’s College London.
TW acknowledges support by the NIHR collaboration for Leadership in
Applied Health Research and Care South London at King’s College Hospital
NHS Foundation Trust. The views expressed are the author(s) and not
necessarily the NHS, NIHR or the Department of Health.
DFr is supported by an NIHR research professorship.
We would like to acknowledge the support of our design collaborators at
the Helen Hamlyn Centre for Design, Royal College of Art.
This project is funded by the Efficacy and Mechanism Evaluation (EME)
Programme, an MRC and NIHR partnership. The views expressed in this
publication are those of the author(s) and not necessarily those of the MRC,
NHS, NIHR or the Department of Health. The EME Programme is funded by
the MRC and NIHR, with contributions from the CSO in Scotland and NISCHR
in Wales and the HSC R&D Division, Public Health Agency in Northern
Availability of data and materials
Not currently applicable. The datasets generated and/or analysed during the
current study will be available from the corresponding author on reasonable
request following the publication of results.
PAG is the CI of the study and accountable for all aspects of the work in
ensuring that questions related to the accuracy or integrity of any part of
the work are appropriately investigated and resolved. PAG took responsibility
for the main drafting of the manuscript and made substantial contributions
to conception and design. TW took responsibility for the main drafting of
the manuscript and made substantial contributions to conception and
design. AH took responsibility for the main drafting of the manuscript and
made substantial contributions to conception and design. DFr made
substantial contributions to conception and design. DFow made substantial
contributions to conception and design. EK made substantial contributions
to conception and design. PB made substantial contributions to conception
and design. HH made substantial contributions to conception and design.
KG made substantial contributions to conception and design. RE is
accountable for the statistical (i.e. outcome, moderation and mediation)
analyses and made substantial contributions to conception and design. GD
is accountable for the statistical (i.e. outcome, moderation and mediation)
analyses and made substantial contributions to conception and design. All
authors have been involved in drafting the manuscript or revising it critically
for important intellectual content. All authors read and approved the final
Ethics approval and consent to participate
The trial has received a favourable ethical opinion from Camberwell St. Giles
Research Ethics Committee (REC) (REC Reference: 16/LO/1862; IRAS: 206680).
Participants will be identified through close liaison with clinical staff.
Clinicians will obtain verbal consent from potential participants to be
contacted by a study research worker, but no further demands will be
placed on their time. Members of the research team will then proceed with
establishing eligibility and informed consent to take part in the trial.
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in
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