European Psychiatry - Volume 41 - April 2017

72 / 916

S68 25th European Congress of Psychiatry / European Psychiatry 41S (2017) S53–S68
W049
Identifying service and care needs
from the users’ perspective in
treatment-resistant schizophrenia
K. Rubinstein
1 The Gertner Institute of Epidemiology and Health Policy Research,
Israel
2 Psychiatric Division, Sheba Medical Center, Israel
3 Tel-Aviv University, The Sackler School of Medicine, Israel
Exploring service and care needs of patients with treatment-
resistant schizophrenia is necessary for a better understanding of
their psychosocial functioning, in order to develop rehabilitation
goals as well as to provide them with better care.
m-RESIST is an innovative project aimed to empower patients
with resistant schizophrenia, to personalize treatment by integrat-
ing pharmacological and psycho-social approaches, and to develop
knowledge related to the illness using predictive models designed
to exploit historical and real-time data, based on environmental
factors and treatment outcomes.
m-RESIST is a system based on computer and cellular applications
and wearable computing devices. The system will serve patients,
caregivers and clinicians, and include the following functions:
Information, Assessment, Monitoring, Communication, and Inter-
vention.
The first step in the development process included definition of
the end user needs and preferences, in order to involve users in
the design of the system. Outpatients with treatment-resistant
schizophrenia, informal carers (relatives), and clinicians were
included in the sample. There were a total of 9 focus groups, 3
in each pilot country. Each group was composed of one of the
participant profiles. Additionally, 35 individual interviews were
performed, which were unevenly distributed throughout the 3
institutions.
The current workshop section will present the outcomes of this
process: perceived advantages and disadvantages of the techno-
logical solution, as well as conclusions for further development. In
addition, methodological issues, future challenges, relevant for the
evolution of the m-RESIST project, in particular, as well as techno-
logical developments in the field of mental health, in general, will
be discussed.
1 Disclosure of interest The author has not supplied his decla-
ration of competing interest.
W050
m-RESIST project as an example of
m-health approach in schizophrenia:
Content, aims and realization
I. Corripio
Barcelona, Spain
This communication aims to present m-RESIST, the first mHealth
program for patients with treatment resistant schizophrenia (TRS).
The main objective of this European project is to develop an inter-
vention programme to allow TRS patients to self-manage their
condition, which is associated with persistent positive symptoma-
tology, extensive periods of hospital care, and a greater risk of
excess mortality and multi-morbidity.
m-RESIST could offer a new tool for mental health professionals
to better monitor TRS patients, providing a tailored and optimized
therapeutic intervention. In this sense, m-RESIST will develop and
validate amHealth tool aimed to reduce the severity of episodes and
further complications. Moreover, this tool will involve and promote
a proactive role of patients and caregivers in the therapeutic pro-
cess, promoting an active and collaborative role with the medical
team in the treatment decision-making procedure.
m-RESIST intervention, will integrate: (1) a sensor data analysis
module, which will process data coming from smart phone and
wearable devices, providing passive information such as move-
ment or social activity; (2) a predictive modeling engine, which
will enable prediction of clinically significant events, such as hos-
pitalization, risk behaviors and social isolation; and (3) a clinical
decision support system (CDSS), which will provide the users
with necessary information to support health-related and clinical
decision-making.
The pilots of this project will take place in Tel-Aviv, Budapest
and Barcelona during May, June and July of 2017. Although cost-
effectiveness variables will also be measured, the main assessment
will be focused on acceptability, usability, satisfaction, empower-
ment and quality of life outcomes.
Disclosure of interest The author has not supplied his declaration
of competing interest.