European Psychiatry - Volume 33 - March 2016

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S68 24th European Congress of Psychiatry / European Psychiatry 33S (2016) S56–S71
The goals of this study are to analyze the pattern of SC variables in
schizophrenia using cluster analysis, to examine the relationship
of real-life functioning with cluster membership, and to identify
cut-offs that best discriminate among clusters in a large sample
of patients with schizophrenia recruited to the Italian Network for
Research on Psychoses (NIRP). A full assessment of different aspects
of SC was carried out, including emotional intelligence, recognition
and theory of mind (TOM).
Disclosure of interest The author has not supplied his declaration
of competing interest.
W39
The effects of integrated treatment
with atypical antipsychotics and
social cognition training on functional
outcome
G. Sachs ∗, B. Winklbaur , A. Erfurth
1 Medical University of Vienna, Department of Psychiatry and
Psychotherapy, Vienna, Austria
2 Otto-Wagner-Spital, 6th Psychiatric Department, Vienna, Austria
∗ Corresponding author.
Social cognition is impaired in patients with schizophrenia his
impairment is one of the core features of the illness and has a clear
impact on functional outcome.
While conventional antipsychotics might have a worsening effect
on social cognition, e.g. on amygdala attenuation in fMRI studies on
facial recognition typical antipsychotics might not show this
effect
Social cognitive training – such as the training of affect
recognition – is a promising approach in the treatment of
schizophrenia.
Holistic strategies including both treatment with atypical antipsy-
chotics and social cognitive training can improve functional
outcome in patients with schizophrenia
Disclosure of interest The author has not supplied his declaration
of competing interest.
References
[1] Green MF, et al. Nat Rev Neurosci 2015;16(10):620–31.
[2] Fahim C, et al. Psychiatry Res 2005;140(1):1–15.
[3] Sachs G, et al. Psychiatry Res 2012;202(2):168–71.
[4] Kurtz MM, et al. Clin Psychol Rev 2015 [Epub ahead of print].
[5] Wölwer W, et al. Schizophr Res 2005;80(2–3):295–303.
[6] Sachs G, et al. Schizophr Res 2012;138(2–3):262–7.
Suicide risk evaluation: From research to clinical
practice
w40
Future direction of suicidal risk
assessment
H. Blasco-Fontecilla
CIBERSAM, Autonoma University, Navacerrada, Spain
Objective to explore future directions on the assessment of the
risk of suicidal behavior (SB).
Methods narrative review of current and future methods to
improving the assessment of the risk of suicidal behavior (SB).
Results Predicting future SB is a long-standing goal. Currently, the
identification of individuals at risk of SB is based on clinician’s sub-
jective reports. Unfortunately, most individuals at risk of SB often
do not disclose their suicidal thoughts. In the near future, predict-
ing the risk of SB will be enhanced by: (1) introducing objective,
reliable measures – i.e. biomarkers – of suicide risk; (2) select-
ing the most discriminant variables, and developing more accurate
measures – i.e. questionnaires – and models for suicide predic-
tion; (3) incorporating new sources of information – i.e. facebook,
online monitoring; (4) applying novel methodological instruments
such as data mining, or computer adaptive testing; and, (5) most
importantly, combining predictors fromdifferent domains (clinical,
neurobiological and cognitive).
Conclusions Given the multi-determined nature of SB, a combi-
nation of clinical, neuropsychological, biological, and neuroimaging
factors, among other might help overcome current limitations in
the prediction of SB. Furthermore, given the complexity of predic-
tion of future SB, currently our efforts should be focused on the
prevention of SB.
Disclosure of interest The author has not supplied his declaration
of competing interest.
W41
New technologies for detecting
suicidal risk of psychiatric patients
J. Lopez-Castroman
CHRU de Nimes, Psychiatry, Nimes, France
Suicide is a major health issue with considerable human and
economic costs. There have been many attempts to develop tech-
niques capable of predicting future suicidal behavior, but known
risk factors are insufficiently specific. However, during the last
decades, technical developments have made possible the use of
new technologies to assess potential clinical markers for psy-
chiatric patients. In many cases the technologies are affordable,
wearable and interconnected, multiplying the wealth of data
resulting from their use. Quite logically, psychiatrists from all over
the world are investing in recently developed devices for their
research projects and have consequently started to collaborate
with engineering and pattern recognition groups in the study of
potential clinical markers. These groups provide the expertise and
computational methods required to process this wealth of data,
and can improve the classification accuracy to predict a certain
condition using data mining techniques. In the field of suicidal
behavior, new devices that capture promising predictors such as
electrodermal response activity, some facial expressions or speech
properties have been developed and are being tested. In view of
these facts, during the workshop we will review some of the new
methodologies that can be used for the assessment of suicidal risk
and how can multidisciplinary and complementary approaches be
implemented.
Disclosure of interest The author has not supplied his declaration
of competing interest.
W42
Electrodermal hyporeactivity
evaluation for detecting suicidal
propensity in depressed patients
L.H. Thorell
Linkoping University, Linkoping, Sweden
Introduction Since 1987 several publications have focused on
electrodermal reactivity in groupswithdifferent suicidal behaviors,
but with varying results. However, using an untraditional statisti-
cal approach with clinical application in focus revealed between
themselves confirming results of a strong relationship between
electrodermal hyporeactivity and suicide.