European Psychiatry - Volume 41 - April 2017

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S310 25th European Congress of Psychiatry / European Psychiatry 41S (2017) S303–S364
schizophrenic psychosis (12.6%), schizophrenia (9.1%), and other
diagnosis (6.8%).
Conclusions The formulation of the dual diagnosis provided a bet-
ter approach of the patients on the part of the team, promoting the
strengthening of the therapeutic bond and causing positive impact
on the evolution of these disorders.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
EW0596
Comorbid depressive symptoms in
persistent delusional disorder:
A retrospective study from India
K. Kulkarni , R. Arasappa , K. Prasad , A. Zutshi , P. Chand ,
P. Murthy , M. Kesavan ∗
1 National institute of mental health & neurosciences, psychiatry,
Bangalore, India
2 University of Melbourne, psychiatry, Melbourne, Australia
∗ Corresponding author.
Background Previous studies have reported depressive symp-
toms in patients with persistent delusional disorder (PDD). Patients
with PDD and depression may need antidepressants for treatment.
Aim The aim of the study was to compare the sociodemographic
profile, clinical presentation and treatment response in patients
with PDD with and without comorbid depressive symptoms.
Methods We conducted a retrospective chart review of patients
diagnosed with PDD (ICD-10) from 2000 to 2014 (n = 455). We
divided the patients into PDD + depression (n = 187) and PDD only
(n = 268) for analysis.
Results Of the 187 patients with PDD + D, only eighteen (3.9%)
were diagnosed with syndromal depression. There were no signifi-
cant differences in sociodemographic profile including sex, marital
and socioeconomic status (all P > 0.05). PDD + D group had a signifi-
cantly younger age at onset ([PDD + D: 30.6 9.2 years vs. PDD: 33.5
11.1 years]; t = 2.9, P< 0.05). Therewas no significant difference bet-
ween the clinical presentation including mode of onset, the main
theme of their delusion and secondary delusions (all P> 0.3). Howe-
ver, comorbid substance dependence was significantly higher in
patients with PDD only. ( 2 = 5.3, P = 0.02). In terms of treatment,
response to antipsychotics was also comparable ([> 75% response:
PDD + D = 77/142 vs. PDD = 106/179); 2 = 1.9, P = 0.3). There was a
significant difference between the two groups in terms of antide-
pressant treatment ([PDD + D = 32/187; 17% vs PDD: 17/268; 6%),
2 = 12.9, P = 0.001).
Discussion Patientswith PDD + Dhad significantly earlier onset of
illness. These patients may require antidepressants for treatment.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
EW0597
Association between Internet
addiction and depression in medical
students, faculty of medicine in
Thailand
S. Kuladee ∗ oonvisudhi
Faculty of medicine Ramathibodi hospital, psychiatry, Bangkok,
Thailand
∗ Corresponding author.
Introduction Internet addiction has become a harmful behavio-
ral problem found to be highly prevalent in high school and college
students. Many studies demonstrated significantly association bet-
ween Internet addiction and depression.
Aims To study the prevalence of Internet addiction and the
association between internet addiction and depression in medical
students, faculty of medicine, Ramathibodi hospital.
Methods A cross-sectional study was conducted. Participants
were the first to fifth-year medical students who agreed to par-
ticipate in this study. Demographic characteristics were derived
from self-rated questionnaire and were analyzed by descriptive
statistics. Thai version of Young’s Internet Addiction Diagnostic
Questionnaire and Thai version of Patient Health Questionnaire
(PHQ-9) were used to assess internet addiction and depression,
then Chi2 test and logistic regression were used to analyze the
associations between internet addiction, depression and associated
factors.
Results From 705 participants, 24.5% had internet addiction and
29.0% had depression. There was statistically significant associa-
tion between Internet addiction and depression (odd ratio: 1.92;
95% confidence interval [CI]: 1.34–2.77, P -value < 0.000). Logistic
regression analysis illustrated that the Internet addiction group
had risk of depression 1.58 times higher than the group without
Internet addiction (95% CI: 1.04-2.38; P -value < 0.031). Academic
problem was found to be a significant predictor of both Internet
addiction and depression. Furthermore, Internet addiction, rela-
tionship problems with friend and lover, and health problem were
also significant predictors of depression.
Conclusions Internet addictionwas common psychiatric problem
which associated with depression among medical students. We
suggest that surveillance of Internet addiction should be considered
in medical schools.
Disclosure of interest The authors have not supplied their decla-
ration of competing interest.
EW0598
The cannabis profile: A high-risk
subtype
R. Landera Rodríguez ∗ Gómez Revuelta García Egea
O. Porta Olivares Juncal Ruíz Pérez Herrera
L. Sánchez Blanco Abejas Díez
G. Pardo de Santayana Jenaro Fernández Rodríguez
1 Hospital Universitario Marqués de Valdecilla, psychiatry,
Santander, Spain
2 Hospital Universitario de Álava-Sede Santiago, psychiatry,
Vitoria-Gastéiz, Spain
3 Hospital Universitario Virgen del Rocío, psychiatry, Sevilla, Spain
4 Hospital Universitario Marqués de Valdecilla, general medicine,
Santander, Spain
∗ Corresponding author.
Introduction The first phase following the diagnosis of a first psy-
chotic episode (FEP), is crucial to determine clinical and functional
long-term outcome. Cannabis exerts a mediating action on the
debut of the disease and determines a poor prognosis.
Objectives The description of a specific population profile of
increased vulnerability to maintain cannabis use after a FEP could
help to identify this high risk subtype of patients and speed up the
implementation of specific interventions.
Materials and methods One hundred and seventy-eight patients
were recruited from PAFIP (early intervention program on FEP),
obtaining detailed socio-demographic assessment. They were
followed-up for a year during which cannabis consumption was
assessed by Drake scale every threemonths. We divided the sample
into two groups:
– those patients who neither smoked cannabis before the FEP nor
during follow-up period (nn);
– consumers group: cannabis users before the FEP who kept on
smoking during the follow-up period (ss) and those who smoked
before the FEP and gave up consumption during follow-up (sn).