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Introduction The evolution of technologies like artificial intelligence and robotics has already begun to shape the future of health care delivery and will have an undeniable impact on patient experiences over the next decades. In times of shortened human resources, especially in the field of health care settings, we should also consider robots as assistance for existing treatment settings. The use of robotic assisted surgery has already found its way into clinical practice and allows doctors to perform many types of complex procedures with more precision, flexibility and control. Nevertheless, to date, the use of robotics in the field of psychiatry is sparse, at least in European countries. Socially assistive robots (SARs) are robotic technology platforms with audio, visual, and movement capabilities that are being developed to interact with individuals while also assisting them with their management of their well-being. Robots could support classic psychiatric treatment by training cognition and motivation as well as educating patients. Objectives The robot “Pepper” has found its home at the Medical University of Graz, Department of Psychiatry & Psychotherapeutic Medicine in Austria in summer 2022. It is friendly and positive, around 1,30m tall, can make conversations, learn people’s tastes, preferences, and habits to help personalize responses and better address needs. He can also offer games, make music and dance. Methods In our ongoing studies we use the robot “Pepper” in the context of psychoeducational settings on different mental diseases, training of cognitive functions as well as motivational aspects in inpatients with psychiatric disorders. It can also react and suggest a break during the sessions if he has the impression that participants are stressed or overstrained with content. We collect personal feedback of the patients and associated employees in the hospital through the ongoing usability study, as well as perform a randomized controlled trial to test effects of cognitive and motivational training aspects in comparison to standardized treatment settings. Results It is time to apply new technologies in healthcare, especially in times when the staff is decreasing. Better integrating and expanding on the mental health implications of social robots will complement the ongoing drive in the field of psychology and psychiatry to better assist clients with supportive exercises and education, cognitive training, and an asynchronous care option. Conclusions Although the use of SARs in mental health research is not yet widespread, new robots and programming are constantly changing, adapting and expanding. There is an abundance of opportunity for growth, expansion, and exploration to triangulate SARs usability and efficacy as the next step in advancing this field. We should not be afraid of this new and expanding technology but come to use it as soon as possible as a support in psychiatric treatment. Let‘s make fiction become reality! Disclosure of Interest None Declared

Introduction The COVID-19 outbreak is a serious global public health issue with wide-ranging negative effects on people’s lives, which is reflected in steadily rising mental health problems. In order to appropriately respond to the increased occurrence of psychiatric illness, protect mental health and strengthen resilience it is necessary to include new technologies, such as extended reality (XR) or socially assistive robots (SAR) in not only psychiatric treatment but also in the prevention of psychiatric diseases. In this context, the use of new technologies offers innovative ways to strengthen resilience, self-efficacy and stress coping skills and plays an important role in improving psychological wellbeing. Objectives Preliminary results from studies at the Clinical Department of Psychiatry and Psychotherapeutic Medicine in Graz, Austria, dealing with new technologies in psychiatry, show new options for psychiatric settings. Methods Project AMIGA: The aim of this study is to test the effectiveness of a cognitive training session, conducted with the SAR named Pepper. In this randomized controlled trial, the effectiveness of SAR on depressive symptoms and correlates is evaluated in a sample of 60 individuals with major depression. While the intervention group will receive cognitive training with the SAR Pepper, the control group will receive “treatment-as-usual” therapy with a common PC software. Participants will receive 30 minutes of training 2 times per week over a period of 3 weeks. Project XRes4HEALTH: The aim of this study is to develop an XR resilience training to increase resilience and stress coping mechanisms in healthcare workers. A total of 40 people will be included. To test the effectiveness of the resilience training, 3 XR training sessions of 15 minutes each will be held. A pre-post measurement will test the effectiveness of the training on wellbeing and stress levels as well as the acceptance and satisfaction with the training. Project AI-REFIT: The overall goal of this study is to explore key information to increase resilience in healthy individuals who are at increased risk for mental health problems. Through a usability study, the artificial intelligence-based prototype app of the resilience training will be tested for acceptance, usability, functionality, and efficiency. During the resilience training, participants are wearing a smartwatch which measures psychophysiological parameters. Conclusions about the success of the therapy can be drawn based on digital data acquisition. Results New technologies including XR and SAR support classical psychiatric treatment in the topics of resilience and cognitive training as an add-on therapy in times of reduced availability of healthcare workers. Conclusions The rapid development of new technologies holds a lot of potential in the treatment of psychiatric disorders, which is why it is important to scientifically evaluate those innovative tools. Disclosure of Interest None Declared

Introduction Patients with bipolar disorder have a hig risk of becoming overweight and obese, associated with an increased risk of somatic diseases and premature mortality. The Austrian BIPFAT/BIPLONG study aims at investigating lipid metabolism, psychosocial functioning, and cognitive parameters in bipolar disorder (BD). Objectives The aim was to investigate to what extent overweight, obesity and metabolic syndrome (MetS) are associated with clinical symptoms (e.g. suicidality, depressive symptoms) and cognitive factors (attention, memory, executive function) in BD. Methods In addition to anamnestic interview and psychological tests, all participants were tested with a neuropsychological test battery including the Trail Making Test A/B, the Stroop Color and Word Interference Test, the d2 Test of Attention Revised, Digit Span, Digit-Symbol-Test, and the California Verbal Learning Test. Additionally, body mass index (BMI) and variables defining MetS including waist circumference, serum triglycerides, high-density lipoprotein, blood pressure, and fasting glucose levels have been collected in DSM-5 diagnosed patients with BD and healthy controls. Results In our Austrian bipolar cohort (n=290), the median BMI was 27.9 (SD=5.9), 30.5 % of the patients were overweight (BMI = 25.5-29.9) and 24.6% of the patients were obese (BMI ≥ 30.0). In the control group (n=183), the median BMI was 24.5 (SD=4.8), 15.2% were overweight and 8.0% were obese. A sub-analysis in 215 patients showed that compared to overweight patients, normal weight patients showed more suicidal ideation in psychiatric history (χ2(2)=7.97, p=.019). In addition, there was a significant association between suicidal ideation and glucose (r=.15, p=.043) and cholesterol (r=−.17, p=.028). In another sub-analysis with 148 euthymic bipolar patients, we found a high prevalence of MetS in patients with BD (30.4% versus 15.4% in healthy controls) associated with impaired executive function compared to patients without MetS or healthy controls with and without MetS (p=.020). Clinical variables (illness duration, suicidality, number of affective episodes, medication, age of onset, and history of psychosis) did not relate to MetS in BD (p > .05). A longitudinal analysis in 52 patients (35 without MetS and 17 with MetS) did not find an association of MetS on the one-year trajectory of cognitive decline in BD. In contrast, high baseline BMI predicted a decrease in the patient’s performance in working memory in the 12-months observation period. Conclusions The BIPFAT/BIPLONG study demonstrated a high prevalence of overweight, obesity and MetS in bipolar patients with adverse effects on cognitive function. Clinical variables such as suicidality were not related to the presence of obesity or MetS. Clinical impact and further (unpublished) results will be presented. Disclosure of Interest None Declared