To discuss novel approaches in the development early detection, response and interventions of drug overdoses.

There is an urgent need to research and develop novel strategies to rapidly and accurately detect, respond, and treat them with the ultimate goal of reducing drug deaths secondary to fatal drug overdose incidents. This should be additional to supporting communities and networks able to intervene utilizing novel public health approaches.

We will describe technologies and associated systems that are able to accelerate detection and result in a timely response to potential overdose with effective and timely intervention to these occurrences using digital technologies and therapeutics. This will be contextualised around novel public health approaches.

We will describe 11 protypes as part of a £5 million UK inititiative. The themes will include:

1. – Use of discrete digital technology for easy use by people who use drugs in clinical and non-clinical settings

2. – Simple alert / responder pathways that created effective responses to potentially fatal overdose events

3. – Enhance innovative therapeutics as antidotes to overdose episodes

4. – Novel public health approaches

The use of remote monitoring devices like wearables and smartphone applications, paired with artificial intelligence and innovative therapeutics is an emerging field of research. This needs to be balanced around novel public health approaches.

None Declared

The intelligence quotient (IQ) of patients with first-episode psychosis (FEP) and their unaffected relatives may be related to the genetic burden of schizophrenia (SCZ). The polygenic score approach can be useful for testing this question.

To assess the contribution of the polygenic risk scores for SCZ (PGS-SCZ) and polygenic scores for IQ (PGS-IQ) to the individual IQ and its difference from the mean IQ of the family (named family-IQ) through a family-based design in an FEP sample.

The PAFIP-FAMILIES sample (Spain) consists of 122 FEP patients, 131 parents, 94 siblings, and 176 controls. They all completed the WAIS Vocabulary subtest for IQ estimation and provided a DNA sample. We calculated PGS-SCZ and PGS-IQ using the continuous shrinkage method. To account for relatedness in our sample, we performed linear mixed models. We controlled for covariates potentially related to IQ, including age, years of education, sex, and ancestry principal components.

FEP patients significantly deviated from their family-IQ. FEP patients had higher PGS-SCZ than other groups, whereas the relatives had intermediate scores between patients and controls. PGS-IQ did not differ between groups. PGS-SCZ significantly predicted the deviation from family-IQ, whereas PGS-IQ significantly predicted individual IQ.

PGS-SCZ discriminated between different levels of genetic risk for the disorder and was specifically related to patients’ lower IQ in relation to family-IQ. The genetic background of the disorder may affect neurocognition through complex pathological processes interacting with environmental factors that prevent the individual from reaching their familial cognitive potential.

There is heterogeneity in the long-term trajectories of depressive symptoms among patients. To date, there has been little effort to inform the long-term trajectory of symptom change and the factors associated with different trajectories. Such knowledge is key to treatment decision-making in primary care, where depression is a common reason for consultation. We aimed to identify distinct long-term trajectories of depressive symptoms and explore pre-treatment characteristics associated with them.

A total of 483 patients from the PsicAP clinical trial were included. Growth mixture modeling was used to identify long-term distinct trajectories of depressive symptoms, and multinomial logistic regression models to explore associations between pre-treatment characteristics and trajectories.

Four trajectories were identified that best explained the observed response patterns: “recovery” (64.18%), “late recovery” (10.15%), “relapse” (13.67%), and “chronicity” (12%). There was a higher likelihood of following the recovery trajectory for patients who had received psychological treatment in addition to the treatment as usual. Chronicity was associated with higher depressive severity, comorbidity (generalized anxiety, panic, and somatic symptoms), taking antidepressants, higher emotional suppression, lower levels on life quality, and being older. Relapse was associated with higher depressive severity, somatic symptoms, and having basic education, and late recovery was associated with higher depressive severity, generalized anxiety symptoms, greater disability, and rumination.

There were different trajectories of depressive course and related prognostic factors among the patients. However, further research is needed before these findings can significantly influence care decisions.

In Sweden, four lives are lost to suicide each day. Hence, identifying relevant risk factors to inform effective prevention strategies is key. Such strategies can range from individual (‘micro’) -level prevention methods, to broader national suicide prevention policies.

Whilst a range of studies have explored individual-level risk factors, highlighting municipal, regional, or national-level predictors can be valuable to identify broader social and contextual determinants. This study will therefore aim to go beyond proximal predictors of suicide by looking through a wider national- and regional-level lens in Sweden.

This project will be conducted utilizing routinely collected and publicly available data and applying longitudinal modelling to investigate potential predictors of changes in suicide rates across time in Sweden. More specifically, the study will explore whether regional data on economic (e.g. proportion of state benefit recipients), socio-demographic (e.g. educational level) and healthcare related variables (e.g. trust in the healthcare system) are associated with suicide rates over time.

This is an ongoing project and results will be available and presented at the time of the conference.

Utilizing publicly available data to explore potential predictors of suicide rates is not only cost-effective, but adding such findings to existing knowledge of individual-level risk factors can also be important when targeting wider policy and ensuring effective coordination and implementation of regional suicide prevention strategies.

None Declared

Amygdala subregion-based network dysfunction has been determined to be centrally implicated in major depressive disorder (MDD). Little is known about whether ketamine modulates amygdala subarea-related networks. We aimed to investigate the relationships between changes in the resting-state functional connectivity (RSFC) of amygdala subregions and ketamine treatment and to identify important neuroimaging predictors of treatment outcomes.

Thirty-nine MDD patients received six doses of ketamine (0.5 mg/kg). Depressive symptoms were assessed, and magnetic resonance imaging (MRI) scans were performed before and after treatment. Forty-five healthy controls underwent one MRI scan. Seed-to-voxel RSFC analyses were performed on the amygdala subregions, including the centromedial amygdala (CMA), laterobasal amygdala (LBA), and superficial amygdala subregions.

Abnormal RSFC between the left LBA and the left precuneus in MDD patients is related to the therapeutic efficacy of ketamine. There were significant differences in changes in bilateral CMA RSFC with the left orbital part superior frontal gyrus and in changes in the left LBA with the right middle frontal gyrus between responders and nonresponders following ketamine treatment. Moreover, there was a difference in the RSFC of left LBA and the right superior temporal gyrus/middle temporal gyrus (STG/MTG) between responders and nonresponders at baseline, which could predict the antidepressant effect of ketamine on Day 13.

The mechanism by which ketamine improves depressive symptoms may be related to its regulation of RSFC in the amygdala subregion. The RSFC between the left LBA and right STG/MTG may predict the response to the antidepressant effect of ketamine.

Several changes to the classification of mental disorders have been made during the past half century to increase the reliability, clinical use and validity of the diagnostic classification. Despite the high expansion of knowledge about mental disorders, understanding of their components and processes still requires fine-tuning. This symposium identifies key issues on different classification systems with different purposes relevant to understanding and classifying mental disorders. We discuss how key issues such as ICD-11, RDoC or Biomarkers correspond or diverge because of their different purposes, and constituencies. Although these approaches have varying degrees of overlap and distinguishing features, they share the goal of reducing the burden of suffering due to mental disorder.

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Benzodiazepines and related drugs (BZDRs) are widely used in the treatment of anxiety and sleep disorders, but cognitive adverse effects have been reported in long-term use, and these may increase the risk of labor market marginalization (LMM). The aim of this study was to investigate whether the risk of LMM is associated with new long-term BZDR use compared to short-term use.

This register-based nationwide cohort study from Finland included 37,703 incident BZDR users aged 18–60 years who initiated BZDR use in 2006. During the first year of use, BZDR users were categorized as long-term users (≥180 days) versus short-term users based on PRE2DUP method. The main outcome was LMM, defined as receipt of disability pension, long-term sickness absence (>90 days), or long-term unemployment (>180 days). The risk of outcomes was analyzed with Cox regression models, adjusted with sociodemographic background, somatic and psychiatric morbidity, other types of medication and previous sickness absence.

During 5 years of follow-up, long-term use (34.4%, N = 12,962) was associated with 27% (adjusted Hazard Ratio, aHR 1.27, 95% CI 1.23–1.31) increased risk of LMM compared with short-term use. Long-term use was associated with 42% (aHR 1.42, 95% CI 1.34–1.50) increased risk of disability pension and 26% increased risk of both long-term unemployment and long-term sickness absence.

These results indicate that long-term use of BZDRs is associated with increased risk of dropping out from labor market. This may be partly explained by cognitive adverse effects of prolonged BZDR use, which should be taken into account when prescribing BZDRs.

Electroencephalography (EEG) serves as a non-invasive, cost-effective, and robust tool, directly measuring in-vivo neuronal mass activity with high temporal resolution. Using state-of-the-art machine learning techniques, EEG recordings have the potential to generate in silico biomarkers for severe mental disorders. In this study, we developed EEG-based classification models for schizophrenia and depression taking into account physiological and pathological aging processes.

From a cohort (N=735, 51.6% male) that is acquired in LMU Hospital, Department of Psychiatry and Psychotherapy, comprising healthy control individuals (HC, N=245) and patients with schizophrenia (SCZ, N=250) or major depressive disorder (MDD, N=240), we extracted power spectrum density and connectivity measures based on 60 second resting-state EEG recordings with 19 channels. The support vector machine models were trained to 1) classify patients with SCZ or MDD and HC individuals, and 2) predict age in HC individuals using ten-by-ten repeated nested-cross validation. The age-predicting model was applied to patient groups to calculate EphysAGE (Electrophysiological Age Gap Estimation) by subtracting chronological age from chronological age. The links between diagnosis, medication, and EphysAGE, i.e., accelerated aging, were then further explored with univariate analyses.

The EphysAGE Model had an explained variance of 46% (MAE=8.7 years, T=14.31, P1000<0.001). The patients with SCZ had a significantly higher EphysAGE (mean[SD]=0.61[10.32]) than the patients with MDD (mean[SD]=-1.10[10.49], p=0.04). The classification models discriminated SCZ from HC (Balanced Accuracy, BAC=72.7%, p<0.001), MDD from HC (BAC=67.0%, p<0.001), and SCZ from MDD individuals (BAC=63.2%, p<0.001). Higher EphysAGE was associated with an increased likelihood of being misclassified as SCZ in HC and MDD (ρHC=0.23, p<0.001; ρMDD=0.17, p=0.01) based on percentile rank scores from the SCZ Model. Moreover, in the Differential Diagnostic Model, higher EphysAGE is positively correlated with being misclassified as SCZ in patients with MDD (ρMDD=0.14, p=0.03).

Machine learning models can extract electrophysiological signatures of MDD and SCZ for potential clinical use. However, the impact of aging processes on diagnostic separability calls for timely application of such models, possibly in early recognition settings.

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Several meta-analyses demonstrated the efficacy of unilateral High-Frequency Left-sided (HFL) repetitive Transcranial Magnetic Stimulation (rTMS) for individuals with Major Depressive Disorder (MDD); however, results are contradictory due to heterogeneity of the included studies. Empirical evidence on the relative efficacy of rTMS treatment compared with standard pharmacotherapy in Treatment-Resistant Depression (TRD) is presented. Random effects models were used to assess the effects of rTMS on response and remission rates. In 19 randomized double-blinded sham-controlled studies were included for quantitative analysis for response (n = 854 patients) and 9 studies for remission (n = 551 patients), the risk ratio (RR) for response and remission are 2.25 and 2.78, respectively for patients after two treatment failures using rTMS as add-on treatment compared to standard pharmacotherapy. The presentation will conclude, that rTMS is significantly more effective than sham rTMS in TRD in response and remission outcomes and may be beneficial as an adjunctive treatment in patients with MDD after two treatment failures. This finding is consistent with previous meta-analyses; however, the effect size was smaller than in the formerly published literature.

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Schizophrenia has a heterogeneous range of possible outcomes. A portion of patients with schizophrenia significantly improves over the long term, with both clinical and functional remission. Recovery has been differently conceptualized by clinicians and service users, the former focusing on clinical and functional outcomes, the latter more underlying issues as the building a trail of personal meaning and subjective well-being. Besides the “clinical” and “personal” recovery, attention is now put on a wider perspective of “societal” recovery . The frequency of recovery achievement depends on which of these perspectives is considered. Many factors, demographic, clinical, contextual and treatment-related are involved in modulating the probability to meet these objectives. Both pharmacological and psychosocial interventions, and their integration, and attention to environmental and social circumstances could substantially improve the outcome of schizophrenia and achievement of specific recovery goals.

None Declared

One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia.

Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model’s accuracy (% agreement between patient classification of our model and the CGI-S).

Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728).

We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

Although obsessive–compulsive disorder (OCD) is highly prevalent in schizophrenia, its relationship with patients’ real-life functioning is still controversial.

The present study aims at investigating the prevalence of OCD in a large cohort of non-preselected schizophrenia patients living in the community and verifying the relationship of OCD, as well as of other psychopathological symptoms, with real-life functioning along a continuum of OCD severity and after controlling for demographic variables.

A sample of 327 outpatients with schizophrenia was enrolled in the study and collapsed into three subgroups according to OCD severity (subclinical, mild–moderate, severe). A series of structural equation modeling (SEM) was performed to analyze in each subgroup the association of obsessive–compulsive symptoms with real-life functioning, assessed through the Specific Levels of Functioning Scale and the UCSD Performance-Based Skills Assessment. Moreover, latent profile analysis (LPA) was performed to infer latent subpopulations. In the subclinical OCD group, obsessive–compulsive symptoms (OCS) were not associated with functioning, whereas in the mild–moderate OCD group, they showed a positive relationship, particularly in the domains of work and everyday life skills. The paucity of patients with severe OCD did not allow performing SEM analysis in this group. Finally, LPA confirmed a subgroup with mild–moderate OCS and more preserved levels of functioning.

These findings hint at a positive association between mild–moderate OCD and real-life functioning in individuals with schizophrenia and encourage a careful assessment of OCD in personalized programs to sustain daily life activities.

Comprehensive care programs, which include individually planned pharmacotherapy are associated with higher rates of recovery1 and better long-term prognosis2. However, there are barriers to individually optimised antipsychotic treatment both from both the patients and treatment teams perspectives.

To summarize the potential contribution of adequate long-term antipsychotic treatment to recovery or better outcomes in schizophrenia.

Review of research data.

Results A shorter duration of untreated psychosis, a lower number of relapses, and the absence of a chronic course of psychosis are associated with higher rates of recovery and a better prognosis. The OPUS early intervention program was associated with better outcomes for up to 10 years, but not for more than 20 years3. Second generation antipsychotics are associated with lower mortality rates, including suicides in young people with schizophrenia.4

Higher doses of antipsychotics are associated with poorer outcomes and with potential structural brain changes, while adequate (lower) doses of antipsychotics are associated with lower side effect burden and better overall outcomes5. A significant proportion of patient may benefit from polypharmacy (combination of 2 antipsychotics)6. Antipsychotic treatment discontinuation strategies are associated with the development of treatment resistance.7

Adequate (low dose) antipsychotic treatment is part of the complex early intervention programs and long term treatment of schizophrenia, which are associated with higher rates of recovery and good outcomes. The role of polypharmacy (combination of 2 antipsychotics) may need a reconsideration in the treatment guidelines of schizophrenia.

1. 1. Kane JM et al. The Journal of clinical psychiatry. 2015 Mar 25;76(3):16590.

2. 2. Posselt CM et al. 2021. American Journal of Psychiatry, 2021, 178(10):941-951

3. 3. Hansen HG et al. 2023. JAMA Psychiatry, 2023, 80(4): 371-379.

4. 4. Correll CU et al. World Psychiatry. 2022 Jun;21(2):248-71.

5. 5. Andreasen NC et al. 2013 Jun;170(6):609-15.

6. 6. Katona L et al. 2014 Jan 1;152(1):246-54.

7. 7. Emsley R et al2013 Feb 1;33(1):80-3.

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Recovery in Schizophrenia: The Role of Psychosocial interventions Recovery is individual and so needs individual responses from the mental health services. Different interventions are useful at different stages and of course they only “work” for some people. The paper will describe some psychosocial interventions and the role they might pay in the patient’s journey to their expected recovery. Three main strategies are often referred to – reducing symptoms, reducing barriers to recovery, and extending and maintaining recovery to achieve some stable and acceptable (to the patient) optimal level of functioning. Psychosocial intervention strategies are beneficial for each of these often thought of as independent, but they are inter-related with one type of therapy leading to reductions in the need for other therapies. The process of considering which one to start with is a choice and this paper will describe some decision making to ensure that patients have the best options.

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Codes of ethics provide guidance to address ethical challenges encountered in clinical practice. The harmonization of global, regional, and national codes of ethics is important to avoid gaps and discrepancies.

We compare the European Psychiatric Association (EPA) and the World Psychiatric Association (WPA) Codes of Ethics, addressing main key points, similarities, and divergences.

The WPA and EPA codes are inspired by similar fundamental values but do show a few differences. The two codes have a different structure. The WPA code includes 4 sections and lists 5 overarching principles as the basis of psychiatrists’ clinical practice; the EPA code is articulated in 8 sections, lists 4 ethical principles, and several fundamental values. The EPA code does not include a section on psychiatrists’ education and does not contain specific references to domestic violence and death penalty. Differences can be found in how the two codes address the principle of equity: the EPA code explicitly refers to the principle of universal health care, while the WPA code mentions the principle of equity as reflected in the promotion of distributive justice.

We recommend that both WPA and EPA periodically update their ethical codes to minimize differences, eliminate gaps, and help member societies to develop or revise national codes in line with the principles of the associations they belong to.

Minimizing differences between national and international codes and fostering a continuous dialogue on ethical issues will provide guidance for psychiatrists and will raise awareness of the importance of ethics in our profession.

The World Health Organization (WHO) has stated that in situations of armed conflict, “Around 10 percent of the people who experience traumatic events will have serious mental health problems, and another 10 percent will develop behavior that will hinder their ability to function effectively.” Problems include post-traumatic stress disorder, anxiety, depression, substance misuse, and possibly precipitation of psychosis. War has a catastrophic effect on the health and well being of nations. Studies have shown that conflict situations cause more mortality and disability than any major disease. Only through a greater understanding of conflicts and the myriad of mental health problems that arise from them, coherent and effective strategies for dealing with such problems can be developed.

None Declared

Theories propose that judgment of and reactivity to inner experiences are mediators of the effect of mindfulness-based interventions on generalized anxiety disorder (GAD). However, no study has tested such theories using brief, mindfulness ecological momentary intervention (MEMI). We thus tested these theories using a 14-day MEMI versus self-monitoring app (SM) control for GAD.

Participants (N = 110) completed self-reports of trait mindfulness (Five Facet Mindfulness Questionnaire), GAD severity (GAD-Questionnaire-IV), and trait perseverative cognitions (Perseverative Cognitions Questionnaire) at prerandomization, posttreatment, and 1-month follow-up (1MFU). Counterfactual mediation analyses with temporal precedence were conducted.

Improvement in pre–post mindfulness domains (acceptance of emotions, describing feelings accurately, acting with awareness, judgment of inner experience, and reactivity to inner experience) predicted pre-1MFU reduction in GAD severity and pre-1MFU reduction in trait perseverative cognitions from MEMI but not SM. MEMI reduced pre–post reactivity to inner experiences (but not other mindfulness domains) significantly more than SM. Only reduced pre–post reactivity significantly mediated stronger efficacy of MEMI over SM on pre-1MFU reductions in GAD severity (indirect effect: β = −2.970 [−5.034, −0.904], p = .008; b path: β = −3.313 [−6.350, −0.276], p = .033; percentage mediated: 30.5%) and trait perseverative cognitions (indirect effect: β = −0.153 [−0.254, −0.044], p = .008; b path: β = −0.145 [−0.260, −0.030], p = .014; percentage mediated: 42.7%). Other trait mindfulness domains were non-significant mediators.

Reactivity to inner experience might be a mindfulness-based intervention change mechanism and should be targeted to optimize brief MEMIs for GAD.

War represents one of the major traumatic events for humans and comes with enormous consequences for individuals and society over a long period of time. War causes acute psychological trauma, but also results in subacute, chronic psychiatric disorders for all those experiencing or witnessing direct war trauma and to those experiencing indirect war trauma resulting from losing the safety of home and financial income, to losing family members and close ones. Therefore, acute reaction to trauma may result in maladaptive disorders and PTSD within days of experiencing trauma and with chronic posttraumatic stress conditions even years after the traumatic experience. Chronic PTSD is associated with higher morbidity of somatic conditions, including hypertension, hyperlipidemia, metabolic syndrome, all resulting in cardiovascular and cerebrovascular disorders. Additionally, according to reports from World Health Organisation (WHO), it has been projected that in emergencies, on average, the percentage of people with a severe mental disorder increases by 1 per cent over and above an estimated baseline of 2–3 per cent. In addition, the percentage of people with mild or moderate mental disorders, including mood and anxiety disorders (including PTSD), may increase by 5–10 per cent above an estimated baseline of 10 per cent. Furthermore, research indicate the possibility of a transgenerational effect of trauma, via maternal psychosocial stress and socioeconomic disadvantage during pregnancy but also through adverse parenting practices, as parenting style may change when exposed to war traumas.

As war affects mental health of different population groups dramatically and long-term, establishment of long term and coordinated mental health care is necessary. In the presentation, examples of practices from Croatia will be discussed.

None Declared