Early life experiences, particularly childhood adversity, can have enduring effects on mental health. Males and females differ in their vulnerability to specific adversities, symptom expression, and the mechanisms linking adversity to psychopathology. For example, certain symptoms may be more strongly associated with abuse in females and with neglect in males, reflecting sex-specific patterns of risk. Moreover, the developmental pathways through which adversity contributes to psychopathology may also differ by sex. In females, one pathway linking early adversity to later psychosis-related outcomes may involve pubertal timing, particularly age at menarche. Puberty represents a critical developmental period during which environmental exposures interact with biological maturation, shaping hormonal, neural, and psychosocial processes. As such, pubertal timing may function as a sex-specific mediator of risk, helping to explain why females exposed to early adversity show heightened susceptibility to certain symptoms. Previous research suggests that childhood adversity is associated with earlier menarche, which in turn increases vulnerability to both internalizing and externalizing difficulties. However, the role of pubertal timing in the development of psychosis-related outcomes remains underexplored. This presentation reports new findings on sex differences in the impact of environmental exposures on symptom profiles, as well as female-specific developmental mechanisms shaping mental health outcomes. By elucidating how early adversity interacts with pubertal timing and other sex-specific pathways, this work contributes to improved early identification, prevention, and targeted intervention strategies.

None Declared

Worldwide, the increasing trend of young people experiencing mental health challenges constitutes a major public health concern. There is a need for preventive and mental health-promoting initiatives targeting youths. This study examines the effectiveness of headspace Denmark – a nationwide counseling service for 12- to 25-year-olds – at 6-month follow-up.

The study was a quasi-experimental trial. 12- to 25-year-olds who had participated in counseling sessions in headspace were matched with a comparable control group, using propensity score matching. Survey data, collected at baseline and at 6-month follow-up, were linked to national register data. Outcome measures were well-being, loneliness, self-efficacy, life satisfaction, and health-related quality of life. Linear regression was used to test differences between the two groups. Subgroup analyses were conducted. Post-hoc Population Attributable Fractions (PAFs) were estimated to describe the effect sizes at the population level.

The inclusion period was 14.5 months from September 2022. Follow-up data were collected until mid-August 2024. The number of participants in the intervention group was 1,362. In the control group was 3,192. A statistically significant difference between the groups was observed for well-being at 6-month follow-up (Cohen’s D = 0.11; p = 0.018). The estimated PAF was 4%, assuming a prevalence of low well-being in the target group of 70% and the intervention reaching 80% of the target group.

headspace had an effect on participants’ well-being. Based on the estimated PAF, headspace can play a crucial role in early health promotion and disease prevention among young people in Denmark.

Bipolar disorder (BD) exhibits heterogeneous characteristics, frequent comorbidities, and suboptimal treatment response, negatively impacting health outcomes. Environmental and biological models are being investigated, but overall findings are fragmented. Our study proposes an innovative framework that combines multi-source and multi-site clinical, environmental and neuroimaging data with artificial intelligence tools to create and test predictive diagnostic and stratification models for BD.

Data of healthy controls (HC) and BD were analyzed, including (i) magnetic resonance imaging (MRI) from Human Connectome Project (n>1000 HC) and the STRATIBIP network (n>500 HC, n>500 BD), (ii) environmental data from Italian BD patients (n>200). Normative deep learning models of brain morphology were created using HCP and applied to STRATIBIP for anomaly detection; graph neural networks (GNNs) were applied to brain morphological networks (MBNs) to identify BD brain network markers; in Italian BD, topological data analysis (TDA) was applied to environmental data for outcome stratification.

Normative model application to STRATIBIP showed significant deviations in BD in basal ganglia and hippocampus. In STRATIBIP, BD vs. HC classification based on MBNs reached maximum accuracy with GNNs (68%), overcoming traditional ML methods. In Italian BD, TDA showed key predictive roles of (i) external environment for psychiatric comorbidities, (ii) psychiatric history for episode’s polarity.

Using advanced AI, we showed the potential of brain regions and networks as candidate BD biomarkers. We showed that brain alterations in BD are heterogeneous and partly shared with physiological variations. We found that environment plays a pivotal role in predicting BD symptomatology, underscoring the necessity to transition from unifying to multi-dimensional disease perspective.

None Declared

The European Brain Council project “Rethinking Schizophrenia” aims to examine the existing state of patient care pathways across Europe. The study objectives of Phase 2 were to evaluate the current models of schizophrenia care on mental health outcomes, access and satisfaction with care, and to identify the foundations of integrated care pathways for young people with first-episode psychosis.

Using the care pathway, a questionnaire was developed and anonymously disseminated to mental health professionals in nine European countries (Belgium, Denmark, France, Germany, Hungary, Italy, Poland, Spain, and the United Kingdom). The survey included 45 questions and addressed the quality and continuity of care from the first onset of psychosis to long-term care, including assessment of the mental health care systems.

A total of 203 responses were obtained. The majority of mental health professionals were psychiatrists (75%), followed by psychologists (11%), nurses (7%), social workers (2%), and GPs and others (5%). The responses were analyzed qualitatively. The results revealed dissatisfaction with the current state of schizophrenia care systems and significant variability in quality of care. The factors that affect the care pathways most are assessment and early intervention services, continuity of care, availability of various types of services and treatments, collaborative decision-making, and utilization of new technologies.

A comprehensive, integrated approach is essential to improve schizophrenia care across Europe. This strategy emphasizes early intervention, equitable access to treatments, coordinated care models, psychosocial support, and long-term recovery through a biopsychosocial framework and emerging technologies.

Randomized-controlled trials (RCTs) are not free of biases. For instance, expectation effects are an important confound in psychiatric RCTs. In this talk, I will explore the relationship between expectation effects, blinding integrity, and estimates of efficacy regarding active treatment and placebo. Proposed methods to mitigate these confounders and enhance the reliability of RCTs across psychiatry will be discussed. I will conclude with suggested research directions and novel approaches to reduce potential confounding by expectation effects.

N. Huneke Grant / Research support from: I have received funding from the NIHR and MRC.

Clinical care guidelines on psychiatric pharmacotherapies are based on evidence derived from randomized controlled trials (RCTs). RCTs typically have strict eligibility criteria, which may lead to situations where evidence on the effectiveness and safety of medications represents only a subset of the real-world population, i.e., unselected patients seen in everyday clinical practice.

To quantify the proportion of real-world individuals who would be ineligible for participation in RCTs of schizophrenia or major depressive disorder (MDD), to explore outcomes of eligible versus ineligible individuals, and to compare these rates between schizophrenia and MDD.

Typical RCT eligibility criteria were applied to real-world populations derived from Finnish and Swedish national registers, in designs mimicking RCTs in terms of duration and inclusion. Proportions of RCT-ineligible individuals were calculated based on any exclusion criteria as well as specific criteria, and risks of outcomes were compared between ineligible versus eligible individuals using Cox regression.

In schizophrenia, 79% of individuals would be ineligible for RCTs, whereas in MDD, the proportion was approximately 34%. These proportions depended heavily on the definition of concomitant somatic conditions as an exclusion criterion. Substance use disorders contributed significantly more to schizophrenia RCT ineligibility than to MDD RCT ineligibility. However, the risk estimates for primary outcomes were considerably larger for MDD than for schizophrenia when comparing ineligible with eligible individuals.

RCTs may face challenges in representing real-world individuals with schizophrenia and MDD. More inclusive eligibility criteria for RCTs are needed to improve the generalizability of trial evidence and the foundation of treatment guidelines.

H. Taipale Grant / Research support from: Janssen, Speakers bureau of: Gedeon Richter, Janssen, Lundbeck, Otsuka.

Non-substance-related addictive behaviours have traditionally been treated separately from substance use disorders. However, the DSM-5 reclassification of gambling disorder within Substance-Related and Addictive Disorders has opened new avenues for research. This decision was justified by the similarities in the phenomenology, psychological, neurobiological, and genetic correlates across these disorders. Through a comprehensive systematic analysis, we aimed to identify factors associated with gambling disorder and examine their involvement in candidate behavioural addictions to assess the case for reclassification.

Using gambling disorder as the gold standard, we identified 75 factors grouped into 9 categories to compare gambling disorder with alcohol use disorder (AUD) as a standard chemical addiction, gaming disorder, compulsive sexual behaviour disorder (CSBD), binge eating disorder (BED), compulsive buying–shopping disorder (CBSD), exercise addiction, and work addiction.

Data availability, compared to gambling disorder, was 100% for AUD; however, it was limited, ranging between 48% and 69% for gaming disorder, BED, and CSBD, and remained below 23% for other behaviours. The analyses confirmed a strong similarity between gambling disorder and alcohol use disorder (92.2%) and gaming disorder (98.9%), followed by CSBD (89.7%) and BED (84.9%). All other conditions showed weaker, although still high, congruence with gambling disorder (between 67% and 74% for the unweighted concordance rates).

Our findings reaffirm AUD, gambling, and gaming disorder as addictive disorders and provide evidence that the studied candidates could be considered as behavioural addictions, especially binge eating disorder and CSBD.

In the post-pandemic context, demand for mental health care has increased substantially worldwide, exceeding the capacity of traditional service delivery models. While integrated care and task-shifting approaches have partially addressed this gap, scalable solutions that reduce reliance on highly specialized staff are increasingly needed. Digital health technologies offer significant potential to improve access, efficiency, and equity in mental health care delivery.

Tools such as mobile apps, web-based platforms, wearable devices, and digital phenotyping can support diagnosis, monitoring, and intervention, particularly in settings where mental health professionals are scarce.

National health systems are obligated to deliver evidence-based care equitably and efficiently. However, evaluating and implementing digital mental health interventions presents unique challenges. Unlike pharmacological or psychological treatments, apps lack clear placebo equivalents, face high attrition rates, and often exclude individuals without access to compatible devices or sufficient digital literacy. As a result, evidence derived from traditional randomized controlled trials may not fully capture real-world effectiveness, usability, or reach, particularly among vulnerable and marginalized populations.

A key advantage of digital interventions is their capacity for continuous data collection at minimal cost. This enables ongoing evaluation before, during, and after implementation, analogous to post-marketing surveillance for medications but without reporting delays. Continuous monitoring of clinical outcomes, engagement, and potential harms—including privacy breaches, misuse, and unintended increases in healthcare utilization—should be a prerequisite for apps adopted by national health systems.

Robust evaluation frameworks are required to assess not only clinical outcomes and population reach, but also usability, acceptability, safety, and ethical use of data. Clear distinctions are needed between apps that claim therapeutic benefit and those supporting lifestyle or wellness goals, with corresponding regulatory standards. As app prescription becomes more common, dedicated expertise may be required to guide safe and effective use, similar to the role of pharmacists in medication management. Looking ahead, advances in artificial intelligence may further expand the role of digital tools in mental health care, reinforcing the need for adaptive, continuous, and system-level evaluation approaches.

None Declared

To prospectively examine cancer-related mortality over a 10-year period in patients affected by major depression (MDD), Emilia Romagna Region (ERR), Northern Italy, and to compare these findings with those observed in the regional population.

The ERR Mental Health Registry was used to identify all patients aged ≥18 years who accessed the ERR mental health departments with an ICD-9CM diagnosis of MDD between 2008–2017. Information on deaths were retrieved from the ERR Cause of Death Registry. We calculated standardized mortality ratio using the regional population as the standard.

Among 13,351 patients suffering from MDD, 34,11% died of cancer. In comparison with the ERR population, cancer mortality was 86% (95% CI 1.69–2.04) higher among patients with MDD. Site-specific analyses showed significantly increased mortality for gastrointestinal (esophagus, colon, rectosigmoid, rectum, anus, liver, gallbladder and biliary tract, pancreas), respiratory (trachea, bronchus and lung), uro-genital (breast, ovary and other genital organs, bladder, prostate, kidney, pelvis, ureter and unspecified urinary organs) and other cancers (melanoma, brain and other CNS tumors, lymphoid, hematopoietic and related tissue).

The study confirms the risk for people affected by MDD to have a higher mortality rate and shorter survival in comparison with the general population. These findings highlight the urgent need for greater attention to the physical health of psychiatric patients through optimal collaboration between mental health, oncology and primary care departments.

The ICD-11 introduces a dimensional, severity-based approach to personality disorder (PD) diagnosis, moving away from categorical typologies. While generally well received by clinicians and service providers, concrete examples of its implementation in clinical practice remain limited.

This presentation draws on an ongoing study examining the learnability and acceptability of the ICD-11 model across clinical and training settings in Sweden. We focus on experiences at the Unit for Personality Disorders, Sahlgrenska University Hospital in Gothenburg, using clinician reports and organizational observations to assess how the new framework influences routine care.

Early observations highlight practical challenges in integrating severity-based assessment into diagnostic workflows, treatment planning, and multidisciplinary collaboration. Organizational factors—including aligning level of care with severity, establishing a shared clinical language, and coordinating planning across specialties—emerge as important for facilitating implementation. Clinicians report potential benefits of the stratified approach, such as more nuanced clinical descriptions, improved communication, and individualized care planning, alongside ongoing hurdles in translating the model into practice within existing organizational structures.

These initial findings provide insight into the feasibility and implications of ICD-11 adoption in Sweden. They illustrate both the opportunities and practical challenges of implementing a dimensional model for PD, offering lessons relevant to other European and international settings.

None Declared

It is well-established that mental illness is associated with excess and premature mortality. Consequently, the assessment of physical health should be routine in the evaluation of persons living with mental disorders. Herein, we introduce the development of a global instrument to assess physical health status in persons with mental disorders.

Following the development of the Transdiagnostic Global Impression–Psychopathology (TGI-P) scale, a novel scale of physical health status, the Transdiagnostic Global Impression–Somatic Symptoms and Signs (TGI-3S), was created using similar principles. Scale development followed a multistage process involving (1) item generation using deductive methods, (2) two content validations by an expert panel, and (3) two iterative usability-testing rounds with patients and caregivers. These rounds therefore assessed understandability and ease of use for wording, visual format, and emotional/cognitive load of the instrument. The psychometric validation is underway.

The TGI-3S was developed as a front-end screening tool resulting in a broad somatic burden map, rather than a diagnostic instrument. Throughout the development process, experts, patients, and caregivers evaluated the TGI-3S positively. In the final usability round, 96% found the aim of the scale clear, and 87% considered the instructions easy to follow. The scale demonstrated high-level usability, with 72% completing the TGI-3S in <5 minutes. Emotional and cognitive burden of completing the TGI-3S was rated as low, and item wording was well-understood.

With psychometric validation underway, the TGI-3S offers an anamnesis-embedded, brief, yet comprehensive tool for facilitating the assessment of somatic health in patients with mental disorders.

Predictive validity is the sine qua non of any diagnostic system. Although prior research supports the clinical utility of the DSM-5 Alternative Model for Personality Disorders (AMPD), longitudinal interview-based studies examining whether impairment of personality functioning predicts long-term psychosocial and occupational outcomes remain limited.

The Norwegian Multisite Study of the AMPD (NorAMP) included 282 clinically assessed patients at baseline (2015–2016), of whom 153 participated in an 8-years follow-up study. Patients were recruited from a variety of clinical sites, including mental health outpatient departments, inpatient departments, addiction treatment units, and units specialized in the assessment and treatment of personality disorders. The latter units were all part of the Norwegian Network for Personality Disorders, a large clinical network including 18 treatment units.

Traditional personality disorder diagnoses were assessed using the Structured Clinical Interview for DSM-5 Personality Disorders (SCID-5-PD). The Level of Personality Functioning Scale (LPFS) was assessed using the Structured Clinical Interview for DSM-5 AMPD (SCID-5-AMPD-I), administered by trained clinicians at baseline and 8-years follow-up.

Preliminary longitudinal analyses indicate modest rank-order stability of global LPFS across eight years (r ≈ .37), suggesting both continuity and substantial individual change. Baseline LPFS severity was significantly associated with long-term psychosocial impairment and occupational functioning. More findings will be presented at the symposium.

None Declared

Anti-LGI1 autoimmune encephalitis can initially present with affective, psychotic, or behavioral symptoms, leadingto misdiagnosis as a primary psychiatric condition. Catatonia associated with this entity is rare and oftenunderrecognized. We report a case of delayed diagnosis, where catatonia emerged in the context of a progressiveneuropsychiatric syndrome later confirmed as anti-LGI1 autoimmune encephalitis

A 49-year-old male presented with an 8-month evolution of neuropsychiatric symptoms, including panic attacks,hallucinations, disorganized behavior, and faciobrachial dystonic seizures. He received multiple psychiatrictreatments with no sustained improvement. In early 2025, neurology evaluation included a brain MRI showingcortical atrophy and temporal FLAIR hyperintensities; EEG showed diffuse delta slowing and temporal sharp waves.CSF analysis revealed elevated protein levels without pleocytosis. Serology confirmed anti-LGI1 antibodies. InMarch 2025, psychiatry assessed catatonia using the Bush-Francis Catatonia Rating Scale (BFCRS), scoring 10 onscreening and 18 on severity. Treatment with lorazepam and quetiapine, and later instalation of memantine led to significant clinical improvement.Rituximab was later administered with favorable neurological stabilization.

The patient exhibited catatonic features including fixed gaze, rigidity, echolalia, automatic obedience, stereotypies,and disorganized speech. Marked clinical improvement followed immunotherapy and benzodiazepines.

This case highlights the importance of considering autoimmune encephalitis in patients with atypical psychiatricsymptoms and poor response to psychotropics. Early neurological evaluation and systematic screening forcatatonia can significantly improve diagnostic accuracy and outcomes. Multidisciplinary collaboration is crucial foridentifying catatonia as a possible manifestation of underlying neuroinflammatory disorders.

None Declared

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder, with symptoms that remit or persist over time. Biological mechanisms underlying symptom change remain poorly understood, though epigenetic processes, like DNA methylation (DNAm), may serve as dynamic biomarkers of clinical outcomes. We examined change in DNAm in children and adolescents with and without ADHD, including differences between remitted and persistent ADHD.

We analyzed 219 saliva samples from 94 participants (aged 9.5–14.5 years) attending two to three waves of NICAP (Neuroimaging of the Children’s Attention Project). DNAm was profiled using the Infinium MethylationEPIC BeadChip. Linear mixed models adjusted for age, sex, medication, batch, and cell-proportion assessed longitudinal change. Comparisons included (1) individuals with versus without ADHD, (2) persistent or remitted ADHD versus without ADHD, and (3) persistent versus remitted ADHD. False discovery rate correction controlled for multiple testing (FDR-adjusted-p < 0.05).

Comparison (1) showed null findings after correction for multiple testing. In contrast to those without ADHD (2), the average DNAm was statistically different at 2 sites in persistent ADHD (FDR-adjusted-p < 0.05) and 3 sites in remitted ADHD (FDR-adjusted-p < 0.03), and methylation of 3 additional CpGs differentially changed in persistent ADHD (FDR-adjusted-p < 0.04). Remitted differed from persistent ADHD (3) at 4 CpGs, including cg21443143 (ZFAT), which showed a decline over time. Gene enrichment links findings to brain structures and function, though these did not survive multiple testing.

Our study identified several epigenetic differences between remitted and persistent ADHD outcomes from typical development, and from each other. Given the early stage of this research, our findings warrant further prospective epigenome-wide studies into these diagnostic trajectories.

Major psychiatric disorders (MPDs) and premenstrual disorders (PMDs) are often comorbid, with indications of shared genetic architecture. However, the specific genetic variants underlying this comorbidity remain elusive. The aim of this study was to identify genomic loci shared between MPDs and PMDs, and to assess the functional characteristics of genes mapped to these loci.

We used genome-wide association data for symptoms of PMDs (S-PMD, n = 67 068) from the Norwegian Mother, Father and Child Cohort Study (MoBa), and for MPDs (schizophrenia, n = 130 644; bipolar disorder, n = 827 335; major depression, n = 1 918 432) from the Psychiatric Genomic Consortium. Shared genetic loci were identified with the conjunctional false discovery rate (conjFDR). Genes mapped to the identified loci were included in functional and pharmacological gene-set enrichment analyses (GSEAs).

We identified 20 loci shared between S-PMD and the MPDs, including 19 novel loci for S-PMD (conjFDR<0.05). GSEA revealed genes involved in calcium signaling and neuronal projection pathways. The drug enrichment analysis identified 36 drugs, including riluzole and mianserin, significantly associated with the identified molecular pathways.

We identified 20 genetic loci shared between the S-PMD and MPDs, implicating calcium transmission in the pathogenesis of PMDs. Together with the drug enrichment results, this provides a biological basis for repurposing existing drugs in the treatment of PMD.

Catatonia is most commonly associated with schizophrenia and mood disorders, particularly depressive episodes; however, its occurrence during manic episodes of bipolar affective disorder remains relatively rare and insufficiently described. This presentation reports the case of a female patient with a long history of bipolar affective disorder and multiple psychiatric hospitalizations, who developed prominent catatonic symptoms during a severe manic episode.

During hospitalization, the patient exhibited marked psychomotor agitation, severely disorganized behavior, and repetitive motor automatisms, fulfilling criteria for an excited form of catatonia. The clinical course, diagnostic challenges, and therapeutic interventions are discussed in detail. The diagnostic work-up included laboratory testing, neuroimaging, and neurological hospitalisations to exclude organic causes of catatonic symptoms. Treatment strategies comprised pharmacotherapy tailored to both manic and catatonic symptoms, with careful monitoring of clinical response and adverse effects.

In addition, a brief review of the available literature on catatonia occurring in the course of mania is presented. Published reports suggest that such cases are uncommon and often underrecognized, contributing to diagnostic uncertainty and therapeutic difficulties. This case highlights the need for increased clinical awareness of catatonic manifestations in manic episodes and emphasizes the importance of early recognition to optimize treatment outcomes. Further research is warranted to establish clear diagnostic and therapeutic guidelines for this challenging clinical presentation.

None Declared

Psychometric network analysis offers a granular understanding of problem gambling (PG) by modeling individual symptoms within an interconnected system. Identifying central symptoms can help explain symptom co-occurrence and core symptoms relevant for escalating severity.

We estimated undirected cross-sectional and directed cross-lagged network models based on four representative Norwegian population surveys (2013, 2015, 2019, and 2022; age range 16–74) and assessed network stability, accuracy, and generalizability. Cross-sectional samples ranged from n = 3,232 to 6,034 (47–50% women) and cross-lagged samples included n = 3,043 (2013–2015, 50% women) and n = 2,749 (2019–2022, 47% women). PG symptoms were measured with the Problem Gambling Severity Index alongside self-reported gambling expenditure.

Within undirected networks, financial problems showed the strongest strength centrality and these networks showed strong generalizability, including the 2019 and 2022 surveys per Network Comparison Test (p = .65), edge presence (φ = .79), and edge weight (r = .85) correlations. Within directed networks, borrowing money had the strongest association with symptoms at follow-up (out-strength), while guilt at follow-up was most strongly predicted by other symptoms (in-strength). Generalizability between the 2013–2015 and 2019–2022 networks was inconclusive, with low correlation in edge presence (φ = .08) and high correlation in edge weights (r = .74).

Financial problems and borrowing money emerged as the most central PG symptoms in undirected and directed networks, respectively. Following further investigation, these symptoms may act as informative targets for screening, early intervention, and harm-reduction policy.

Catatonia is a potentially life-threatening psychomotor syndrome that can complicate substance intoxication and may be missed in acute psychiatric and addiction settings. Synthetic cannabinoids (e.g., Spice/K2) are associated with severe neuropsychiatric presentations including agitation, psychosis, autonomic instability, and diagnostic ambiguity. This talk presents a clinical case of a 17-year-old male admitted with first-episode psychosis and behavioural disorganisation after synthetic cannabinoid use (positive K2 toxicology). Despite initial management for acute psychosis, the patient developed catatonic features including elective mutism, rigidity and impaired self-care, accompanied by escalating agitation and hallucinations. The case highlights key diagnostic dilemmas (catatonia vs delirium, intoxication, NMS/serotonin toxicity), practical bedside assessment, and evidence-based management principles, including early consideration of benzodiazepines, medical monitoring, and avoidance of potentially harmful treatment delays. The presentation emphasises that recognition of substance-induced catatonia enables timely intervention and prevention of complications such as dehydration, rhabdomyolysis, aspiration and cardiovascular instability.

None Declared