In addition to play a key role in the generation of the inflammatory response, cyclooxygenases (COXs) are involved in a variety of other physiological processes, including dopaminergic signaling, and the skin flush response to the water-soluble B vitamin niacin. Patients with schizophrenia frequently exhibit abnormal signaling of dopamine and other neurotransmitters and attenuated niacin skin flush response. Clinical studies reported beneficial effects of selective cyclooxygenase-2 (COX-2) inhibitors on the simptom expression of schizophrenia, as measured by the Positive and Negative Syndrome Scale (PANSS). Several studies investigated potential correlations between functional rs689466 polymorphism (A/G polymorphism) of the COX-2 gene and etiology of schizophrenia, but the results have not been consistent. While we did not find evidence that the COX-2 polymorphism was associated with an elevated risk of schizophrenia risk in a Croatian population, we observed that the COX-2 polymorphism contributes to attenuated niacin skin flushing in patients with schizophrenia.

To the best of our knowledge, no studies have investigated the potential associations between any COX-2 gene polymorphisms and the etiology of nicotine dependence. Based on the elevated smoking rate observed consistently in patients with schizophrenia and the possible relevance of COX-2 genes in schizophrenia and nicotine dependence via dopaminergic signaling, we investigated whether the risk of nicotine dependence among patients with schizophrenia is associated with the COX-2 gene rs689466 polymorphism. Given evidence suggesting that smoking influences the severity of schizophrenia, we also hypothesized that an interaction between smoking and the COX-2 polymorphism may contribute to the age of schizophrenia onset and/or PANSS psychopathology.

Polymerase chain reaction analysis/restriction fragment length polymorphism analysis was used to genotype 190 chronically ill schizophrenia patients treated with antipsychotic medications (104 males/86 females).

There were no significant differences in the distribution of COX-2 genotypes and alleles in male or female schizophrenia patients who were stratified based on their smoking status and no COX-2 genotype-smoking interaction on PANSS psychopathology (P > 0.05). We revealed a significant COX-2 genotype-smoking interaction on the time of disease onset among female patients (P < 0.05). An earlier onset, observed for female smokers carrying the G-allele in their COX-2 genotypes (COX-2-GG homozygous and COX-2-AG heterozygous), in comparison to nonsmoking COX-2-G allele carriers, contributed mostly to this finding.

Our results indicate no COX-2 gene polymorphism’s effect on the risk of nicotine dependence, but they suggest that COX-2 genotype-smoking interaction might be of relevance in disease onset, in a gender-specific fashion.

None Declared

Inflammation has emerged in recent year as one potential contributor pathway in the background of several neuropsychiatric disorders, including depression. It is also increasingly understood that inflammation may exert its role via mediating the effect of stress in the etiology of such conditions. Therefore, understanding the role of inflammation in the background of depression would offer novel insight into the involved processes facilitating the identification of related biomarkers, novel treatment targets, as well as possibilities for early screening, risk identification, and prevention and intervention. In spite of these promising possibilities, currently we know little about the shared genetic risk in case of autoimmune or inflammatory conditions and depression.

Our present analyses aimed at investigating, using polygenic risk scores, if genetic predisposition to inflammatory or autoimmune disorders predicts depression scores and if recent exposure to life stressors interacts with the effect of genetic variation.

For establishing polygenic risk scores (PRS) for different inflammatory/autoimmune conditions, we pre-existing GWAS summary statistics were used for systemic lupus erythematosus (SLE) (7219 cases, 15991 controls), autoimmune thyroid disease (AT) (859 cases, 324074 controls), and atrophic gastritis (AG) (180 cases, 456168 controls). The NewMood database (N=1820) was used as target data. Brief Symptom Inventory Depression Scale scores reflecting current depressive symptom severity was used as outcome depression phenotype. PRS calculations were performed with LDpred2. Linear regression models performed with R (4.1.3) were used to investigate the main effect of the PRS and the interacting effect of recent stress and PRS on current depression score.

The main effect analyses showed that SLE-PRS had a significant effect on depression (beta=0.2389, p=0.0175) while AT-PRS (beta=0.4094, p=0.9763) and AG-PRS (beta=0.4741, p=0.5795) did not show significant main effects. Interaction analyses did not show significant effect in case of any of the examined autoimmune/inflammatory disorders (SLE-PRS x recent stress: beta=0.1041, p=0.2016; AT-PRS x recent stress: beta=19.82, p=0.05811; AG-PRS x recent stress: beta=0.3169, p=0.6661).

Our present results show that while there is an overlap in the genetic background of depression and some autoimmune or inflammatory conditions, current stressors may not have an interacting role in this relationship. Our results need replication in larger samples, and should be extended to investigate polygenic scores for other conditions and other types of stress.

This study was funded by NAP2022-I-4/2022, K143391, 2019-2.1.7-ERA-NET-2020-00005, TKP2021-EGA-25, ÚNKP-23-3-I-SE-73.

None Declared

Methamphetamine use disorder (MUD) and associated conditions impose a significant burden not only on affected individuals and their families but also on communities. Neurotransmitter system imbalances, mitochondrial dysfunction, oxidative stress, and activation of the inflammasome have all been implicated in methamphetamine-induced neurotoxicity. However, whether MUD is associated with peripheral mtDNA alterations remains uncertain.

This study aimed to investigate the relationship between mtDNA copy number and clinical parameters in individuals diagnosed with MUD, comparing them with healthy controls.

Our study is a case-control research involving 52 patients diagnosed with MUD based on DSM-5 criteria and 52 healthy controls. Peripheral blood samples were collected, and leukocytes were isolated using the ELK Biotech Genomic DNA Extraction Kit for genomic DNA extraction. DNA samples were diluted to a concentration of 0.5-2 ng/μl for mtDNA copy number analysis, which was performed using the ScienCell qPCR Assay Kit. Two qPCR reactions were carried out for each sample using mtDNA and SCR primer sets. Known mtDNA copy number samples were used as references, and mtDNA copy numbers for each sample were calculated using the comparative ∆∆Cq method.

When comparing the mtDNA copy numbers between patients diagnosed with MUD and the control group, the mtDNA copy number in individuals with MUD was found to be significantly lower than that of the control group (p=.001). After controlling for age and gender, clinical parameters (suicide attempt, non-suicidal self-injury, duration of disorder, withdrawal symptoms, psychosis) and scale scores were compared based on mtDNA copy numbers. Among these, only substance use duration showed a statistically significant difference between the groups (p=.045). Additionally, in this study, a significant negative correlation was found between mtDNA copy numbers and the duration of disorder in MUD patients (r=-.369, p=.008).

This is the first study examining the relationship between peripheral mtDNA alterations and clinical parameters in individuals diagnosed with MUD. A previous study showed that individuals with MUD exhibited decreased mtDNA copy numbers and increased mtDNA damage compared to healthy individuals in the Chinese population. Consistent with these findings, it was suggested that methamphetamine could lead to mitochondrial dysfunction and a reduction in mtDNA copy numbers in cell lines and animal models. In conclusion, individuals with MUD show decreased mtDNA copy numbers in peripheral blood samples, potentially related to increased autophagy. In this context, the reduction in mtDNA copy numbers could be used as a biomarker for MUD, and preventing this reduction may be beneficial in the clinical treatment of addiction.

None Declared

Mental disorder may affect individual’s ability to operate the motor vehicle. Previous studies have found that patient’s negative emotions may trigger aggressive driving behaviors. Thus, efficiently evaluating the correlation between emotions and driving behaviors in individuals with mental disorders has been drawn emphasis.

To explore the related factors of fitness-to-drive of individuals with mental disorders, to determine the application value of traffic psychology scales in assessment for fitness-to-drive of individuals with mental disorders, and to help establish consummate and effective assessment systems.

One hundred individuals with mental disorders were enrolled as the patient group, and 100 healthy individuals were enrolled as the control group. Positive and Negative Syndrome Scale (PANSS) was used to assess the psychiatric symptoms of the patient group. Driver Profile of Mood States (DPOMS), Driver Anger Scale (DAS), and Driving Behavior Scale (DBS) were used to evaluate the performance during driving within two groups. T-test were used to compare the differences in each factor score of traffic psychology scales within two groups. Pearson’s correlation analysis was used to calculate the correlation between scores of PANSS and scores of traffic psychology scales of the patient group.

The patient group had significantly higher score of driving function deficit in DBS than the control group (t=2.48, P<0.05), but scores of hostile gestures, impolite driving, overly cautious behaviors in DBS and total score of DAS showed the opposite (P<0.05). Positive syndrome in PANSS was positively related to traffic congestion in DAS (r = 0.315, P < 0.05). Anger in DPOMS was positively related to driving function deficit (r = 0.488, P < 0.01) and hostile behaviors in DBS (r = 0.510, P < 0.01), whereas it was negatively related to overly cautious behaviors in DBS (r = -0.417, P < 0.05). Anxiety and depression were also related to some factors in DAS and DBS.

The study found the practical application value of DPOMS, DAS, and DBS in assessment for fitness-to-drive of individuals with mental disorders. Patient’s anger in specific traffic situations such as traffic congestion may be mainly related to their positive syndrome. Patient’s anger may be a trigger of aggressive driving behaviors, and other emotions such as anxiety and depression also play important roles. Patient’s aggressive driving behaviors may be attributed to the compounding of many negative emotions.

S. Wang: None Declared, X. Ling: None Declared, Q. Zhang: None Declared, H. Li Grant / Research support from: This study was supported by National Key R & D Program of China [grant number 2022YFC3302001], National Natural Science Foundation of China [grant number 81801881], Science and Technology Committee of Shanghai Municipality [grant numbers 20DZ1200300, 21DZ2270800, 19DZ2292700].

Psychiatric emergencies are a global challenge requiring timely, effective interventions. Traditional intra-hospital approaches often struggle to address the complexity of these crises in a patient-centered and family-inclusive manner. Trento’s Mental Health Service has implemented a community-based, multidisciplinary approach to manage psychiatric emergencies, emphasizing the socio-familial context of each crisis.

This study aims to evaluate the effectiveness of the Trento Crisis Team in managing psychiatric emergencies outside of hospital settings, reducing hospital admissions, and enhancing patient and family engagement in the recovery process. Additionally, we assess the impact of the crisis service on public stigma related to mental health crises.

The study reviews the structure and organization of the Trento Crisis Team, which operates within the Mental Health Centre. The team includes 3 psychiatrists, 5 nurses, 5 educators/psychiatric rehabilitation technicians (TERP), and 5 Peer Support Specialists (“ESP” in Italian). Data were collected from emergency intervention records, hospital admission rates, and user satisfaction surveys. Comparisons were made between territorial and intra-hospital crisis management outcomes, with statistical analysis on key performance indicators such as the number of hospital admissions and compulsory health treatments.

Preliminary results indicate a reduction in hospital admissions (Image 1) and a significant decrease in the number of compulsory interventions (Image 2) since the establishment of the dedicated Crisis Team. While overall user numbers have increased (Image 3), the availability of peer support and home-based interventions has improved patient satisfaction and engagement. However, the system still faces challenges in reducing hospital admissions due to the increasing volume of psychiatric emergency cases.

Image 1:

Image 2:

Image 3:

The community-based crisis management model adopted by the Trento Crisis Team offers a promising alternative to traditional hospital-based interventions. By focusing on the individual’s socio-familial environment and engaging Peer Support Specialists, the service has demonstrated a capacity to humanize mental health crises and reduce public stigma. Continued efforts are necessary to address resource constraints and further integrate crisis management into community mental health pathways.

None Declared

Patients with mental disorders often engage in extreme and unpredictable violent behaviors that seriously endanger the public security and stability of the society. Violence risk is commonly assessed by subjective judgement, which may lead to bias and uncertainty in the appraisal results. Existing expression recognition and analysis techniques have limitations in identifying the emotional states of patients with mental disorders.

The study aimed to explore the association between violent behaviors and facial expression in patients with mental disorders by machine learning algorithm, to evaluate the application value of facial expression analysis system in violence risk assessment of individuals with mental disorders.

Thirty-nine patients with mental disorders were enrolled and assessed by using Modified Overt Aggression Scale (MOAS), positive and negative syndrome scale (PANSS) and brief psychiatric rating scale (BPRS). An emotional arousal paradigm was performed and the intensity of baisc emotions and expression action units was recorded before, during and after the paradigm. The processed quantitative data was used to generate one-dimensional waveform maps and two-dimensional time-frequency maps and then quantized feature data were extracted. A machine learning model with high accuracy was trained using these feature data, which can accurately determine the violence risk states of patients and output the probability. All individuals participated voluntarily and provided informed consent. This study was approved by the ethics committee of the Academy of Forensic Science.

The intensity difference of sadness, surprise and fear in different time periods was statistically significant. The intensity of the left medial eyebrow lift action unit was found significantly different before and after the emotional arousal. The intensity of anger and disgust was positively correlated with the MOAS scores, PANSS scores and BPRS scores. The features of time-frequency diagrams of 5 expression action units (medial eyebrow raise, eyebrow lowering, slightly open lips, chin drop and eye closure) and 8 basic emotions were selected and then support vector machine was used for triple classification, which is a classifier that can well distinguish the three stages of non-violence risk period, violence risk period, and post-violence risk period. In the 4:1 training-testing grouping, the classification accuracy reaches 91.2%.

Featured expressive action units and various baisc emotions might be used to capture information associated with violent behaviors. The facial expression analysis system mentioned above can be used as an auxiliary tool to assess the potential risk of violence in patients with mental disorders.

X. Ling: None Declared, S. Wang: None Declared, X. Zhou: None Declared, N. Li: None Declared, W. Cai: None Declared, H. Li Grant / Research support from: This study was supported by National Key R & D Program of China [grant number 2022YFC3302001], National Natural Science Foundation of China [grant number 81801881], Science and Technology Committee of Shanghai Municipality [grant numbers 20DZ1200300, 21DZ2270800, 19DZ2292700].

Aggression and violence are common in psychiatric in-patient wards. Preventive measures such as de-escalation, increased observations, extra medication, restraint and seclusion are utilised by nurses and authorised by doctors in a highly skilled way that should be proportionate to the risks posed. There is limited empirical data on the proportionality of the use of restrictive practices within Irish forensic psychiatric units.

The aim of this study was to rate the severity of incidents and proportionality of response to incidents in the high secure unit within the National Forensic Mental Health Service.

This is a prospective cohort study set in the Central Mental Hospital. Patients were assessed each day using the Dynamic Assessment of Situational Aggression (DASA) scale and incidents were rated each day using the DUNDRUM Restriction-Intrusion of Liberty Ladders Scales (DRILL), which includes the assessment of adverse incidents, violence and self-harm, interventions including restrictive practices and consequences. In this study we used episodes of restriction as an outcome measure. Data were gathered as part of the Dundrum Forensic Redevelopment Evaluation Study (D-FOREST). Generalised Estimating Equations were used to analyse repeated measures in the same subjects.

There were 384 patient days in scope, 411 lines of data including 326 patient-days, 85 incidents and 63 incidents of seclusion. The DRILL scales had good internal consistency (DRILL behaviours scale Cronbach’s alpha=0.789; DRILL interventions scale Alpha=0.866). The DASA on the day before an incident predicted the score on the DRILL behaviours scale (severity of behaviours) Wald X2=39565.2, p<0.001, with DUNDRUM-1 triage security scale also contributing significantly to the model Wald X2=884.3, p<0.001. The best model to predict the DRILL interventions scale included DASA on the day before (Wald X2=14.6, p=0.012) DRILL-behaviours scale (Wald X2=728.7, p<0.001) and DUNDRUM-1 (Wald X2=10,819.4, p<0.001). This was also the best model to predict whether or not a patient was secluded (DASA day before Wald X2=46.4, p<0.001; DRILL-behaviours scale Wald X2=173.2, p<0.001; DUNDRUM-1 Wald X2=6153.5, p<0.001).

Harmful behaviours and preventive and restrictive interventions can be described by rating items (‘ladders’) with good internal consistency, demonstrating that behaviour escalates in a meaningful sequence of increasingly serious harmful occurrences. The more serious the incident, the higher the level of restrictive practice used, demonstrating proportionality. This model of short term risk assessment and preventative interventions can be used to develop more effective and less restrictive interventions. Future research will explore moderating and mediating factors.

None Declared

Depressive disorders are the most prevalent chronic mental disorders globally, affecting approximately 322 million people, or 4.4% of the world’s population, with a significant portion residing in the Americas, including Mexico. Adolescence represents a critical period for the onset of depression, where preventive interventions should focus on enhancing cognitive abilities, which are malleable and can mitigate the impact of early negative experiences, particularly in marginalized areas and indigenous communities.

To identify the prevalence of depressive symptoms and characteristics associated with the presence or absence of depressive symptoms in a population of adolescents and young adults residing in rural and indigenous communities in San Luis Potosi state, Mexico.

A cross-sectional study was conducted. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), while anxiety symptoms were measured using the Generalized Anxiety Disorder-7 (GAD-7) scale. Descriptive statistics, a comparative analysis and a principal components analysis were performed with the sociodemographic data and the evaluations of each item of the PHQ9 and GAD7.

1,057 participants aged between 15 and 25 years (16.63 ± 1.53 years) were included in the study. The sample comprised 60.51% females 39.48% males, and 7 participants reported speaking an indigenous language. 28.67% of participants had responses compatible with anxiety, while 34.98% had depression, of which 46.1% qualified as having major depressive disorder. Regarding GAD7, participants with higher severity scores presented a higher average response on item 3 about feeling excessively worried about different things, while those with depression did not respond predominantly to questions regarding mood, but rather to item 3 referring to having difficulty falling or staying asleep and item 4 about feeling tired or having low energy. 4.67% of participants reported suicidal ideation almost every day. When the GAD7 and PHQ9 items were subjected to a principal component analysis, it was observed that PC1=51.67%. The factors self-reported as most closely linked to depressive and anxious symptoms included the age of the caregiver, sex and age of the participant, as well as whether they spoke an indigenous language.

Difficulty falling and staying asleep, as well as perceived lack of energy or fatigue, are the main ways in which this population recognizes signs of depression, rather than feelings of sadness or anhedonia. Given the high prevalence of depressive symptoms and the identified risk profiles, there is an urgent need for targeted mental health services and interventions in these vulnerable populations.

None Declared

People living with severe mental illness (SMI) face a life expectancy reduction of 10 to 20 years, often due to physical comorbidities. In addition to medication side effects, unhealthy lifestyle choices may contribute to this disparity.

Understanding the experiences and views of people living with SMI regarding diet is essential in addressing these challenges.

To explore the role of nutrition and its determinants within a biopsychosocial framework, 28 semi-structured interviews were conducted with service users living in Germany, Austria, and Australia. A generic thematic analysis was applied to uncover key themes around implications of dietary behavior and its determinants.

Both positive and negative effects of diet were reported. A prominent theme was the mental strain related to body weight, which contributed to feelings of guilt and experiences of stigma. Numerous biological, psychological, and social factors were identified as influencing dietary choices and behaviors. Many participants expressed a desire for greater support in achieving dietary balance and breaking the vicious cycle between diet and mental health.

From the viewpoint of people living with SMI, dietary interventions should be more integrated into mental health care. Psychosocial aspects, such as the emotional impact of eating, are as important as biological factors like nutrient intake, emphasizing the need for a holistic approach to addressing diet in mental health care.

None Declared

Non-suicidal self-injury (NSSI) refers to the deliberate act physical harm without intent of suicide. Common forms of NSSI include cutting, burning, and hitting oneself. The prevalence of NSSI among college students have been estimated to be between 15% to 25%.and higher than in the general population. Investigating patterns associated neurobiological and personality traits may provide a more comprehensive understanding of NSSI.

We aim to identify latent trajectory classes for NSSI behavior among college students. We expect that baseline personality and the behavioral inhibition/activation scales (BIS/BAS) will predict NSSI trajectory.

A total of 704 first-year university students at University of Victoria, Canada, were recruited in the beginning of the first semester over two consecutive academic years. Participants attended a baseline testing session completing self-report measures including the Ten Item Personality Inventory, BIS/BAS and NSSI instruments. There were monthly follow-up sessions from October to April. Longitudinal data will be analysed with latent growth curve modeling and group-based trajectory modeling, and baseline predictors will be analysed with multivariate logistic regression.

Latent class growth analysis found three distinct classes of NSSI during the follow-up period. A small percentage (2.4%) of the participants had a high degree of self-injury throughout the follow-up period. A second class of 13.4% of the participants had a moderate degree of self-injury at baseline, which fell throughout the follow-up period. Lastly, a third class of the majority of the participants (84.3%) had minor or none self-injury both at baseline and in the follow-up period. Concerning baseline predictors, higher openness and BAS drive were associated with lower NSSI at baseline.

In line with previous studies, we identified three distinct trajectories of NSSI behavior among college students. Notably, low openness and low BAS drive were associated with a degree of NSSI at baseline. These findings suggest that openness and drive may play a protective role in NSSI, providing valuable insights for future prevention and intervention efforts. The project is part of the Collaborative Research Program at the International Society for the Study of Self-Injury.

None Declared

Attachment styles are essential for understanding how individuals form and maintain emotional connections and relationships, significantly influencing emotional well-being and interpersonal dynamics. In Tunisia, where cultural expectations around gender and relationships play a prominent role, exploring attachment styles provides insight into how women navigate intimacy, trust, and emotional security.

This study aims to assess the prevalence of attachment styles among Tunisian women and investigate their associations with various sociodemographic and psychological factors

a cross-sectional study was conducted online using a Google Forms questionnaire between July and August 2024.The inclusion criteria were sexually active women aged 18 years or older who provided informed consent to participate. Participants completed a self-administered questionnaire that included sociodemographic information, personal medical history, lifestyle habits, and psychometric assessments. The relationship Questionaire (RQ) was used to evaluate attachement style and self-esteem was assessed using the Rosenberg Self-Esteem Scale (RSE).

A total of 180 women participated in the study, with an average age of 32.79 years, ranging from 21 to 60 years. The majority, 97.78%, resided in urban areas, while 94.44% held a university degree, and 80% were employed. Medical history revealed that 21.11% reported organic issues, and 27.22% had a psychiatric history. Lifestyle habits indicated that 18.9% of women smoked, 21.1% consumed alcohol, and only 1.1% used psychoactive substances.

Evaluation of attachment styles showed that 57.78% of women exhibited a secure attachment style (n=104), 26.67% had an avoidant style (n=48), 8.89% displayed a disorganized style (n=16), and 6.67% had an anxious style (n=12). Attachment styles were significantly associated with age (p=0.003), employment status (p=0.004), marital status (p=0.01), organic health issues (p=0.02), history of suicide attempts (p<0.001), self-esteem (p<0.001), and the number of sexual partners (p=0.01).

The findings highlight that attachment styles are significantly linked to several sociodemographic and psychological factors among Tunisian women. Understanding these associations is crucial for developing targeted interventions that promote secure attachment patterns, improve emotional well-being, and enhance relationship quality. By addressing these dynamics, we can foster psychological resilience and support healthier relational patterns. Further research could extend these insights to broader sociocultural contexts, offering more tailored approaches to improving women’s mental health and relational satisfaction.

None Declared

Increasing access to short, evidence-based psychotherapies is essential for responding to the rapid increase of demand. This can be achieved only by implementing scalable digital solutions. The Finnish guided self-help (F-GSH) is a digitally supported treatment based on Cognitive Behavioral Therapy (CBT). It was implemented in 2020 onward as part of the national First Line Therapies initiative to face the increased demand and shortage of therapists in primary health care.

We describe the implementation and preliminary results of the Finnish Guided Self-Help (F-GSH) of GSH for depression and anxiety in adults.

Description of the digitally supported F-GSH and therapist training using e-learning platform. We report preliminary outcomes from F-GSH for depression (n=766) and anxiety (n=1043). As outcomes we report self-reported depression (PHQ-9) and anxiety (GAD-7) symptoms measured at the beginning and end of the F- GSH treatment, patient and employee satisfaction, and proportion of patients in need of further treatment after F-GSH. Results are gathered from a wide geopraphical area covering 12 well-being counties.

The training program includes a 5-7 hours online training. A multiple-choice exam must be passed at the end course to gain certification. The training can be enhanced locally by skills workshops, to refine abilities, discuss specific GSH programs and patient groups, or address local implementation issues. In August 2024 more than 2700 employees had undergone the F-GSH training. The symptom severity changes during the treatment in our sample were as follows: Depression program the mean PHQ-9 for depression were at the beginning and end of the treatment 15.4 (SD 5.4)- 11.2(6.0) and for anxiety symptoms GAD-7 10.3(4.7)-7.9(4.8). Respectively, for during the treatment program targeted for anxiety symptoms the GAD-7 levels were 12.25(4.8)- 8.8(5.0) and for PHQ-9 12.43(5.5)- 9.1(5.6). Worsening of the symptoms were reported for 0-2% of the patients. Further treatment needed 38% of patients after F-GSH for depression and After F-GSH 38% of patients had no need for any further treatment.

E-learning platform forms a scalable and acceptable solution for training large number of professionals on a short time period at low cost for an evidence based treatment model. The symptoms reductions during the digitally supported F-GSH for depression and anxiety were comparable with previously reported in other studies, and comparable with longer CBT treatments. The F-GSH seems to be acceptable for the patients and employees. Also, the symptoms seem to ameliorate clinically significantly during the treatment.

None Declared

Social media has significantly changed the way we communicate, interact, and access mental health information for both the public and practitioners. Research indicates that rising rates of suicidal behaviors among adolescents may be linked to increased screen time on social media (Balt et al., 2023). Excessive use of online social networks can exacerbate self-harm and suicidal thoughts in vulnerable young people (Memon et al., 2018). Given Emergency Mental Health Professionals are most often in contact with suicidal patients, we developed a survey to gain a deeper understanding of their practices and attitudes toward social media platforms.

We aim to explore social media usage patterns among mental health practitioners in Singapore’s sole psychiatric emergency department, assess their views on the impact of social media as a mental health resource, and evaluate whether they believe suicide posts on social media should be treated with the same seriousness as traditional suicide notes.

The authors surveyed 58 mental health professionals - psychiatrists, nurses, psychologists, social workers, and pharmacists - who worked during 2023-2024. The survey, consisting of 19 multiple-choice questions, assessed attitudes toward mental health-related internet technologies and the perceived advantages and disadvantages of social media, based on a previous scientific paper titled “The Role of Social Media as a Resource for Mental Health Care”. Responses were measured on a Likert scale (1 = Strongly Disagree to 5 = Strongly Agree). SPSS 16.0 was used to analyze correlations between demographics and attitudes toward social media as a mental health resource.

Of the practitioners, 58.6% viewed social media’s impact on mental health as negative. Notably, 32.4% of those with less than one year of experience held this view, compared to just 8.8% of those with 6 to 9 years of experience. A significant negative correlation was found between actively following mental health content on social media and the belief that social media increases suicide risk among vulnerable individuals (P = 0.003, R = -0.389). However, years of work experience did not significantly correlate with this belief (P = 0.213).

The study finds that while mental health professionals generally view social media negatively, those who engage with mental health content online are less likely to associate it with increased suicide risk. Our limited literature review found no similar studies, and we aim to provide new insights into how familiarity with mental health content influences professional attitudes. Expanding the research beyond Emergency Department practitioners could reveal how demographic factors shape opinions on social media.

None Declared

The field of psychiatry is going through a rapid transformation as a result of the rapid advancements in artificial intelligence (AI), which are providing novel opportunities for the diagnosis, treatment, and management of mental health disorders. AI can deliver more precise and personalized mental health care by utilizing machine learning algorithms, natural language processing (NLP), and neuroimaging analysis. This paper investigates the current applications of AI in psychiatry, its prospective benefits, and the challenges that must be overcome in order to effectively integrate AI into clinical practice.

To investigate contemporary advancements in artificial intelligence (AI) applications in psychiatry, emphasizing enhancements in diagnostic precision, therapeutic personalization, and ethical considerations for integration into clinical practice.

A thorough examination of AI applications in psychiatry was performed, encompassing AI utilization for psychiatric diagnosis, digital mental health therapies, neuroimaging analysis, and suicide risk assessment.

Artificial intelligence demonstrated considerable potential in enhancing diagnostic precision, especially via technologies such as natural language processing for evaluating speech and text, and machine learning algorithms for assessing brain imaging. AI-driven chatbots and virtual therapists shown effectiveness in administering cognitive behavioral therapy (CBT) and facilitating continuous mental health care. Predictive algorithms for suicide risk and digital phenotyping instruments present opportunities for early intervention. Nonetheless, obstacles including algorithmic bias, data security issues, and the necessity for human oversight were identified as barriers to full implementation.

Artificial intelligence possesses revolutionary potential in psychiatry, facilitating earlier diagnoses, more individualized treatment strategies, and continuous monitoring of mental health disorders. For AI to be included into standard psychiatric care, continuous efforts are required to guarantee ethical implementation, mitigate algorithmic bias, and preserve the vital human connection in psychiatric therapy. Collaboration among AI engineers, physicians, and ethicists will be essential to fully leverage AI’s potential while ensuring the safety of patients.

None Declared

Depression is a major concern in patients with chronic heart failure (CHF), with a prevalence of approximately 20-40%. It has been linked to worsened outcomes, including mortality and significant declines in physical and social functioning. Understanding the relationship between depression and hemodynamic as well as lipid metabolism parameters in CHF patients can provide insights into the underlying mechanisms of these worsened outcomes.

This study aims to evaluate the correlation between depression and central hemodynamic and lipid metabolism parameters in patients with chronic heart failure (CHF).

The study involved 80 patients with CHF II-III NYHA classes caused by chronic coronary artery disease. They were divided into two groups: 20 without signs of depression and 60 with depression, as diagnosed using the Zung Self-Rating Depression Scale, Beck Depression Inventory, and Hamilton’s Depression Scale. Hemodynamic parameters were assessed using echocardiography (EchoCG), and lipid levels were measured in blood plasma. Statistical analyses were performed using t-tests, Mann–Whitney U tests, and correlation coefficients to determine relationships between variables.

Depressive symptoms were prevalent in 71.6% of the CHF patients, with severe depression observed in 3.3%. Significant correlations were found between depression severity and blood pressure, triglyceride levels (r = 0.7, p < 0.05), and key echocardiographic measures such as left atrium diameter (r = 0.57, p < 0.05), end-diastolic size (r = 0.53, p < 0.05), and ejection fraction (r = -0.29, p < 0.05). Additionally, situational anxiety was significantly correlated with serum urea levels (r = 0.42, p < 0.05), triglycerides (r = 0.91, p < 0.05), and echocardiographic parameters.

Image 1:

Image 2:

Patients with CHF and depression exhibit more severe central hemodynamic and lipid metabolism disorders than those without depression. These findings suggest that addressing depression in CHF management may mitigate some of the adverse effects on cardiovascular health.

None Declared

Functional neurological disorders (FND), also referred to as conversion disorder or psychogenic neurological disorders, are one of the most common and disabling conditions in the neurology practice field, with very limited treatment options. FNDs present with sensory and/or motor symptoms that can mimic other neurological conditions, but appear to be related to recognizable psychological factors and are thought to occur via mechanisms other than those related to identifiable structural neuropathology. This condition has very limited treatment options, but there is preliminary evidence that psychedelic-assisted therapy (PAT) might be effective in a growing number of psychiatric disorders, including FNDs.

We aim to review the current literature regarding the role of psychedelic-assisted therapy in the treatment of functional neurological disorders.

We search PubMed with the following keywords: psychedelics, functional neurological disorder and conversion disorder.

Only nine studies were published, between 1954 and 1967, reporting the use of psychedelics in the treatment of FNDs, with a total of 22 patients, of which 69% (n = 18) were found to have made at least some recovery, though the included studies were of low quality, often lacking control groups and valid outcome measures.

There is a lack of evidence for the efficacy of PTA on the treatment of FNDs. Nevertheless, the discussion remains, as several abnormalities of the default mode network activity (DMN) have been reported in patients with FND and many of the proposed therapeutic benefits of psychedelics have been theorized to relate to their action on the DMN.

None Declared

Emerging evidence on the bidirectional connection between gastrointestinal microbiota and brain, through the gut-brain axis, and its influence on mental disorders makes the gut microbiota a potential target for novel therapeutic approaches.

We aim to study and synthetize the current data about the influence of gut microbiome on psychiatric disorders.

Our literature research focused on some of the most significative English-written articles published in the last decade.

Most of the relevant literature suggests that the presence of a healthy and diverse gut microbiota is essential to normal cognitive and emotional processing. Also, it has been shown that consumption of probiotics can modify the functional activity of the areas in the brain that are implicated in cognitive functions.

The literature also supports that stress can change gut permeability as well as the composition of gut microbiota resulting in a pro-inflammatory profile of cytokines produced by gut microbiota. Besides, gut microbes can modulate the stress response and the level of anxiety through alterations in serotonin signaling.

It has been also demonstrated that in animal models of depression the composition of gut microbiota was changed. On the other hand, other studies demonstrated certain probiotics can attenuate depressive symptoms in rodent models.

Regarding eating disorders, Anorexia Nervosa seems to have impact on the gut microbiota balance through restrictive diets and the abrupt change in diet during nutritional rehabilitation. The use of prebiotics, probiotics, antibiotics or faecal transplantation looks promising as important novel adjuvant treatments.

The effect of gut microbiota on several mental disorders is supported by a increased volume of experimental data.

However, research in this field is still unfolding and more studies should be performed to apply new techniques focusing on gut-brain axis in clinical practice.

None Declared

The development of artificial intelligence (AI) has led to significant advancements in various fields, including mental health applications. As AI technologies like ChatGPT continue to evolve, questions have arisen about whether AI can eventually develop a true personality, and what implications this might have for fields such as psychology and psychiatry. Isaac Asimov’s ideas about AI and the Turing test have gained renewed attention, yet these frameworks do not address the core psychological components such as empathy, emotion, and personal interaction—key elements in therapeutic settings.

This article explores whether AI could develop a personality and replace human therapists in psychological counseling and psychiatry. Specifically, it aims to evaluate AI’s current capabilities in providing emotional and psychological support and to address whether AI can evolve to meet therapeutic practice’s deeper, human-centered requirements.

The analysis is based on reviewing current AI applications in mental health, such as AI-based therapy platforms for post-traumatic stress disorder (PTSD), which provide symptom management tools and promote adaptive coping strategies. These applications were compared to the human therapist’s role, focusing on emotional interaction, empathy, and the therapeutic relationship. Additionally, the philosophical and psychiatric aspects of personality formation in both humans and AI were examined.

AI systems have made progress in simulating therapeutic techniques, providing guidance, and mimicking emotional responses. They can support symptom relief and enhance coping strategies, especially in areas where human therapists are scarce. However, AI’s ability to engage with deeper aspects of the therapeutic process, such as emotional empathy and personal connection, remains limited. AI lacks subjective experience, emotional depth, and self-awareness—essential factors for forming a genuine personality.

While AI has the potential to augment clinical practice, it cannot replace the human element in therapy. The development of AI-based tools is valuable for symptom management, but psychotherapy is inherently rooted in human connection, intuition, and emotional engagement—qualities AI does not possess. For AI to truly replace human therapists or develop a personality, significant advancements in consciousness and emotional cognition would be required, which remain speculative at this stage. Thus, AI will likely continue to serve as a supportive tool rather than a replacement for human therapists in the foreseeable future.

None Declared

In clinical studies on psychosis prediction, small sample sizes have been a persistent issue. Most studies rely on limited data, lack cross-validation, and use poor model strategies, leading to overfitting and overestimated accuracy. This challenge also affects traditional studies, where recruiting few participants introduces biases. Data harmonization is another hurdle, especially in speech analysis, which is crucial in psychiatry for conditions like psychosis, aphasia, and PTSD, but suffers from inconsistent methodologies across databases.

Our goal was to develop an method using Large Language Models (LLMs) to create diverse, synthetic speech datasets, addressing these challenges: 1. Develop an evolutionary system for optimizing high-quality speech data generation. 2. Incorporate contrastive learning for improved model decision boundaries. 3. Provide a methodology for training classification models and conducting cross-cultural studies. 4. Create a large-scale, diverse database of synthetic psychiatric speech samples.

Our findings suggest that this approach could significantly benefit psychiatric research by addressing the challenges of small sample sizes and data inconsistency. The method shows promise for creating more reliable and generalizable predictive models, which could lead to advancements in mental health care practices. The system’s flexibility indicates potential applications beyond our case study, possibly extending to other areas where data scarcity has impeded progress.

None Declared

Mental health is one of the fundamental personal values of every human being. Thus its protection should be one of the primary obligations of every state. To ensure common standards in aforementioned matter, it is necessary to exist an universal (supranational) grounds and rules for the protection of mental health, as well as the protection of people with mental disorders rights. Especially that, mental disorders are found all over the world, and in an age of globalisation and migration, borders are only a legal construct. In the Western European axionormative order, one of the factors shaping common normative standards is European Union law.

The aim of this study is to identify the norms of European Union primary law from which the right to mental health protection can be derived (directly or indirectly), with a subsequent assessment of their adequacy.

The study is based on a dogmatic analysis of the primary legislation of the European Union (i.a. the founding Treaties or the Charter of Fundamental Rights of the EU - CFR) with analysis of the relevant literature of the subject and jurisprudence of the Court of Justice of the European Union.

No provision of EU primary law explicitly statutes a ‘right to mental health protection’. Currently, this right can be derived indirectly from norms relating to its particular aspects - e.g. the protection of mental integrity (Article 3 of CFR or Article 165(2) of the Treaty on the Functioning of the European Union - TFEU), the removal of threats to mental health (Article 168(1) TFEU) or the prohibition of discrimination on grounds of disability (Article 10 TFEU).

The current regulations are incomplete and therefore inadequate. The protection of mental integrity or the fight against discrimination are necessary for mental health (well-being) of entities, but do not fully cover the latter concept. The strengthening of the legal position of people with mental disorders requires the introduction into EU legislation of a comprehensive regulation that statutes the right to mental health protection, together with mechanisms for its enforcement against state authorities.

None Declared