This scientific review addresses the critical issue of high prevalence of mental disorders among university students, which negatively impacts their academic performance, quality of life, and future well-being. Consequently, the necessity of this research is driven by the growing need to develop effective prevention and intervention strategies. The aim of the article is to present a comprehensive description of the prevalence of various mental disorders among students, explore associated risk factors, successful treatment methods and prevention approaches. The review aims to create an overall picture of the problem, identify knowledge gaps, and determine promising directions for further research. The research methodology includes analysis of data from scientific publications indexed in databases such as E-library, PubMed, Scopus, and MedLine, using keywords: “mental disorders,” “students,” “depression,” “anxiety,” “prevention,” “treatment.” As a result of analyzing 63 publications in Russian and English over the past 8 years, the most common disorders were identified. The review included epidemiological studies examining the prevalence of depression, anxiety disorders, sleep disorders, substance abuse, suicidal behavior, Internet addiction, and other psychiatric disorders. The analysis covers data on prevalence, risk factors, and effectiveness of various treatment and prevention methods, including the application of psychotherapy and digital technologies. In particular, the potential of mobile applications, web-based interventions, and artificial intelligence tools is examined. Additionally, the analysis includes interdisciplinary approaches. In conclusion, the high prevalence of mental disorders among students presents a serious problem requiring a holistic approach. Digital technologies and interdisciplinary approaches demonstrate certain potential but require further development and optimization to enhance the effectiveness of prevention, early detection, and treatment.

Adverse childhood experience (ACE) is considered one of the key predictors of the development of mental disorders. The findings of recent research show the stable and significant association of ACE with increased suicide risk in general, and primarily in patients with mental disorders such as depression, schizophrenia, and bipolar affective disorder. This makes the study of ACE particularly relevant. Thus, correct analysis of the spectrum, intensity, and severity of ACE is extremely important for the construction of complex multidimensional predicting models of the level of suicide risk in patients with mental disorders. However, to date, there is no unique and universally accepted approach to assessment of ACE, which may lead to controversy and low reproducibility of results.

The purpose of this review is to examine and compare various methods of assessing and interpreting of ACE in order to identify optimal research algorithms within the current interpretation of the biopsychosocial model in psychiatry.

This article reviews current terms, concepts, and methods of studying ACE. We discuss the definitions and phenomenology of the ACE, the specificity and features of some of the methodological approaches to measuring ACE, and various approaches to using ACE to build predictive models.

To summarize, research on ACE and its consequences is actively developing: earlier studies' data are being corrected and clarified, methods of detecting and grading ACE are being improved, and ways of forecasting the consequences of ACE in adulthood are being improved. We can see that theoretical claims are becoming more developed and refined; rigorous definitions are emerging, despite not previously being the focus of attention. Despite the existence of different approaches to the examination of the consequences of ACE in adulthood, at the current stage of research development, the best approach is to analyze ACE within the framework of the biopsychosocial model, focusing on the interaction of genome and environment and taking into account the complex effects of genetic, social, and personal factors.

The rapid growth of artificial intelligence (AI) technology has led to its integration into various fields, including medicine, including psychiatry. Modern neural networks, such as neural networks and large language models (LLMs), claim to be able to diagnose, prescribe treatments, and predict the course of mental disorders based on historical and clinical data. The capabilities of neural networks in identifying hidden patterns make them an essential component of scientific research, and these advances are expected to be implemented in clinical practice in the near future. Artificial intelligence technology shows great potential in medical education. This study was conducted to evaluate the capabilities of ChatGPT-4-based system in the clinical analysis of a patient with a mental disorder. The analysis involved comparing the results of the LLM's analysis of clinical data with psychiatrists’ clinical analysis. The findings showed that the LLM demonstrated high potential in formulating psychiatric diagnoses within an operational framework and supporting the algorithm for therapy and prognosis based on evidence-based approach. However, at the current stage of development, neural networks are unable to fully implement dynamic and phenomenological analysis of the clinical case, which significantly limits the accuracy of diagnostics. This clinical case emphasizes the importance of considering patients’ cultural and psychological background when conceptualizing their phenomenological experiences. Assessing subjective experience in a biopsychosocial context and considering temporal dynamics allows for the most accurate diagnosis. The work on "neuromorphizing" neural networks and adapting their analytical apparatus to human thinking patterns seems promising.

Relevance. To date, there is convincing evidence in favour of the immuno-inflammatory hypothesis of the etiopathogenesis of schizophrenia. As markers of immuno-inflammatory disorders in schizophrenia, a small number of studies have examined haematological indices (HI) and systemic inflammation coefficients (SIC): neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR) and platelet-lymphocyte ratio (PLR). Considering that HI may hypothetically reflect immuno-inflammatory processes in schizophrenia, it is relevant to assess their relationship with other known biochemical markers of inflammation and oxidative stress in this disease. The aim of this study was to evaluate the association of HI with biochemical markers of inflammation and oxidative stress in schizophrenia, as well as with the severity of clinical symptoms. Materials and methods: 50 patients with schizophrenia were examined: 42 women, 8 men, age 36 [7] years (median and interquartile range, hereafter Me [Q1; Q3]). Clinical assessment was performed using the Schizophrenia Positive and Negative Syndrome Scale and the Calgary Depression Scale for Schizophrenia. HI, homocysteine (Hc), tetrahydrobioterine (BH4), reduced glutathione (GSH), interleukin-6 (IL-6), C-reactive protein (CRP) and tumour necrosis factor-alpha (TNF-a) were studied. Results: Serum CRP levels were significantly correlated with leukocyte count, total monocyte, basophil and eosinophil counts, and granulocyte counts, but not with SIC (NLP, MLR and PLR). TNF-a has stronger direct correlations with a number of HI (granulocyte and erythrocyte counts, leukocyte counts at the level of trend towards significance) and coefficients (NLP, MLR at the level of trend). Conclusions: HI in the studied sample of patients with schizophrenia correlate with the data obtained by foreign authors, which indicates the prospect of studying this topic in the Russian population. Further evaluation of the relationship between HI (SIC) and serum TNF-a seems relevant. The study of associations of biochemical immuno-inflammatory markers with SIC further requires a thorough assessment of the stage of disease development, duration of its course, peculiarities of response to therapy.

The relevance of studying mental disorders in anti-NMDA encephalitis is due to a number of aspects: psychopathological manifestations in anti-NMDA encephalitis are polymorphic and manifest in the form of an acute psychotic disorder resistant to neuroleptic therapy is not uncommon; cases with periodic course are described; patients of childhood, adolescence and young age are more predisposed to the development of the disease, the quality of prognosis is associated with early the beginning of pathogenetic immunosuppressive therapy. Objective: to describe psychopathological manifestations in autoimmune encephalitis in a group of adolescent patients. Material and methods: the clinical and dynamic features of the course of autoimmune anti-NMDA receptor encephalitis in the acute and recovery period in four adolescent patients were studied. Conclusion: the study revealed specific disorders characteristic of organic mental disorders in the acute period of the disease and symptom complexes that might determine the severity of the disease – reversible regression of the psyche, cognitive impairment, motor coordination disorders.

The aim is to compare patients with bipolar type I and II disorders according to socio–demographic characteristics, the structure of depressive and hypo-/manic episodes, as well as patterns of concomitant mental disorders.

Materials and methods: 173 patients with bipolar disorder were included in this multicenter cross-sectional study, 46.8% of them with type I (n=81). The study participants independently filled out a computerized structured questionnaire for screening for affective disorders, where symptoms of depression and hypo-/mania were recorded. After that, the participants underwent a structured interview with a researcher to verify the diagnosis and identify concomitant mental disorders. The analysis was performed in RStudio version 4.4.0 using the standard R package and the "psych“ package.

Results: In patients with bipolar type I and II disorders, there were no significant differences in age, sex, and level of education, as well as the frequency of concomitant mental disorders. Patients with bipolar type I disorder were significantly more likely to have symptoms of depression such as psychomotor retardation and thoughts of self–harm or death, and patients with bipolar type II disorder had symptoms of decreased energy levels. In addition, patients with bipolar type I disorder, compared with patients with bipolar type II disorder, were significantly more likely to have all the symptoms of mania, with the exception of hyperthymia and increased talkativeness. Nevertheless, the classification of bipolar type I and II disorders based on cluster analysis for all symptoms of depression and hypo-/mania had sensitivity = 77.92% and specificity = 56.63%.

Conclusion: There are no symptoms of depression and hypo-/mania that are pathognomonic only to type I or type II bipolar disorder. Despite some significant differences, clustering-based classification has moderate sensitivity and low specificity. Thus, a single bipolar disorder cannot be divided into two independent nosologies based solely on the structure of mood episodes.

Persistent orofacial pain belongs to a group of pain conditions of non-dental etiology affecting the face and mouth, significantly impacting quality of life and having a biopsychosocial nature. Temporomandibular joint pain dysfunction syndrome (TMD) is one of the most common causes of chronic orofacial pain, involving the masticatory muscles. It is a musculoskeletal disorder characterized by pain and discomfort in the muscles and joints responsible for chewing and jaw movement. Psychopathological factors such as anxiety and depression play an important role in the development and maintenance of persistent pain and muscle dysfunction in the orofacial region. Objective: To study the severity of anxiety and depression in patients with chronic orofacial pain associated with temporomandibular joint dysfunction syndrome. Materials: A total of 354 patients with chronic orofacial pain were examined. The clinical picture of their condition was dominated by pain symptoms and pronounced myotonic disorders of the masticatory muscles, which were comorbidly associated with anxiety and depressive disorders (ICD-10 codes: K07.8+F43; F45.8). The average age of the patients was 48.6±12.9 years. Results: The studied group showed significantly higher levels of anxiety and depression compared to the healthy population. These manifestations were mostly subclinical in nature and often presented as somatized complaints, mild anxiety, and self-critical attitudes towards appearance. Patients with complaints of myotonic disorders and orofacial pain without marked symptoms of anxiety and depression constituted 52.0% of the group. Among the patients, 6.8% had pronounced anxiety disorders on the background of orofacial dysfunction, while 41.2% were diagnosed with depressive disorders of varying severity. Both somatic and psychological factors are involved in the development of TMD pain dysfunction and comorbid anxiety-depressive disorders, making it reasonable to approach this pathology from a psychosomatic perspective.

Anxiety disorders (AD) and risky alcohol use are often interrelated, creating a vicious cycle that reduces treatment efficacy and patients' quality of life. A study involving 120 AD patients identified key predictors of risky alcohol consumption. Patients with generalized anxiety disorder were found to have a 2.3 times higher risk of alcohol abuse compared to those with episodic anxiety. Key risk factors included high levels of neuroticism, emotional discomfort, phobic reactions, and a lack of adaptive coping strategies. Using CHAID analysis and logistic regression, researchers developed a predictive model with high accuracy (AuROC=0.937), which takes into account both clinical and individual psychological characteristics. The results highlight the importance of considering the type of anxiety and associated psychological traits when designing prevention programs. For patients with generalized anxiety, the focus should be on reducing emotional discomfort and phobic reactions, while for those with episodic anxiety, developing emotional support-seeking skills and addressing neuroticism are crucial. The findings align with current understanding of the relationship between anxiety disorders and alcohol use, offering practical recommendations for clinical practice. The study contributes to a deeper understanding of the mechanisms underlying the transition from moderate to risky alcohol use in patients with anxiety disorders and suggests directions for further research, including the role of coping strategies and the development of comprehensive prevention models.

Hyperkinetic disorder (HD) is a common mental disorder in children and affects 5% of the population. In recent years, the important role of systemic inflammation in the pathogenesis of HD has been discussed. It is believed that the level of neutrophils, lymphocytes, platelets and monocytes, as well as their ratios, can serve as markers of systemic inflammation in HD. However, the question of the specificity of the data obtained remains open due to insufficient data. The specificity of markers of neuroinflammation and systemic inflammation, levels of hyperkinetic disorder remains insufficiently studied, which requires clarification in future studies with the exclusion of background residual organic pathology of the brain, inflammatory and autoimmune diseases in comparison not only with a group of healthy controls, but also with a group of patients with other mental disorders.

Craving for psychoactive substances is a hallmark feature of psychoactive substance use and one of the central symptoms of substance use disorder in the DSM-5 and ICD-10. However, the debates about its precise definition, operationalization, and appropriate methods of assessment continue to this day, thus underscoring the complexity and multifaceted nature of this phenomenon. Understanding the mechanisms and dynamics of craving holds significant theoretical and practical implications for both research and clinical practice. The article explores the challenges inherent in conceptualizing craving and discusses the main strengths and limitations of current assessment methods, including self-report and experimental approaches, with a particular focus on visual analog scales (VAS). The VAS are widely regarded as rapid, simple and flexible tool that is adaptable to diverse research paradigms, requires minimal financial and time investments, places minimal low demands on respondents. Recent studies further demonstrated that the VAS has acceptable psychometric properties for assessing craving. Nevertheless, the use of VAS has its limitations. In addition to the inherent constraints of self-report methods, such as reliance on self-reflection, the VAS requires a clear definition of the construct being measured, lacks norms or thresholds, and maybe affected by the variability of how the respondents interpret maximum and intermediate scale values. When employing the VAS to assess craving, it is essential to account for the dynamic and multifaceted nature of the phenomenon. This requires careful selection of the terminology used in the instruction, the choice of the specific aspects of craving being measured, the temporal framework of assessment (“here and now” vs over a defined period of time), and the frequency and duration of measurement.