Mental disorders affect nearly one billion persons worldwide, having a substantial burden on individuals, families, and healthcare systems. Current diagnostic and therapeutic approaches could fail to reach optimal outcomes, highlighting the need for more effective and personalized interventions. Precision psychiatry aims to address this challenge by integrating multidimensional data, ranging from genomics and epigenomics to neuroimaging and psychometric assessments, through advanced computational tools such as machine learning and artificial intelligence. This transdisciplinary approach could allow the study of biologically informed endophenotypes, improve diagnostic accuracy, and support individualized treatment strategies. Emerging technologies, including pharmaco-neuroimaging, virtual histology, and large-scale consortia, are advancing the field by elucidating the molecular and circuit-level correlates of mental disorders. Although significant progress has been made, the translational gap between research and clinical practice remains a critical issue. Effective implementation will require the systematic integration of bioinformatic tools, big data analytics, and clinician-guided interpretation, in a context in which the evolving landscape of precision psychiatry continues to prioritize therapeutic alliance and individualized patient care.

The comorbidity between late-life depression and neurocognitive disorders (NCDs) in the elderly is a subject of increasing interest within the scientific and medical community. We conducted a narrative review of clinical studies focused on depression and NCDs, primarily covering articles published over the past 25 years. Compared with younger adults, depression in the elderly is often characterized by difficulties in expressing sadness, more pronounced somatic, anxiety, and psychotic symptoms, as well as a heightened risk of suicide and cognitive impairment. Depressive symptoms in the elderly may mimic NCDs, act as prodromal signs of future NCDs, or represent a clinical dimension of dementia. NCDs and late-life depression share specific clinical similarities, particularly at illness onset, emphasizing the importance of early differential diagnosis to guide the development of precise, integrated, and tailored interventions.

Background/Objectives: Violence against workers (physical, verbal, or psychological abuse), even if it affects all professional categories, is up to ten times higher in healthcare workers. A University Hospital of Central Italy has gradually implemented a series of preventive measures, which might have impacted the trend of the phenomenon. Methods: In order to monitor the episodes, an aggressive event reporting form was adopted throughout the hospital. Data extracted both from this form and the root cause analysis documentation regarding the period January 2019–December 2023 were used. Descriptive statistical analysis was performed using the Chi-squares test, while the join point regression program was used to analyze the trends. Results: The average age of the sample is 43.5 years, with twice as many female workers as male workers. Nurses are more frequently involved (76.6%), and 58% of the events involved 2 to 4 HWs. Verbal violence was reported by 51.2% of HWs, and over 35% of them did not suffer any damage, while 25% suffered mild to moderate damage (illness, injury, or material harm, whether physical or psychological). The hospital divisions which are primarily concerned are the Psychiatry department (36.2%) and the Emergency Room (33.4%). There is no difference in hospital management of aggressive events between males and females. Join point regression analyses showed that there was a significant increase in the reporting of episodes of aggression. Conclusions: The presence of a strong culture of reporting among HWs guarantees a seemingly constant increase in the reporting of nonphysical forms of violence. The statistically significant differences found will allow hospital management to categorize the risk levels and act accordingly.

Gender-diverse populations are at a higher risk of experiencing adverse childhood experiences (ACEs) and social stigma, with a significant impact on both mental and overall health. This systematic review, conducted in accordance with PRISMA guidelines, included 14 studies published between 2016 and 2024. Observational studies were extracted from MEDLINE, CINAHL, APA PsycInfo, and APA PsycArticles to explore the prevalence of ACEs and their effects on mental and physical health in gender-diverse individuals. Studies were assessed for quality using the AXIS tool. The studies included revealed elevated rates of ACEs, particularly in the form of abuse. ACEs were strongly associated with an increased risk of depression, anxiety, stress-related disorders, and suicidality. Discrimination further amplified these effects, particularly among racial and ethnic minorities, leading to a higher engagement in risky behaviors and poorer physical health outcomes. Protective factors identified included secure attachment, access to gender-affirming care, and strong social support. The findings emphasize the urgent need for trauma-informed and culturally sensitive interventions that address both the immediate and long-term effects of ACEs in gender-diverse populations. Future studies should prioritize longitudinal designs and tailored interventions to meet the healthcare needs of these communities and develop mental health prevention strategies.

Background: The objective of this study was to investigate the DRD2 rs1800497, rs1799732, rs1801028, DRD3 rs6280, and HTR2A rs6314, rs7997012, and rs6311 single-nucleotide polymorphism (SNP) correlations with resistance to second-generation antipsychotics (SGAs) in a real-world sample of patients with treatment-resistant mental disorders. Methods: We divided 129 participants into a high treatment resistance (HTR) group (current treatment with two SGAs, or clozapine, or classic neuroleptics for a failure of previous SGAs trials) and a low treatment resistance (LTR) group (current treatment with one atypical antipsychotic). We used Next-Generation Sequencing on DNA isolated from peripheral blood samples to analyze the polymorphisms. We performed logistic regression to search for predictors of HTR membership. Results: A diagnosis of schizophrenia significantly predicted the HTR membership compared to other diagnoses. Other predictors were the DRD3 rs6280 C|T (OR = 22.195) and T|T (OR = 18.47) vs. C|C, HTR2A rs7997012 A|G vs. A|A (OR = 6.859) and vs. G|G (OR = 2.879), and DRD2 rs1799732 I|I vs. D|I (OR = 12.079) genotypes. Conclusions: A diagnosis of schizophrenia and the DRD2 rs1799732, DRD3 rs6280, and HTR2A rs7997012 genotypes can predict high treatment resistance to SGAs.

Schizophrenia spectrum disorders represent a varied class of mental illnesses characterised by psychosis. In addition to negative and positive symptoms, a significant lack of insight often hinders the therapeutic process. We performed an overview of the existing literature concerning these disorders to summarise the state of knowledge in the psychotherapies applied to treating psychotic symptoms. We searched the PubMed database, including randomised controlled and clinical trials, including 17 studies conducted on 1203 subjects. Psychotherapy of schizophrenia spectrum disorders can improve social functioning and positive symptoms, as well as many other symptomatic areas, and could therefore be considered a helpful adjunctive treatment of schizophrenia spectrum disorders. Among cognitive-behavioural therapies and the newest derived approaches, there is evidence that they can improve different psychotic symptoms. On the other hand, psychodynamic psychotherapies can have a positive influence on psychotic symptoms as well. Further studies are needed to identify better-tailored treatment protocols for schizophrenia spectrum disorders.