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Lesbian, gay, bisexual, transgender, intersex, queer people and minority gender identities and sexualities (LGBTIQ+) are often stigmatized and experience discrimination in health care settings, leading to poorer mental health outcomes and unmet needs compared to heterosexual and cisgendered peers. It is thus imperative that mental health providers consider and address structural challenges in order to reduce mental health inequalities of this population. This narrative review assessed the barriers that may prevent access to care and the pathways for care in LGBTIQ + communities. PubMed, PsycInfo, Embase, and Scopus were searched for papers published between December 2021 and February 2022. A total of 107 papers were included with studies reflecting five themes: (1) Unmet mental health needs; (2) Young people; (3) Substance abuse and addiction; (4) Barriers and pathways to care; and (5) Interventions. Findings demonstrate that LGBTIQ + people experience stigmatization and higher rates of substance misuse and mental ill health, which may lead to barriers in accessing health care services, and fewer tailored interventions being provided. These findings have implications for policy, health care screening, and how specialist services are structured. Substantial gaps in the evidence-base exist, and future research should examine how mental health care providers can challenge social issues that maintain discriminatory and stigmatizing practices, and support LGBTIQ + individuals to sustain their resilience. [ABSTRACT FROM AUTHOR]

AbstractModern psychiatry aims to adopt precision models and promote personalized treatment within mental health care. However, the complexity of factors underpinning mental disorders and the variety of expressions of clinical conditions make this task arduous for clinicians. Globally, major depression is a common mental disorder and encompasses a constellation of clinical manifestations and a variety of etiological factors. In this context, the use of Artificial Intelligence might help clinicians in the screening and diagnosis of depression on a wider scale and could also facilitate their task in predicting disease outcomes by considering complex interactions between prodromal and clinical symptoms, neuroimaging data, genetics, or biomarkers. In this narrative review, we report on the most significant evidence from current international literature regarding the use of Artificial Intelligence in the diagnosis and treatment of major depression, specifically focusing on the use of Natural Language Processing, Chatbots, Machine Learning, and Deep Learning. [ABSTRACT FROM AUTHOR]

AbstractAfter the approval of the law 81/2014, a new care-framework has been outlined for the psychiatric offenders in Italy and alternative facilities have been gradually activated. This pilot national survey was conducted in order to explore the attitudes of a panel composed by Italian psychiatrists, engaged in forensic vs. not-engaged in forensic activities, on the changes related to the application of the law. We employed an ad-hoc questionnaire named SOPF: Superamento degli O.P.G. sulla Metodologia Peritale Psichiatrico Forense (in english: The Psychiatric Forensic Assessment after the Closing of the Forensic Psychiatric Hospitals) to explore the opinions regarding ten relevant issues in the field of forensic psychiatry and forensic assessment. Findings suggested that the lack of specific resources for the management of psychiatric offenders in the Departments of Mental Health in Italy may lead to clinical risks for patients and health professionals. In particular the task of treating offenders in the community may be even more challenging for those patients whose social dangerousness has been revaluated and their security measures expired. [ABSTRACT FROM AUTHOR]