Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions.

BACKGROUND: Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI). OBJECTIVE: An international multidisciplinary group was convened to reach a consensus on the challenges and potential solutions regarding collecting data, delivering treatment, and the ethical challenges in digital mental health approaches for schizophrenia and SMI. METHODS: The consensus development panel method was used, with an in-person meeting of 2 groups: the expert group and the panel. Membership was multidisciplinary including those with lived experience, with equal participation at all stages and coproduction of the consensus outputs and summary. Relevant literature was shared in advance of the meeting, and a systematic search of the recent literature on digital mental health interventions for schizophrenia and psychosis was completed to ensure that the panel was informed before the meeting with the expert group. RESULTS: Four broad areas of challenge and proposed solutions were identified: (1) user involvement for real coproduction; (2) new approaches to methodology in digital mental health, including agreed standards, data sharing, measuring harms, prevention strategies, and mechanistic research; (3) regulation and funding issues; and (4) implementation in real-world settings (including multidisciplinary collaboration, training, augmenting existing service provision, and social and population-focused approaches). Examples are provided with more detail on human-centered research design, lived experience perspectives, and biomedical ethics in digital mental health approaches for SMI. CONCLUSIONS: The group agreed by consensus on a number of recommendations: (1) a new and improved approach to digital mental health research (with agreed reporting standards, data sharing, and shared protocols), (2) equal emphasis on social and population research as well as biological and psychological approaches, (3) meaningful collaborations across varied disciplines that have previously not worked closely together, (4) increased focus on the business model and product with planning and new funding structures across the whole development pathway, (5) increased focus and reporting on ethical issues and potential harms, and (6) organizational changes to allow for true communication and coproduction with those with lived experience of SMI. This study approach, combining an international expert meeting with patient and public involvement and engagement throughout the process, consensus methodology, discussion, and publication, is a helpful way to identify directions for future research and clinical implementation in rapidly evolving areas and can be combined with measurements of real-world clinical impact over time. Similar initiatives will be helpful in other areas of digital mental health and similarly fast-evolving fields to focus research and organizational change and effect improved real-world clinical implementation.

A machine learning approach on whole blood immunomarkers to identify an inflammation-associated psychosis onset subgroup.

Psychosis onset is a transdiagnostic event that leads to a range of psychiatric disorders, which are currently diagnosed through clinical observation. The integration of multimodal biological data could reveal different subtypes of psychosis onset to target for the personalization of care. In this study, we tested the existence of subgroups of patients affected by first-episode psychosis (FEP) with a possible immunopathogenic basis. To do this, we designed a data-driven unsupervised machine learning model to cluster a sample of 127 FEP patients and 117 healthy controls (HC), based on the peripheral blood expression levels of 12 psychosis-related immune gene transcripts. To validate the model, we applied a resampling strategy based on the half-splitting of the total sample with random allocation of the cases. Further, we performed a post-hoc univariate analysis to verify the clinical, cognitive, and structural brain correlates of the subgroups identified. The model identified and validated two distinct clusters: 1) a FEP cluster characterized by the high expression of inflammatory and immune-activating genes (IL1B, CCR7, IL12A and CXCR3); 2) a cluster consisting of an equal number of FEP and HC subjects, which did not show a relative over or under expression of any immune marker (balanced subgroup). None of the subgroups was related to specific symptoms dimensions or longitudinal diagnosis of affective vs non-affective psychosis. FEP patients included in the balanced immune subgroup showed a thinning of the left supramarginal and superiorfrontal cortex (FDR-adjusted p-values < 0.05). Our results demonstrated the existence of a FEP patients' subgroup identified by a multivariate pattern of immunomarkers involved in inflammatory activation. This evidence may pave the way to sample stratification in clinical studies aiming to develop diagnostic tools and therapies targeting specific immunopathogenic pathways of psychosis.

Association between Diffusion Tensor Imaging, inflammation and immunological alterations in unipolar and bipolar depression: A review.

Major Depressive Disorder (MDD) and Bipolar Disorder Depression (BDD) are common psychiatric illnesses characterized by structural and functional brain alterations and signs of neuroinflammation. In line with the neuroinflammatory pathogenesis of depressive syndromes, recent studies have demonstrated how white matter (WM) microstructural impairments detected by Diffusion Tensor Imaging, are correlated to peripheral immunomarkers in depressed patients. In this context, we performed a comprehensive systematic search on PubMed, Medline and Scopus of the original studies published till June 2022, exploring the association between immunomarkers and WM alteration patterns in patients affected by MDD or BDD. Overall, the studies included in this review showed a consistent association between blood proinflammatory and counter-regulatory immunomarkers, including regulatory T cells and natural killer cells markers, as well as measures of demyelination and dysmyelination in both MDD and BDD patients. These pathogenetic insights could outline an integrated clinical perspective to affective disorders, helping psychiatrists to develop novel biotype-to-phenotype models of depression and opening the way to tailored approaches in treatments.

Migrants rescued on the Mediterranean Sea route: nutritional, psychological status and infectious disease control.

INTRODUCTION: North Africa has become a key migratory hub where a large number of migrants attempt the journey by sea from the Libyan coastline to the south of Europe. In this humanitarian disaster scenario, the Mediterranean route has been one of the most used by illegal boats. METHODOLOGY: In this report, the state of physical and psychological health of a cluster of Eritrean migrants, escaped from Libya and rescued in the Mediterranean Sea after a shipwreck, was described by epidemiological, clinical and laboratory investigations. RESULTS: Data suggest that despite the majority  of the migrants being apparently in good health upon a syndromic surveillance approach, most of them suffered a decline in psychological status as well as severe malnutrition. The emergence of infectious diseases, related to poor living conditions during the journey, is not a rare event. CONCLUSION: The present report highlights the risks of failures of the syndromic medical approach in the setting of the extremely challenging migration route and underlines migrant frailties consequent to a prolonged journey and long period of detention. These stressors, which can degrade the initial health condition of traveling migrants, can lead to a premature "exhausted migrant effect" that should be carefully investigated in order to avoid the early emergence of diseases related to frailty.