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Modern research has proven that the “typical patient” requiring standardized treatments does not exist, reflecting the need for more personalized approaches for managing individual clinical profiles rather than broad diagnoses. In this regard, precision psychiatry has emerged focusing on enhancing prevention, diagnosis, and treatment of psychiatric disorders through identifying clinical subgroups, suggesting personalized evidence-based interventions, assessing the effectiveness of different interventions, and identifying risk and protective factors for remission, relapse, and vulnerability. Literature shows that recent advances in the field of precision psychiatry are rapidly becoming more data-driven reflecting both the significance and the continuous need for translational research in mental health. Different etiologies underlying depression have been theorized and some factors have been identified including neural circuitry, biotypes, biopsychosocial markers, genetics, and metabolomics which have shown to explain individual differences in pathology and response to treatment. Although the precision approach may prove to enhance diagnosis and treatment decisions, major challenges are hindering its clinical translation. These include the clinical diversity of psychiatric disorders, the technical complexity and costs of multiomics data, and the need for specialized training in precision health for healthcare staff, besides ethical concerns such as protecting the privacy and security of patients' data and maintaining health equity. The aim of this review is to provide an overview of recent findings in the conceptualization and treatment of depression from a precision mental health perspective and to discuss potential challenges and future directions in the application of precision psychiatry for the treatment of depression.

Background As a rising concern in the medical and mental health fields, this study aims to examine predictors of depressive symptoms in a sample of Egyptian patients with chronic pain in terms of coping styles and personality traits. Patients with chronic pain are believed to experience different stressors, which include, but are not limited to, pain, disability, reduced productivity, and financial difficulties. Such factors, in addition to various psychosocial factors, constitute the disease burden of chronic pain. Objective This study examines the degree to which coping styles and personality traits can influence the disease outcome in terms of comorbid depressive symptoms. Patients and methods A total of 98 (50 patients with fibromyalgia and 48 patients with rheumatoid arthritis) patients were interviewed and were assessed in terms of their coping styles, personality profile, and severity of depressive symptoms. Results Findings show a high prevalence of depressive symptoms and suggest passive coping, high neuroticism, low extraversion, unmarried status, and more years of education to be moderate predictors of the severity of chronic pain. Conclusion Conclusion Findings of this study shed light on the significance of the psychological aspects of chronic pain conditions and may help in designing liaison interventions for the management of secondary and comorbid depressive symptoms.