Vascular depression is regarded as a subtype of late-life depression characterized by a distinct clinical presentation and an association with cerebrovascular damage. Although the term is commonly used in research settings, widely accepted diagnostic criteria are lacking and vascular depression is absent from formal psychiatric manuals such as the Diagnostic and Statistical Manual of Mental Disorders, 5th edition – a fact that limits its use in clinical settings. Magnetic resonance imaging (MRI) techniques, showing a variety of cerebrovascular lesions, including extensive white matter hyperintensities, subcortical microvascular lesions, lacunes, and microinfarcts, in patients with late life depression, led to the introduction of the term “MRI-defined vascular depression”. This diagnosis, based on clinical and MRI findings, suggests that vascular lesions lead to depression by disruption of frontal–subcortical–limbic networks involved in mood regulation. However, despite multiple MRI approaches to shed light on the spatiotemporal structural changes associated with late life depression, the causal relationship between brain changes, related lesions, and late life depression remains controversial. While postmortem studies of elderly persons who died from suicide revealed lacunes, small vessel, and Alzheimer-related pathologies, recent autopsy data challenged the role of these lesions in the pathogenesis of vascular depression. Current data propose that the vascular depression connotation should be reserved for depressed older patients with vascular pathology and evident cerebral involvement. Based on current knowledge, the correlations between intra vitam neuroimaging findings and their postmortem validity as well as the role of peripheral markers of vascular disease in late life depression are discussed. The multifold pathogenesis of vascular depression as a possible subtype of late life depression needs further elucidation. There is a need for correlative clinical, intra vitam structural and functional MRI as well as postmortem MRI and neuropathological studies in order to confirm the relationship between clinical symptomatology and changes in specific brain regions related to depression. To elucidate the causal relationship between regional vascular brain changes and vascular depression, animal models could be helpful. Current treatment options include a combination of vasoactive drugs and antidepressants, but the outcomes are still unsatisfying.

Introduction: Sleep disorders, especially insomnia, are very common in different kinds of cancers, but their prevalence and incidence are not well-known. Disturbed sleep in cancer is caused by different reasons and usually appears as a comorbid disorder to different somatic and psychiatric diagnoses, psychological disturbances and treatment methods. There can be many different predictors for sleep disturbances in these vulnerable groups, such as pre-existing sleep disorders, caused by the mental status in cancer or as side effect of the cancer treatment. Methods: A systematic literature review of 8073 studies was conducted on the topic of sleep and sleep disorders in cancer patients. The articles were identified though PubMed, PsycInfo and Web of Knowledge, and a total number of 89 publications were qualified for analysis. Results: The identified eighty-nine studies were analyzed on the topic of sleep and sleep disorders in cancer, twenty-six studies on sleep and fatigue in cancer and sixty-one studies on the topic of sleep disorders in cancer. The prevalence of sleep disturbences and/or sleep disorders in cancer was up to 95%. Discussion: Sleep disturbances and sleep disorders (such as insomnia, OSAS, narcolepsy and RLS; REM-SBD) in cancer patients can be associated with different conditions. Side effects of cancer treatment and cancer-related psychological dysfunctions can be instigated by sleep disturbances and sleep disorders in these patients, especially insomnia and OSAS are common. An evidence-based treatment is necessary for concomitant mental and/or physical states.

Background Excessive fatigue and insomnia are common among shift workers and can lead to negative effects such as reduced work performance, processing errors, accidents at work, absenteeism, reduced...

Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide.Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs.Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large.DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

In western societies, about one in six employees works in shifts. Shiftwork is associated with a number of poor somatic and psychological health outcomes, especially sleep issues. Higher rates of absenteeism and accidents in the workplace are possible consequences. Still, prevention programs and treatment options that are specifically tailored to shift-workers’ needs are rare. We devised a 4-week online cognitive behavioral therapy for insomnia (CBT-I) intervention (n = 21) and compared sleep outcomes to a face-to-face outpatient treatment for shift-workers (n = 12) using a sleep diary and the Epworth Sleepiness Scale (ESS). In the online sample, measures also included the World Health Organization wellbeing questionnaire (WHO-5) and the Insomnia Severity Index (ISI). In the outpatient sample, the Beck Depression Inventory (BDI-II), the Montgomery–Åsberg Depression Rating Scale (MADRS), and the Pittsburgh Sleep Quality Index (PSQI) were administered. Results showed significant improvements in sleep efficiency by 7.2% in the online sample and 7.7% in the outpatient sample. However, no significant difference was found in the rate of improvement in sleep efficiency across four weeks of treatment between the samples. In the online sample, the wellbeing (WHO-5) and insomnia symptoms (ISI) scores were significantly improved following the CBT-I intervention (p < 0.004 and p < 0.002 respectively). In the outpatient sample, symptoms of depression (BDI-II and MADRS scores) and insomnia symptoms (PSQI scores) improved significantly following the CBT-I intervention. In summary, CBT-I significantly improved sleep efficiency in both the online and outpatient samples, in addition to wellbeing, symptoms of insomnia, and depression. The findings of this study demonstrate online CBT-I as a feasible approach for treating insomnia in shift-workers. Future randomized controlled trials are needed.