Endogenous depression represents a severe mental health condition projected to become one of the worldwide leading causes of years lived with disability. The currently available clinical and non-clinical interventions designed to alleviate endogenous depression-associated symptoms encounter a series of inconveniences, from the lack of intervention effectiveness and medication adherence to unpleasant side effects. In addition, depressive individuals tend to be more frequent users of primary care units, which markedly affects the overall treatment costs. In parallel with the growing incidence of endogenous depression, researchers in sleep science have discovered multiple links between rapid eye movement (REM) sleep patterns and endogenous depression. Recent findings suggest that prolonged periods of REM sleep are associated with different psychiatric disorders, including endogenous depression. In addition, a growing body of experimental work confidently describes REM sleep deprivation (REM-D) as the underlying mechanism of most pharmaceutical antidepressants, proving its utility as either an independent or adjuvant approach to alleviating the symptoms of endogenous depression. In this regard, REM-D is currently being explored for its potential value as a sleep intervention-based method for improving the clinical management of endogenous depression. Therefore, this narrative review represents a comprehensive inventory of the currently available evidence supporting the potential use of REM-D as a reliable, non-pharmaceutical approach for treating endogenous depression, or as an adjuvant practice that could improve the effectiveness of currently used medication.

Introduction: Wearable devices capable of continuously sampling movement, autonomic arousal and neuro-electrical activity are emerging as promising complements to traditional assessment and treatment of Attention-Deficit/Hyperactivity Disorder (ADHD). By moving data collection from the clinic to everyday settings, these technologies offer an unprecedented window onto the moment-to-moment fluctuations that characterise the condition. Methods: Drawing on a comprehensive literature search spanning 2013 to February 2025 across biomedical and engineering databases, we reviewed empirical studies that used commercial or research-grade wearables for ADHD-related diagnosis, monitoring or intervention. Titles and abstracts were screened against predefined inclusion criteria, with full-text appraisal and narrative synthesis of the eligible evidence. A narrative synthesis was conducted, with inclusion criteria targeting empirical studies of wearable devices applied to ADHD for monitoring, mixed monitoring-plus-intervention, or intervention-only applications. No quantitative pooling was undertaken due to heterogeneity of designs, endpoints, and analytic methods. Results: The reviewed body of work demonstrates that accelerometers, heart-rate and electrodermal sensors, and lightweight EEG headsets can enrich clinical assessment by capturing ecologically valid markers of hyperactivity, arousal and attentional lapses. Continuous monitoring studies suggest that wearable-derived metrics align with symptom trajectories and medication effects, while early intervention trials explore haptic prompts, attention-supporting apps and non-invasive neuromodulation delivered through head-worn devices. Across age groups, participants generally tolerate these tools well and value the objective feedback they provide. Nevertheless, the literature is limited by heterogeneous study designs, modest sample sizes and short follow-up periods, making direct comparison and clinical translation challenging. Conclusions: Current evidence paints an optimistic picture of the feasibility and acceptability of wearables in ADHD, yet larger, standardised and longer-term investigations are needed to confirm their clinical utility. Collaboration between clinicians, engineers and policymakers will be crucial to address data-privacy, equity and cost-effectiveness concerns and to integrate wearable technology into routine ADHD care.

On 24 February 2022, the Russian Federation invaded Ukraine, starting a military conflict that soon turned into a full-scale war. The Romanians have been actively involved in helping their neighbors, causing the accumulation of emotional and mental pressure upon the Romanian population exposed to such a close military conflict. This cross-sectional study assessed, through an online survey (1586 adult Romanian residents), the primary coping mechanisms, quality of life and anxiety levels in response to the psychological trauma associated with the Russo—Ukrainian war. Based on the results, focusing on and venting emotions along with behavioral disengagement were the coping strategies that had the strongest negative impact on anxiety and well-being. On the other hand, positive reinterpretation and growth were associated with less anxiety, a higher degree of overall health and better quality of life. To the best of our knowledge, this study is the first of its kind to be performed among the Romanian population so far. Thus, we equip mental health practitioners with the tools (real-life evidence data) that will allow them to establish a more meaningful doctor—patient relationship, maximizing therapy results.

This study investigates the correlation between REM sleep patterns, as measured by the Apple Watch, and depressive symptoms in an undiagnosed population. Employing the Apple Watch for data collection, REM sleep duration and frequency were monitored over a specified period. Concurrently, participants’ depressive symptoms were evaluated using standardized questionnaires. The analysis, primarily using Spearman’s correlation, revealed noteworthy findings. A significant correlation was observed between an increased REM sleep proportion and higher depressive symptom scores, with a correlation coefficient of 0.702, suggesting a robust relationship. These results highlight the potential of using wearable technology, such as the Apple Watch, in early detection and intervention for depressive symptoms, suggesting that alterations in REM sleep could serve as preliminary indicators of depressive tendencies. This approach offers a non-invasive and accessible means to monitor and potentially preempt the progression of depressive disorders. This study’s implications extend to the broader context of mental health, emphasizing the importance of sleep assessment in routine health evaluations, particularly for individuals exhibiting early signs of depressive symptoms.

Background: Rapid-eye-movement (REM) sleep disinhibition—shorter REM latency and a larger nightly REM fraction—is a well-described laboratory correlate of major depression. Whether the same pattern can be captured efficiently with consumer wearables in everyday settings remains unclear. We therefore quantified REM latency and proportion of REM sleep out of total sleep duration (labeled “REM sleep coefficient”) from Apple Watch recordings and examined their association with depressive symptoms. Methods: 191 adults wore an Apple Watch for 15 consecutive nights while a custom iOS app streamed raw accelerometry and heart-rate data. Sleep stages were scored with a neural-network model previously validated against polysomnography. REM latency and REM sleep coefficient were averaged per participant. Depressive severity was assessed twice with the Beck Depression Inventory and averaged. Descriptive statistics, normality tests, Spearman correlations, and ordinary-least-squares regressions were performed. Results: Mean ± SD values were BDI 13.52 ± 6.79, REM sleep coefficient 24.05 ± 6.52, and REM latency 103.63 ± 15.44 min. REM latency correlated negatively with BDI (Spearman ρ = −0.673, p < 0.001), whereas REM sleep coefficient correlated positively (ρ = 0.678, p < 0.001). Combined in a bivariate model, the two REM metrics explained 62% of variance in depressive severity. Conclusions: Wearable-derived REM latency and REM proportion jointly capture a large share of depressive-symptom variability, indicating their potential utility as accessible digital biomarkers. Larger longitudinal and interventional studies are needed to determine whether modifying REM architecture can alter the course of depression.

Introduction. Post-traumatic brain injury (TBI) dementia is a serious neurodegenerative condition, with or without behavioral disturbances, that can dramatically change the quality of life of both patients and their caretakers, and without an available effective treatment, the prognosis of these patients is not favorable. Objective. The purpose of this case report study was to present the effects of the porcine brain-derivate hydrolysate (PBDH) in a severe case of post-TBI dementia and the gradual improvement of symptoms based on cognitive function tests. Methodology. A high-dose regimen of neurotrophic factors was initiated, consisting of PDBH 30 mL/administration, 10 days/month, for three months, while the treatment efficacy was monitored using the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Global Assessment of Functioning Scale (GAFS). Conclusions. Following the completion of the PBDH regimen, the patient registered an improvement in the cognitive function, from severe impairment to moderate impairment, and in the functionality as well. The same regimen will be repeated three months later to maintain or improve the current results, which reflected the efficacy of PBDH in post-TBI dementia.