Somatic depression in the picture:Insights in the comorbidity between somatic diseases and depression

“Why is depression so common among individuals with a somatic disease?” Depression is very common among individuals with a somatic disease, and is associated with a poor quality of life and worsening of the somatic disease. This dissertation studied explanations for the association between somatic disease and depression. The results indicated that depression is probably not merely a psychological consequence or a reflection of the somatic disease. In addition, biological and behavioral factors are likely to play an important role in the relation with somatic disease. We found that depression was already more prevalent in individuals with undiagnosed diabetes. Because individuals were unaware of their diabetes, they were not yet confronted with the consequences of having a chronic disease. They were, for instance, not yet dependent on medication and diet prescriptions and not aware of changing future perspectives. In addition, MRI studies indicated a possible biological link. Structural abnormalities in depression-related brain areas were observed in individuals with respectively hypertension and chronic kidney disease. Possibly, a biological vulnerability in the brain may lead to the development of depression as well as somatic disease. In addition, somatic disease may cause damage to the brain, which could lead to the development of depressive symptoms. Finally, behavioral factors associated with depression may also lead to the development and worsening of somatic disease. We observed that cardiac rehabilitation was associated with lower mortality rates specifically for depressed myocardial infarction patients. Probably, a complex of interactions between psychological, biological, and behavioral factors underlie the relation between somatic disease and depression. Future studies should therefore study these factors in concert

An evaluation of the efficacy of two add-on ecological momentary intervention modules for depression in a pragmatic randomized controlled trial (ZELF-i)

BACKGROUND: Depression treatment might be enhanced by ecological momentary interventions (EMI) based on self-monitoring and person-specific feedback. This study is the first to examine the efficacy of two different EMI modules for depression in routine clinical practice.METHODS: Outpatients starting depression treatment at secondary mental health services (N = 161; MIDS-DEPRESSION = 35.9, s.d. = 10.7; MAGE = 32.8, s.d. = 12.1; 46% male) participated in a pragmatic randomized controlled trial with three arms. Two experimental groups engaged in 28 days of systematic self-monitoring (5 times per day), and received weekly feedback on either positive affect and activities (Do-module) or negative affect and thinking patterns (Think-module). The control group received no additional intervention. Participants completed questionnaires on depressive symptoms (primary outcome), social functioning, and empowerment before and after the intervention period, and at four measurements during a 6-month follow-up period.RESULTS: Of the 90 (out of 110) participants who completed the intervention, 86% would recommend it. However, the experimental groups did not show significantly more or faster changes over time than the control group in terms of depressive symptoms, social functioning, and empowerment. Furthermore, the trajectories of the two EMI modules were very similar.CONCLUSIONS: We did not find statistical evidence that this type of EMI augments the efficacy of regular depression treatment, regardless of module content. We cannot rule out that EMIs have a positive impact on other domains or provide a more efficient way of delivering care. Nonetheless, EMI's promise of effectiveness has not materialized yet.</p

"Get used to the fact that some of the care is really going to take place in a different way":General practitioners' experiences with E-health during the COVID-19 pandemic

The first outbreak of the COVID-19 pandemic led to the introduction of the more extensive use of e-health in Dutch general practices. The objective of this study was to investigate the experiences of general practitioners (GPs) regarding this change. In addition, the necessary conditions for e-health technology to be of added value to general practices were explored. In April 2020, 30 GPs were recruited for in-depth interviews via a web survey which contained questions regarding the use of e-health during the first wave of the pandemic. While most GPs intend to keep using e-health applications more extensively than before the pandemic, the actual use of e-health depends on several factors, including the characteristics of the application’s users. The following conditions for successful and sustainable implementation of e-health were identified: (1) integration of e-health technology in the organization of GP care, (2) sufficient user-friendliness of applications as well as digital skills of professionals and patients, and (3) adequate technological and financial support of e-health services. GPs clearly recognize the benefits of using e-health, and most GPs intend to keep using e-health applications more extensively than before the pandemic. However, improvements are needed to allow widespread and sustainable adoption of e-health technology in general practices

Music Alters Visual Perception

Background: Visual perception is not a passive process: in order to efficiently process visual input, the brain actively uses previous knowledge (e.g., memory) and expectations about what the world should look like. However, perception is not only influenced by previous knowledge. Especially the perception of emotional stimuli is influenced by the emotional state of the observer. In other words, how we perceive the world does not only depend on what we know of the world, but also by how we feel. In this study, we further investigated the relation between mood and perception. Methods and Findings: We let observers do a difficult stimulus detection task, in which they had to detect schematic happy and sad faces embedded in noise. Mood was manipulated by means of music. We found that observers were more accurate in detecting faces congruent with their mood, corroborating earlier research. However, in trials in which no actual face was presented, observers made a significant number of false alarms. The content of these false alarms, or illusory percepts, was strongly influenced by the observers ’ mood. Conclusions: As illusory percepts are believed to reflect the content of internal representations that are employed by the brain during top-down processing of visual input, we conclude that top-down modulation of visual processing is not purely predictive in nature: mood, in this case manipulated by music, may also directly alter the way we perceive the world

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Why do we see what’s not there?

Conscious perception is not the result of passively processing sensory input, but to large extent of active inference based on previous knowledge. This process of inference does go astray from time to time, and may lead to illusory perception: sometimes people see things that are not there. In a recent study we have shown that this inference may also be influenced by mood. Here we present some additional data, suggesting that illusory percepts are the result of increased top-down processing, which is normally helpful in detecting real stimuli. Finally, we speculate on a possible function of mood-dependent modulation of this top-down processing in social perception in particular

Experimental design and results.

<p><b>a</b>. Schematic of a single trial. Patches of noise were presented for 107 ms, creating an animation of dynamic noise; the middle patch contained either a face stimulus or just noise and was accompanied by an annulus surrounding the patch. After the trial, observers had to indicate whether they had seen a happy, a sad or no face. <b>b</b>. Proportions of real faces seen (black bars) and correctly identified emotional expressions (white bars). Error bars indicate 1 S.E. (n = 42), asterisks (**) indicate significant difference at p<.001. <b>c</b>. Proportions of reported false alarms (black bars) and proportion false alarms classified as happy (white bars). Error bars indicate 1 S.E. (n = 42), asterisks (**) indicate significant difference at p<.001.</p