Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this paper we critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality. We show that problems with centrality indices discussed in the social network literature also apply to the psychological networks. Assumptions underlying centrality indices, such as presence of a flow and shortest paths, may not correspond with a general theory of how psychological variables relate to one another. Furthermore, the assumptions of node distinctiveness and node exchangeability may not hold in psychological networks. We conclude that, for psychological networks, betweenness and closeness centrality seem especially unsuitable as measures of node importance. We therefore suggest three ways forward: (1) using centrality measures that are tailored to the psychological network context, (2) reconsidering existing measures of importance used in statistical models underlying psychological networks, and (3) discarding the concept of node centrality entirely. Foremost, we argue that one has to make explicit what one means when one states that a node is central, and what assumptions the centrality measure of choice entails, to make sure that there is a match between the process under study and the centrality measure that is used.

OBJECTIVEDepression is a common comorbidity of diabetes, undesirably affecting patients' physical and mental functioning. Psychological interventions are effective treatments for depression in the general population as well as in patients with a chronic disease. The aim of this study was to assess the efficacy of individual mindfulnessbased cognitive therapy (MBCT) and individual cognitive behavior therapy (CBT) in comparison with a waiting-list control condition for treating depressive symptoms in adults with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODSIn this randomized controlled trial, 94 outpatients with diabetes and comorbid depressive symptoms (i.e., Beck Depression Inventory-II [BDI-II] ‡14) were randomized to MBCT (n = 31), CBT (n = 32), or waiting list (n = 31). All participants completed written questionnaires and interviews at pre-and postmeasurement (3 months later). Primary outcome measure was severity of depressive symptoms (BDI-II and Toronto Hamilton Depression Rating Scale). Anxiety (Generalized Anxiety Disorder 7), well-being (Well-Being Index), diabetes-related distress (Problem Areas In Diabetes), and HbA 1c levels were assessed as secondary outcomes. RESULTSResults showed that participants receiving MBCT and CBT reported significantly greater reductions in depressive symptoms compared with patients in the waitinglist control condition (respectively, P = 0.004 and P < 0.001; d = 0.80 and 1.00; clinically relevant improvement 26% and 29% vs. 4%). Both interventions also had significant positive effects on anxiety, well-being, and diabetes-related distress. No significant effect was found on HbA 1c values. CONCLUSIONSBoth individual MBCT and CBT are effective in improving a range of psychological symptoms in individuals with type 1 and type 2 diabetes.

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Background: In complex systems early warning signals such as rising autocorrelation, variance and network connectivity are hypothesized to anticipate relevant shifts in a system. For direct evidence hereof in depression, designs are needed in which early warning signals and symptom transitions are prospectively assessed within an individual. Therefore, this study aimed to detect personalized early warning signals preceding the occurrence of a major symptom transition. Methods: Six single- subject time-series studies were conducted, collecting frequent observations of momentary affective states during a time-period when participants were at increased risk of a symptom transition. Momentary affect states were reported three times a day over three to six months (95-183 days). Depressive symptoms were measured weekly using the Symptom CheckList-90. Presence of sudden symptom transitions was assessed using change point analysis. Early warning signals were analysed using moving window techniques. Results: As change point analysis revealed a significant and sudden symptom transition in one participant in the studied period, early warning signals were examined in this person. Autocorrelation (r=0·51; p<2.2e-16), and variance (r=0·53; p<2.2e-16) in ‘feeling down’, and network connectivity (r=0·42; p<2.2e-16) significantly increased a month before this transition occurred. These early warnings also preceded the rise in absolute levels of ‘feeling down’ and the participant’s personal indication of risk for transition. Conclusions: This study replicated the findings of a previous study and confirmed the presence of rising early warning signals a month before the symptom transition occurred. Results show the potential of early warning signals to improve personalized risk assessment in the field of psychiatry.

HowNutsAreTheDutch (Dutch: HoeGekIsNL) is a national crowdsourcing study designed to investigate multiple continuous mental health dimensions in a sample from the general population (n = 12,503). Its main objective is to create an empirically based representation of mental strengths and vulnerabilities, accounting for (i) dimensionality and heterogeneity, (ii) interactivity between symptoms and strengths, and (iii) intra-individual variability. To do so, HowNutsAreTheDutch (HND) makes use of an internet platform that allows participants to (a) compare themselves to other participants via cross-sectional questionnaires and (b) to monitor themselves three times a day for 30 days with an intensive longitudinal diary study via their smartphone. These data enable for personalized feedback to participants, a study of profiles of mental strengths and weaknesses, and zooming into the fine-grained level of dynamic relationships between variables over time. Measuring both psychiatric symptomatology and mental strengths and resources enables for an investigation of their interactions, which may underlie the wide variety of observed mental states in the population. The present paper describes the applied methods and technology, and presents the sample characteristics. Copyright © 2015 John Wiley & Sons, Ltd.

Evidence is growing that vulnerability to depression may be characterized by strong negative feedback loops between mental states. It is unknown whether such dynamics between mental states can be altered by treatment. This study examined whether treatment with imipramine or treatment with Mindfulness-Based Cognitive Therapy (MBCT) reduces the connectivity within dynamic networks of mental states in individuals with depressive symptoms. In the Imipramine trial, individuals diagnosed with major depression were randomized to imipramine treatment or placebo-pill treatment (n = 50). In the Mind-Maastricht trial, individuals with residual depressive symptoms were randomized to Mindfulness-Based Cognitive Therapy (MBCT) or to a waiting-list control condition (n = 119). Lagged associations among mental states, as assessed with the Experience Sampling Method (ESM), were estimated at baseline and post-intervention. The results show that few of the dynamic network connections changed significantly over time and few of the changes after MBCT and imipramine treatment differed significantly from the control groups. The decrease in average node connectivity after MBCT did not differ from the decrease observed in the waiting-list control group. Our findings suggest that imipramine treatment and MBCT do not greatly change the dynamic network structure of mental states, even though they do reduce depressive symptomatology.

Objective: The current qualitative study aimed to map the relevance of the experience sampling method (ESM) for psychiatric practice and identify barriers and facilitators for implementation, as perceived by patients and clinicians. Methods: Participants were 22 patients with various diagnoses and 21 clinicians (e.g., psychiatrists, psychologists) who participated in interviews or focus groups. Using Atlas.TI, qualitative thematic analysis was conducted to analyze the transcripts, resulting in four themes: 1) applications, 2) advantages, 3) undesirable effects, and 4) requirements for implementation of ESM in care. Results: Clinicians and patients believed ESM could be relevant in every phase of care to increase patients' awareness, insight and self-management, personalize interventions, and alert patients to rising symptoms. Further, ESM was expected to improve the patient-clinician relationship, lead to objective, personalized, reliable and visual data, and increase efficiency of care. However, participants warned against high assessment burden and potential symptom worsening. Conclusions: This study provides first evidence that the potential of ESM is recognized by both patients and clinicians. Key recommendations for optimal implementation of ESM in psychiatric care include flexible application of ESM, collaboration between patient and clinician, regular evaluation, awareness of negative reactivity, availability to patients with different psychiatric syndromes, and implementation by an interdisciplinary team of patients, clinicians, researchers, and information technology specialists.

Increases in mindfulness are assumed to lead to improvements in psychological well-being during mindfulness-based treatments. However, the temporal order of this association has received little attention. This intensive longitudinal study examines whether within-person changes in mindfulness precede or follow changes in negative affect (NA) and positive affect (PA) during a mindfulness based stress reduction (MBSR) program. This study also examines interindividual differences in the association between mindfulness and affect and possible predictors of these differences. Mindfulness, NA, and PA were assessed on a daily basis in 83 individuals from the general population who participated in an MBSR program. Multilevel autoregressive models were used to investigate the temporal order of changes in mindfulness and affect. Day-to-day changes in mindfulness predicted subsequent day-to-day changes in both NA and PA, but reverse associations did not emerge. Thus, changes in mindfulness seem to precede rather than to follow changes in affect during MBSR. The magnitude of the effects differed substantially between individuals, showing that the strength of the relationship between mindfulness and affect is not the same for all participants. These between-subjects differences could not be explained by gender, age, level of education, average level of mindfulness home practice, or baseline levels of mindfulness and affect. Mindfulness home practice during the day did predict subsequent increases in mindfulness. The findings suggest that increasing mindfulness on a daily basis can be a beneficial means to improve daily psychological well-being.