Abstract Depression has a huge societal impact, making accurate measurement paramount. While there are several available measures, the Center for Epidemiological Studies Depression Scale (CESD) is a ...popular assessment tool that has wide applicability in the general population. In order to reflect modern diagnostic criteria and improve upon psychometric limitations of its predecessor, the Center for Epidemiologic Studies Depression Scale Revised (CESD-R) was recently created, but has yet to be publicized. This study explored psychometric properties of the CESD-R across a large community sample ( N = 7389) and smaller student sample ( N = 245). A newly proposed algorithmic classification method yielded base-rates of depression consistent with epidemiological results. Factor analysis suggested a unidimensional factor structure, but important utility for two separate symptom clusters. The CESD-R exhibited good psychometric properties, including high internal consistency, strong factor loadings, and theoretically consistent convergent and divergent validity with anxiety, schizotypy, and positive and negative affect. Results suggest the CESD-R is an accurate and valid measure of depression in the general population with advantages such as free distribution and an atheoretical basis.
During the past two decades, mindfulness meditation has gone from being a fringe topic of scientific investigation to being an occasional replacement for psychotherapy, tool of corporate well-being, ...widely implemented educational practice, and “key to building more resilient soldiers.” Yet the mindfulness movement and empirical evidence supporting it have not gone without criticism. Misinformation and poor methodology associated with past studies of mindfulness may lead public consumers to be harmed, misled, and disappointed. Addressing such concerns, the present article discusses the difficulties of defining mindfulness, delineates the proper scope of research into mindfulness practices, and explicates crucial methodological issues for interpreting results from investigations of mindfulness. For doing so, the authors draw on their diverse areas of expertise to review the present state of mindfulness research, comprehensively summarizing what we do and do not know, while providing a prescriptive agenda for contemplative science, with a particular focus on assessment, mindfulness training, possible adverse effects, and intersection with brain imaging. Our goals are to inform interested scientists, the news media, and the public, to minimize harm, curb poor research practices, and staunch the flow of misinformation about the benefits, costs, and future prospects of mindfulness meditation.
•Anxiety can be characterized by consistently altered intrinsic connectivity between and/or within networks.•Hypo-connectivity of the affective network with executive control network and default mode ...network are associated with anxiety.•Anxiety is associated with consistently attenuated anti-correlations between the executive control network and default mode network.•The connectivity within the salience network as well as its connectivity with sensorimotor network is weakened in anxiety.
Anxiety and anxiety disorders are associated with specific alterations to functional brain networks, including intra-networks and inter-networks. Given the heterogeneity within anxiety disorders and inconsistencies in functional network differences across studies, identifying common patterns of altered brain networks in anxiety is imperative. Here, we conducted an activation likelihood estimation meta-analysis of resting-state functional connectivity studies in anxiety and anxiety disorders (including 835 individuals with different levels of anxiety or anxiety disorders and 508 controls). Results show that anxiety can be characterized by hypo-connectivity of the affective network with executive control network (ECN) and default mode network (DMN), as well as decoupling of the ECN with the DMN. The connectivity within the salience network and its connectivity with sensorimotor network are also attenuated. These results reveal consistent dysregulations of affective and cognitive control related networks over networks related to emotion processing in anxiety and anxiety disorders. The current findings provide an empirical foundation for an integrated model of brain network alterations that are common across anxiety and anxiety disorders.
Affective distress (as observed in anxiety and depression) has been observed to be related to insufficient sensitivity to changing reinforcement during operant learning. Whether such findings are ...specific to anxiety or depression is unclear given a wider literature relating negative affect to abnormal learning and the possibility that relationships are not consistent across incentive types (i.e., punishment and reward) and outcomes (i.e., positive or negative). In two separate samples (n1 = 100; n2 = 88), participants completed an operant learning task with positive or negative, and neutral socio-affective feedback, designed to assess adaptive responses to changing environmental volatility. Individual parameter estimates were generated with hierarchical Bayesian modelling. Effects of manipulations were modelled by decomposing parameters into a linear combination of effects on the logit scale. While effects tended to support prior work, neither general affective distress nor anxiety or depression were consistently related to a decrease in the adaptive adjustment of learning-rates in response to changing environmental volatility (Sample 1: βα:volatility = −0.01, 95 % HDI = −0.14, 0.13; Sample 2: βα:volatility = −0.15, 95 % HDI = −0.37, 0.05). Interaction effects in Sample 1 suggested that while distress was associated with decrements in adaptive learning under punishment-minimisation, it was associated with improvements under reward-maximisation. While our results are broadly consistent with prior work, they suggest that the role of anxiety or depression in volatility learning, if present, is subtle and difficult to detect. Inconsistencies between our samples, along with issues of parameter identifiability complicated interpretation.
•General affective distress, rather than anxiety or depression, was somewhat associated with impaired adaptation of learning in a social learning paradigm•A distressed sample showed many differences in behavior to a normative sample that may reflect difficulties with such a task•The effect of psychological distress on learning behaviour is likely small and difficult to detect
The Buddhist construct of mindfulness is a central element of mindfulness-based interventions and derives from a systematic phenomenological programme developed over several millennia to investigate ...subjective experience. Enthusiasm for 'mindfulness' in Western psychological and other science has resulted in proliferation of definitions, operationalizations and self-report inventories that purport to measure mindful awareness as a trait. This paper addresses a number of seemingly intractable issues regarding current attempts to characterize mindfulness and also highlights a number of vulnerabilities in this domain that may lead to denaturing, distortion, dilution or reification of Buddhist constructs related to mindfulness. Enriching positivist Western psychological paradigms with a detailed and complex Buddhist phenomenology of the mind may require greater study and long-term direct practice of insight meditation than is currently common among psychologists and other scientists. Pursuit of such an approach would seem a necessary precondition for attempts to characterize and quantify mindfulness.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Research highlights ▶ Self-compassion predicts more variance in psychopathology than mindfulness. ▶ Mindfulness subscale of Self-Compassion Scale has low correlation with mindfulness measure. ▶ ...Self-compassion reflects complex nature of relationship between mindful constructs and health. ▶ Self-compassion predicts 18–44% of variance in anxiety, depression, worry, and quality of life.
IMPORTANCE Substance use disorders (SUDs) are among the most common sequelae of childhood maltreatment, yet the independent contributions of SUDs and childhood maltreatment to neurobiological changes ...and the effect of the latter on relapse risk (a critical variable in addiction treatment) are relatively unknown. OBJECTIVES To identify structural neural characteristics independently associated with childhood maltreatment (CM; a common type of childhood adversity), comparing a sample with SUD with a demographically comparable control sample, and to examine the relationship between CM-related structural brain changes and subsequent relapse. DESIGN, SETTING, AND PARTICIPANTS Structural magnetic resonance imaging study comparing 79 treatment-engaged participants with SUD in acute remission in inpatient treatment at a community mental health center vs 98 healthy control participants at an outpatient research center at an academic medical center. Both groups included individuals with a range of CM experiences. Participants with SUD were followed up prospectively for 90 days to assess relapse and relapse severity. INTERVENTION Standard 12-step, recovery-based, inpatient addiction treatment for all participants with SUD. MAIN OUTCOMES AND MEASURES Gray matter volume (GMV), subsequent substance use relapse, days to relapse, and severity of relapse. RESULTS Controlling for SUD and psychiatric comorbidity, CM (dichotomously classified) was uniquely associated with lower GMV across all participants in the left hippocampus (cornu ammonis 1-3, dentate gyrus), parahippocampus (presubiculum, parasubiculum, prosubiculum, subiculum, and entorhinal cortex), and anterior fusiform gyrus (corrected P < .05; uncorrected P = .001). Among the sample with SUD, CM prospectively predicted a shorter relapse to use of any drug (P = .048), while CM-related GMV reductions predicted severity of substance use relapse (P = .04). CONCLUSIONS AND RELEVANCE Findings indicate that CM was related to decreased GMV in limbic regions, which in turn predicted increased risk of relapse in SUD. These results suggest that CM may significantly affect the course of SUD treatment outcomes and that SUD treatment planning may benefit from identifying and addressing CM.
Both cognitive and affective processes require mental resources. However, it remains unclear whether these 2 processes work in parallel or in an integrated fashion. In this functional magnetic ...resonance imaging study, we investigated their interaction using an empathy-for-pain paradigm, with simultaneous manipulation of cognitive demand of the tasks and emotional valence of the stimuli. Eighteen healthy adult participants viewed photographs showing other people's hands and feet in painful or nonpainful situations while performing tasks of low (body part judgment) and high (laterality judgment) cognitive demand. Behavioral data showed increased reaction times and error rates for painful compared with nonpainful stimuli under laterality judgment relative to body part judgment, indicating an interaction between cognitive demand and stimulus valence. Imaging analyses showed activity in bilateral anterior insula (AI) and primary somatosensory cortex (SI), but not posterior insula, for main effects of cognitive demand and stimulus valence. Importantly, cognitive demand and stimulus valence showed a significant interaction in AI, SI, and regions of the frontoparietal network. These results suggest that cognitive and emotional processes at least partially share common brain networks and that AI might serve as a key node in a brain network subserving cognition-emotion integration.
Although state anxiety has been characterized by hyper-responsive subcortical activity and its bottom-up connectivity with cortical regions, the role of cortical networks in state anxiety is not yet ...well understood. To this end, we decoded individual state anxiety by using a machine-learning approach based on resting-state functional connectivity (RSFC) with functional near-infrared spectroscopy (fNIRS). Our results showed that the RSFC among a set of cortical networks were highly predictive of state anxiety, rather than trait anxiety. Specifically, these networks included connectivity between cortical areas in the default mode network (DMN) and dorsal attention network (DAN), and connectivity within the DMN, which were negatively correlated with state anxiety; connectivity between cortical areas in the DMN and frontoparietal network (FPN), FPN and salience network (SN), FPN and DAN, DMN and SN, which were positively correlated with state anxiety. These findings suggest a predictive role of intrinsic cortical organization in the assessment of state anxiety. The work provides new insights into potential neural mechanisms of emotion states and implications for prognosis, diagnosis, and treatment of affective disorders.
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