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.
The coronavirus disease 2019 (COVID-19) pandemic causes fear, as its immediate consequences for the public have produced unprecedented challenges for the education and healthcare systems. We aimed to ...validate the fear of COVID-19 scale (FCoV-19S) and examine the association of its scores with health literacy and health-related behaviors among medical students. A cross-sectional study was conducted from 7 to 29 April 2020 on 5423 students at eight universities across Vietnam, including five universities in the North, one university in the Center, two universities in the South. An online survey questionnaire was used to collect data on participants' characteristics, health literacy, fear of COVID-19 using the FCoV-19S, and health-related behaviors. The results showed that seven items of the FCoV-19S strongly loaded on one component, explained 62.15% of the variance, with good item-scale convergent validity and high internal consistency (Cronbach's alpha = 0.90). Higher health literacy was associated with lower FCoV-19S scores (coefficient, B, -0.06; 95% confidence interval, 95%CI, -0.08, -0.04;
< 0.001). Older age or last academic years, being men, and being able to pay for medication were associated with lower FCoV-19S scores. Students with higher FCoV-19S scores more likely kept smoking (odds ratio, OR, 1.11; 95% CI, 1.08, 1.14;
< 0.001) or drinking alcohol (OR, 1.04; 95% CI, 1.02, 1.06;
< 0.001) at an unchanged or higher level during the pandemic, as compared to students with lower FCoV-19S scores. In conclusion, the FCoV-19S is valid and reliable in screening for fear of COVID-19. Health literacy was found to protect medical students from fear. Smoking and drinking appeared to have a negative impact on fear of COVID-19. Strategic public health approaches are required to reduce fear and promote healthy lifestyles during the pandemic.
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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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We compare approximately 3 years of GPS height residuals (with respect to the International Terrestrial Reference Frame) with predictions of vertical surface displacements derived from the Gravity ...Recovery and Climate Experiment (GRACE) gravity fields for stations in Europe. An annual signal fit to the residual monthly heights, corrected for atmospheric pressure and barotropic ocean loading effects, should primarily represent surface displacements due to long‐wavelength variations in water storage. A comparison of the annual height signal from GPS and GRACE over Europe indicates that at most sites, the annual signals do not agree in amplitude or phase. We find that unlike the annual signal predicted from GRACE, the annual signal in the GPS heights is not coherent over the region, displaying significant variability from site to site. Confidence in the GRACE data and the unlikely possibility of large‐amplitude small‐scale features in the load field not captured by the GRACE data leads us to conclude that some of the discrepancy between the GPS and GRACE observations is due to technique errors in the GPS data processing. This is evidenced by the fact that the disagreement between GPS and GRACE is largest at coastal sites, where mismodeling of the semidiurnal ocean tidal loading signal can result in spurious annual signals.
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.
Seasonal signals in GPS time series are of great importance for understanding the evolution of regional mass fluctuations, i.e., ice, hydrology, and ocean mass. Conventionally these signals ...(quasi-annual and semi-annual signals) are modeled by least-squares fitting harmonic terms with a constant amplitude and phase. In reality, however, such seasonal signals are modulated, i.e., they will have a time-variable amplitude and phase. Recently, Davis et al. (2012) proposed a Kalman filter based approach to capture the stochastic seasonal behavior of geodetic time series. Singular Spectrum Analysis (SSA) is a non-parametric method, which uses time domain data to extract information from short and noisy time series without a priori knowledge of the dynamics affecting the time series. A prominent benefit is that trends obtained in this way are not necessarily linear. Further, true oscillations can be amplitude and phase modulated. In this work, we will assess the value of SSA for extracting time-variable seasonal signals from GPS time series. We compare our SSA-based results to those obtained using (1) least-squares analysis and (2) Kalman filtering. Our results demonstrate that SSA is a viable and complementary tool for extracting modulated oscillations from GPS time series.
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.
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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