Response style and severity and chronicity of depressive disorders in primary health care

Background: Response styles theory of depression postulates that rumination is a central factor in occurrence, severity and maintaining of depression. High neuroticism has been associated with tendency to ruminate. We investigated associations of response styles and neuroticism with severity and chronicity of depression in a primary care cohort study. Methods: In the Vantaa Primary Care Depression Study, a stratified random sample of 1119 adult patients was screened for depression using the Prime-MD. Depressive and comorbid psychiatric disorders were diagnosed using SCID-I/P and SCID-II interviews. Of the 137 patients with depressive disorders, 82% completed the prospective five-year follow-up with a graphic life chart enabling evaluation of the longitudinal course of episodes. Neuroticism was measured with the Eysenck Personality Inventory (EPI-Q). Response styles were investigated at five years using the Response Styles Questionnaire (RSQ-43). Results: At five years, rumination correlated significantly with scores of Hamilton Depression Rating Scale (r = 0.54), Beck Depression Inventory (r = 0.61), Beck Anxiety Inventory (r = 0.50), Beck Hopelessness Scale (r = 0.51) and Neuroticism (r = 0.58). Rumination correlated also with proportion of follow-up time spent depressed (r = 0.38). In multivariate regression, high rumination was significantly predicted by current depressive symptoms and neuroticism, but not by anxiety symptoms or preceding duration of depressive episodes. Conclusions: Among primary care patients with depression, rumination correlated with current severity of depressive symptoms, but the association with preceding episode duration remained uncertain. The association between neuroticism and rumination was strong. The findings are consistent with rumination as a state-related phenomenon, which is also strongly intertwined with traits predisposing to depression. (C) 2015 Elsevier Masson SAS. All rights reserved.Peer reviewe

Health-related quality of life of primary care patients with depressive disorders

Background: Depressive disorders are known to impair health-related quality of life (HRQoL) both in the short and long term. However, the determinants of long-term HRQoL outcomes in primary care patients with depressive disorders remain unclear. Methods: In a primary care cohort study of patients with depressive disorders, 82% of 137 patients were prospectively followed up for five years. Psychiatric disorders were diagnosed with SCID-I/P and SCID-II interviews; clinical, psychosocial and socio-economic factors were investigated by rating scales and questionnaires plus medical and psychiatric records. HRQoL was measured with the generic 15D instrument at baseline and five years, and compared with an age-standardized general population sample (n = 3707) at five years. Results: Depression affected the 15D total score and almost all dimensions at both time points. At the end of follow-up, HRQoL of patients in major depressive episode (MDE) was particularly low, and the association between severity of depression (Beck Depression Inventory [BDI]) and HRQoL was very strong (r = -0.804). The most significant predictors for change in HRQoL were changes in BDI and Beck Anxiety Inventory (BAI) scores. The mean 15D score of depressive primary care patients at five years was much worse than in the age-standardized general population, reaching normal range only among patients who were in clinical remission and had virtually no symptoms. Conclusions: Among depressive primary care patients, presence of current depressive symptoms markedly reduces HRQoL, with symptoms of concurrent anxiety also having a marked impact. For HRQoL to normalize, current depressive and anxiety symptoms must be virtually absent. (C) 2016 Elsevier Masson SAS. All rights reserved.Peer reviewe

Evaluation of the hyperspectral radiometer (HSR1) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site

The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site in Lamont, Oklahoma, for 2 months from May to July 2022. The HSR1 is a prototype instrument that measures total (Ftotal) and diffuse (Fdiffuse) spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers, including two multifilter rotating shadowband radiometers (MFRSRs) and the Shortwave Array Spectroradiometer–Hemispheric (SASHe) radiometer. The Ftotal at 500 nm for the HSR1 compared to the MFRSRs has a mean (relative) difference of 0.01 W m−2 nm−1 (1 %–2 %). The HSR1 mean Fdiffuse at 500 nm is smaller than the MFRSRs' by 0.03–0.04 (10 %) W m−2 nm−1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 AOD at 500 nm is larger than the CSPHOT's by 0.010 (8 %) and larger than the MFRSRs' by 0.007–0.017 (6 %–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the Ftotal, Fdiffuse, and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments. The comparisons are within ∼ 10 % for the Ftotal and Fdiffuse, except for 940 nm, where there is relatively larger disagreement. The AOD comparisons are within ∼ 10 % at 415 and 440 nm; however, a relatively larger disagreement in the AOD comparison is found for higher wavelengths.</p

Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models

Contributions of a global network of tree diversity experiments to sustainable forest plantations

status: publishe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe