The counselling self-estimate inventory (COSE): Does it work in Chinese counsellors?

Counselling self-efficacy is an important construct for research and evaluation in counsellors' competencies and training effectiveness. Larson et al. developed the Counselling Self-Estimate Inventory (COSE) for counsellors in America and examined its factor structure using exploratory factor analysis. They recommended a five-factor model (microskills, counselling process, difficult client behaviour, cultural competence, and awareness of values) and the use of the COSE for future research. However, little research has investigated the validity of the COSE in the context of counselling Chinese students in schools. In the present study, the factor structure of responses to the Chinese version of the Counselling Self-Estimate Inventory in a sample of 578 Hong Kong secondary school guidance teachers was examined using the EQS approach to confirmatory factor analysis. The results showed that while a five-factor model was fairly able to fit the data, the deletion of items related to the awareness of values factor yielded a better fitting model. The discussion of potential uses and limitations of the C-COSE in the context of preparing and supervising school guidance personnel in student counselling is relevant to counselling psychologists and researchers in Hong Kong and other parts of the world.postprin

Identifying Meteorological Controls on Open and Closed Mesoscale Cellular Convection Associated with Marine Cold Air Outbreaks

Mesoscale cellular convective (MCC) clouds occur in large‐scale patterns over the ocean and have important radiative effects on the climate system. An examination of time‐varying meteorological conditions associated with satellite‐observed open and closed MCC clouds is conducted to illustrate the influence of large‐scale meteorological conditions. Marine cold air outbreaks (MCAO) influence the development of open MCC clouds and the transition from closed to open MCC clouds. MCC neural network classifications on Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2008 are collocated with Clouds and the Earth's Radiant Energy System (CERES) data and ERA‐Interim reanalysis to determine the radiative effects of MCC clouds and their thermodynamic environments. Closed MCC clouds are found to have much higher albedo on average than open MCC clouds for the same cloud fraction. Three meteorological control metrics are tested: sea‐air temperature difference (ΔT), estimated inversion strength (EIS), and a MCAO index (M). These predictive metrics illustrate the importance of atmospheric surface forcing and static stability for open and closed MCC cloud formation. Predictive sigmoidal relations are found between M and MCC cloud frequency globally and regionally: negative for closed MCC cloud and positive for open MCC cloud. The open MCC cloud seasonal cycle is well correlated with M, while the seasonality of closed MCC clouds is well correlated with M in the midlatitudes and EIS in the tropics and subtropics. M is found to best distinguish open and closed MCC clouds on average over shorter time scales. The possibility of a MCC cloud feedback is discussed

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

BACKGROUND Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation. CONCLUSION This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57

The Parkinson’s Disease Mendelian Randomization Research Portal

Mendelian randomization is a method for exploring observational associations to find evidence of causality. To apply Mendelian randomization between risk factors/phenotypic traits (exposures) and PD in a large, unbiased manner, and to create a public resource for research. We observed evidence for causal associations between 12 exposures and risk of PD. Of these, nine were effects related to increasing adiposity and decreasing risk of PD. The remaining top three exposures that affected PD risk were tea drinking, time spent watching television, and forced vital capacity, but these may have been biased and were less convincing. Other exposures at nominal statistical significance included inverse effects of smoking and alcohol. We present a new platform which offers Mendelian randomization analyses for a total of 5,839 genome-wide association studies versus the largest PD genome-wide association studies available (https://pdgenetics.shinyapps.io/MRportal/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.AJN reports grants from Parkinson’s UK, Barts Charity, Leonard Wolfson Experimental Neurology Centre, UCL Movement Disorders Centre and the Virginia Kieley Benefaction; honoraria or consultancy fees from Britannia, Global Kinetics Corporation, Profile Pharmaceuticals, Guide point, Biogen and Roche. KH and DAH are employees of 23andMe and hold stock or stock options in 23andMe. DAL reports grants from the Medical Research Council, numerous charitable funders,Medtronic and Roche. ZG-O reports consultancy fees from Inceptions Sciences,Idorsia, Denali, Lysosomal Therapeutics inc. HM reports reports consultancy from Biogen, UCB, Abbvie, Denali, Biohaven; lecture fees/honoraria from Biogen, UCB,C4X Discovery, GE-Healthcare, Welcome Trust, Movement Disorders Society; Research Grants from Parkinson’s UK, Cure Parkinson’s Trust, PSP Association, CBD Solutions, Drake Foundation, Medical Research Council. Dr Morris is a co-applicanton a patent application related to C9ORF72 (PCT/GB2012/052140)