龙虎山天师府隆重举行建府九百周年庆典

2005年10月23日,天师府隆重举行道教正一派祖庭龙虎山天师府建府九百周年庆典活动。中央统战部副部长朱维群,国家宗教局一司副司长杨伯明,中国道教协会会长任法融、副会长林舟、张凤林、秘书长袁炳栋、副秘书长袁志鸿、李兆彩、张明心;江西省政协副主席、省委统战部部长王林森,     

Does rejection lead to disidentification? The role of internal motivation and avoidance strategies

Getting rejected can either push newcomers out of the group or make them try harder to become accepted. It is suggested that newcomers' internal motivation to become a group member and their strategies determine the outcomes of rejection. It was expected that in rejected newcomers, avoidance strategies (but not approach strategies) lead to stronger disidentification. Moreover, the disidentification effect of avoidance strategies is predicted to be buffered by the internal motivation to become a group member. Two studies supported these predictions. Study 1 manipulated the group's feedback (rejection vs. acceptance) and assessed internal motivation and strategies. Study 2 measured feedback and replicated the findings in the field. Thus, by the adoption of the right motivational approach, newcomers can prepare themselves not to be driven out of a new group by the almost unavoidable experiences of rejection. Copyright © 2010 John Wiley & Sons, Ltd.     

国宗局、陕西省政府、中国道协共同组团赴港协商《道德经》论坛事宜

江苏省道教协会第三次代表会议于2006年7月25日至26日在南京双门楼宾馆隆重召开,来自全省12个市的80多名代表参加了会议。会议期间,中国道教协会黄信阳、张凤林副会长、袁炳栋秘书长,江苏省委张连珍副书记,省政府仇和副省长,省政协林玉英副主席,省政协副主席、省委统战部周珉部     

学校联结和学业能力对高中生自尊的影响:一个多层线性模型

为探究高中生自尊的影响因素,本研究以来自18所学校的4776名高中生为研究对象,以自尊的价值—能力理论为依据,采用问卷法探讨价值因素(学校联结)和能力因素(学业能力)对高中生自尊的影响,并基于生态系统学视角构建多层线性模型。结果表明:(1)班级层面学校联结对个体自尊具有显著正向预测作用;(2)个体学业能力在学校联结与自尊之间具有中介作用;(3)个体学业能力对个体自尊的正向预测作用受到班级学业能力的调节,在高学业能力的班级条件下,个体学业能力对自尊水平的预测作用更强。     

父母情感温暖对儿童青少年学校投入的影响:有调节的中介模型

研究探索了青少年自我管理能力在父母情感温暖与学校投入之间的中介作用,以及学校氛围对上述中介效应的调节作用。采用父母情感温暖量表、青少年自我管理量表、学校氛围量表和学校投入量表对1033名中小学生进行测查。结果表明:(1)父母情感温暖可以正向预测学校投入;(2)自我管理在其中起中介作用,即父母情感温暖可以通过自我管理间接影响学校投入;(3)父母情感温暖影响学校投入的有调节的中介模型成立,其中学校氛围在前半段和后半段路径中均起调节作用,但作用有所不同。     

Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data

Cocaine is a type of drug that functions to increase the availability of the neurotransmitter dopamine in the brain. However, cocaine dependence or abuse is highly related to an increased risk of psychiatric disorders and deficits in cognitive performance, attention, and decision-making abilities. Given the chronic and persistent features of drug addiction, the progression of abstaining from cocaine often evolves across several states, such as addiction to, moderate dependence on, and swearing off cocaine. Hidden Markov models (HMMs) are well suited to the characterization of longitudinal data in terms of a set of unobservable states, and have increasingly been used to uncover the dynamic heterogeneity in progressive diseases or activities. However, the existence of outliers or influential points may misidentify the hidden states and distort the associated inference. In this study, we develop a Bayesian local influence procedure for HMMs with latent variables in the presence of missing data. The proposed model enables us to investigate the dynamic heterogeneity of multivariate longitudinal data, reveal how the interrelationships among latent variables change from one state to another, and simultaneously conduct statistical diagnosis for the given data, model assumptions, and prior inputs. We apply the proposed procedure to analyze a dataset collected by the UCLA center for advancing longitudinal drug abuse research. Several outliers or influential points that seriously influence estimation results are identified and removed. The proposed procedure also discovers the effects of treatment and individuals’ psychological problems on cocaine use behavior and delineates their dynamic changes across the cocaine-addiction states.