儿童早期"心理理论"发展研究中的几个基本问题

儿童"心理理论"的发展研究是当今发展心理学中最活跃的领域之一.近年来,该领域的研究重点已逐渐由一般的发展描述,转向关于"心理理论"的缘起与发展机制的研究.由此,有许多密切相关的关于早期"心理理论"发生发展及其评估的基本问题,横亘于研究者面前,迄今仍悬而未决,并引发诸多争议.如何解决这些问题并理顺它们之间的关系,将极大地影响着该领域今后的研究进展.     

佛教"疑伪经"与弥勒信仰--以佛教经录为中心的考察

"疑伪经"是中国佛教经典中所特有的一类经典,它们尽管受到种种鄙视和排斥而难以流传,但是,从佛经目录中可以看出这类经典在特定时期仍然大量存在和流行,有些甚至保存至今.其中,有一部分关于弥勒信仰的疑伪经,是反映弥勒信仰在中国特定历史时期发展的重要资料,从中可以看出弥勒信仰在当时社会中的流传情况.     

国外学校心理学的发展及其启示

本文首先考察了国外学校心理学的发展历史和现状,并对国外学校心理学的发展趋势作出了预测。接着从我国中小学生及大学生的心理健康现状及我回学校心理服务现状两方面分析了建立我国学校心理学的条件。最后,对如何建立建设我国学校心理学提出了建议。     

幼儿心理理论发展的一般认知基础--不同心理理论任务表现的特异性与一致性

本研究试图探究中国幼儿心理理论发展的一般变化趋势,通过探查90位3～5岁幼儿在不同心理理论任务表现的特殊性及内在一致性,结果表明：3～5岁间幼儿的心理理论发生急剧变化;幼儿在各任务上的表现总体上存在某种潜在的一致性;但他们在不同任务上的表现存在较大差异,这表明心理理论表现具有显著的任务特异性。     

亲子互动研究及其进展

亲子互动研究是从父母与儿童互动的角度来研究父母与儿童的交往行为,在近几十年来越来越受到国内外研究者的关注。该文从亲子互动影响因素和亲子互动与儿童心理、行为发展的关系两个方面介绍了亲子互动的有关研究,同时又从有缺陷儿童的亲子互动和父亲在亲子互动中的作用介绍了亲子互动研究的进展。     

峨眉山蒲公传说及其相关问题

峨眉山普贤道场的建立与蒲公传说联系密切。笔者分析认为峨眉山普贤道场的建立不始于蒲公传说,但该传说也包含某种历史性的暗示。     

时间变量对大学新生人格特质的影响

以台湾地区某大学新生,从1998至2003共六届3141人为对象,分析人格改变情形,统计结果发现13项人格特质的赖氏人格量表中达显著差异的有6项,包括社会外向、攻击性、变异性、神经质、自卑感及虚伪性。性别分析达显著差异的共7项,包括活动性、客观性、协调性、攻击性、变异性、自卑感及神经质;男学生显著高于女学生的有活动性及攻击性,女学生显著高于男学生的有客观性、协调性、变异性、自卑感及神经质。结果显示在时间变量中,大学新生的人格的确发生了转变。     

Influence and adjustment goals: sources of cultural differences in ideal affect

Previous studies have found that in American culture high-arousal positive states (HAP) such as excitement are valued more and low-arousal positive states (LAP) such as calm are valued less than they are in Chinese culture. What specific factors account for these differences? The authors predicted that when people and cultures aimed to influence others (i.e., assert personal needs and change others' behaviors to meet those needs), they would value HAP more and LAP less than when they aimed to adjust to others (i.e., suppress personal needs and change their own behaviors to meet others' needs). They test these predictions in 1 survey and 3 experimental studies. The findings suggest that within and across American and Chinese contexts, differences in ideal affect are due to specific interpersonal goals.     

Does a Nation's Religious Composition Affect Generalized Trust? The Role of Religious Heterogeneity and the Percent Religious

Is religion more of an integrative or a divisive force in contemporary societies? We use multilevel analyses of World Values Survey data from 77,409 individuals in 69 countries to examine how both the percent of the population that is religious and the religious heterogeneity of a country are related to generalized social trust, the willingness of individuals to trust “most people.” When we first examine the main effects of the percent religious and religious heterogeneity we find no evidence that either variable is related to trust in the ways predicted by major theories. However, the combination of these two variables has a huge negative relationship with trust. Countries that are both highly religious and religiously heterogeneous (diverse) have, on average, levels of trust that are only half the average levels of countries with other combinations of these two variables. The results have important implications for understanding the role of religion in modern societies.     

Robust Methods for Moderation Analysis with a Two-Level Regression Model

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.