森田疗法与认知行为疗法的比较分析

规律是客观的,而规则具有主观性,虽然两者本质上不同,但他们又是相关的。从口腔临床医学规则的制定过程来看,我们不难得出结论:口腔临床医学规则的制定要遵循临床医学的一般规律,突出口腔临床医学的特点,并受到我国经济、文化、政治等因素的影响,且随着这些因素的改变而改变,以适应新的环境条件。     

People accounting: Social category-based choice

This paper presents people accounting—a hypothesis that describes how a simple numerical imbalance in representation along nominal social category lines can affect people’s choice of candidates in highly competitive situations (e.g., awards, jobs, etc.). For example, two scholarship finalists from California and New York may be equally qualified, but the award-winning chance for the California candidate will drop precipitously if 8 of the past 10 winners were from California. Studies 1-3 illustrate this effect. Study 4 links people accounting to intergroup fairness concerns and suggests that people accounting is more likely to occur when the category dimension is meaningful (e.g., Stanford/Princeton) than when it is not (e.g., left/right-handedness). Study 5 shows that candidates from overrepresented categories (e.g., “Californians”) must achieve higher minimum standards in order to be selected. The implication is that highly competitive decisions are often influenced by headcounts along mundane social category lines.     

Regulatory focus and investment decisions in small groups

Regulatory Focus Theory was applied to small interactive groups. Based on previous research, it was expected that groups with a promotion focus would discuss gain-relevant information, whereas groups with a prevention focus would be concerned with potential losses. Furthermore, promotion groups were expected to make riskier decisions than prevention groups. Regulatory focus was manipulated by rewarding good or penalizing poor group performance on a preliminary task. Subsequently, three-person groups discussed several investment funds and made a consensual investment decision. Results supported the hypotheses and suggested that regulatory focus requires time to exert its influence in groups.     

材料规则难度对内隐与外显协同学习的影响

选取两种规则难度的人工语法字母串.采用强分离的实验程序,探索了材料规则难度对内隐学习、内隐与外显的协同学习的影响.结果显示: (1)规则难度较大的限定状态人工语法学习中,内隐学习成绩显著好于外显学习;而在难度较小的双条件语法学习中,外显学习显著好于内隐学习. (2)在两种规则难度的材料学习中,内隐与外显的协同学习成绩均好于单独的内隐或者外显学习,具有优势效应. (3)内隐学习获得的规则知识具有可迁移性.     

Distortion of probability and outcome information in risky decisions

Substantial evidence indicates that information is distorted during decision making, but very few studies have assessed the distortion of probability and outcome information in risky decisions. In two studies involving six binary decisions (e.g., banning blood donations from people who have visited England, because of “mad cow disease”), student and nonstudent participants distorted their evaluations of probability and outcome information in the direction of their preferred decision alternative and used these biased evaluations to update their preferences. Participants also evaluated the utilities of possible outcomes more positively when the outcomes could follow only from the preferred alternative and more negatively when they could follow only from the competing alternative. Such circular reasoning is antithetical to the normative consequentialist principles underlying decision analysis. Presenting numerical information as precise values or as ranges of values did not significantly affect information distortion, apparently because the manipulation did not affect perceived ambiguity as intended.     

Short-term gains, long-term pains: How cues about state aid learning in dynamic environments

Successful investors seeking returns, animals foraging for food, and pilots controlling aircraft all must take into account how their current decisions will impact their future standing. One challenge facing decision makers is that options that appear attractive in the short-term may not turn out best in the long run. In this paper, we explore human learning in a dynamic decision making task which places short- and long-term rewards in conflict. Our goal in these studies was to evaluate how people’s mental representation of a task affects their ability to discover an optimal decision strategy. We find that perceptual cues that readily align with the underlying state of the task environment help people overcome the impulsive appeal of short-term rewards. Our experimental manipulations, predictions, and analyses are motivated by current work in reinforcement learning which details how learners value delayed outcomes in sequential tasks and the importance that “state” identification plays in effective learning.     

Loyalty and Creativity in a Disciplinary Organization

The relationship between loyalty to rules and the creativity that attempts to improve those same rules was examined among Norwegian army officers deployed in international operations. Today's army officers are faced with rapidly changing work conditions and unpredictable enemies, both of which challenge and outdate rules and routines. They thus may experience that they are either guided by too few or inadequate rules, or by many rules that need to be constantly updated. Assuming that following rules is advantageous to officers, then, contrary to classical theory, it was hypothesized that officers scoring both low and high on loyalty to rules would score high on creativity. Hierarchical regression analyses revealed a significant U‐shaped relationship between loyalty to rules and creativity.     

Cognitive models of choice: comparing decision field theory to the proportional difference model

People often face preferential decisions under risk. To further our understanding of the cognitive processes underlying these preferential choices, two prominent cognitive models, decision field theory (DFT; Busemeyer & Townsend, 1993 ) and the proportional difference model (PD; González-Vallejo, 2002 ), were rigorously tested against each other. In two consecutive experiments, the participants repeatedly had to choose between monetary gambles. The first experiment provided the reference to estimate the models' free parameters. From these estimations, new gamble pairs were generated for the second experiment such that the two models made maximally divergent predictions. In the first experiment, both models explained the data equally well. However, in the second generalization experiment, the participants' choices were much closer to the predictions of DFT. The results indicate that the stochastic process assumed by DFT, in which evidence in favor of or against each option accumulates over time, described people's choice behavior better than the trade-offs between proportional differences assumed by PD.