Evaluating advisors: A policy‐capturing study under conditions of complete and missing information

Decision‐makers' relative preferences for various advisor characteristics were investigated in two multilevel policy‐capturing studies. The characteristics under consideration were: advisor expertise, advisor confidence, advisor intentions, and whether that advisor was the sole available source of advice. In Study 1, decision‐makers had access to all relevant information about the advisors. In contrast, some relevant information about the advisors was systematically made unavailable in Study 2, which allowed an investigation of the effect of missing information on decision‐makers' evaluations of advisors. Results from both studies indicated that advisor expertise and intentions were most important in promoting decision‐makers' positive evaluations of advisors, that this effect was even more pronounced under conditions of missing information, and that advisor expertise and intentions also interacted synergistically. Given that expertise and good intentions are determinants of an advisor's trustworthiness, the results highlight the interpersonal nature of advice giving and taking. Copyright © 2009 John Wiley & Sons, Ltd.     

When forewarning backfires: Paradoxical effects of elaborating social feedback on entrapment in a losing course of action

Entrapment occurs if people persist with losing courses of action. In two experiments, we show how elaborating social feedback (i.e., premature praise or forewarning regarding the chosen course of action) can have paradoxical effects on entrapment. The participants acted as head of a translation department and had to choose one out of four possible translation strategies for their employees. After choosing, they read four arguments (presumably written by former participants) which were either all in favor of the strategy chosen, all against it, or mixed. Half of the participants only read these arguments, whereas the other half elaborated on them by providing written comments (Experiment 1). The results showed that elaborating on other persons' arguments led to stronger entrapment, independently of whether the arguments were positive or negative. This pattern was due to biased argument processing: Whereas confirming thoughts were generated for positive arguments, negative arguments were refuted. Experiment 2 confirmed that this biased argument processing caused subsequent entrapment. These results indicate that elaborating any type of argument can lead to heightened entrapment and, hence, forewarning can backfire. Copyright © 2009 John Wiley & Sons, Ltd.     

When consensus counts: Exploring the impact of consensus claims in advertising

Consensus claims are broad declarative statements used in an advertisement purporting that a majority of a certain group of consumers prefer or use the sponsor's product or service. While consensus claims are frequently used by advertisers, little is known about how they operate or their effectiveness. We utilize attribution theory to provide insight about how consensus claims operate, and to investigate the impact of consensus claims on attributions and brand attitudes. Results suggest consensus claims are an effective advertising strategy, but their persuasive impact varies according to the featured social information and the processing motivation of audience members.     

How persuasive messages can influence behavior without awareness

A persuasive message that favors one option in a binary choice can enhance the apparent value of its target by biasing the interpretation of subsequent information. The message installs its target as the initial leader in preference and lets the predecisional distortion of information defend that leadership position. An experiment that contrasts showing TV commercials before and after objective product information demonstrates this process. Ratings of the importance of the commercials to the choice indicate that people are aware of advertising's direct effect on their choice but not of its indirect effect through the biased evaluation of the product information.     

Seven-month-olds detect ordinal numerical relationships within temporal sequences

Previous evidence has shown that 11-month-olds represent ordinal relations between purely numerical values, whereas younger infants require a confluence of numerical and non-numerical cues. In this study, we show that when multiple featural cues (i.e., color and shape) are provided, 7-month-olds detect reversals in the ordinal direction of numerical sequences relying solely on number when non-numerical quantitative cues are controlled. These results provide evidence for the influence of featural information and multiple cue integration on infants’ proneness to detect ordinal numerical information.     

语音信息对中国英语学习者语义加工的影响及其脑机制

本研究采用经典的句尾畸义词诱发N400的ERP实验范式探讨了中国英语学习者在进行英文阅读时语音的影响及其相关脑机制。实验包括两类畸义语句:1.同音畸义:句尾词有畸义,但语音和相应正常语义句尾词相同;2.非同音畸义:句尾词有畸义,且语音和相应正常语义句尾词不同。行为数据显示:在错误率上同音畸义显著地高于非同音畸义。ERP显示:无论在早期(N100)还是晚期(N400)脑电成份上,同音畸义和非同音畸义的ERP振幅都有明显差异。本研究从行为和脑电两个方面一致揭示中国英语学习者阅读英文时受到了语音的影响。     

Maximum Likelihood Methods in Treating Outliers and Symmetrically Heavy-Tailed Distributions for Nonlinear Structural Equation Models with Missing Data

By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the development of robust methods to reduce the influence of outliers and the distributional deviation in the analysis. In this paper we develop a maximum likelihood (ML) approach that is robust to outliers and symmetrically heavy-tailed distributions for analyzing nonlinear SEMs with ignorable missing data. The analytic strategy is to incorporate a general class of distributions into the latent variables and the error measurements in the measurement and structural equations. A Monte Carlo EM (MCEM) algorithm is constructed to obtain the ML estimates, and a path sampling procedure is implemented to compute the observed-data log-likelihood and then the Bayesian information criterion for model comparison. The proposed methodologies are illustrated with simulation studies and an example. The research described herein was fully supported by a grant (CUHK 4243/03H) from the Rearch Grants Council of the Hong Kong Special Administration Region. The authors are thankful to the Editor, the Associate Editor, and anonymous reviewers for valuable comments which improve the paper significantly, and are grateful to ICPSR and the relevant funding agency for allowing the use of their data. Requests for reprints should be sent to S. Y. Lee, Department of Statistics, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.     

多属性决策任务中焦虑型个体的信息加工特点研究

该研究以多属性职业选项为材料,采用计算机化的信息板技术初步考察了焦虑型个体在多属性决策过程中的信息加工特点,结果表明焦虑型个体与非焦虑个体的决策过程有所不同。主要表现在与非焦虑型的决策者相比,焦虑型的被试在决策过程中对职业属性的加工时间更长,加工的信息也更多;在决策前后他们对完成决策任务的信心水平评估都很低,但是在搜索模式上焦虑型的决策者与非焦虑型的决策者没有差别。在研究的讨论部分对焦虑型个体决策过程中信息加工特点的原因进行了分析。     

临床医生如何应对社会发展对医疗的影响

目前我国的网络及教育均有了长足的进步,信息量迅速增加,信息技术得到了充分的发展,人们获取信息的手段更加便捷,信息不对称较以前有了很大的变化,这些都对医学产生了重大的影响。临床医生必须及时认识到这种变化及发展,及时改变自己的学习、思维及医疗行为模式,这样才能根据不同情况做出最适合的医疗决策,才能更好地履行自己的职责。