Mentoring: Some ethical considerations

To counter confusion about the term ‘mentor’, and address concerns about the scarcity of mentoring, I argue for an “honorific” definition, according to which a mentor is virtuous like a saint or hero. Given the unbounded commitment of mentors, mentoring relationships must be voluntary. In contrast, the role of advisor can be specified, mandated, and monitored. I argue that departments and research groups have a moral responsibility to devise a system of roles and structures to meet graduate students’ and postdoctoral fellows’ needs for information and advice. An earlier version of this paper was presented at a conference sponsored by the National Science Foundation on Mentoring and Research Values: Students as Vital Human Resources, Chicago, March 1995.     

Mentors, advisors and supervisors: Their role in teaching responsible research conduct

Although the terms mentor and thesis advisor (or research supervisor) are often used interchangeably, the responsibilities associated with these roles are distinct, even when they overlap. Neither are role models necessarily mentors, though mentors are role models: good examples are necessary but not sufficient. Mentorship is both a personal and a professional relationship. It has the potential for raising a number of ethical concerns, including issues of accuracy and reliability of the information conveyed, access, stereotyping and tracking of advisees, and the abuse of power. Nevertheless, mentors can be critically important for professional success and are one of a number of elements that affect the responsible conduct of research. In addition, the community as a whole has a responsibility to mentor junior members. An earlier version of this paper was presented at a conference sponsored by the National Science Foundation on Mentoring and Research Values: Students as Vital Human Resources, Chicago, USA, March 1995.     

建立新一代的精神分裂症动物模型

精神分裂症动物模型的建立与发展,是当前探索精神分裂症的神经生物学和认知心理学机制的一个关键课题。在加工-保护理论的基础上所建立起来的感觉运动门控精神分裂症模型一直受到普遍的关注。然而,高级认知活动是如何对感觉门控进行调节的这一核心问题目前还有待进一步的解决。本综述围绕着这个核心问题,系统地解释为什么惊反射前脉冲抑制成为目前最为流行的一种精神分裂症的模型,并介绍恐惧情绪学习对感觉运动门控调节作用的最新研究成果,以及阐述这种自上而下的调节作用如何受到在早期发育阶段的社会隔离的影响     

心理疾病污名形成理论述评

心理疾病污名是加诸于患者身上的耻辱标记,妨碍患者的治疗和康复。心理疾病污名的成因理论包括功能主义和生物文化两个派别,污名的发展模型解释了污名的形成过程,身份威胁模型对污名的作用机制进行了阐述。通过抗议、教育和接触可以有效地减少污名。在中国开展相关研究应注重分析传统文化、心理疾病类型与污名的关系,探讨各种减少污名策略的可行性     

TAS-20 alexithymia in obesity, and its links to personality

We studied the association between alexithymia (20-item Toronto Alexithymia Scale, TAS-20) and obesity, and also assessed the construct validity of the TAS-20 in terms of personality dimensions in obese patients. The TAS-20 and its subscales were analysed for their correlations with the NEO Personality Inventory - Revised (NEO PI-R) in an obese sample of 259 patients. Obesity was associated with higher scores on the TAS-20 than a Swedish reference sample. Obese men furthermore scored higher on Externally Oriented Thinking than the obese women. TAS-20 scores correlated with elevated Neuroticism and lower levels of Extraversion and Openness, in agreement with most previous research, but also somewhat unexpectedly with lower Conscientiousness and for women also with lower Agreeableness. The TAS-20 subscales showed divergent associations with personality variables, largely in accordance with previous findings. The associations were more prominent for the women, and some gender-specific patterns not previously reported were also revealed.     

Community-driven learning activities,creating futures: 30,000 people can't be wrong—Can they?

A major vehicle for the practice of community psychology is through the organization of community-based activities. My colleagues and I have developed many programs for community learning centers, in-school and after school programs, and community technology centers. In the last 10 years, 30,000 people (mostly children) have participated in activities designed for enjoyment and learning, with a view to adding protective factors and reducing negative factors in at-risk communities. Development of these programs for literacy, education, life and work skills, has increasingly followed a community responsive model. Within each program, we created explicit images of future success. That is, people could see themselves being successful where they normally fail: self modeling with feedforward. Data reports show that individuals generalized and maintained their new skills and attitudes, but the sustainability of programs has been variable. Analysis of the variations indicates the importance of program level feedforward that brings the future into the present. The discussion includes consideration of how individual-level and community-level practices can inform each other. Author Note: Aspects of this article have been presented at the 10th Trans-Tasman Community Psychology Conference, Sydney, April 2006, and in an invited address at the 114th annual convention of the American Psychological Association, New Orleans, August 2006. Partial support in the preparation of this paper was provided by mutliple grants from the US Department of Education, although no endorsement is implied.     

Interpersonal Attachment and Patterns of Ideological Belief

We examine whether two general dimensions of sociopolitical belief—right-wing authoritarianism (RWA) and social dominance orientation (SDO)—are rooted in insecure psychological attachment. Based on an undergraduate sample ( N =  255), we model the relations among attachment styles, general worldviews, RWA, and SDO. A structural equation model indicated that anxious attachment led to RWA but not SDO and that this effect was mediated by the belief that the world is a dangerous place. In contrast, avoidant attachment led to SDO but not RWA, and this effect was mediated by the belief that the world is an uncaring, competitive jungle in which people are motivated to maximize personal utility. We discuss the implications of these findings for the nature and origins of political conservatism.     

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models, unfolding models, latent class models with random effects, multilevel latent class models, models with log-normal latent variables, and zero-inflated Poisson models with random effects. Some of the ideas are illustrated by estimating an unfolding model for attitudes to female work participation. We wish to thank The Research Council of Norway for a grant supporting our collaboration.     

Doubly Robust-Type Estimation for Covariate Adjustment in Latent Variable Modeling

Due to the difficulty in achieving a random assignment, a quasi-experimental or observational study design is frequently used in the behavioral and social sciences. If a nonrandom assignment depends on the covariates, multiple group structural equation modeling, that includes the regression function of the dependent variables on the covariates that determine the assignment, can provide reasonable estimates under the condition of correct specification of the regression function. However, it is usually difficult to specify the correct regression function because the dimensions of the dependent variables and covariates are typically large. Therefore, the propensity score adjustment methods have been proposed, since they do not require the specification of the regression function and have been applied to several applied studies. However, these methods produce biased estimates if the assignment mechanism is incorrectly specified. In order to make a more robust inference, it would be more useful to develop an estimation method that integrates the regression approach with the propensity score methodology. In this study we propose a doubly robust-type estimation method for marginal multiple group structural equation modeling. This method provides a consistent estimator if either the regression function or the assignment mechanism is correctly specified. A simulation study indicates that the proposed estimation method is more robust than the existing methods. This research was partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Young Scientists (B), 187-30406.     

Multilevel Modeling with Correlated Effects

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized method of moments (GMM) estimation techniques in multilevel modeling, the authors present a series of estimators along a robust to efficient continuum. This continuum depends on the assumptions that the analyst makes regarding the extent of the correlated effects. It is shown that the GMM approach provides an overarching framework that encompasses well-known estimators such as fixed and random effects estimators and also provides more options. These GMM estimators can be expressed as instrumental variable (IV) estimators which enhances their interpretability. Moreover, by exploiting the hierarchical structure of the data, the current technique does not require additional variables unlike traditional IV methods. Further, statistical tests are developed to compare the different estimators. A simulation study examines the finite sample properties of the estimators and tests and confirms the theoretical order of the estimators with respect to their robustness and efficiency. It further shows that not only are regression coefficients biased, but variance components may be severely underestimated in the presence of correlated effects. Empirical standard errors are employed as they are less sensitive to correlated effects when compared to model-based standard errors. An example using student achievement data shows that GMM estimators can be effectively used in a search for the most efficient among unbiased estimators. This research was supported by the National Academy of Education/Spencer Foundation and the National Science Foundation, grant number SES-0436274. We thank the editor, associate editor, and referees for detailed feedback that helped improve the paper.