Treating a Chronically Depressed Adolescent Female Using the Cognitive Behavioral Analysis System of Psychotherapy: A Case Study

A case is presented of an adolescent female with double depression who was treated using the Cognitive Behavioral Analysis System of Psychotherapy (CBASP). CBASP is designed to teach a social problem-solving procedure called Situational Analysis (SA). Generalized treatment effects were measured through monitoring of diagnostic status, two administrations of the Minnesota Multiphasic Personality Inventory-Adolescent, weekly administrations of the Child Depression Inventory, and acquisition performance ratings on the SA task. The results showed that CBASP appeared to be an effective treatment. The double depressive disorder remitted, and the patient learned to identify behavioral consequences as well as target and attain her interpersonal goals. CBASP can be effective for adolescents, although modifications of the adult form of the therapy may be necessary.     

The Beck Anxiety Inventory in Older Adults With Generalized Anxiety Disorder

The authors investigated the psychometric properties of the Beck Anxiety Inventory (BAI) in a sample of 75 older generalized anxiety disorder (GAD) patients and a comparison group of 32 older adults without significant psychopathology. Internal consistency was above .80, and the BAI showed evidence of convergent validity in both groups. Evidence for discriminant validity with respect to measures of depression was weaker. Two items, fearing the worst and nervousness, correctly distinguished 86.5% of patients with GAD and 93.8% of the normal controls. Medical comorbidity was associated with somatic but not cognitive anxiety symptoms in the normal older sample. Overall, results indicate the limitations of the BAI in assessing anxiety symptoms in older adults and suggest the need for use of an instrument focusing on cognitive aspects of anxiety.     

Bayesian estimation and testing of structural equation models

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, for example, output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters underidentified models, as we illustrate on a simple errors-in-variables model.We thank David Spiegelhalter for suggesting applying the Gibbs sampler to structural equation models to the first author at a 1994 workshop in Wiesbaden. We thank Ulf Böckenholt, Chris Meek, Marijtje van Duijn, Clark Glymour, Ivo Molenaar, Steve Klepper, Thomas Richardson, Teddy Seidenfeld, and Tom Snijders for helpful discussions, mathematical advice, and critiques of earlier drafts of this paper.     

Aggregate item response analysis

A stochastic postulate is given for the multiple-item, successive-intervals scaling of populations. The logistic equivalent of this postulate provides an aggregate item response model in which a unidimensional submodel may be nested. This reduction provides a subtractive conjoint measurement of several items and stimuli on the same latent scale. Generalized-least-squares methods are used to estimate and test the multiple-item model, and its unidimensional reduction, on aggregate survey responses. The entire procedure is illustrated with an analysis of semantic-differential attitude data. This analysis exhibits an item selection procedure that is applicable to various social constructs.The authors dedicate this paper to the memory and contributions of Clyde Coombs.The programming and data analyses for the present paper were carried out by José Ventura of the Department of Industrial and Systems Engineering, and Jerry Meiten of the Department of Statistics, University of Florida.The study was also supported by the College of Business Administration, University of Florida, and the Faculty of Social Sciences, Hebrew University of Jerusalem.     

Model comparison of nonlinear structural equation models with fixed covariates

Recently, it has been recognized that the commonly used linear structural equation model is inadequate to deal with some complicated substantive theory. A new nonlinear structural equation model with fixed covariates is proposed in this article. A procedure, which utilizes the powerful path sampling for computing the Bayes factor, is developed for model comparison. In the implementation, the required random observations are simulated via a hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm. It is shown that the proposed procedure is efficient and flexible; and it produces Bayesian estimates of the parameters, latent variables, and their highest posterior density intervals as by-products. Empirical performances of the proposed procedure such as sensitivity to prior inputs are illustrated by a simulation study and a real example.This research is fully supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project No. CUHK 4346/01H). The authors are thankful to the Editor, the Associate Editor, and anonymous reviewers for valuable comments which improve the paper significantly, and grateful to ICPSR and the relevant funding agency for allowing use of the data in the example. The assistance of Michael K.H. Leung and Esther L.S. Tam is gratefully acknowledged.     

Rural Neighborhoods and Child Aggression

Structural equation modeling with latent variables was used to evaluate the direct and mediated effects of a neighborhood risk factor (negative teen behaviors) on the parent-report aggressive behavior of 213 students in grades 3 through 5 attending a school in a low-income, rural community. Contagion and social control hypotheses were examined as well as hypotheses about whether the neighborhood served as a microsystem or exosystem for rural pre-adolescents. Analyses took into account the clustering of students and ordinal nature of the data. Findings suggest that rural neighborhoods may operate as both a microsystem and exosystem for children, with direct contagion effects on their aggressive behaviors as well as indirect social control effects through parenting practices. Direct effects on aggression were also found for parenting practices and child reports of friends’ negative behaviors. Pre-adolescence may be a transitional stage, when influences of the neighborhood on child behavior begin to compete with influences of caregivers. Findings can inform the timing and targets of violence prevention in rural communities.     

拓展后的GGUM在LOT-R中的适用性分析

该研究对拓广等级展开模型（GGUM）进行了拓展,取消GGUM中关于主观反应类别阈限对称的假设,并将拓展之后的新模型和GGUM同时用于生活取向测验修订版（LOT-R）的被试反应数据分析,采用新编的单项目、两项目对和三项目组χ2/df计算程序计算和比较新模型和GGUM在该测验数据上的拟合差异。结果显示,新编程序与Stark等人开发的MODFIT程序具有同样的有效性,新模型在这些指标上的值显著小于GGUM,并且均小于3,表明新模型较GGUM更适合于分析LOT-R的反应数据,说明新模型更适用于分析具有多个评定等级的人格测验数据。根据以上结果,该研究认为,未来人格测验的数据分析应该使用没有对主观反应类别阈限进行对称限定的新拓展的模型更合理。     

新生市民主动发展倾向对城市生活适应性的影响:社会支持的中介效应

为探究主动发展倾向和社会支持对新生市民城市生活适应性的作用机制,本研究构建了结构方程模型.采用两个自编量表和一个现成量表,运用两阶段抽样调查法,在作为统筹城乡发展试验区的重庆市范围内,对已经取得城镇户口的新生市民进行问卷调查,获得有效样本322人.对采集的数据运用统计分析软件SPSS17.0和AMOS18.0进行数据分析和模型检验.结果表明,城市化新生市民的主动发展倾向和社会支持均对新生市民的城市生活适应具有显著影响,其中,社会支持在主动发展倾向对城市生活适应影响中具有部分中介作用.     

Knowing what to look for: Voice affects face race judgements

The study examined the effect that auditory information (speaker language/accent: Japanese or French) had on the processing of visual information (the speaker's race: Asian or Caucasian) in two forced-choice tasks: Classification and perceptual judgement on animated talking characters. Two (male and female) sets of facial morphs were constructed such that a 3-D head of Caucasian appearance was gradually morphed (in 11 steps) into one of Asian appearance. Each facial morph was animated in association with spoken French/Japanese or English with a French/Japanese accent. To examine the auditory effect, each animation was played with or without sound. Experiment 1 used an Asian or Caucasian classification task. Results showed that faces heard in conjunction with Japanese or a Japanese accent were more likely to be classified as Asian compared to those presented without sound. Experiment 2 used a same or different judgement task. Results showed that accuracy was improved by hearing a Japanese accent compared to without sound. These results were discussed in terms of the voice information acting as a cue to assist in organizing and attending to face features.     

Are Past Normative Behaviors Predictive of Future Behavioral Intentions?

We acknowledge the limitations in measures of moral reasoning and pursue an alternative technique by investigating past behaviors as they relate to present behavioral intentions. Our purpose is to evaluate the merits of patterned normative behavior for predicting present and future, morally relevant outcomes. Participants (N = 177) completed a policy capturing experimental design responding to questions that orthogonally varied the situational nature of the decision context. Results indicate that past normative behaviors are significantly and directly related to ethical behavioral intentions. Moreover, they moderate the relationships between situational factors and intended outcomes as well as moral reasoning and intended outcomes.