Early Change Trajectories in Cognitive-Behavioral Therapy for Binge-Eating Disorder

Rapid response is considered the most well-established outcome predictor across treatments of binge-eating disorder (BED), including cognitive-behavioral therapy (CBT). This study sought to identify latent trajectories of early change in CBT and compare them to common rapid response classifications. In a multicenter randomized trial, 86 adults with BED (DSM-IV) or subsyndromal BED provided weekly self-reports of binge eating over the first 4 weeks of CBT, which were analyzed to predict binge eating, depression, and body mass index at posttreatment, 6-, and 18-month follow-up. Using latent growth mixture modeling, three patterns of early change—including moderate and low decreasing—as well as low stable binge eating were identified, which significantly predicted binge-eating remission at 6-month follow-up. Other classifications of rapid response based on Receiver Operating Characteristics curve analyses or on the literature (≥ 10% reduction in binge eating at week 1, ≥ 70% reduction in binge eating at week 4) only predicted posttreatment remission or overall depression, respectively. Latent change trajectories, but not other rapid response classifications, predicted binge-eating frequency over time. A fine-grained analysis of change over the first 4 weeks of CBT for BED revealed different trajectories of early change in binge eating that led to an improved prediction of binge-eating outcome, compared to that of common rapid response classifications. Thorough monitoring of early change trajectories during treatment may have clinical utility.     

Against all odds – is a more differentiated view of personality development in emerging adulthood needed? The case of young apprentices

Personality development in emerging adults who do not attend college after high school has been largely overlooked so far. In this study, we investigated personality development in emerging German adults (N_T1 = 1,886, M_ageT1 = 18.01 years, 29% female) undergoing vocational education and training (VET). The trainees were assessed at the start of VET, 1.5 years later, and another 1.5 years after that, just before graduation. Longitudinal latent change score analyses were applied. Bivariate analyses investigated life satisfaction and job strain as social and work‐related aspects that are potentially reciprocally related to personality development. Mean‐level personality changes included increases in neuroticism and decreases in agreeableness and conscientiousness in the first interval. In the second interval, neuroticism decreased and conscientiousness increased. Simultaneously, trainees reported a gradual decrease in extraversion and openness across the 3‐year time span. Personality, especially agreeableness and conscientiousness, emerged as a stronger predictor of changes in job strain and life satisfaction than vice versa. For example, more agreeable and more conscientious trainees subsequently showed increases in life satisfaction. Trainees reporting higher job strain subsequently showed decreases in agreeableness. Trajectories of personality development partly support the maturity principle that has been established in many college student samples.     

Prototypes of Faith: Findings with the Faith Q‐Sort

Defining religion and finding ways to assess it in individual lives has long challenged psychologists of religion. At first, open‐ended questionnaires were used, but with the advent of modern statistical methods, a succession of religiosity scales was developed. But these usually brief scales were typically based on the preconceptions of their authors, who were overwhelmingly Protestant Christian and often conservative, much as were those who completed them. To provide a more adequate way of assessing “faith,” a term here encompassing both religious and nonreligious attitudes, a new assessment device was developed that incorporates the singular advantages of Q methodology. The Faith Q‐Sort consists of 101 statements that respondents sort on a nine‐category continuum, indicating the degree to which each statement describes himself or herself. Factor analysis based on correlations of the sorts rather than individual items yielded, for the initial group of participants, three major prototypes and five minor ones, accounting for 67 percent of the variance. Of the 42 participants, 31 proved to be exemplars of one or another of the eight prototypes. Subsequent explorations illustrate the wealth of possibilities the FQS offers, both as a research instrument and a counseling tool.     

A General Approach for Fitting Pure Exploratory Bifactor Models

This article proposes a procedure for fitting a pure exploratory bifactor solution in which the general factor is orthogonal to the group factors, but the loadings on the group factors can satisfy any orthogonal or oblique rotation criterion. The proposal combines orthogonal Procrustes rotations with analytical rotations and consists of a sequence of four steps. The basic input is a semispecified target matrix that can be (a) defined by the user, (b) obtained by using Schmid-Leiman orthogonalization, or (c) automatically built from a conventional unrestricted solution based on a prescribed number of factors. The relevance of the proposal and its advantages over existing procedures is discussed and assessed via simulation. Its feasibility in practice is illustrated with two empirical examples in the personality domain.     

A Limited Information Estimator for Dynamic Factor Models

Structural equation modeling (SEM) is an increasingly popular method for examining multivariate time series data. As in cross-sectional data analysis, structural misspecification of time series models is inevitable, and further complicated by the fact that errors occur in both the time series and measurement components of the model. In this article, we introduce a new limited information estimator and local fit diagnostic for dynamic factor models within the SEM framework. We demonstrate the implementation of this estimator and examine its performance under both correct and incorrect model specifications via a small simulation study. The estimates from this estimator are compared to those from the most common system-wide estimators and are found to be more robust to the structural misspecifications considered.     

Contrast effects in judgmental forecasting when assessing the implications of worst and best case scenarios

Two experiments investigated whether individuals' forecasts of the demand for products and a stock market index assuming a best or worst case scenario depend on whether they have seen a single scenario in isolation or whether they have also seen a second scenario presenting an opposing view of the future. Normatively, scenarios should be regarded as belonging to different plausible future worlds so that the judged implications of one scenario should not be affected when other scenarios are available. However, the results provided evidence of contrast effects in that the presentation of a second “opposite” scenario led to more extreme forecasts consistent with the polarity of the original scenario. In addition, people were more confident about their forecasts based on a given scenario when two opposing scenarios were available. We examine the implications of our findings for the elicitation of point forecasts and judgmental prediction intervals and the biases that are often associated with them.     

Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest

In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.     

Utility of the REDFLAGS Model for Supporting Community College Students’ Mental Health: Implications for Counselors

The counseling literature is lacking in research on supporting the mental health needs of the growing community college student population. A number of past investigators have demonstrated the utility of mental health literacy for supporting college students’ mental health on 4‐year universities. The present researchers examined the validity of the REDFLAGS model (a theoretical model for promoting mental health literacy) with a national stratified random sample (N = 640, stratified by age, gender, and ethnicity) of community college students. Collectively, the results of the confirmatory factor analysis, hierarchical logistic regression, and factorial analysis of variance supported the use of the model with community college students. Implications for enhancing counseling practice as well as directions for future research are provided.     

基于多层验证性因素分析的各种信度系数方法

近年来,心理学研究的复现性受到广泛关注,许多实证研究难以重复验证,信度较低。大量研究使用多层技术,但只报告整体信度,导致研究可重复危机。基于各种信度系数和验证性因素分析的理论,以二层模型为例,总结多层信度计算方法,通过文献综述检索应用情况,并用MPLUS进行实例演示,最后讨论单层信度估计存在的偏差及分层估计的好处。总之,对多层数据进行分层信度估计是很有必要的,可消除因测量工具缺乏信度而导致的研究不可重复。