Tokenism also works with groups as tokens: The impact of group openness and group qualification on reactions to membership in a low-status group.

Two experiments tested whether the tokenism effect would also emerge when groups as a whole rather than individual group members are denied access into a high-status group. In total, 317 pupils were led to believe that their class was not accepted into a high-status group. The openness of this high-status group toward other groups (open, minimally open, and closed) and the qualification of the own class (low, high) were manipulated. In both studies, pupils of a highly qualified class confronted with a closed high-status group differed from all other conditions by preferring nonnormative action to normative action. These results indicate that tokenism is a very robust phenomenon that occurs even when groups strongly expected to join the high-status group. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Validation of diagnostic measures based on latent class analysis: A step forward in response bias research.

The use of criterion group validation is hindered by the difficulty of classifying individuals on latent constructs. Latent class analysis (LCA) is a method that can be used for determining the validity of scales meant to assess latent constructs without such a priori classifications. The authors used this method to examine the ability of the L scale of the MMPI-2 (J. N. Butcher et al., 2001), the Impression Management scale of the Balanced Inventory of Desirable Responding (D. L. Paulhus, 1991), and the Endorsement of Excessive Virtue scale of the Psychological Screening Inventory (R. I. Lanyon, 1970) to identify favorable response bias (misrepresentation) in a situation where no criterion for individual classifications existed. Results suggest that LCA can be used as a method for assessing the validity of scales that measure unobservable conditions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Understanding the heterogeneity of BPD symptoms through latent class analysis: Initial results and clinical correlates among inner-city substance users.

The current study investigated the heterogeneity of borderline personality disorder (BPD) symptoms in a sample of 382 inner-city, predominantly African American male substance users through the use of latent class analysis. A 4-class model was statistically preferred, with 1 class interpreted to be a baseline class, 1 class interpreted to be a high-BPD class, and 2 classes interpreted as intermediate classes. As a secondary goal, we examined the resulting BPD classes with respect to relevant clinical correlates, including temperamental vulnerabilities (affective instability, impulsivity, and interpersonal instability), childhood emotional abuse, drug choice, and co-occurring mood and anxiety disorders. The high-BPD class evidenced the highest levels of the temperamental vulnerabilities and environmental stressors, the baseline class evidenced the lowest levels, and the 2 intermediate classes fell in between. In addition, the high-BPD class had a higher probability of cocaine and alcohol dependence, as well as mood and anxiety disorders, than did the baseline class. Rates of alcohol use and mood disorders for the intermediate classes fell in between the high-BPD and the baseline classes. Results are discussed in relation to the current diagnostic conceptualization of BPD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prevalence estimation and validation of new instruments in psychiatric research: An application of latent class analysis and sensitivity analysis.

Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to estimate sensitivity (Se) and specificity (Sp) of each measure. With simple algebraic sensitivity analysis (SA), one uses researcher-specified RS misclassification rates to correct prevalence and test characteristic estimates and can succinctly summarize a range of scenarios with Monte Carlo simulation. The authors applied LCA to a validation study of a new substance use disorder (SUD) screener and a larger prevalence study. With a traditional validation study analysis in which an error-free RS (Structured Clinical Interview for DSM–IV Axis I Disorders [SCID]; M. H. First, R. L. Spitzer, M. Gibbon, & J. Williams, 1990) is assumed, the authors estimated the screener had 86% Se and 75% Sp. Validation study estimates from LCA were 91% Se, 81% Sp (screener), 73% Se, and 98% Sp (SCID). SA in the prevalence study suggested the prevalence of SUD was underestimated by 22% because SCID was assumed to be error-free. LCA and SA can assist investigators in relaxing the unrealistic assumption of perfect RSs in reporting prevalence and validation study results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A latent class analysis of maternal depressive symptoms over 12 years and offspring adjustment in adolescence.

The authors used data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development to model patterns of maternal depressive symptoms, from the period of infants’ age 1 month to adolescence (age 12 years), and then examined adolescent adjustment at age 15 years as a function of the course and severity of maternal symptoms. The authors identified 5 latent classes of symptoms in 1,357 women, while also taking into account sociodemographic measures: never depressed, stable subclinical, early decreasing, moderately elevated, and chronic. Women with few symptoms were more likely to be married, better educated, and in better physical health than were women with more elevated symptoms. At age 15 years, adolescents whose mothers were in the chronic, elevated, and stable subclinical latent classes reported more internalizing and externalizing problems and acknowledged engaging in more risky behavior than did children of never depressed mothers. Latent class differences in self-reported loneliness and dysphoria were also found. Discussion focuses on adolescent adjustment, especially among offspring whose mothers reported stable symptoms of depression across their childhoods. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Screening for disruptive behavior syndromes in children: The application of latent class analyses and implications for prevention programs.

The predictive accuracy of classifying children at risk for disruptive disorders through latent class analyses (LCA) was evaluated. Child Behavior Checklist/4-18 (T. M. Achenbach, 1991) items, reflecting symptoms of Diagnostic and Statistical Manual of Mental Disorders (4th ed., American Psychiatric Association, 1994) defined disruptive disorders, alone and in combination with other child and familial risk factors, were used to predict children's risk for disruptive disorder. Predictive accuracy reached a positive predictive value of 69%. Children incorrectly classified (false positive and false negative) were compared with correctly classified children (true positive and true negative) on risk factors in the family context to test whether the screening procedure could be improved through a multiple-gating procedure. The differences in familial context factors between these children were limited, and no clear indications were found on how to use familial context factors to improve the screening procedure after the initial classification by LCA. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A latent growth examination of fear development in infancy: Contributions of maternal depression and the risk for toddler anxiety.

Growth modeling was used to examine the developmental trajectory of infant temperamental fear with maternal fear and depressive symptoms as predictors of infant fearfulness and change in infant fear predicting toddler anxiety symptoms. In Study 1, a sample of 158 mothers reported their own depressive symptoms and fear when their children were 4 months of age and infant fearfulness at 4, 6, 8, 10, and 12 months. Maternal symptoms of depression predicted steeper increases in infant fearfulness over time (z = 2.06, p z = 2.32, p z = 1.88, p z = 2.30, p z = 2.08, p