Developing a Community Science Research Agenda for Building Community Capacity for Effective Preventive Interventions

Research has shown that prevention programming can improve community health when implemented well. There are examples of successful prevention in local communities, however many continue to face significant challenges, demonstrating a gap between science and practice. Common strategies within the United States to address this gap are available (e.g., trainings), but lack outcomes. Building community capacity to implement high quality prevention can help communities achieve positive health outcomes, thereby narrowing the gap. While there is ample research on the efficacy of evidence-based programs, there is little on how to improve community capacity to improve prevention quality. In order to narrow the gap, a new model of research—one based in Community Science—is suggested that improves the latest theoretical understanding of community capacity and evaluates technologies designed to enhance it. In this article, we describe this model and suggest a research agenda that can lead to improved outcomes at the local level.     

Summoning White Bears or Letting Them Free: The Influence of the Content of Control Instructions on Target Thought Frequency

In the clinical literature, thought suppression is considered to play a role in the development of intrusion-related psychiatric syndromes, such as obsessive-compulsive disorder, acute or posttraumatic stress disorder, phobias, and addiction. This assumption goes back to a study by D. M. Wegner, D. J. Schneider, S. R. Carter, and T. L. White (1987) in which participants were asked to suppress thoughts of a white bear, an assignment that proved to be nearly impossible to complete. The present two studies sought to explore the influence of the content of control instructions on intrusion frequency in thought suppression experiments. Notably, during nonsuppression (i.e., control) periods, participants can either be instructed to think about white bears (i.e., expression instruction), or to think of anything including white bears (i.e., liberal instruction). Results indicated that expression instructions resulted in an increased number of target thoughts, while liberal instructions did not. Implications for the interpretation of thought suppression findings are discussed.     

Self-reported personality disorder in the children in the community sample: convergent and prospective validity in late adolescence and adulthood

Approximately 800 youths from the Children in the Community Study (Cohen & Cohen, 1996) have been assessed prospectively for over 20 years to study personality disorders (PDs) in adolescents and young adults. In this article we evaluate the Children in the Community Self-Report (CIC-SR) Scales, which were designed to assess DSM-IV PDs using self-reported prospective data from this longitudinal sample. To evaluate convergent validity, we assessed concordance between the CIC-SR Scales and the Structured Clinical Interview for DSM-IV Personality Disorders (SCID-II; First, Gibbon, Spitzer, Williams, & Benjamin, 1995) in 644 participants at mean age 33. To assess predictive validity, we used CIC-SR Scales at mean age 22 to predict subsequent CIC-SR and SCID-II Personality Questionnaire scores at mean age 33. In these analyses the CIC-SR Scales matched or exceeded benchmarks established in previous comparisons between self-report instruments and structured clinical interviews. Unlike other self-report scales, the CIC-SR did not appear to overestimate diagnoses when compared with SCID-II clinical diagnoses.     

WAIS digit span-based indicators of malingered neurocognitive dysfunction: classification accuracy in traumatic brain injury

The present study determined specificity and sensitivity to malingered neurocognitive dysfunction (MND) in traumatic brain injury (TBI) for several Wechsler Adult Intelligence Scale (WAIS) Digit Span scores. TBI patients (n = 344) were categorized into one of five groups: no incentive, incentive only, suspect, probable MND, and definite MND. Performance of 1,063 nonincentive patients (e.g., cerebrovascular accident, memory disorder) was also examined. Digit Span scores included reliable digit span, maximum span forward both trials correct, maximum span forward, combined maximum forward and backward span, Digit Span scaled score, maximum span backward both trials correct, and maximum span backward. In TBI, sensitivity to MND ranged from 15% to greater than 30% at specificities of 92% to 98%. Patient groups with documented brain pathology had higher false-positive error rates. These results replicate previous known-groups malingering studies and provide valuable data supporting the WAIS Digit Span scores in detection and diagnosis of malingering.     

An introduction to Bayesian hierarchical models with an application in the theory of signal detection

Although many nonlinear models of cognition have been proposed in the past 50 years, there has been little consideration of corresponding statistical techniques for their analysis. In analyses with nonlinear models, unmodeled variability from the selection of items or participants may lead to asymptotically biased estimation. This asymptotic bias, in turn, renders inference problematic. We show, for example, that a signal detection analysis of recognition memory data leads to asymptotic underestimation of sensitivity. To eliminate asymptotic bias, we advocate hierarchical models in which participant variability, item variability, and measurement error are modeled simultaneously. By accounting for multiple sources of variability, hierarchical models yield consistent and accurate estimates of participant and item effects in recognition memory. This article is written in tutorial format; we provide an introduction to Bayesian statistics, hierarchical modeling, and Markov chain Monte Carlo computational techniques.     

Omnibus hypothesis testing in dominance-based ordinal multiple regression

Often quantitative data in the social sciences have only ordinal justification. Problems of interpretation can arise when least squares multiple regression (LSMR) is used with ordinal data. Two ordinal alternatives are discussed, dominance-based ordinal multiple regression (DOMR) and proportional odds multiple regression. The Q2 statistic is introduced for testing the omnibus null hypothesis in DOMR. A simulation study is discussed that examines the actual Type I error rate and power of Q2 in comparison to the LSMR omnibus F test under normality and non-normality. Results suggest that Q2 has favorable sampling properties as long as the sample size-to-predictors ratio is not too small, and Q2 can be a good alternative to the omnibus F test when the response variable is non-normal.     

Category learning and multiple memory systems

Categorization is a vitally important skill that people use every day. Early theories of category learning assumed a single learning system, but recent evidence suggests that human category learning may depend on many of the major memory systems that have been hypothesized by memory researchers. As different memory systems flourish under different conditions, an understanding of how categorization uses available memory systems will improve our understanding of a basic human skill, lead to better insights into the cognitive changes that result from a variety of neurological disorders, and suggest improvements in training procedures for complex categorization tasks.     

Using the score method to construct asymmetric confidence intervals: An SAS program for content validation in scale development

Expert review sessions are often conducted to determine the content validity of scale items. The accurate quantification of content validity is usually limited by a relatively small number of experts as well as by a small number of rating categories. These factors, combined with the bounded and discrete nature of rating scale categories, hinder use of traditional methods for computing standard errors and confidence intervals. Using an application of the score method, researchers can construct an asymmetric interval that is better suited for these situations. SAS code is provided to automate the computations, and a discussion of two methods for using the obtained results for content validation decisionmaking follows.