Longitudinal Test of a Multiple Domain Model of Adolescent Condom Use

A comprehensive multiple domain model (MDM) to understand condom use in adolescents was proposed and tested using structural equation modeling of data at three time points. The proposed model integrates social psychological theory, demographic and personality factors, social environment, and situational/contextual variables. Adolescents who were sexually active at time 2 (6 months after baseline) and time 3 (1 year after time 2) and completed surveys at all three time points were included in the analyses (N = 511). An iterative process of model testing resulted in a structural equation model that provided a good fit to the data (CFI = .92, RMSEA = .04). Models comparing gender and race as moderators also were calculated and supported the generalizability of the model. Results provide support for an MDM that goes beyond traditional social psychological models for a broader understanding of condom use in adolescents. Implications for further theory testing and safer sexual interventions are discussed.     

The Partisan Impact of Congressional Redistricting: The Case of Texas, 2001–2003*

Objective. In this article we assess the partisan effects of five plans proposed by Republican state legislators during Texas' 2003 congressional redistricting. Methods. Using the JudgeIt statistical program developed by Gelman and King (2001) , and data provided by the Texas Legislative Council, we assess the bias, responsiveness, and the probability that the Democratic Party wins each district for each plan. Results. All five Republican plans, including the one enacted, are strongly biased in favor of the Republican Party. Conclusions. Texas' Democratic legislators were wise to use every parliamentary maneuver available to block the enactment of a new congressional map. Beyond affecting the partisan makeup of the Texas delegation, Texas' redistricting has national implications because it adds to the GOP's narrow majority in the U.S. House of Representatives.     

Trends in the Research and Practice of Health Communication Campaigns

A compelling communication tool that can potentially impact health‐related outcomes and indicators across numerous health problems among a diversity of audiences is the health communication campaign. The purpose of the current article is to discuss trends in the research and practice of health communication campaigns. First, we discuss the issue of campaign effects and discuss a framework that encompasses key principles of effective campaigns. Next, we discuss four trends in health communication campaigns: (a) the increased application of marketing principles in campaigns; (b) the greater use of rigorous outcome evaluation designs in campaign research; (c) the increased use of cost effectiveness analysis in campaigns; and (d) the increased use of new media technologies in campaigns. Finally, we conclude the article with thoughts about the future of health communication campaign research and practice in relation to these trends.     

Effects of Mental Imagery on Gambling Behavior

The influence of a brief mental imagery task was examined to determine if imagining engaging in gambling behaviors would satiate the participant on gambling-related reinforcers and subsequently reduce gambling behavior. Thirty-one participants underwent a mental imagery task consisting of either imagining gambling on a slot machine 30 times and placing quarters into a laundry machine 3 times, or imagining gambling on a slot machine 3 times and placing quarters in a laundry machine 30 times. Following the imagery task, participants were allowed to play a real slot machine and stop whenever they wanted to be finished. The results showed that those who imagined playing the slot machine 30 times before actually gambling played significantly fewer trials than those who imagined playing only 3 times. Clinical implications and future directions are discussed.     

A Flexible Count Data Regression Model for Risk Analysis

In many cases, risk and reliability analyses involve estimating the probabilities of discrete events such as hardware failures and occurrences of disease or death. There is often additional information in the form of explanatory variables that can be used to help estimate the likelihood of different numbers of events in the future through the use of an appropriate regression model, such as a generalized linear model. However, existing generalized linear models (GLM) are limited in their ability to handle the types of variance structures often encountered in using count data in risk and reliability analysis. In particular, standard models cannot handle both underdispersed data (variance less than the mean) and overdispersed data (variance greater than the mean) in a single coherent modeling framework. This article presents a new GLM based on a reformulation of the Conway-Maxwell Poisson (COM) distribution that is useful for both underdispersed and overdispersed count data and demonstrates this model by applying it to the assessment of electric power system reliability. The results show that the proposed COM GLM can provide as good of fits to data as the commonly used existing models for overdispered data sets while outperforming these commonly used models for underdispersed data sets.     

The relationship between indicators of sexual compulsivity and high risk sexual practices among men and women receiving services from a sexually transmitted infection clinic

Sexual compulsivity, defined by sexual preoccupation and lack of sexual impulse control, is related to high-risk sexual behaviors. However, little is known about the prevalence and predictors of sexual compulsivity in people at high risk for contracting sexually transmitted infections (STIs). In the current study, patients receiving diagnostic and treatment services (85% African American) at an urban STI clinic completed measures of demographic characteristics, sexual compulsivity, substance use, and sexual behaviors. Measures were administered to 492 men and 193 women using confidential procedures and audio computer-assisted interviewing technology. Results showed that men and women receiving STI clinic services frequently endorsed multiple indicators of sexual compulsivity. In this mostly African American sample, individuals with scores above the 80th percentile on the sexual compulsivity scale (translating to over one standard deviation above the mean) had more sex partners, engaged in higher rates of sexual risk behaviors with casual or one-time sex partners, and were nearly four times as likely to have been recently diagnosed with multiple STIs than were individuals who scored below the 80th percentile. Although sexual compulsivity scores were associated with alcohol and other drug use, associations between sexual compulsivity and sexual risks were not accounted for by substance abuse. Findings suggest an urgent need for interventions to help men and women with sexual preoccupations and poor sexual impulse control to reduce their risks for sexually transmitted infections.