Assessment of Cigarette Smoking and Smoking Susceptibility among Youth: Telephone Computer-Assisted Self-Interviews versus Computer-Assisted Telephone Interviews

This experimental study assesses the effect of two survey methods,telephone audio computer-assisted self-interviewing (T-ACASI)and computer-assisted telephone interviewing (CATI), on self-reportsof smoking behavior and smoking susceptibility among adolescents12–17 years of age in California. In T-ACASI, participantslisten to prerecorded, computer-controlled questions and respondby pressing the keypad on a touch-tone telephone. In CATI, interviewersadminister the questions and enter responses into a computer.Prior research suggests that youth may be more likely to reportsensitive behaviors in a self-administered survey like T-ACASIcompared to an interviewer-administered survey like CATI, dueto greater perceived confidentiality. Logistic regression analyseswere conducted on unweighted data, controlling for demographicdifferences. Adjusted estimates of current smoking (past 30days) were significantly greater in T-ACASI (8.3 percent) thanCATI (4.5 percent). Smoking susceptibility (i.e., lack of afirm commitment not to smoke among those who have never smoked)was also greater in T-ACASI (45.0 percent) than CATI (34.9 percent).In both surveys, social desirability response bias was negativelyassociated with smoking, which suggests that response bias wasproblematic for both modes. Many respondents reported that aparent was present during the interview (59.4 percent in CATI;42.0 percent in T-ACASI). In both surveys, parental presencewas negatively associated with smoking, which suggests thatthis factor could also contribute to underreporting. Applicationof sample weights to the data eliminated the survey mode effects;however, the CATI current smoking estimate (9.3 percent) fromthis study was significantly less than an estimate (14.2 percent)obtained from a self-administered, school-based survey conductedthe same year on California adolescents.     

East European assimilation and (re)integration: the interwar legacies of transatlantic migration and “Russian” Orthodox conversion (1918–1939)

In the 1920s and 30s, mass conversion movements to “Russian” Orthodoxy emerged among Greek Catholics in Czechoslovakia and Poland, comprising a new chapter in a continuing saga of conversion which began in the late nineteenth century, in what was then Austria–Hungary. Pre-1914 conversion movements arose in large part due to transatlantic migration – especially return migration – between Austria–Hungary and the Americas. Americanists have generally treated the 1920s and 30s as the era when transnational migration’s impact waned owing to US immigration restrictions, while East Europeanists have minimized or ignored the impact of transnational migration upon East European regions. Interwar Catholic-to-Orthodox conversions, however, are not merely attributable to historical legacy: transatlantic migration continued to influence the dynamics of conversion as an active, contemporary force. As had been true prior to World War I, returning migrants and their families comprised the most significant constituency of the movements after the war; migrants remaining in the Americas supported the East European movements with economic and social remittances, and activists on either side of the Orthodox/Catholic divide treated the conversions as transnational phenomena. This essay analyzes the impact of transnational migration upon shifting ethnoreligious identifications, in the context of shifting social, national, and geopolitical circumstances, 1918–1939.     

The Gamma-count distribution in the analysis of experimental underdispersed data

Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of counts by Gaussian regression models ignores the discreteness, asymmetry and heteroscedasticity and is inefficient, providing unrealistic standard errors or possibly negative predictions of the expected number of events. The Poisson regression is the standard model for count data with underlying assumptions on the generating process which may be implausible in many applications. Statisticians have long recognized the limitation of imposing equidispersion under the Poisson regression model. A typical situation is when the conditional variance exceeds the conditional mean, in which case models allowing for overdispersion are routinely used. Less reported is the case of underdispersion with fewer modeling alternatives and assessments available in the literature. One of such alternatives, the Gamma-count model, is adopted here in the analysis of an agronomic experiment designed to investigate the effect of levels of defoliation on different phenological states upon the number of cotton bolls. Data set and code for analysis are available as online supplements. Results show improvements over the Poisson model and the semi-parametric quasi-Poisson model in capturing the observed variability in the data. Estimating rather than assuming the underlying variance process leads to important insights into the process.     

Marginal Religious Affiliates in Canada: Little Reason to Expect Increased Church Involvement

In this paper, I draw on interview data with 21 Canadian marginal religious affiliates, who attend religious services primarily for religious holidays and rites of passage, and ask why they stopped attending on a regular basis, why they continue to attend once or twice a year, and do they express any interest in being more involved in their religious group, and if so, what factors might lead to increased involvement. In contrast to Reginald Bibby and others who explain church involvement patterns by stressing the supply side of the religious marketplace, I argue that we should concentrate more on the demand side.     

Audience effects on solitary faces during imagery: Displaying to the people in your head

Subjects imagined situations in which they reported enjoying themselves either alone or with others. Electromyographic (EMG) activity was recorded bilaterally from regions overlying thezygomatic major muscles responsible for smiling. Controlling for equal rated happiness in the two conditions, subjects showed more smiling in high-sociality than low-sociality imagery. In confirming imaginary audience effects during imagery, these data corroborate hypotheses that solitary facial displays are mediated by the presence of imaginary interactants, and suggest caution in employing them as measures of felt emotion.Avery Gilbert and Amy Jaffey had compelling insights throughout the course of study. We thank Paul Ekman, Carroll Izard, and Paul Rozin for extensive comments on earlier drafts. We also thank Bernard Apfelbaum, Jon Baron, Janet Bavelas, John Cacioppo, Linda Camras, Dean Delis, Rob DeRubeis, Alan Fiske, Stephen Fowler, Greg McHugo, Harriet Oster, David Premack, W. John Smith, and David Williams for their valuable comments and suggestions.     

Meningococcal serogroup B outbreak response University of Wisconsin-Madison

A meningococcal serogroup B (MenB) outbreak at a large public university prompted an emergency response to immunize undergraduates. Objective: To report on a successful meningococcal serogroup B (MenB) vaccine clinic response at a large public university. Methods: We assembled the team leaders to write this case report. Results: Activation of the emergency plan and points of dispensing required cooperation of many units on campus under the leadership of university health officials with support from Centers for Disease Control and Prevention, state division of public health and the city-county health department. Significant efforts to provide consistent messages to students and parents regarding the outbreak and the availability of the MenB vaccines were made. Volunteers were recruited to staff the clinics alongside university healthcare providers. Over 22,000 doses of vaccine were administered. Conclusion: We report our experience and lessons learned which may be helpful to universities in preventing and responding to disease outbreaks.     

What’s New? What’s Normal?1

This article is a response to Amitai Etzioni’s article, “The New Normal,” published in this issue.