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We analyzed comedy series for food and beverage references, with particular attention to their type of presentation, along with the characteristics of actors associated with the references. Because the generally positive tone of comedy series can exert affective influence over audiences, the result that clearly unhealthy products appeared more often (food: 51.6%; beverage: 40.5%) than clearly healthy ones (food: 11.2%; beverage: 19.6%) could be especially problematic. Moreover, women (56.5%; men: 47.4%) and African American characters (62.7%; Caucasians: 51.5%; Other: 44.7%) were significantly more often associated with unhealthy foods, which could prompt stereotypes of such individuals.

Swipe-based dating apps characteristically provide quantitative social feedback in the form of matches. Surveys suggest a link between dating app success and well-being, but the nature of this correlation has yet to be examined. In an experiment with 125 undergraduate women, we manipulated dating app feedback: When accepting a profile, participants had either a high (27/31) or a low chance (3/31) of receiving matches. We found no effect of chance of matches on women's loneliness or fear of being single. However, a higher chance of matches led to higher partner choice overload. Furthermore, in those who accepted seven or more profiles, women in the low chance of matches condition reported higher loneliness than women in the high chance of matches condition. This could mean that matches are rewarding for women with a high approach orientation. Manipulating social feedback in a dating app paradigm seems suitable to study the effects of social acceptance and ostracism.

During the COVID-19 pandemic, researchers have faced a lot of challenges related to their daily work. This article introduces a special issue of the American Behavioral Scientist, which particularly focuses on methodological challenges caused by the COVID-19 pandemic. Based on a brief review of the literature as well as the studies in this issue, we argue that the pandemic has sparked significant methodological innovations with respect to design, data collection, study documentation, and scholarly collaboration. We distinguish two types of innovations, both conceptualized as the outcome of an unprecedented external shock. First, "methodological compromises" that enabled data collection during the pandemic, but are inferior to established approaches. These methodological compromises, therefore, may be abandoned in post-pandemic times. Second, there are also "methodological game changers" that are superior to classic approaches and thus may prevail in the long run. Regardless of the type, we call scholars in the social and behavioral sciences to systematically test, compare, and evaluate the methodological innovations brought to us as a result of the COVID-19 pandemic.

Due to 'stay-at-home' measures, individuals increasingly relied on smartphones for social connection and for obtaining information about the COVID-19 pandemic. In a two-wave panel survey ( NTime2 = 416), we investigated associations between different types of smartphone use (i.e., communicative and non-communicative), friendship satisfaction, and anxiety during the first lockdown in Austria. Our findings revealed that communicative smartphone use increased friendship satisfaction over time, validating how smartphones can be a positive influence in difficult times. Friendship satisfaction decreased anxiety after one month, signaling the importance of strong friendship networks during the crisis. Contrary to our expectations, non-communicative smartphone use had no effects on friendship satisfaction or anxiety over time. Reciprocal effects showed that anxiety increased both types of smartphone use over time. These findings are discussed in the context of mobile media effects related to the COVID-19 pandemic.

Political parties increasingly rely on sophisticated targeting strategies to persuade potential voters. However, questions have been raised about the effectiveness of targeted political ads, considering that citizens frequently oppose the use of their data for political purposes. In this study, we investigate three avoidance behaviors that citizens might employ in order to circumvent targeted political ads: cognitive avoidance, blocking behaviors, and privacy-protective behaviors. We test if privacy concerns, perceived personalization, and overload explain why individuals resort to avoidance behaviors. Moreover, we explore interrelations between the different avoidance strategies. Findings from a two-wave panel study ( N = 428) in the context of the Viennese state election showed that privacy concerns increased cognitive avoidance and privacy-protective behaviors. In contrast, perceived personalization decreased cognitive avoidance and blocking behaviors. Cognitive avoidance further reduced privacy-protective behaviors over time, indicating that low-effort strategies might inhibit preventive actions against data collection practices.