@article{WeissHeinHewig2021, author = {Weiß, Martin and Hein, Grit and Hewig, Johannes}, title = {Between joy and sympathy: Smiling and sad recipient faces increase prosocial behavior in the dictator game}, series = {International Journal of Environmental Research and Public Health}, volume = {18}, journal = {International Journal of Environmental Research and Public Health}, number = {11}, doi = {10.3390/ijerph18116172}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-241106}, year = {2021}, abstract = {In human interactions, the facial expression of a bargaining partner may contain relevant information that affects prosocial decisions. We were interested in whether facial expressions of the recipient in the dictator game influence dictators´ ehavior. To test this, we conducted an online study (n = 106) based on a modified version of a dictator game. The dictators allocated money between themselves and another person (recipient), who had no possibility to respond to the dictator. Importantly, before the allocation decision, the dictator was presented with the facial expression of the recipient (angry, disgusted, sad, smiling, or neutral). The results showed that dictators sent more money to recipients with sad or smiling facial expressions and less to recipients with angry or disgusted facial expressions compared with a neutral facial expression. Moreover, based on the sequential analysis of the decision and the interaction partner in the preceding trial, we found that decision-making depends upon previous interactions.}, language = {en} } @article{GruendahlWeissMaieretal.2022, author = {Gr{\"u}ndahl, Marthe and Weiß, Martin and Maier, Lisa and Hewig, Johannes and Deckert, J{\"u}rgen and Hein, Grit}, title = {Construction and validation of a scale to measure loneliness and isolation during social distancing and its effect on mental health}, series = {Frontiers in Psychiatry}, volume = {13}, journal = {Frontiers in Psychiatry}, issn = {1664-0640}, doi = {10.3389/fpsyt.2022.798596}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-269446}, year = {2022}, abstract = {A variety of factors contribute to the degree to which a person feels lonely and socially isolated. These factors may be particularly relevant in contexts requiring social distancing, e.g., during the COVID-19 pandemic or in states of immunodeficiency. We present the Loneliness and Isolation during Social Distancing (LISD) Scale. Extending existing measures, the LISD scale measures both state and trait aspects of loneliness and isolation, including indicators of social connectedness and support. In addition, it reliably predicts individual differences in anxiety and depression. Data were collected online from two independent samples in a social distancing context (the COVID-19 pandemic). Factorial validation was based on exploratory factor analysis (EFA; Sample 1, N = 244) and confirmatory factor analysis (CFA; Sample 2, N = 304). Multiple regression analyses were used to assess how the LISD scale predicts state anxiety and depression. The LISD scale showed satisfactory fit in both samples. Its two state factors indicate being lonely and isolated as well as connected and supported, while its three trait factors reflect general loneliness and isolation, sociability and sense of belonging, and social closeness and support. Our results imply strong predictive power of the LISD scale for state anxiety and depression, explaining 33 and 51\% of variance, respectively. Anxiety and depression scores were particularly predicted by low dispositional sociability and sense of belonging and by currently being more lonely and isolated. In turn, being lonely and isolated was related to being less connected and supported (state) as well as having lower social closeness and support in general (trait). We provide a novel scale which distinguishes between acute and general dimensions of loneliness and social isolation while also predicting mental health. The LISD scale could be a valuable and economic addition to the assessment of mental health factors impacted by social distancing.}, language = {en} } @article{HeinGamerGalletal.2021, author = {Hein, Grit and Gamer, Matthias and Gall, Dominik and Gr{\"u}ndahl, Marthe and Domschke, Katharina and Andreatta, Marta and Wieser, Matthias J. and Pauli, Paul}, title = {Social cognitive factors outweigh negative emotionality in predicting COVID-19 related safety behaviors}, series = {Preventive Medicine Reports}, volume = {24}, journal = {Preventive Medicine Reports}, doi = {10.1016/j.pmedr.2021.101559}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265008}, year = {2021}, abstract = {Emotion-motivation models propose that behaviors, including health behaviors, should be predicted by the same variables that also predict negative affect since emotional reactions should induce a motivation to avoid threatening situations. In contrast, social cognitive models propose that safety behaviors are predicted by a different set of variables that mainly reflect cognitive and socio-structural aspects. Here, we directly tested these opposing hypotheses in young adults (N = 4134) in the context of COVID-19-related safety behaviors to prevent infections. In each participant, we collected measures of negative affect as well as cognitive and socio-structural variables during the lockdown in the first infection wave in Germany. We found a negative effect of the pandemic on emotional responses. However, this was not the main predictor for young adults' willingness to comply with COVID-19-related safety measures. Instead, individual differences in compliance were mainly predicted by cognitive and socio-structural variables. These results were confirmed in an independent data set. This study shows that individuals scoring high on negative affect during the pandemic are not necessarily more likely to comply with safety regulations. Instead, political measures should focus on cognitive interventions and the societal relevance of the health issue. These findings provide important insights into the basis of health-related concerns and feelings as well as behavioral adaptations.}, language = {en} }