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The recent Coronavirus outbreak, and calls for social distancing, have created an intriguing naturalistic decision making experiment. The overall objective of this proposal is to better understand why some individuals chose to abide by social distancing recommendations (and shelter-in-place or stay-at-home orders) while other individuals do not.

This project will examine how differential time delays impact delayed discounting across the lifespan. More updates to come.

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Trust is an important part of everyday human interaction. It is a learned social behavior that is based on an individual's direct and prior experiences. However in today's world, individuals frequently come into contact with strangers. In these situations, how do people decide to trust a novel person with whom they've had no prior experience? Associative learning (AL) theory describes how experience directs learning, which then shapes behavior. Research has shown that different factors can influence the rate at which people associatively learn, or update the value of a person through repeated interactions (deeming them trustworthy, untrustworthy, or neutral). For example, with age people tend to take longer than their younger counterparts to differentiate an untrustworthy partner from a neutral one (Fareri et al., 2012; Park et al; 2020; Seaman et al., in prep). We are interested in understanding whether group membership affects the rate at which people associatively learn trust information. People tend to have positive beliefs about members of the same same social group (or in-group), which leads them to trust in-group members. Further, these positive ingroup beliefs can make members of an out-group appear less trustworthy (Brewer & Kramer, 1985). Thus, social group membership can bias our initial perceptions of trust. These initial beliefs may be hard to change; studies show that people tend to consider evidence that is consistent with their beliefs and discount evidence that is inconsistent with their beliefs (Wason 1960), particularly in the social domain (Hughes et al., 2016). This suggests that people may only attend to, and learn from, information that is consistent with their beliefs. Prior studies have shown that people tend to rely more on prior social and moral perceptions than experience (Delgado et al., 2005) and tend to update their impressions less for friends compared to strangers (Fareri et al., 2015; Park et al., 2020). Here we explore if this extends to in-group and out-group membership. Do people update their experiences with a trustworthy, untrustworthy, or neutral person differently depending on whether they are an in-group member or an out-group member? We plan to explore these questions with political party groupings, as they have been studied in previous research and are especially relevant in today's political climate. Our goal is to investigate the ways that political group membership influences social associative learning for trust information. Does political group membership affect initial level of trust for a stranger? Can political group membership affect the rate at which people learn trust information, meaning do people update their representations of a person (deeming them trustworthy or not) differently according to in-group or out-group memberships?

Prior research has shown that older adults regulate emotions better (Charles and Luong, 2013), are more emotionally stable (Burr, 2020), and tend to worry less (Brenes, 2005) when compared to younger cohorts. The COVID19 pandemic offers a critical and unique opportunity to understand the ways in which mental health symptoms operate in times of stress. Several international studies conducted near the start of the pandemic similarly found that older adults were faring better than younger adults (Ozamiz-Etxebarria et al., 2020; Shevlin et al., 2020), contributing to evidence that older adults may be more resilient than younger adults. While there are many reports of older adults emotionally regulating better than younger adults, there are several reports of older adults faring worse (Christensen et al., 1999; Teachman, 2006). The SAVI model rectifies these disparate findings by suggesting that with age, situations that disallow the use of effective coping strategies (i.e. social isolation) become more common; when this happens, older adults don’t regulate as well and thus have lower levels of emotional well-being (Charles & Luong, 2013). There is evidence that loneliness could be one situation that precludes emotional regulation in older adults, as it has been shown to predict depressive symptomology in older adults (Caccioppo et al., 2010), and been linked to higher reports of stressors and adversities in older adults (Hawkley and Caccioppo, 2007). Similarly, perceived physical health has also been posited to interfere with emotional regulation (Chui and Diehl, 2016, Shevlin et al., 2020) and is actually a risk factor for loneliness (Perlman, 1990). Given these findings, we wondered whether loneliness and poorer physical health could predict which older adults in our sample were experiencing more mental health symptoms relative to the older adults that were not. We have decided to explore further age trends in mental health symptoms during the pandemic to contribute to a comprehensive picture not only of mental health experiences across the lifespan, but also how this unique stressor may differentially affect people across a nationally representative lifespan sample.

As of November 23, over 12 million Americans have been diagnosed with COVID-19 and over 250,000 of them have died (CDC). One effective way to prevent the spread of COVID-19 is through social distancing. Thus, understanding why people choose to socially distance is critical to promoting this behavior. This study will use existing survey data collected online in May 2020. The survey includes questions about social distancing, health beliefs, media use, and demographic variables. Our research questions are as follows. First, does diversification of media sources predict health beliefs ? Second, do health beliefs predict social distancing behavior? Third, does self-efficacy predict social-distancing behavior?

This is a space to collect all documentation for a project, including lab protocols and IRB forms.

Evidence suggests that Collectivism in cultures influence a society’s behavior on goals and rules. Therefore, we wanted to observe if there’s and effect of individualism and collectivism in how people perceive and follow social distancing recommendations.