What Did You Find About The Problem In The Existing Literature Books Articles Websites
3.What did you find about the problem in the existing literature (books/articles/websites)?
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“Social distancing”, reducing social interactions with others, has the potential to save millions of lives during the COVID-19 pandemic (Ferguson et al., 2020; Greenstone & Nigam, 2020). Governments worldwide have already introduced varying levels of social distancing measures, but compliance by individuals is vital (Anderson, 2020). This paper describes a pre-registered1 experiment to test potential communication strategies to encourage compliance with social distancing.
The experiment formed part of a study commissioned by Ireland’s Department of Health, in support of the Behaviour Change Subgroup of the National Public Health Emergency Team (NPHET). This working paper is designed to present initial results that relate to the pre-registered hypotheses at a time when speed is important. There may be lessons in this research from which others can benefit, as work on the behavioral response to COVID-19 quickly progresses (e.g. Everett et al., 2020; Barari et al., 2020; Pfattheicher et al., 2020). The work has been produced much more rapidly than would be standard for work of this type. Consequently, we have focused on providing robust results in relation to the primary, preregistered hypotheses, with limited further exploration of the data.
This effect arises even when a specific individual is identified but remains anonymous, perhaps because of the mere act of thinking about a specific individual induces stronger caring emotions (Small & Loewenstein, 2003). Hence, we set out to test a communication strategy that highlights specific persons who are especially vulnerable to the coronavirus: an elderly person, someone with an underlying health condition, a healthcare worker, etc.
People struggle to perceive exponential growth accurately and are inclined to greatly underestimate it (Wagenaar & Sagaria, 1975). This “exponential growth bias” may be important for perceiving risk in relation to the coronavirus, given the exponential nature of network transmission. For instance, people may fail to realize how many others could be affected by one individual’s behavior and, conversely, how many onward infections could be prevented by that one individual acting to protect themselves. Communication that stresses the exponential rate of infection might, in turn, affect the likelihood that people endorse beneficial health behavior (Witte, 1992). Thus, we also tested whether highlighting the possibility that one individual’s behavior results in multiple onward infections would influence intended compliance with social distancing. These two streams of literature, on caring for identifiable victims and understanding exponential relationships, formed the basis of two experimental treatments based on exposure to campaign posters. We refer to these as “identifiable person” (IP) and “transmission rate” (TR) treatments.
Responses were compared to a control group who saw an informational poster adapted from materials being employed by Ireland’s public health authorities. 5 Ideally, following exposure to the posters based on random allocation, we would measure behavior over a subsequent period. Given practical restrictions and the need to generate evidence promptly, such a research design was unfeasible. Instead, our outcome variables measure intentions and attitudes.
In addition to the possibility of an intention-action gap (Sheeran, 2002), such variables can be prone to ceiling effects, as some rapidly conducted experiments on messaging strategies have already found (e.g. Everett et al., 2020; Barari et al., 2020). To counter this problem, we inserted questions into Department of Health focus groups that asked people to describe activities where they were unsure whether the behavior was appropriate, given the prevailing social distancing guidelines. We refer to these as “marginal behavior”, i.e. behavior that some individuals deem acceptable and others not. Some marginal behavior was relevant for all participants, such as meeting friends and relatives’ outdoors. We measured participants’ intentions to undertake these behavior “over the next few days”. Other marginal behaviors were relevant to only some participants, such as allowing children from different households to play together. For these, we asked participants to judge the acceptability of the behavior.
We also found that participants’ judgments about the effectiveness of the posters were the opposite of the effects we recorded. This mismatch between participants’ intuitions and empirical observations replicates other research on appeals to moral values (Everett et al., 2020). The finding has two implications. First, it suggests that the main effects we report were not due to the superficial attractiveness of the treatment posters; participants did not like them. Second, it indicates that there are circumstances where testing campaigns via focus groups may backfire, perhaps especially where a message makes people feel uncomfortable or guilty. Generally, individuals may want to believe that their behavior is based on rational information processing, not emotional responses, despite evidence to the contrary (Lerner et al., 2015).
Conducting rapid behavioral research during an unprecedented crisis is challenging, particularly with respect to the reliability and validity of outcome variables. Our strategy was to identify marginal behavior and to create a “caution” score from intentions and judgments of this behavior. As the situation evolves and recommended measures change, behavior that might be considered marginal will change too. However, we hope that other researchers may be able to build on our approach, which mitigated ceiling effects and generated workable variation in the outcomes of interest. Much more research is needed.
Communication strategies will benefit from not only rapid experiments but also the rapid replication of experiments. However, despite the rapidly evolving 18 nature of the COVID-19 pandemic, it is possible to use the techniques of behavioral science to support policy (Lunn et al., 2020), including via the pre-testing of interventions.
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