Is it riskier to meet 100 people outdoors or 14 people indoors? Comparing public and expert perceptions of COVID-19 risk.

People have limited capacity to process and integrate multiple sources of information, so how do they integrate multiple contextual risk factors for Coronavirus disease (COVID-19) infection? In June 2020, we elicited risk perceptions from a nationally representative sample of the public (N = 800) using three psychologically-distinct tasks. Responses were compared to a sample of medical experts who completed the same tasks. Relative to experts, the public perceived lower risk associated with environmental factors (such as whether a gathering takes place indoors or outdoors) and were less inclined to treat risk factors as multiplicative. Our results are consistent with a heuristic simply to "avoid people" and with a coarse (e.g., "safe or unsafe") classification of social settings. A further task, completed only by the general public sample, generated novel evidence that when infection risk competes with risk in another domain (e.g., a different medical risk), people perceive a lower likelihood of contracting the virus. These results inform the policy response to the pandemic and have implications for understanding differences between expert and lay perception of risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Interventions to increase physical activity: An analysis of candidate behavioural mechanisms.

Physical inactivity is a significant driver of health and social inequalities, particularly affecting socioeconomically disadvantaged communities. This poses a major challenge to policymakers worldwide. Despite the large volume of original research and reviews that focus on the design and evaluation of interventions to increase physical activity, there remains little consensus on which interventions are likely to work. This paper discusses physical activity interventions through the lens of behavioural science. We consider the conclusions drawn by previous reviews of this literature and link them to potential behavioural mechanisms that might explain them. We categorise interventions into three broad types: physical environment, information provision and social context, and discuss specific components within each that are known to influence behaviour. The paper is not a systematic nor an exhaustive review. The recommendations are not for implementation without testing. Rather, the paper contributes an analysis of how existing evidence can be used to design research and interventions in future to test not just the main outcome, but the behavioural mechanisms that may determine success.

Using decision aids to support self-isolation during the COVID-19 pandemic.

OBJECTIVE: Self-isolation is a vital element of efforts to contain COVID-19. We set out to test whether decision aids can support self-isolation. DESIGN: We conducted a pre-registered online experiment with a nationally representative sample (n = 500). Three stages tested: (i) whether decision trees help people to decide whether they need to self-isolate; (ii) whether an online planning tool increases people's confidence in their ability to self-isolate; and (iii) whether infographics help people to absorb advice on managing a household in which someone must self-isolate. MAIN OUTCOME MEASURES: (i) Accuracy of matching symptom patterns to a response scale for the need to self-isolate; (ii) self-reported confidence in coping with self-isolation; (iii) objective tests of recall and comprehension. RESULTS: Decision trees improved decisions about when self-isolation was necessary, although participants systematically underestimated the need to self-isolate with less common COVID-19 symptoms (e.g. sore throat, fatigue). The online planning tool increased confidence about coping with self-isolation only among the adults aged under 40. Infographics improved recall and comprehension of how to manage self-isolation. CONCLUSION: Decision aids can be used to support self-isolation during COVID-19. The study also demonstrates how even an emergency public health response can benefit from rapid experimental pre-testing of interventions.

Motivating social distancing during the COVID-19 pandemic: An online experiment.

RATIONALE: Maintaining social distance during the COVID-19 pandemic can save lives. We therefore set out to test communication strategies to promote social distancing. OBJECTIVE: We aimed to test two novel public health messages against a control message. The first was designed to exploit the "identifiable victim" effect by highlighting the risk of transmission to identifiable vulnerable persons. The second sought to counteract intuitive underestimation of exponential transmission. METHOD: In total, 500 Irish adults undertook a pre-registered, online experiment. They were randomly assigned to a control group or one of two treatment groups. The control group viewed a current poster that encouraged a 2-m separation between people. The two treatment groups saw posters of similar design, but with narrative messages describing how an individual had infected a specific vulnerable person or multiple other people. Later questions measured intentions to undertake three specific types of social interaction over the coming days and the stated acceptability of three other types of social interaction. Pilot work had identified these six behaviors as "marginal" - people were unsure whether they were advisable. RESULTS: Participants in the treatment conditions were more cautious about undertaking the behaviors and less accepting of them. This positive effect occurred despite participants rating the treatment posters as likely to be less effective and memorable than the control poster. CONCLUSIONS: Messages that invoke thoughts of infecting vulnerable people or large numbers of people can motivate social distancing and, hence, help to limit the spread of COVID-19. Stated public evaluations (obtained via focus groups or surveys) may underestimate the actual effectiveness of such emotional messages.