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Using Behavioral Science to help fight the Coronavirus
This rapid, narrative review summarizes useful evidence from behavioral science for fighting the COVID-19 outbreak. We undertook an extensive, multi-disciplinary literature search covering five issues: handwashing, face touching, self-isolation, public-spirited behavior, and responses to crisis communication. The search identified more than 100 relevant papers. We find effective behavioral interventions to increase handwashing, but not to reduce face touching. Social supports and behavioral plans can reduce the negative psychological effects of isolation, potentially reducing the disincentive to isolate. Public-spirited behavior is more likely with frequent communication of what is ?best for all?, strong group identity, and social disapproval of noncompliance. Effective crisis communication involves speed, honesty, credibility, empathy, and promoting useful individual actions. Risks are probably best communicated through numbers, with ranges to describe uncertainty ? simply stating a maximum may bias public perception. The findings aim to be useful not only for government and public health authorities, but for organizations and communities.
BASE
Behavioural evidence to inform the COVID-19 pandemic response: Ireland's Social Activity Measure (SAM)
In: Behavioural public policy: BPP, S. 1-15
ISSN: 2398-0648
Abstract
Humankind's main defence against the virus that cuases COVID-19 (SARS-CoV-2), besides vaccine development, was co-ordinated behaviour change. In many countries, co-ordination was assisted by tracking surveys designed to measure self-reported behaviour and attitudes. This paper describes an alternative, complementary approach, which was undertaken in close collaboration with officials in the Department of the Taoiseach (Irish Prime Minister). We adapted the Day Reconstruction Method (DRM) to develop the 'Social Activity Measure' (SAM). The study was conducted fortnightly for 18 months, with findings delivered directly to the Department. This paper describes the method and shows how SAM generated a detailed picture of where and why transmission risk occurred. By using the DRM, we built aggregate measures from narrative accounts of how individuals spent their previous day. SAM recorded the amount, location and type of social activity, including the incidence of close contact and mask-wearing, as well as compliance with public health restrictions by shops and businesses. The method also permitted a detailed analysis of how public perceptions and comprehension are related to behaviour. The results informed government communications and strategies for lifting public health restrictions. The method could be applied to other future situations that might require co-ordinated public behaviour over an extended period.