23 d’abril 2020

Behavioral response to the virus

Using Behavioural Science to Help Fight the Coronavirus

Main topics of the paper:
(1) Evidence on handwashing shows that education and information are not enough. Placing hand sanitisers and colourful signage in central locations (e.g. directly beyond doors, canteen entrances, the middle of entrance halls and lift lobbies) increases use substantially. All organisations and public buildings could adopt this cheap and effective practice.
(2) By contrast, we lack direct evidence on reducing face touching. Articulating new norms of acceptable behaviour (as for sneezing and coughing) and keeping tissues within arm’s reach could help.
(3) Isolation is likely to cause some distress and mental health problems, requiring additional services. Preparedness, through activating social networks, making concrete isolation plans, and becoming familiar with the process, helps. These supports are
important, as some people may try to avoid necessary isolation.
(4) Public-spirited behaviour is most likely when there is clear and frequent communication, strong group identity, and social disapproval for those who don’t comply. This has implications for language, leadership and day-to-day social interaction.
(5) Authorities often overestimate the risk of panic, but undesirable behaviours to watch out for are panic buying of key supplies. Communicating the social unacceptability of both could be part of a collective strategy.  
(6) Evidence links crisis communication to behaviour change. As well as speed, honesty and credibility, effective communication involves empathy and promoting useful individual actions and decisions. Using multiple platforms and tailoring message to
subgroups are beneficial too.
(7) Risk perceptions are easily biased. Highlighting single cases or using emotive language will increase bias. Risk is probably best communicated through numbers, with ranges to describe uncertainty, emphasizing that numbers in the middle are more likely. Stating a maximum, e.g. “up to X thousand”, will bias public perception.