from the editor
‘ Nudge ’ Intervention and the Science of Making It Easy to Do the Right Thing
The feature on human factors engineering and its implications for infection prevention practice which I wrote for this month ’ s issue got me thinking about what goes into trying to ensure that people are given every opportunity to do the right thing , especially when it comes to ensuring optimal patient outcomes .
A recent study from researchers at Queen Mary University of London warns us that despite the widespread use of behavioral interventions across society , failed efforts are surprisingly common . The researchers examined published failed behavioral interventions across all areas that impact society , from healthy eating and organ donation , to tax compliance . They discovered that while any type of behavioral intervention applied in any type of setting could be liable to fail , certain types of intervention were more likely to falter .
The researchers say that after analyzing 65 papers published between 2008 and 2019 , they identified eight types of failures , which include “ backfires ,” whereby the introduction of the nudge intervention made the behavioral problem worse rather than better . The most common type of interventions that resulted in failures were those involving social norming or social comparisons , where individuals are provided with information about the behavior of their peers to encourage a desired behavior change . Interventions that involved the provision of information through letters or text messaging , accounted for almost one-quarter of the failed studies .
Dr . Magda Osman , a professor of experimental psychology at Queen Mary University of London , observes , “ We have shown that failures are quite common and can occur with nudges applied in any type of setting . We found that there are different types of failures , from interventions that simply don ’ t achieve any behavioral change , to those that achieve negative changes such as backfire effects .”
In the paper , the researchers also show the benefits of using computational causal modeling techniques to map out the different
factors that can influence specific behavioral interventions and their likelihood of success . This allows researchers and decision-makers a way of mapping out in advance what might work , as well as what might undermine the intervention ahead of time .
Osman , adds , “ We believe that causal analysis can advance existing behavior change frameworks as they allow us to formally model behavior change problems and the context in which these interventions are situated . By incorporating these approaches into the early design of behavioral interventions , we can begin to understand what factors are relevant to the success of the intervention and how the intervention could influence these factors , and even prepare precautionary measures to help avoid failure .”
The use of psychological insights to motivate people to change their opinions , attitudes and behaviors dates as far back as the 1950s when it was referred to as behavioral engineering . More recently , governments have sought advice from experts on behavioral interventions to ensure public compliance with their proposed strategies to manage the Covid-19 pandemic , for example on behaviors such as social distancing and wearing masks .
Osman says , “ It ’ s clear to see that there ’ s currently a great appetite for the use of behavioral techniques in society ... However , the behavioral change enterprise disproportionately focuses on promoting successes at the expense of examining the failures of behavioral change interventions . Understanding why behavioral changes fail , and being able to anticipate possible types of failures when designing interventions could help to save time and public funds invested in these techniques , and overall increase their success in achieving the desired behavioral change .” Until next month , bust those bugs !
Kelly M . Pyrek Editor & Publisher kelly @ healthcarehygienemagazine . com healthcarehygienemagazine
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Reference : Osman M , McLachlan S , et al . Learning from behavioral changes that fail . Trends in Cognitive Sciences . 2020 .