![]() In fact, how could it? Given how complex human behaviour is, how could one single approach ever hope to change it? There's not a single example of this being successfully done in history, at least not without impinging on human rights.Īs I have shown before, if we are honest about the possibility of failure, then we can use it to learn what to do better. This takes the burden off nudge being solely responsible for behavioural change, especially since alone it doesn't do much. For example, as I have shown, combinations of nudging methods together with changes in taxation and subsidies have a stronger effect on sustainable consumption than either being implemented alone. A better way forward would be to focus on building an evidence base showing which combinations of nudges and other approaches work together. That said, efforts to use behavioural interventions need not be abandoned. But many, including myself, have long known this – spending many years carefully commenting on the various ways research on nudging needs to improve, and have been largely ignored. Right now, the best science we have is seriously questioning the effectiveness of nudging. And they often don't consider the benefits relative to the actual costs of using nudges, or work out whether nudges are in fact the actual reason for positive effects on behaviour. For example, scientists overly rely on certain types of experiments. This year, a colleague and I highlighted that, regardless of the 2021 results, there are still general issues with nudge science. The authors of the original 2021 study, which reported a moderate effect size of nudging on behaviour, ruled out publication bias that was severe enough to have a major influence on the reasonable effect size they found. This may be because editors and reviewers at scientific journals want to see findings showing that an experiment worked – it makes for more interesting reading, after all. This is the cherry-picking of results to show a win for nudge, meaning that studies finding that nudges don't work aren't included or even published in the first place. A big p-value would mean that the differences between the two groups can largely be explained by chance.Ī good study needs to show a moderate or large effect size, but it also needs to set out how much of it was the result of “ publication bias”. This is called the p-value, and the lower it is the better. If I then find a difference, I use statistics to work out how probable it is that this would have happened by chance alone. So, if in my experiment there is a group of people who are exposed to a specific nudge technique, and a control group that isn't nudged, my starting point is that the two groups won't differ.
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