Why do people appear so certain in a time of great uncertainty?
Many who support mitigation restrictions also find the costs unacceptable
One feature of the pandemic has been consistent polling data showing strong public support for non-pharmaceutical interventions (NPIs). This level of support has been constantly reported across most media sources. With help from three excellent co-authors, I recently published a paper outlining why these polling data over-simplify what people think. Our research produced several interesting findings by assessing people’s attitudes in much greater depth than headline polling questions. I shall describe a couple of the key results.
First, we found people were conflicted about the cost-benefit trade-off of NPIs. Just like the polls suggest, we found the majority said they supported the restrictions, but then they also thought they carried serious side effects, and they thought that several of those side effects were an unacceptable cost to bear. The headline polling thus hides much of the ambivalence people feel about NPIs. Importantly, this conflict was already evident in the first wave of our research, back in June 2020, so it is not just a recent development.
This level of inconsistency might appear initially surprising, but attitudinal research shows people are usually conflicted about difficult issues, and if you only examine one aspect of the issue you will misunderstand what people really think. An equivalent example would be to ask people whether they’d like to pay less tax – and when the unsurprising answer is the vast majority say ‘Yes’, to then interpret this as meaning they must also be happy to have fewer hospitals and schools. This would not be the case!
We have understandably wanted to be in control of the virus so we can prevent its worst effects, but the evidence suggests we have not been.
Second, we found that people initially judged the threat of COVID-19 via the policy response. In other words, people thought the threat must be very serious, otherwise, the very serious restrictions would not have been put in place. Using the magnitude of the policy response to judge the novel threat is highly logical. At the start of the pandemic, what other information was available to most people upon which they could base their judgement?
But this also means people supported lockdowns, in essence, because they existed. This circular relationship between threat assessment and policy response makes it hard to judge public support in terms of whether they really saw lockdowns as a proportionate response to the threat, as the proportionality aspect was necessarily embedded within their initial judgement.
This method of threat assessment remains relevant now, as people will have used their initial position to then interpret the incoming ambiguous evidence. And this will have worked in combination with the presentation of strong public support as the norm, to reaffirm people’s confidence that the NPIs must have been necessary and proportionate.
However, as the pandemic has progressed, people now have a direct experience to rely upon. Some people have lost loved ones to COVID-19 or suffered badly from the virus, and such experiences may encourage a desire for restrictions to be maintained or enhanced. Similarly, some people have suffered hugely from the NPIs, and these experiences of course likely increase their desire to see restrictions lifted. As we move forwards, it is crucial that empathy with one another forms a cornerstone of our day-to-day interactions. We have all suffered differently.
Alongside the paper, the Royal Society asked me to write a blog about the motivation behind the work. In this blog, I outline why I felt uneasy from the very start of the pandemic at how scientific questioning of NPIs was sparse and even unwelcome. Instead, we saw near unanimous certainty that the lockdown policies being enacted around the world were, without doubt, the right course of action to deal with COVID-19. I of course recommend looking at the blog, and paper, if you’d like to know more about why I think this certainty arose!
Like any interested person, I have followed discussions of how NPIs have been confidently presented as “working” or “not working”, by politicians, journalists, and scientists. These three groups have differing motives, but they all have somewhat obvious reasons to overstate confidence in their views.
With 17 months of data now available, I remain deeply unsure of precisely where and how NPIs have an impact upon the trajectory of the virus. There are so many confounds around the timing of their introduction and removal, the actual and modelled interactions between different policies, their indirect effects on public behaviour, and their stated aim (e.g., save lives, defer cases, suppress in high prevalence situations or eradicate in low prevalence situations), that it inevitably becomes very difficult to isolate cause and effect of any particular restriction.
In combination, the restrictions clearly reduce the number of contacts people have, and I think there is good evidence to show this can reduce the transmission of many viruses in some contexts. But the way this basic reduction in contacts then translates into an overarching effective strategy for dealing with the pandemic, seems to me, fraught with uncertainty; and the side effects of the restrictions are undoubtedly significant and cannot be ignored if we are to assess the public health situation as a whole.
This is why I think the “follow the science” slogan with relation to COVID-19 has been dangerous – it seems to have promoted the idea there is a right answer, that we know what we are doing, that all people need to do is follow the rules and things will be ok, and that this complex issue is a question of science and not policy. In truth, I think it has always been about policy – that is how democratic societies have always dealt with issues that are too complex to be answered with scientific evidence alone. The passing of responsibility back and forth between science and politics that we have seen in the pandemic could have set a difficult precedent for future collaborations that we need to consider.
I suspect the arguments around NPI efficacy won’t reach a consensus in the near future, partly because so many people are already too strongly committed to certain positions, partly because the sheer complexity of the analyses leaves a lot of room for researcher interpretation, and partly because some physical and psychological effects simply cannot be directly quantified anyway (e.g., the value of being able to visit a terminally ill relative, a day in school, or a coffee with a friend).
We are now a year and a half into the pandemic and still confusion reigns as to how NPIs impact the transmission of COVID-19. Recent weeks and months have seen many scientists confidently predict ups and downs across the world, then have to quickly pivot to new explanations when their predictions haven’t materialised. We have understandably wanted to be in control of the virus so we can prevent its worst effects, but in truth, the evidence suggests we have not been.
However, that is not to resign ourselves to fate – humans are capable of some incredible things when we work together. Some great science has already taken place in tackling COVID-19 and relieved a lot of suffering. But it will be a lot easier to navigate this pandemic, and future threats, if we acknowledge the danger of certain psychological traps – such as confirmation bias (i.e., a tendency to seek out the evidence that confirms our pre-existing view – only studying or commenting when cases are rising or falling in certain places) and the sunk cost fallacy (i.e., a tendency to defend the use of NPIs in part because of the very heavy costs they actually incurred). Even in the heat of a crisis, the empirical principles of humility, open-mindedness and uncertainty are critical to good science, good policy, and good discourse between all of us.
German translation available here.
Colin Foad received his PhD from Cardiff University’s School of Psychology where he currently serves as a Lecturer.
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