Rebuilding hope post-Covid: Understanding risk

Written by: Dr Stephanie Thornton | Published:
Image: Adobe Stock

People who have hope generally have better developmental outcomes. In this four-part series, psychologist Dr Stephanie Thornton looks at building back hope as we emerge from the pandemic. Part three looks at how we can help young people to consider, handle and manage risk

Human beings often make mistakes when it comes to understanding risks. On the one hand, our species is susceptible to misplaced optimism when it suits: it won’t happen to me, the risk is not as big as people think and so on, which all too easily encourages us to ignore the dangers and take risks which we should have avoided, sometimes leading to serious health hazards (Dillard et al, 2006) or even fatal errors of judgement (Little, 2006).

On the other hand, we are also prone to exaggerating risks: we are the only species on the planet whose behaviour can be constrained as much by fear of an invisible spirit world as by a visibly charging rhino. Many mental health issues have their root in the exaggeration of risk which generates a damaging anxiety.

REBUILDING HOPE POST-COVID: To read other articles in this series, visit

  1. The signs of depression and despair
  2. Helping students to overcome despair
  3. Understanding risk
  4. Fostering hope and positivity

All or nothing…

Our propensity to sometimes underestimate or overestimate risk reflects the way we typically think about risk. We tend to have an all-or-nothing approach (it is/isn’t a real risk) rather than a nuanced assessment of the relative level of risk posed by a particular situation or activity.

This is because, despite the long-held view in philosophy and psychology from Aristotle to Piaget (1968) that human beings are logical, we are not. Our reasoning is not based in logic, nor in the assessment of probabilities, but in mental models of the world (Johnson-Laird, 1983) and heuristic rules of thumb (Kahneman et al, 1982).

We draw inferences from the way things look, and how that fits with our understanding of the world, not through logic or probabilistic analysis: if he looks like a musician, he is a musician – and we will ignore any a-priori probability that in fact, in this location, he is statistically much more likely to be a lawyer. By the same token, if this looks like a cool, fun activity or a horrible risk it is a cool, fun activity/horrible risk, and we act accordingly.

Reasoning on the basis of mental models and heuristics is typical of both children and adults (Johnson-laird, 1983; Kahneman et al, 1982). This is our normal way of functioning. In the main, this is a very effective approach, rooting our judgements in knowledge and experience, though it does lead to some errors of judgement in estimating the probability of a risk: for example, we overestimate the danger of being killed in a plane crash, and underestimate the risk of dying in a car crash because plane crashes are reported more vividly and dramatically, and so are easier to remember and therefore seem more common (Kahneman et al, 1982).

Such errors of judgement sometimes matter, and at any time may lead to riskier – or more cautious – behaviour than would be justified by the facts. This may be a more serious issue now than usual, as we face a world of statistical risks in which Covid-19 will be endemic.

What is the risk of catching Covid? What is the risk of infection, of passing the infection on, of being protected by a vaccine, or being seriously ill, getting long Covid or dying?

These risks are explained to us by the authorities in terms of statistics and probabilities (if at all). But neither adults nor children are any good at drawing appropriate inferences from statistics of probability (Bryant & Nunes, 2012).

This was amply demonstrated by the extraordinary reaction of various governments in suspending an effective vaccine against Covid-19 because of the discovery of a miniscule number of young individuals suffering unusual blood clots as a side effect, a suspension that is all the more baffling since the risk of a blood clot, in the same demographic, is massively greater for those taking oral contraceptives, which have not been suspended.

This suspension was not only irrational, but destructive, fuelling vaccine refusal around the world at a time when mass vaccination is vital: it will probably cost many lives.

A nuanced assessment of risk

A nuanced assessment of risk, reflecting the probability that this or that behaviour is safe or dangerous has never been more important than it will be as we come to terms with living with Covid-19 as an endemic disease. It is vital not only that the vast majority take the vaccine, but that we all learn to assess situations for the new risk and behave accordingly.

Our natural ways of thinking are not immediately conducive to that: if a familiar person/situation/activity has always been safe in the past, they are safe now is exactly the kind of reasoning which allows people, and particularly the young, to dismiss risks and behave accordingly.

It is human behaviour, ignoring and underestimating the risks, that has driven the pandemic, with tragic consequences around the world as governments failed to impose restrictions appropriately and individuals failed to take precautions.

But logical and probabilistic reasoning elude most human beings, even the most highly educated of adults. So how are we to help the young develop a more sophisticated approach to managing risk, avoiding both risky and excessively cautious reactions in this new world?

Research (and even public discussion) in this area has hardly begun, yet schools are on the frontline for fostering the responses of the young. There is some research which offers suggestions of what might be useful.

Developing appropriate mental models

All the research we have suggests that trying to teach children and adolescents to manage Covid risk on the basis of reasoning about statistical probabilities is doomed to failure – as noted above, human beings simply don’t think that way.

We are far more likely to succeed by going with the flow: helping the young to develop and use mental models that will better support them in assessing and responding appropriately to risk from this new source. That is a challenge in itself.

In many ways, the risk from Covid is more like the risk from an invisible spirit world than from a visibly charging rhino: we cannot see the virus, and given the low incidence of symptomatic illness especially after the vaccine programme, there may be no visible cues as to a source of risk, even when it is ourselves.

The challenge is to help the young to develop mental models that encompass this invisible threat in constructive ways. Too much fear of this enemy will paralyse, fuelling anxieties and mental health problems. Too little will enable risky behaviours that can easily exacerbate the problem for both the individual and society.

Fostering better mental models of illness and infection

One of the problems in fostering mental models appropriate in managing Covid risk is that the young have surprisingly poor understanding of illness and infection (Bibace & Walsh, 1981). This is not because they lack the capacity to understand such things, but because they have not been given the information they need for understanding in this area. Even 18-year-olds often lack the information required to understand illness (Veldman et al, 2000). However, even very young children can develop quite sophisticated understanding where life experience such as a serious illness in themselves or family exposes them to good medical information (Crisp et al, 1996).

A first obvious step then is to foster better understanding of biological and medical matters pertinent to the transmission and impact of Covid in order to inform the mental models which the young will access in assessing risk. Assume nothing: even the idea that the threat may be invisible may be a new insight to the very young; even adolescents may have naïve views of transmission of the virus, or its ability to affect them (for example, long Covid).

Encouraging a balanced approach to the risks

We in rich Western countries had got used to living in a world where medicine had overcome most of the infectious diseases that frightened our great grandparents (TB, diptheria, polio), a world where antibiotics fixed most problems.

We have no experience of living on a daily basis with the risk of incurable infections as our ancestors did. Their folk wisdom in accepting and managing such risk has gone from our collective memory.

What the young – and society as a whole – needs is to redevelop that kind of wisdom. We’d rather go back to feeling completely safe again, but that is unlikely to be possible any time soon (and in any case, antibiotic resistance poses threats beyond this virus).

What we need is a nuanced approach to balancing the relative risks and gains of this or that way of living. Of course, there is as yet no collective view, no definitive recipe on how to do this. The best we have is government and expert advice, but that is often contradictory (one expert disagreeing with another, or different areas of government espousing different views) or confusing (you can have a cleaner in your home but not a relative).

In the end, each individual will have to resolve the problem of an appropriate lifestyle for themselves. But such resolutions are likely to reflect emerging social norms. There is much to be said for classroom discussions about what such norms should be in helping adolescents develop a balanced view.

Developing personal thresholds for risk

For the very young child, it is appropriate for parents and schools to determine what is or is not an appropriate level of risk. But as they start to become more independent in middle childhood and adolescence, the young must begin to set thresholds of risk for themselves.

There will be strong individual differences in this: some will be very risk-averse, perhaps excessively so. Others will be blasé, dismissing or down-playing the danger, sometimes as a genuine reflection of the level of risk they perceive as appropriate for themselves, sometimes in a boastful bravura.

In an ideal world, we would be able to reduce this diversity: fostering more courage in the excessively anxious, more caution in the excessively risky.

Again, classroom discussion may be a useful tool in that process, exposing individuals to other thoughts and opinions. Two ideas are worth emphasising in such debates.

First, we must all take responsibility for our actions, and that requires us to reflect on what the consequences of doing this or that may be. Second, while it is appropriate for individuals to decide how risky or risk-averse they want to be, it is irresponsible to make decisions that could damage others.

Special issues for teenagers?

Adolescents often take risks which seem absurd to their elders. One theory was that this reflects a gross dismissal of risk because teenagers imagine themselves to be invincible, but the evidence does not support that view (Shatkin, 2017).

An alternate theory that has gained ground in recent years suggests that adolescent risk-taking reflects imbalances in brain development: that emotional areas of the brain, which promote the attractions arising from riskier behaviours, develop before those areas of the brain which support self-regulation and self-control.

As a result, emotions dominate adolescent thinking and the executive control needed to inhibit impulsive behaviour is limited (Casey et al, 2008). This suggested to some commentators that it might be futile to try to foster better risk analysis in teenagers, until brain structures had matured.

However, this “neurological imbalance” theory is very controversial, and has been strongly challenged in a major review (Romer et al, 2017). The data taken to support it can be interpreted in other ways. The evidence suggests that poor executive control over impulsive action in adolescence is actually characteristic only of a subset of teenagers. And age-related improvements in executive control seem to be associated with increases in information relevant to specific risks, rather than neurological change.

In sum, there is no reason why teenagers cannot benefit from enriched mental models of infectious illness in general and the transmission of Covid in particular, and from explicit consideration of appropriate thresholds of risk. Indeed, this is the age group most likely to benefit from such interventions.

  • Dr Stephanie Thornton is a chartered psychologist, author and lecturer in psychology and child development. She is the co-author of Understanding Developmental Psychology (Macmillan International/Red Globe, 2021). The fourth article in this series is due out next week. To read her previous articles in SecEd, go to

Further information & references

  • Bibace & Walsh: New directions for child development: Children’s conceptions of health, illness and bodily functions, Jossey-Bass, 1981.
  • Bryant & Nunes: Children’s understanding of probability, Nuffield Foundation, 2012.
  • Casey et al: The adolescent brain, Developmental Review (28), 2008.
  • Crisp et al: The impact of experience on children’s understanding of illness, Journal of Pediatric Psychology (21), 1996.
  • Dillard et al: Unrealistic optimism in smokers: Implications for smoking myth endorsement and self-protective motivation, Journal of Health Communication: International Perspectives (11), 2006.
  • Kahneman et al: Judgement under uncertainty: Heuristics and biases, Cambridge University Press, 1982.
  • Little: Children’s risk-taking behaviour: Implications for early childhood policy and practice, International Journal of Early Years Education (14), 2006.
  • Johnson-Laird: Mental Models, Harvard University Press, 1983.
  • Piaget: Genetic Epistemology, Columbia University Press, 1968.
  • Romer et al: Beyond stereotypes of adolescent risk taking: Placing the adolescent brain in developmental context, Developmental Cognitive Neuroscience (27), 2017.
  • Shatkin: Born to be wild, Tarcher Perigee, 2017.
  • Veldman et al: Illness understanding in children and adolescents with heart disease, Heart (84), 2000.


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