Psychology replication crisis © Getty

Psychology is in a crisis. But not the one you’re thinking of

Can we still have faith in psychology in the face of the ‘replication crisis’? Perhaps, but the field has a much larger problem to tackle.

The last few years have seen a lot of discussion about a ‘replication crisis’ or ‘credibility crisis’ in psychology. Various scientific findings, it seems, don’t appear to be repeatable when other scientists run exactly the same experiments.

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Most of the focus in this crisis is on how scientists behave: were the original experiments biased? Was the work sloppy? Was someone gaming the system or even cheating? But perhaps a more pernicious problem is deeply rooted in how people think.

Many people who practise, use and report on the science of psychology assume that thoughts, feelings, behaviours and other psychological outcomes are the result of one or two strong factors or causes. This is called a ‘mechanistic mindset’.

Typical experiments attempt to isolate one or two variables, manipulate them and observe moderate to strong effects that are easy to replicate.

For example, if we cause people to feel angry by showing them a film clip that violates their deeply held values, a mechanistic mindset says that they should scowl, their blood pressure should rise and they should be more likely to act aggressively.

According to a mechanistic mindset, you should be able to plop this simple experiment into any scientific lab and produce very similar results.

It shouldn’t matter what time of day the experiment is run, what country it’s run in, what sex or gender the researchers are, what culture the participants come from, what they ate for breakfast or how much they slept, whether any of them are taking medication, and so on.

Such factors are treated as noise and their influence is ignored. If the experiment doesn’t produce the same observations over and over again, then the logical conclusion is that the original study was flawed and the finding is false.

A more realistic assumption, however, is that psychological outcomes do not arise from a few simple, strong factors in the first place. They emerge from an intricate web of many weak, interacting factors.

This is called a complexity mindset. The brain and the body are complex, dynamic systems. Any single variable in the system will have a weak effect. More importantly, we can’t manipulate one variable and assume that the others remain unaffected.

Our brains are complex organs that can be affected by many factors. We need to account for all the factors we can if we’re to understand how our brains work © Getty
Our brains are complex organs that can be affected by many factors. We need to account for all the factors we can if we’re to understand how our brains work © Getty

If we treat the brain and body like simple mechanistic systems, targeting one or two variables and leaving the rest unmeasured, then the impact of that fuller web of weak factors masquerades as a failure to replicate.

The absence of replication may, in fact, be the presence of meaningful variation. The structure of that variation can be discovered and modelled only when scientists design experiments to measure and observe it.

As such, psychology’s most cherished experimental method – the lab experiment – may need a major overhaul in order to observe and account for complexity.

Even when scientists carefully design experiments with complexity in mind, their results, when reported in the popular press, are often explained in mechanistic terms. News stories about science are simpler and more digestible when they have a pithy headline such as, “Brain circuit X causes fear” or “Gene Y causes depression”.

Is there a credibility crisis in psychology? Perhaps, but not the one that tongues are wagging about.

Psychological science may need to get its act together, not because its findings are unreliable, but because variation is being dismissed as noise rather than being investigated as something meaningful.

Psychological phenomena arise out of complexity, not from simple, mechanistic cause-and-effect.

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