At-tractor what-tractor? Tipping points in behaviour change science, with applications to risk management

Back in 2020, our research group was delivering the last of five symposia included in a project called Behaviour Change Science and Policy (BeSP). I was particularly excited about this one because the topic was complexity, and the symposia series brought together researchers and policy makers interested in improving the society – without making things worse by assuming an overly narrow view of the world.

I had a particular interest in two speakers. Ken Resnicow had done inspiring conceptual work on the topic already back in 2006, and had been an influence on both me and my PhD supervisor (and BeSP project lead) Nelli Hankonen, in her early career. Sadly, the world hadn’t yet been ready for an extensive uptake of the ideas, and much of the methodological tools were inaccessible (or unsuitable) to social scientists. The other person of particular interest, Daniele Proverbio, on the other hand, was a doctoral researcher with training in physics and systems biology; I had met him by chance at the International Conference on Complex Systems, which I probably wouldn’t have attended, had it not been held online due to COVID. He was working on robust foundations and real-world applications of systems with so-called tipping points.

I started writing a paper with Ken, Daniele, Nelli and Gwen Marchand, who was also speaking at the symposium, as she had been working extensively on complexity in education. The paper started out as an introduction to complexity for behaviour change researchers, but as I took up a position in the newly founded behavioural science advisory group at the Finnish Prime Minister’s Office late 2020, the whole thing went to a back burner. It wasn’t just that, though. Being a scholar of motivation, I knew that being bored of your own words is a major warning sign, and things you prefer not to eat, you shouldn’t feed to others. So I didn’t touch the draft for over a year.

Meanwhile, I finished a manuscript which started out as a collection of notes from arguments about study design and analysis within our research group, when we were doing a workplace motivation self-management / self-organisation intervention. The manuscript demonstrated, how non-linearity, non-ergodicity and interdependence can be fatal for traditional methods of analysis. It was promptly rejected from Health Psychology Review, the flagship journal of the European Health Psychology Society – on the grounds that linear methods can solve all the issues, which was exactly the opposite of manuscript’s argument. That piece was later published in Behavioural Sciences, outlining the foundations of complex systems approaches in behaviour change science.

As the complexity fundamentals paper had now been written, I wasn’t too keen on continuing on our BeSP piece, before I was hit by a strange moment where everything I had dabbled with (and discussed with Daniele) for the previous year sort of came together. I re-wrote the entire paper in a very short time, partly around analysis I had started due to natural curiosity with no particular goal in mind.

This is non-linearity in action: instead of “productively” writing a little every day, you write nothing for a very long time, and then everything at once. And this is not a pathology – except in the minds of people who think everything in life should follow a pre-planned process of gradual fulfillment. I’ve spent decades trying to unlearn this, so I should know.

The paper turned out very non-boring to me, and I was particularly happy the aforementioned flagship journal (the one which rejected the earlier piece) accepted it with no requests for edits – despite being based on the same underlying ideas as the earlier one.

Graphical abstract of the attractor landscapes paper; courtesy of Daniele Proverbio. Describes two types of tipping points in systems with attractors.
Graphical abstract of the attractor landscapes paper; courtesy of Daniele Proverbio.

Implications to risk management

The theory underlying attractor landscapes and tipping points, points to two important issues in risk management. Firstly, large changes need not be the result of large events, but small pushes can suffice, when the system resides in a shallow attractor or on the top of a “hill” in the landscape. Secondly, the fact that earlier events have not caused large-scale behaviour change, does not imply that they continue not do so in the future. This is a mistake constantly made by Finnish doctors and epidemiologists throughout the pandemic, e.g. about people’s unwillingness to take up masks – we could stop COVID, for example, but don’t do so because people have been told this attractor is inescapable.

In a recent training for public servants, we experimented with conveying these ideas to non-scientists – lots of work to be done, but some did find it an enlightening escape from conventional linear thinking.

To sum up, some personal takeaways (your mileage may vary):

  1. The quality of motivation you experience when working on something boring is information: there might be a better idea, one actually worth your time, which gets trampled as you muddle through something less attractive. Same applies to health behaviours.
  2. Remain able to seize opportunities when they arise: steer clear of projects with deadlines, and milestones in particular. They coerce you to finish what you started, instead of dropping it for a time and starting anew much later.

The astute reader may have noticed, that I did not explain the damned attractors in this post at all. You’ll find all you need here:

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