What Does “Behaviour Change Science” Study?

This is an introductory post about this paper. The paper introduces to the object of study in “behaviour change science”, i.e. complex systems – which include most human systems from individuals to communities and nations.

In a health psychology conference many years ago (when we still travelled for that sort of thing), I wandered into the conference venue a bit late, and the sessions had already started. There was just one other person in the hallways, looking a bit lost. I was scared to death of another difficult-to-escape presentation cavalcade about how someone came up with p-values under 0.05, so I made some joke about our confusion and ended up preventing his attendance, too. Turned out he was a physicist recently hired in a behavioural medicine research group, sent to the conference to get his first bearings about the field. Understandably, he was confused with a hint of distraught: “I don’t understand a word about what these people talk about. And I’ve been to several sessions already without having seen a single equation!” (nb. if you don’t think this is funny, you’re probably not a social scientist.)

Given that back then I was finding my first bearings on network science, we had a lot to talk about during the rest of the conference. I don’t remember much about the conference, but I remember him making an excellent point about learning: The best way to learn anything is to talk to someone who’s just learned about the thing. While not yet mega-experts, they still have an idea of where you stand, and can hence make things much more understandable than those, who already swim in a sea of concepts unfamiliar to you.

In a recent paper about behaviour change as a topic of research, we tried to do exactly this. I know I’m crossing the chasm where I’m not yet the mega-expert, but am already losing the ability to see what people in my field find hard to grasp. I presented the paper in a research seminar and people found it quite challenging, but on the other hand, I’ve never seen such ultra-positivity from reviewers. So maybe it’s helpful to some.

This impeccably written manuscript provides a thorough, state-of-the-art review of complex adaptive systems, particularly in the context of behavior change, and it does an excellent job explaining difficult concepts.

– Reviewer 2

Here’s a quick test to see if it might be valuable to you. Have a look at this table, and if you think all is clear, you can skip the piece with good conscience:

I also made a video introduction to the topic. If you’re in a rush, you can just run through a pdf of the slides.

If you’re in an even bigger rush, the picture below gives a quick synopsis. To find out more, check out this post: www.mattiheino.com/besp.

Complexity perspectives on behaviour change interventions

I had the great pleasure to be involved in organising a symposium on the topic of my dissertation. Many if not most societal problems are both behavioural and complex; hence the speakers’ backgrounds varied from systems science, and psychology to social work and physics. Below is a list of video links along with a short synopsis of the talks. See here for other symposia in the Behaviour Change Science and Policy series.

A live-tweeting thread on 1st day here, 2nd day (not including presentations by me, Nanne Isokuortti or Ira Alanko) here. See here for the official web page, and here for the YouTube playlist!

Nelli Hankonen: Opening words & introduction to the Behaviour Change Science & Policy (BeSP) project

  • See here for videos of previous symposia (I: Intervention evaluation & field experiments; II: Behavioural insights in developing public policy and interventions; III: Reverse translation: Practice-based evidence; IV: Creating real-world impact: Implementation and dissemination of behaviour change interventions)

Marijn de Bruijn: Integrating Behavioural Science in COVID-19 Prevention Efforts – The Dutch Case

  • Behaviour change efforts for COVID-19 protective behaviours are operations on a complex system’s user experience: A virus is the problem, but behaviour is the solution.
  • Knee-jerk communication responses of health officials can be improved upon by using methods derived from what works in real-world behavioural science interventions.
  • Protective behaviours entail feedback dynamics: for example, crowding leads to difficulty maintaining distance, which leads to perceiving that others don’t consider it important, which leads to more crowding, etc.

Nelli Hankonen: Why is it Useful to Consider Complexity Insights in Behaviour Change Research?

  • Complexity-informed approaches to intervention have been around for a long time, but only recently analytical methodology has become widely available.
  • There are important differences between “complicated” and “complex” behavioural interventions.
  • By not taking the complexity perspective into account, we may be missing opportunities to properly design interventions.

Olli-Pekka Heinonen: Complexity-Informed Policymaking

  • If a civil servant wants to be effective, maximum control doesn’t work – even what constitutes “progress” can be difficult to ascertain.
  • Systems, such as the society, move: what worked yesterday, might not work today.
  • Hence continuous learning, adaptation and experimenting are not optional for societal decision-making.

Gwen Marchand: Complexity Science in the Design and Evaluation of Behaviour Interventions

  • What does it mean to define behavior and behavior change from a complex systems perspective?
  • Focal units and well-defined timescales are key considerations for design and research of intervention 
  • Context acts to constrain and afford possible states for behavior change related to intervention

Jari Saramäki: How do Behaviours, Ideas, and Contagious Diseases Spread Through Networks?

  • People are embedded in networks that influence their behaviour and health
  • Network structure – how the networks’ links are organized – strongly affects this influence
  • Interventions that modify network structure can be used to promote or hinder the spread of influence or contagion.

Matti Heino: Studying Complex Motivation Systems – Capturing Dynamical Patterns of Change in Data from Self-assessments and Wearable Technology

  • Analysis of living beings involves addressing interconnected, turbulent processes that vary across time.
  • Recruiting less individuals and collecting more data on fewer variables, may be a considerably beneficial tradeoff to better understand dynamics of a psychological phenomenon.
  • Methods to deal with such data include building networks of networks (multiplex recurrence networks) and assessing early warning signals of sudden gains or losses.

If you’re interested in the links, download my slides here. I actually forgot to show what a multiplex network of variables combined from several theories looks like (you don’t condition on all other variables, so you can combine stuff from different frameworks without the meaning of the variables changing, as in a regression-based analysis). Anyway, it looks like this:

A single person’s multiplex recurrence network, i.e. a network of recurrence networks of work motivation variables queried daily for 30+ days. Colored connectors are relationships which can’t be attributed to randomness.

Nanne Isokuortti: From Exploration to Sustainment – Understanding Complex Implementation in Public Social Services

  • Illustrate the complexity in an implementation process with a real-world case example
  • Introduce Exploration, Preparation, Implementation, and Sustainment (EPIS) Framework
  • Provide suggestions how to aid implementation in complex settings

Ira Alanko: The AuroraAI Programme

  • The Finnish public sector is taking active steps to utilise AI to make using of  services easier
  • AI has opened a window for a systemic shift towards human-centricity in Finland
  • The AuroraAI-network is a collection of different components, not a platform or collection of chatbots

Daniele Proverbio: Smooth or Abrupt? How Dynamical Systems Change Their State

  • Natural phenomena don’t necessarily follow smooth and linear patterns while evolving.
  • Abrupt changes are common in complex, non-linear systems. These are arguably the future of scientific research.
  • There exist a limited number of transition classes. Understanding their main drivers could lead to useful insights and applications.

Ken Resnicow:  Behavior Change is a Complex Process. How does that impact theory, research and practice?

  • Behavior change is a complex, non linear process.
  • Sudden change is more enduring than gradual change.
  • Failure to replicate prior interventions can be understood from a complexity lens.

(nb. on the last talk: personally, I’m not a huge fan of mediation analysis, moderated or otherwise. Stay tuned for an interview where I discuss the topic at some length with Fred Hasselman)

Notes from the symposium by Grace Lau

The Power of Inflexibility in Improving Science and Fighting COVID-19

In case you’re new to this blog, you might not be aware of the ongoing crisis of confidence—also known as the Replication Crisis—in social and life sciences, including but not limited to psychology, medicine and economics. (To learn more, see weeks I-II of my course Critical Appraisal of Research Methods and Analysis.)

In short, major problems include:

  • Less than half (exact number depending on the field) of studies can be replicated
  • Way too few studies can be computationally reproduced, that is, getting the same results from the same data and same analysis code
  • Research tends to ignore context, making generalisability difficult
  • Published studies are reported intransparently, so it’s hard to tell what was actually done – and if p-hacking practices were used (e.g. the results were cherry picked from a large pool of random data)
  • … etc.

There are several initiatives to address these concerns, but where do they spring from, and how can we eventually fix science in large scale? I’m going to suggest a solution which will rub a lot of people the wrong way. Incidentally, it is the same tool we need to fight the Coronavirus. But first, we need to understand Nassim Taleb’s presentation of the minority rule.

The basic idea is, that under particular conditions, once a stubborn niche population reaches a small level such as 3-4% of the total population, the majority will have to submit to the preferences of the minority. For example, consider a children’s party, where the organiser needs to make the decision on whether to offer milk products, as some of the guests are lactose-intolerant. Let us call these the inflexible ones: They would suffer great harm from milk products, so they avoid them. The majority of the guests, the flexible ones, can consume both lactose-free products, as well as those which contain milk. Given that the lactose-free supplies are easily available and of not significantly inferior quality, it makes the organiser’s (as well as those party guests who are inflexible) life much easier to serve no milk products at all.

As another example, during my previous life as a business person, I did a degree where my peers were about 50% Finnish, and 50% other nationalities ranging all the way from Russia to Peru. Us Finns spoke Finnish with each other, but whenever a non-Finnish person entered the group, we switched to English. The proportion of non-Finnish speakers was irrelevant, whenever it was above 0%.

So, an inflexible minority can drastically affect how the majority acts. But the infexibility can also stem from one’s worldview; if you had to decide on a daytime activity with a bunch of friends during Ramadan, and one of them was Muslim, you wouldn’t go to a steak house.

What does this mean for improving science and weakening the Coronavirus?

  • In order to promote good research, transparency advocates need to be inflexible about questionable research practices. To the point that they lose potential career opportunities – although they may, in turn, gain better ones as they can work with likeminded people.
  • In order to smash COVID-19, citizens need to be inflexible about risk behaviours. To the point that some people consider them overzealous and rigid – although it may not matter, if it leads to surviving the crash.

Both of these causes have a very important fractal, or multiscale component: Much of the action is not top-down but happens bottom-up; the individual reels in their family (or immediate research group), who then become norm-setters in their apartment building/neighbourhood (or scientific society of their research area), who again affect local governance (or scientific discipline).

But there are at least three crucial success factors for the behaviour change effect to work:

  1. The inflexible group needs to be spatially spread widely, instead of being confined in particular geographic (or intellectual) pockets, in which case the majority can just isolate and ignore them.
  2. The cost of aligning with the inflexible group needs to be small for the flexible group. For minority members to change behaviour, therefore, it may be necessary to take up some of its costs to the majority – at least initially. The other option is to move steps that are so small they are almost imperceptible.
  3. Crucially, the inflexible group… Does. Not. Budge. People always tend to say that one “must not be so strict”, but there is a reason it is not okay to steal, murder, or cheat upon your spouse “just a bit”. If the inflexibles are perceived to be flexible, after all, the majority can expect to dominate over them.

no_stretching_alora-griffiths-WX7FSaiYxK8-unsplash
No rest for the wicked, and no stretching for the inflexible! (Photo: Alora Griffiths on Unsplash)

For our case examples, spatial spread is mostly taken care of: The internet has done much to allow for the minority members to connect, while being perhaps the only ones in their own immediate vicinity passionate about their cause. So I’ll address #2-#3.

Lowering the cost of transparency: In the scientific transparency scene, this means the minority representatives need to spend tons of time learning about transparent research practices (e.g. pre-registration and data sharing, the TOP Factor, etc.). This knowledge they can then either disseminate to the rest of their research group, or act as the person who does most of the heavy lifting required in reporting reproducible work.

Lowering the cost of Coronavirus safety: The anti-Coronavirus advocates, on the other hand, need to make information easily available (as they do in endcoronavirus.org), share it, and translate it – both literally and figuratively. An example would be sharing research studies, ways to make and wear masks correctly, or how to acquire them (if you’re in Finland, check this out to have masks made for you, while donating some to healthcare workers). They may also need to learn about technicalities of video conferencing and other solutions, so that they can readily teach their peers after refusing face-to-face meetings.

Not budging in research transparency: The research transparency people obviously need to refuse co-authoring papers which contain p-hacking, hyperbole or other ways of distorting the findings to improve chances of publication. They need to refuse projects which do not plan to share analysis code (and data, within privacy constraints), ask about transparency before peer reviewing, and walk away from papers where the first author insists on presenting exploratory hypotheses as confirmatory ones, or is not willing to properly discuss constraints to generalisability, model assumptions (stationarity, homogeneity, independence, interference, ergodicity… see here if these are strange words) and sensitivity analyses.

Not budging in Coronavirus safety: The anti-Coronavirus folks need show example by performing hand hygiene, self-isolating, wearing masks, social distancing, and taking their kids off school/daycare – but also making sure their family does the same. In addition, they need to speak out when they see their friends or neighbours acting out risk behaviours, such violating the 2-meter (6-feet) physical distance requirement. They need to make it clear they are only available for meetings via video conferencing, which they’re happy to help setting up.

Remaining steadfast and vocal is not for everyone, and calling out behaviour you perceive to be wrong, can be extremely anxiety-provoking. That’s also why one needs to start with those closest to them. And it is hard to be inflexible in the beginning, when the majority norms are against you and everyone is expected to play along. The “happy” news is, that not everyone needs to be inflexible – just the small minority. (I’m putting happy in quotes, because the minority rule can be leveraged to gradually promote any fascist ideology the majority is foolish enough to tolerate.)

Hence, if you’re the type of person who feels strongly enough to be inflexible about these things, perhaps you can feel comforted by the idea that you don’t need to convert the majority: The stubborn few can create the critical mass and change the world.

Pathways and complexity in behaviour change research

These are slides of a talk given at the Aalto University Complex Systems seminar. Contrasts two views to changing behaviour; the pathway view and the complexity view, the latter being at its infancy. Presents some Secret Analysis Arts of Recurrence, which Fred Hasselman doesn’t want you to know about. Includes links to resources. If someone perchance saw my mini-moocs (1, 2) and happened to find them useful, drop me a line and I’ll make one of this.

Lifestyle factors are hugely relevant in preventing disease in modern societies; unfortunately people often fail in their attempts to change health behaviour – both their own, as well as that of others’. In recent years, behaviour change design has been conceived as a process where one identifies deficiencies in factors influencing the behaviours (commonly called “determinants”). Complexity thinking suggests putting emphasis on de-stabilisation instead.

The perspective taken here is mostly at the idographic level. At the time of writing, we have behaviour change methods to affect e.g. skills, perceived social norms, attitudes and so forth – but very little on general de-stabilisation of the motivational system as an important predictor of change.

Perspectives are welcome!

ps. Those of you to worry about brainwashing and freedom of thought: Chill. Stuff that powerful doesn’t really exist, and if it did, marketers would know about it and probably rule the world. [No, they don’t rule the world, I’ve been there]

pps. Forgot to put it in the slides, but this guy Merlijn Olthof will perhaps one day tweet about his work about destabilisation in psychotherapy contexts. Meanwhile, you can e.g. be his 10th Twitter follower, or keep checking his Google Scholar profile, as there’s a new piece coming out soon!

Complexity considerations for intervention (process) evaluation

For some years, I’ve been partly involved in the Let’s Move It intervention project, which targeted dysfunctional physical activity and sedentary behaviour patterns of older adolescents, by affecting their school environment as well as social and psychological factors.

I held a talk at the closing seminar; it was live streamed and is available here (on stage starting from about 1:57:00 in the recording). But if you were there, or are otherwise interested in the slides I promised, they are now here.

For a demonstration of non-stationary processes (which I didn’t talk about but which are mentioned in these slides), check out this video and an experimental mini-MOOC I made. Another blog post touching on some of the issues is found here.

 

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