Macro Unit | Week 1 - Design with BCTs I

Team: Gabrielle Bennett/ Moxue Jia/ Sebastian Ervi/ Zhaolu Song

Brief: Using the taxonomy of behaviour change techniques (BCTs) design a digital system that encourages behaviour change.

Time: 11.02.2021-18.02.2021

In the Macro UX Unit, we will work with the external partner, Centre for Behaviour Change UCL in the next six weeks.

BCT Taxonomy

On the briefing day, Dr. Paulina Bondaronek and Dr. Marion Lean showed us what is the BCT Taxonomy, the problem that technologies often don’t implement BCTs into the design and the brief. In short, BCTs, behaviour change techniques, are defined as a replicable component of an intervention designed to alter or redirect causal processes that regulate behaviour. (Carey, R. et al., 2019)

Least Used BCTs

I was amazed to see the huge amount of health apps in the market, but only a few BCTs are applied. So, during our group meeting with Dr. Paulina Bondaronek and Dr. Marion Lean, I asked them about the full list of the least used BCTs and unexpectedly, I found four-fifths BCTs are seldom used in the design process. So, I was thinking of how to apply the least used BCTs to the design and make the behaviour change to a large degree.

Least common BCTs. Picture by Centre for Behaviour Change UCL.

Our brief. Picture by Centre for Behaviour Change UCL.

The mechanism of Behavior change

The behavioral professions accept that any behavior, any choice, requires motive, opportunity, and means as necessary ingredients. Without all three, no behavior occurs (Turvey, 1999).

In order to understand what factors affecting behavior change, I did some research about the mechanism of Behavior change. The article Behavior Change Theories and Techniques analyzed the planned behavior mechanism and how the intervention affects planned behaviors (Changing Public Behavior, 2015). I found that there are two main factors influencing behavior: internal motivation and the external environment which reminds me of the least used BCTs which are related to the two factors.

An Integrative Model of Behavior. (Fishbein & Cappella, 2006)

Behaviour caused and least used BCT. Diagram by me.

Linguistic frames and behavior change

Researching the mechanism, I came across an article about how linguistic frames affect behavior change. Joseph and Sommer (2007) argue that written and spoken language contains inherent mechanisms driving motivation. It discussed that linguistic frames create an external context that strongly affects the internal thinking of each one, resulting in different behaviors.

How the different linguistic languages could affect behavior change in design? I found “Active2Gether”, which combines BCTs and a Reasoning System. It uses a model-based reasoning engine tailoring the intervention with respect and sends tailored messages and dynamically tailored feedback according to the user’s behavioral determinants, occupational status, and weather. So, I think it’s quite important to consider the tailored linguistic language within the later design process.

"Active2Gether" analysis. Diagram by me.

The next blog will show what kind of behavior our group chooses to change and practical research about that behavior.

References

1. Carey, R. et al. (2019) ‘Behavior Change Techniques and Their Mechanisms of Action: A Synthesis of Links Described in Published Intervention Literature’, Annals of Behavioral Medicine, 53(8), pp. 693–707. Doi: https://doi.org/10.1093/abm/kay078.

2. Changing Public Behavior. (2015) Behavior Change Theories and Techniques. Available at: https://fyi.extension.wisc.edu/wateroutreach/files/2016/04/CPB-Behavior-Change-TheoriesTechniques8.pdf (Accessed: 15 Feb. 2021).

3. Joseph Yeager, J. and Sommer, L. (2007) ‘Linguistic Mechanisms Cause Rapid Behavior Change Part Two: How Linguistic Frames Affect Motivation’, The Qualitative Report, 12(3), pp. 467-483. Doi: http://www.nova.edu/ssss/QR/QR12-3/yeager2.pdf

4. Middelweerd A, te Velde S, Mollee J, Klein M, Brug J, (2018). ‘App-Based Intervention Combining Evidence-Based Behavior Change Techniques With a Model-Based Reasoning System to Promote Physical Activity Among Young Adults (Active2Gether): Descriptive Study of the Development and Content.’, JMIR Research Protocols, 7(12), doi: 10.2196/resprot.7169. Available at: https://www.researchprotocols.org/2018/12/e185 (Accessed: 15 Feb. 2021)