Behaviour change is a fundamental component of social marketing programs. The pandemic has created new challenges and opportunities for social marketers (like me), behavioural economists and others who fall under the umbrella of behavioural science. We will encounter new post-pandemic behaviours to address and may find that previous approaches are no longer practical or as effective as they were pre-pandemic. Like many in the behavioural sciences, I too have been horizon scanning and pondering the possible behaviour change futures that may unfold. I’ve organised my initial thoughts on what this brave new world will look like into three themes.
Theme 1: Apathy and resistance to behaviour change in a post-pandemic world.
Apathy has been somewhat of a sidenote in social marketing and behavioural economics. We know it exists, yet it is rarely discussed among the behaviour change community or documented in our projects. In 2003, Peattie and Peattie (p. 377) identified apathy as a competing idea, what they called a “deadening hand that prevents behaviour change adoption”. My initial thoughts are that widespread change fatigue will be the natural result in our post-pandemic world due to the experience of rapid and continuous change throughout the pandemic. This change fatigue may lead to a more conspicuous presence of apathy among the population, which undermines interest in behaviour change. When compared to the upheaval of a pandemic, some people may perceive concerns about particular behaviours as trivial or relatively harmless.
Similarly, as social marketing is linked to the agendas of governments, resistance may also become more pronounced. The pandemic shone a light on the role and span of power of governments of which many Australians were unaware. Circulating conspiracy theories added to what seems to be more widespread questioning and scepticism of what governments are seeking to achieve. It would seem probable that social marketers and other behaviour change agents working with governments may experience more conspicuous resistance from participants. Non-participation is a form of resistance. Non-participation biases results, leading to inaccurate conclusions and it would seem sensible to monitor, report and discuss it in this brave new world.
Theme 2: Doing battle with the infodemic.
Too little information, too much information, misinformation and disinformation are real threats to post-pandemic behavioural sciences. The World Health Organisation[i] highlighted that the infodemic “causes confusion and increases risk-taking behaviours”. They offer four infodemic management activities to enable good health, which might be considered by the broader behaviour change practitioner community. The four activities are:
- Listening to community concerns and questions;
- Promoting understanding of risk and health expert advice;
- Building resilience to misinformation; and
- Engaging and empowering communities to take positive action.
Beyond our participants, governments, mid-stream institutions and behaviour change practitioners are not immune from the infodemic. Sharpening our critical thinking skills and recalibrating our knowledge curation processes and reviewing our information dissemination practices may be needed.
Theme 3: The quantum leap in the social machine —accelerated digital adoption, AI-powered predictions and mass digital surveillance.
The pandemic both accelerated and amplified the rise of digital technology[ii], assisting governments, institutions, businesses, communities, families and individuals. The globe, it seemed, turned to technology leading to a quantum leap in the acceptance of digital solutions, enabling us to attempt to predict, prevent and personalise behaviours[iii].
Globally, we have manifested the age of the social machine. The social machine is a step forward in human-computer relationships where shared digital infrastructure (e.g., apps, platforms) not only connect people but “invisibly orchestrate our social processes and help us achieve the previously impossible…[creating] digitally connective tissue” that mediates “interactions among individuals on unprecedented scales and with unprecedented efficiency”[iv].
Professionally and personally, we have collectively digitally upskilled during the pandemic, accelerating the merging of a wide range of social processes with machines. More than ever, it seems, we are feeding data into systems. These systems use AI to process our data and then present back to us algorithmic solutions and predictions that shape our decision making. Furthermore, during the pandemic, mass digital surveillance emerged around the world as a tool to manage COVID-19, primarily by assisting with contact tracing[v]. There have been mixed responses to mass digital surveillance that will continue to evolve post-pandemic.
The quantum leap in the social machine will change behavioural sciences in big and small ways. For example:
- our post-pandemic project funders’ needs and expectations may shift;
- new or previously hidden post-pandemic behaviours may surface through mass digital surveillance;
- our traditional sources of evidence of behaviour change may be superseded or require expansion;
- some of our analogue tools, techniques and processes for bringing about behaviour change may require digital renewal, requiring new practitioner skills and resources; and
- our participants armed with enhanced adaptability, self-efficacy and problem-solving from the pandemic may choose to address their own behaviour either in full or in part.
Recommendations for behavioural science researchers and research students.
The post-pandemic world will be the coming of the ‘VUCA world’ where volatility, uncertainty, complexity and ambiguity will require new ideas and radical creativity in the behavioural sciences. I offer the following recommendations for established or emerging behavioural science researchers as we enter this brave new VUCA world.
My overarching recommendation is to sharpen your VUCA foresight and insight and encourage you to:
- Pay attention to the speed, nature, dynamics and catalysts of change in your social cause and observe how they impact behaviour change among your program participants, yourself and relevant institutions in the broader ecology.
- Deepen your understanding of your social cause including its links to systemic failures, unpredictable situations, surprise events and confusion.
- Be open to the absence of clear cause-and-effect relationships and extended chains of events (some random) that have created a particular behaviour.
- Declutter your behaviour change toolkit editing out ineffectual pre-pandemic approaches so as to make space for new techniques to address apathy, the infodemic and the social machine.
Overall, I encourage you to spend time pondering the different behavioural science futures that may unfold. What additional ‘big-picture’ themes would you add to my list?
*This blog is based on my BEST 2022 Round Table Discussion presentation delivered on 11 February 2022.
Professor Maria Raciti is a social marketer at the University of the Sunshine Coast. To learn more about Maria and her research, please visit her research profile https://www.usc.edu.au/staff/professor-maria-raciti
[ii] Renu, N. (2021). Technological advancement in the era of COVID-19. SAGE Open Medicine, [online] 9, p.205031212110009. Available at: https://journals.sagepub.com/doi/full/10.1177/20503121211000912.
[iii] Radanliev, P., De Roure, D., Walton, R., Van Kleek, M., Montalvo, R.M., Santos, O., Maddox, L. and Cannady, S. (2020). COVID-19 what have we learned? The rise of social machines and connected devices in pandemic management following the concepts of predictive, preventive and personalized medicine. EPMA Journal, 11(3), pp.311–332. https://doi.org/10.1007/s13167-020-00218-x
[iv] Shadbolt, N., Van Kleek, M. and Binns, R. (2016). The rise of social machines: The development of a human/digital ecosystem. IEEE Consumer Electronics Magazine, 5(2), pp.106–111. https://doi.org/10.1109/MCE.2016.2516179.
[v] Ram, N. and Gray, D. (2020). Mass surveillance in the age of COVID-19. Journal of Law and the Biosciences, 7(1), pp. 1-17. https://doi.org/10.1093/jlb/lsaa023