When international development programs want people to get vaccinated, the behavior they are targeting is clear, even if the complex set of things that influence that behavior take time and effort to address. Social and behavioral change (SBC) approaches have evolved in public health to address these sorts of complexities. But what about programs that want people to stop spreading misinformation or to treat each other with respect? Sometimes it is difficult to even identify what behavior to target for change.
Like many of my colleagues, I have been trying to apply the insights of behavioral science to the democracy, human rights, and governance (DRG) sector. A number of recent publications, including David McRaney’s How Minds Change: The Surprising Science of Belief, Opinion, and Persuasion (2022) and Damon Centola’s Change: How to Make Big Things Happen (2021), inspired me to think through a few implications of their findings for DRG programs that aim to do things like promote pluralism and inclusion, or expand civic and political participation.
Key concepts for practitioners to think with
The first thing to know about social change is that people are resistant to it. This idea may be surprising when we see fads and other viral phenomena sweeping the globe, but Centola shows that the things that go viral do so because they do not encounter resistance. Nor do they endure; enduring change happens when an innovation overcomes multiple forms of resistance.
Resistance to change is built into human cognition. We are both creatures of habit and ones who are attuned to social norms – the perceptions we have about how other people might perceive us. Changing behavior is hard because it means breaking habits and putting at risk how others see us. Centola elaborates other sources of resistance that we should be aware of:
coordination costs (some changes are not worth the trouble of adopting unless everyone else you know is already using it – think about learning how to use Facebook)
concerns about the credibility of the new behavior or belief (credibility requires social proof – do other people you trust believe in the health benefits of intermittent fasting? If yes, then you might, too!)
concerns about legitimacy of the new behavior or belief (change entails reputational risk for the adopter of the innovation – like when you wonder “if no one else is speaking out on this injustice, can it really be that bad?”)
Additionally, McRaney shows that changing minds is hard because humans are lazy and biased thinkers. We don’t often reflect on our own thinking, we take the path of least resistance when deciding what to do and say, and we tend to believe new information that corresponds to our existing beliefs about ourselves and the world (confirmation bias). Other research shows that people are indeed receptive to updating their beliefs when presented with new facts but tend to revert back to their old beliefs without additional reinforcement.
Finally, telling someone they are wrong or need to change also triggers a common psychological response called reactance – that stubborn feeling you get when someone tells you what to do. When people perceive facts or opinions as a threat to their autonomy or to their group’s identity (as is the case with political polarization in the United States), they are unlikely to adopt those facts or opinions. McRaney shows that avoiding reactance and changing minds is possible, but it requires one-on-one empathetic listening techniques rather than the mass-mediated campaigns typical of many DRG programs.
Implications of this research for DRG program design
The unavoidable but challenging conclusion I drew from this research is that social change interventions should target networks, not individuals. This isn’t the way that most of us design our interventions in the DRG Sector. However, the means by which social change happens (social proof, collective excitement, feelings of solidarity, and norms) are all phenomena that spread through networks.
The most striking point for me from Centola’s book is that there is a tipping point for change that tends to be at around 25% of a network. In other words, when a quarter of your friends adopt a change, you are likely to adopt it, too. This tipping point was found in numerous studies and points to an important aspect of measurement in development work: if we know what proportion of a given network has adopted the change we are promoting, we can more accurately predict how much more we need to do to make a widespread change. In other words, hovering around a 20% adoption level (a “committed minority” or “positive deviants”) for years does not necessarily mean that you are stuck; it may mean that you need to make a push for that additional five percent of the network and the rest will likely follow. To help with the research needed to design that kind of push, the Behavioral Insights Team has a useful set of resources here.
Another implication is that when development programs use influencers to spread ideas, the ideas should be simple things that do not encounter resistance. Spreading an uncontroversial idea like voter registration through social pressure or a highly centralized influencer network is effective at increasing voting behavior, but interventions driving more challenging behavior changes (such as curtailing corruption) would benefit from thinking through questions of how to address resistance coming from coordination costs and credibility. Changing petty corruption behavior entails huge coordination costs as well as making sure that new behaviors are being perceived by peers in the network, thereby shifting the norms.
Centola also points out that global north organizations advocating for a change may be less credible to organizations in the global south (and may engender reactance). To overcome this kind of resistance, south-south network building and exchange is likely to be more effective in spreading innovations because social proof needs to come from people we see as similar to us.
The second challenging conclusion I reached is that meaningful change is often incremental and depends on interpersonal interactions. McRaney shows that one-on-one conversations in the tradition of deep canvassing and street epistemology are effective at achieving small but lasting changes in attitudes and beliefs. However, one-on-one conversations are difficult to scale, making it a challenge to see how to apply these findings in development work.
My hunch is that if we combine McRaney’s persuasion techniques with Centola’s insights about the power of networks, it may take just a few targeted conversations within a particular network to trigger a cascade effect across the network. For example, in an intervention designed to increase access to government services for a stigmatized group, an effective strategy might be to do deep canvassing with, say, 25-30% of the service providers in network. If other network members interact with them enough that they are likely to see each other’s changed attitudes as “social proof” that people like them don’t discriminate, the whole network might adopt a more inclusive approach.
Designing interventions for networks would require a radical change in how implementors in the DRG sector design our programs, but it may be the key to promoting change that lasts.