Why Training in Cognitive Science Matters for Behaviour Change

~ Pavan Mamidi, Director, and Anandita Lidhoo, Deputy Manager, Centre for Social and Behaviour Change, Ashoka University

Behaviour change is often framed in terms of incentives, information, and motivation. But beneath all of these lies a more fundamental question: how do people actually process the world around them? This is where cognitive science becomes indispensable.

At its core, behaviour change is about helping people notice, interpret, and act differently in their everyday environments. That is not possible without understanding attention, perception, memory, emotion, and decision-making (Kahneman, 2011; Mullainathan & Shafir, 2013). Behaviour does not emerge in a vacuum. It is shaped by what people attend to, how they interpret information, what feels effortful, and what feels possible in a given moment.

This is why cognitive science is not a peripheral input into behaviour change work. It is foundational. And applying it well requires more than intuition. It requires training through theory and experience.

One of the clearest contributions of cognitive science is its explanation of how mental bandwidth affects decision-making. People do not make choices under neutral conditions. Their cognitive resources are shaped by stress, time scarcity, uncertainty, and competing demands. When cognitive load is high, the ability to process information and act on it is reduced (Mullainathan & Shafir, 2013; Shah et al., 2012).

For practitioners, this has immediate implications. Interventions that are too complex, too text-heavy, or poorly timed often fail not because people lack intent, but because they demand more cognitive effort than individuals can afford (Sweller, 1988). This becomes especially visible in frontline systems. Community workers, for instance, are often expected to communicate large volumes of information clearly and persuasively.

But when their own cognitive bandwidth is constrained, even well-designed messages can break down in delivery. Designing for behaviour change in such contexts is not only about what is communicated, but how much cognitive effort is required at every step, for both providers and beneficiaries.

Cognitive science also helps explain why information alone is often insufficient.

In work on exclusive breastfeeding, awareness was not the primary barrier. Mothers often knew what was recommended. The challenge lay in how these decisions were embedded within family structures, particularly the influence of mothers-in-law. When communication was redesigned to align with these dynamics, by positioning senior family members as enablers rather than barriers, behaviour became more likely to shift (Cislaghi & Heise, 2018).

Similarly, large-scale public health efforts have shown how making consequences cognitively salient can shift behaviour. Campaigns addressing anaemia have been more effective when they connect abstract health risks to personally meaningful goals, such as aspirations for strength, caregiving, or achievement. By making the cost of inaction visible in everyday terms, these interventions work with, rather than against, how people evaluate trade-offs (Tversky & Kahneman, 1974; Thaler & Sunstein, 2008).

The same principle applies to risk perception. During vaccination campaigns, communicating potential consequences through emotionally and socially relevant scenarios has often proven more effective than presenting statistical information alone. People do not respond to information in a neutral way. They respond to what feels immediate, meaningful, and real (Loewenstein et al., 2001; Betsch et al., 2015).

Choice architecture offers another clear example. When environments are structured so that the desired behaviour is more visible, accessible, or easier to perform, behaviour shifts without requiring active deliberation.

The Behavioural Insights Team UK and the NHS demonstrate this through the power of defaults: when organ donation systems move from opt-in to opt-out, participation rates increase significantly (Johnson & Goldstein, 2003; Thaler & Sunstein, 2008). Such effects arise from how cognitive systems respond to effort, inertia, and perceived norms.

Frameworks such as the COM-B model help translate these insights into practice. Capability includes not only knowledge and skills, but also attention and cognitive bandwidth. Opportunity depends not only on what exists objectively, but on what individuals perceive as accessible or relevant. Motivation is shaped by affect, expectations, and beliefs about outcomes (Michie et al., 2011).

For a practitioner, this means behaviour change cannot be designed at the level of surface behaviour alone. It must engage with the cognitive processes that produce that behaviour.

This is where training becomes critical.

Without training in cognitive science, there is a risk of designing interventions based on observation rather than mechanism. Problems may be misdiagnosed. Low uptake, for instance, may be attributed to lack of awareness, when the real constraint lies in service quality, trust, or cognitive overload. In complex systems such as healthcare, what appears to be a demand-side issue may in fact be rooted in supply-side constraints that shape how services are experienced (Banerjee & Duflo, 2011).

Training enables practitioners to move beyond these surface interpretations. It allows them to identify when behaviour is shaped by bandwidth constraints, when it is driven by social norms, and when it reflects rational responses to uncertainty rather than cognitive error.

This becomes particularly important when applying concepts such as present bias. These frameworks are useful, but they can be misapplied if stripped from context. When individuals are navigating unstable conditions, prioritising the present may not simply reflect a bias. In contexts of scarcity, what we label as bias may, in fact, be a form of risk management under uncertainty (Laibson, 1997; Mullainathan & Shafir, 2013).

Without a grounding in cognitive science, there is a risk of treating such behaviour as a problem to be corrected, rather than a reality to be understood and designed for.

Across the lifecycle of an intervention, from diagnostics to design to implementation, cognitive training shapes how problems are defined and how solutions are built. It influences how field researchers interpret behaviour, how programmes reduce friction, how communication is structured, and how systems are adapted for real-world use.

When behaviour change fails, it is often not because people resist change, but because interventions fail to account for how cognition operates under constraint.

As behavioural challenges grow more complex, this understanding becomes increasingly important. Training in cognitive science equips practitioners with the tools to design interventions that are not only effective, but also grounded in how people actually think, perceive, and act within their environments.

Without it, behaviour change risks remaining intuitive but incomplete. With it, it becomes more precise, more humane, and more aligned with the realities it seeks to transform.