Why does policy change not lead to citizen behavior change?

Policy defines what should happen. Behavior determines what actually happens. The gap between the two is often enormous, and it follows the same pattern seen in organizational change: people can understand, agree with, and even value a policy while still not complying with it.

A classic example: pre-booked vaccination appointments in Uppsala County, Sweden increased vaccine uptake by 11.7 percentage points compared to a control group that required people to opt in. The policy (vaccination availability) was identical for both groups. The behavioral design was different. Pre-booking reduced the opportunity barrier (effort required to schedule) and leveraged default effects (automatic motivation: it is easier to keep an appointment than to make one).

COM-B analysis reveals why policy alone is insufficient.

Policy typically addresses motivation (creating incentives or penalties) and opportunity (making services available). But it rarely addresses capability (does the citizen know how to navigate the process?), automatic motivation (does the old behavior feel easier?), or social opportunity (are peers complying?).

Behavioral science brings three capabilities to policy design. First, diagnostic precision: identifying which specific barriers prevent compliance for which specific populations, rather than assuming one-size-fits-all solutions. Second, intervention design using BCTs and implementation strategies: tested techniques for changing behavior rather than relying solely on information campaigns. Third, iterative testing: piloting behavioral interventions before scaling, measuring behavior change (not just awareness), and adapting based on evidence.

Government teams that integrate behavioral science into policy implementation consistently find that small design changes (simplifying forms, changing defaults, adding social proof messaging, reducing steps) produce larger compliance gains than large communication campaigns.