For centuries, scholars have grappled with a deceptively simple question: How do we make choices? Early philosophers and classical economists viewed decision-making as a purely rational process, assuming people carefully weighed costs and benefits to maximize their interests. This model of economic rationality dominated much of modern history, emphasizing that to change decisions, one need only adjust costs and benefits (or people’s interests), even as psychology and neuroscience was revealing the brain’s deeper complexities.
Over time, a different picture emerged. Rather than exhaustively evaluating every possible option, our brains take a more “biologically rational” approach, honed for survival in a complex, social, and uncertain world. Far from being logic machines, we rely on cognitive shortcuts, social norms, and emotional cues. In essence, we are not designed to maximize our economic resources; we are designed to maximize our cognitive ones.
This understanding has shaped what we now often call “behavioral science”, a field that draws on psychology, behavioral economics, neuroscience, and related disciplines. Within this broader domain, Applied Behavioral Science, Behavioral Public Policy, and Behavioral Design adapt these insights to work with (rather than against) the ways people naturally think and decide. Many sectors, from public health to finance, have embraced these methods over the last few decades, designing interventions and policies that tap into social influences, emotional appeals, and choice architecture - all key elements of our decision-making. Conservation, by contrast, has often stubbornly relied on the assumption that people simply lack the right information about their choices. While that may help in some contexts, it fails to address deeper behavioral and psychological drivers behind decision-making, leaving many of our planet’s environmental challenges unmet.
Fortunately, things are finally starting to change. Although conservation has been slower to bring onboard expertise on behavior (often prioritizing the natural over the behavioral sciences), a growing set of frameworks and design tools is emerging to help practitioners bridge this gap. These resources equip conservationists to develop programs rooted in how people actually make decisions, rather than how we assume they should. By pairing ecological knowledge with proven behavioral insights, the conservation community can design more effective interventions that work for real-world settings, leading to far more lasting and scalable change that benefits both people and the planet.
With the proliferation of practitioners and policy-makers seeking to integrate behavioral science into their work, there has been a parallel explosion of behavioral frameworks and methodologies, each designed with specific goals, contexts, and user needs in mind. Some focus on design thinking, emphasizing in-depth research, iterative brainstorming, and prototyping to develop behaviorally informed solutions. Others offer simplified pathways or checklists that highlight common variables (such as social norms, cognitive biases, and choice architecture), making it easier to adapt these insights to various behavior change challenge and quickly capitalize on low-hanging fruits.
Naturally, not all frameworks are created equal, and they vary in both depth and focus. More importantly, success hinges on whether a framework is used in the way it was intended, rather than forcing an ill-fitting model onto a problem it cannot address well. In fact, some conservation initiatives do not necessarily require a behavior change component, or may need structural or sociopolitical changes in place to set the stage for an effective behavior change solution. When a framework’s original scope and design principles align with a practitioner’s objectives and context, it can guide conservationists toward more effective, evidence-based interventions. By choosing or adapting the right tools for each unique challenge (and respecting each framework’s intended applications), practitioners can more reliably create lasting results.
No single framework or methodology is universally “better” than another; each was developed with particular contexts and goals in mind. What truly matters is matching a framework’s strengths to the specific problem at hand. A simple heuristic approach might be perfect for a quick campaign that nudges every-day behaviors, whereas a major policy overhaul or a complex conservation challenge might call for a deeper, diagnostic or design-focused process.
Typically, successful behavior change interventions often combine elements from multiple frameworks. One may go through a diagnosis and design process, for example, and rely on existing frameworks to analyse and understand insights gathered in the field. Or, one might choose to simply add to their planned intervention using one of the “checklist” frameworks. By recognizing the purpose and limitations of each, practitioners can choose (or adapt) the tools that best resonate with their target audience, organizational capacity, and real-world constraints.
Design and diagnosis methodologies center on uncovering why people behave as they do, then using that understanding to design more effective interventions. Rare’s Behavior Centered Design and The BehaviourWorks Method both draw on human-centered design principles (iterative prototyping, stakeholder engagement, and real-world testing) while also emphasizing insights from the behavioral sciences. These approaches typically involve mixed-methods research to examine cultural norms, individual beliefs, and environmental constraints that shape a target behavior for a given target actor (or groups of actors).
While such depth can yield insights specific to a given context, it also demands significant time and in-house expertise (from data collection to analysis) before any intervention can be prototyped or piloted. In other words, proper diagnosis and design is seldom quick, but it often leads to solutions more firmly rooted in the realities of the communities and environments involved. Many of these methodologies also pair directly with specific conceptual models, which can simplify analysis and hypothesis-making for practitioners. Ultimately, those that choose to go through a design and diagnosis process invest heavily in the early stages but may see more robust, context-specific outcomes later on.
Other frameworks to consider: BIT’s TESTS framework, OECD’s BASIC toolkit, World Bank’s Mind, Society, and Behavior framework, Ideas42's Define, Diagnose, Design, Test framework
Conceptual models and frameworks offer a broader, theory-driven view of how preferences come to be, as well as how different variables may guide our choices. The COM-B (Capability, Opportunity, Motivation - Behavior) Model and UNICEF’s Behavioural Drivers Model (BDM) fit here, each highlighting a range of influences (individual, social, and environmental) that can either enable or hinder a specific behavior. For instance, COM-B posits that a behavior is unlikely to change unless the person has sufficient capability, opportunity, and motivation. By providing ready-made hypotheses for why a target behavior is (or isn’t) occurring, existing conceptual frameworks can be deployed relatively quickly (there is no need to go through costly, in-depth research and generate new hypotheses and theories from scratch).
However, this efficiency can be a double-edged sword. Conceptual frameworks may skip over contextual details or factors not included in their theoretical model. Older or more traditional approaches like the Information-Deficit Model, the Theory of Planned Behavior, and Self-Determination Theory also fall under this category, though they often offer narrower perspectives on human behavior. In modern applications, practitioners increasingly favor holistic models such as COM-B or BDM because they acknowledge multiple dimensions that can influence behavior, providing a fuller picture of what drives or impedes change. Alternatively, practitioners may work with behavioral scientists to develop context-specific models more inductively - choosing to develop their own framework to understand a given behavior in a given context, rather than relying on a more deductive process using established frameworks.
Other models to consider: Elephant Rider Path theory, Socioecological model, Fogg B=MAP model (Behavior = Motivation, Ability, Prompts)
Heuristics and checklist frameworks distill core behavioral insights into concise, easy-to-remember acronyms and guidelines. The Behavioural Insights Team’s EAST (Easy, Attractive, Social, Timely) framework is a prime example, offering a straightforward template for small-scale “nudges.” Some organizations, like WWF, have also introduced their own mnemonic-based guides (for example, SAVE NATURE PLEASE).
Such tools are most useful when practitioners need a quick-start method to incorporate basic behavioral principles, possibly because time or resources are limited. They do not rely on a diagnostic or design process, nor do they require much preliminary research - meaning they may be less suited for projects or topic areas that fall beyond the scope of the published evidence, or any situation that demands a deeper understanding of contextual nuances.
Additional example: OECD’s ABCD
Intervention typologies categorize potential solutions based on how they change behavior. Rare’s Levers of Behavior Change and the levers used in this site illustrate this by outlining strategies such as emotional appeals, social incentives, and choice architecture that practitioners can use when designing interventions. The Behavior Change Wheel, developed alongside COM-B, lays out nine behavior change pathways or strategies (for example, education, incentivization, or coercion) and connects them to relevant intervention options too. Because these typologies focus on mechanisms of influence, they become most helpful once a practitioners have established clear hypotheses about why a behavior happens (either by using conceptual model or by having gone through a diagnostic and design process). This targeted approach helps avoid one-size-fits-all solutions by aligning interventions with the actual drivers of behavior they have been shown to influence, though relying solely on a typology without proper contextual research is likely to lead to ineffective outcomes if the setting differs significantly from where the original evidence was validated.
Other typologies to consider: Behavior Change Intervention Ontologies (UCL), “What Works in Conservation” guides
Alongside understanding why and how to shift behaviors, it is equally important to ensure that interventions are designed and implemented responsibly. Ethics and best-practice frameworks help organizations uphold transparency, fairness, and respect for the communities they serve. For example, FORGOOD focuses on principles like Integrity, Respect, and Consent, ensuring that behavioral interventions do not manipulate or exploit vulnerable populations while emphasizing the need to evaluate unintended consequences and maintain accountability throughout a project’s lifecycle. Similarly, the Social Marketing Ethics Framework lays out guidelines to ensure interventions are not only effective but also socially responsible, requiring steps such as securing informed consent, avoiding stigmatizing messages, and ensuring equitable benefits for different groups. Rare created a checklist to ensure Diversity, Equity, and Inclusion principles are included in each step of Behavior-Centered Design. By following such ethics-oriented frameworks, teams can balance impact with integrity, minimize the risk of harm, and build trust among participants and stakeholders. This is especially critical in conservation, where interventions often involve diverse communities and ecosystems.
In reality, most organizations combine approaches from multiple of the above categories. Rare uses Behavior-Centered Design (a diagnosis and design process) to gain deep insights, generates clear hypotheses above what may or may not change a given behavior, then applies its Levers of Behavior Change (an intervention typology) to convert those insights into practical solutions. Meanwhile, COM-B (a conceptual model) often pairs with the Behavior Change Wheel (an intervention typology) to map out targeted functions that address issues like lack of opportunity or motivation.
A typical behavior change project might start with diagnosis (understanding why a behavior occurs), classify findings with or without an existing conceptual model. move into design (developing interventions from those insights), then proceed with testing, refining, and evaluating. In many cases, evaluation uncovers new information, leading back to the diagnostic phase in an iterative loop. Teams differ in how they conduct the initial diagnosis: some take an inductive, bottom-up approach, others prefer a deductive, theory-based one, and many use both. By recognizing each framework and process’s strengths, limitations, and intended uses, practitioners can create robust, context-specific strategies that resonate with the people and environments they serve.
Lastly, new models, hybrid approaches, and ongoing research continue to evolve the field. Staying up to date on these developments empowers practitioners to fine-tune their methods, helping ensure that conservation efforts remain both scientifically valid and responsive to real-world complexities.