Elina Halonen
Building a periodic table for behavioural science
Understanding and influencing human behaviour is a complex challenge for researchers and practitioners. Unlike chemistry and physics, which have established frameworks, behavioural science has traditionally lacked a unifying system, impeding research and the design of effective interventions.
In recent years, two connected frameworks have become more prominent: the COM-B model (Capability, Opportunity, Motivation – Behaviour) and the Theoretical Domains Framework (TDF). COM-B breaks down behaviour into three core components, while TDF provides a more detailed analysis, exploring specific domains like knowledge, skills, emotions, and social influences. Together, these frameworks offer a structured way to analyse and influence behaviour systematically.
This post explores how COM-B and TDF could function as a 'periodic table' for behaviour, organising its fundamental building blocks much like chemists classify elements. While this approach offers valuable insights, it's important to remember that no framework can provide a universal playbook because the world is complex and human behaviour is always shaped by cultural and contextual nuances.
The 'periodic table' for behaviour
In chemistry, the periodic table organizes elements based on their properties, enabling scientists to simplify the study of matter and predict elemental interactions. Similarly, the COM-B model and Theoretical Domains Framework (TDF) serve as tools to categorize and understand the components of human behaviour, breaking it down into distinct, manageable elements: capability, opportunity, and motivation—the essential building blocks for any behaviour to occur.
Let's use COM-B as a lens to look at the behaviour of exercising regularly as an example. If any of these elements are missing, the behaviour is less likely to occur:
Capability: Physical strength or knowledge of exercise routines.
Opportunity: Access to a gym or time.
Motivation: Belief in the benefits of exercise.
We can also go into more detail with the subdimensions of COM-B:
Psychological Capability: Understanding health benefits.
Physical Capability: Being physically able to exercise.
Physical Opportunity: Lack of nearby facilities.
Social Opportunity: Peer support.
Reflective Motivation: Conscious beliefs.
Automatic Motivation: Habitual behaviours.
The TDF adds further depth by breaking these broad categories into specific psychological and environmental domains that influence behaviour:
Capability:
Knowledge: Awareness of the benefits of exercise and understanding how to perform exercises.
Skills: The physical ability to perform exercises correctly.
Opportunity:
Environmental Context and Resources: Access to gyms, equipment, or spaces to exercise.
Social Influences: Peer support, encouragement from friends or family, or the influence of social norms.
Motivation:
Beliefs about Capabilities: Confidence in one’s ability to exercise regularly.
Emotions: Feelings of enjoyment, anxiety, or other emotional responses related to exercise.
By breaking down these behavioural elements into detailed domains, the TDF provides a more comprehensive framework for understanding the factors influencing exercise behaviour. This detailed analysis allows practitioners to identify the most relevant barriers or enablers and design targeted interventions accordingly.
Much like the periodic table helps chemists predict chemical reactions, these frameworks allow behavioural scientists to identify and map the factors driving human actions. For example, an person might have a high level of psychological capability (knowledge about healthy eating), but without the physical opportunity (access to healthy food), their behaviour won't align with their understanding. This kind of discrepancy is sometimes interpreted as the intention-action gap, or alternatively as evidence for the view that knowledge alone doesn't change behaviour. By mapping out these behavioural 'elements,' researchers and practitioners can systematically diagnose which components are missing or need strengthening, making it easier to design targeted interventions.
In this way, the COM-B and TDF frameworks offer a great analogy to the periodic table: both provide a systematic structure to navigate complexity, predict interactions, and craft solutions, whether in the realm of chemistry or human behaviour.
Enhancing research with a standardised system
The diversity of interventions, target populations, and settings in behaviour change research often leads to inconsistent findings. Meta-analyses frequently group different contexts and determinants together, resulting in a muddled understanding of what truly works. Consequently, generalised conclusions drawn from these analyses may not be applicable across all situations, making it challenging to develop effective and targeted interventions.
The COM-B and TDF frameworks provide a structured method for categorising behaviour, enabling researchers to draw more meaningful conclusions and improve study comparability. These tools address key challenges in synthesising behaviour change research, such as the wide variety of interventions, target populations, and settings that often lead to inconsistent findings.
The COM-B model offers a systematic approach to evaluating behaviour by focusing on three key components: capability, opportunity, and motivation. This structure allows researchers and practitioners to:
Identify driving and hindering factors accurately.
Avoid conclusions being lost in conflicting data.
Focus interventions on the most relevant issues.
Example: A study on physical activity might reveal that low motivation, not lack of opportunity, is the primary barrier to regular exercise.
The TDF provides a more nuanced exploration of behaviour by breaking down broad categories into specific domains which allows researchers and practitioners to:
Isolate the most influential factors in a given context (e.g., social support, access to resources, emotional regulation).
Address the comparability issue of effect sizes across diverse behaviours and contexts.
Gain a more targeted and actionable understanding of behaviour.
By adopting COM-B and TDF, researchers can better navigate the complexity of human behaviour, leading to more effective and tailored interventions.
Application in behaviour change interventions
One of the practical benefits of thinking about COM-B and TDF as a 'periodic table' of behaviour is the clarity it brings to intervention design. Much like chemists analyzing the properties of substances to determine their composition, practitioners can use COM-B and TDF to diagnose behavioural issues methodically.
Let's consider an intervention aimed at reducing sedentary behaviour in the workplace as an example. By using the COM-B framework, we can systematically assess if the problem is a lack of psychological capability (awareness of risks), physical/social opportunity (unsupportive office environment), or motivation (no perceived need for change). This process brings clarity by focusing interventions on the most relevant components, avoiding a one-size-fits-all approach.
The TDF can further enrich this process by providing a detailed breakdown of each COM-B component. For example, if motivation is the issue, TDF can help identify whether reflective motivation (beliefs about consequences) or automatic motivation (habitual behaviour) is at play. This level of precision then guides the choice of intervention strategies, such as educational campaigns or environmental restructuring for habitual change.
When addressing health challenges such as increasing physical activity, practitioners can use COM-B and TDF to conduct a diagnostic assessment to identify whether psychological, physical, or social factors are preventing behaviour change. For example, if the diagnosis reveals a lack of social opportunity (e.g., insufficient social support) or lack of physical opportunity (e.g. inadequate community infrastructure), interventions might focus on creating group exercise programs or improving public facilities. Alternatively, if automatic motivation (e.g., ingrained habits or emotional responses) is identified as a major barrier, the focus could shift to habit-restructuring techniques or motivational interventions.
This diagnostic ability positions COM-B and TDF as comprehensive tools for behaviour analysis, akin to how the periodic table enables chemists to determine the reactivity and interactions of different elements. Such a structured approach ensures that interventions are targeted, contextually relevant, and theoretically grounded.
The Takeaway Formula
One of the biggest challenges in using the periodic table analogy for behavioural science is the complexity, fluidity, and cultural variability of human behaviour. Unlike chemical elements, behaviour is dynamic and influenced by numerous biological, psychological, social, and environmental factors. This makes it difficult to neatly categorise behaviours within a static framework. While models like COM-B and TDF offer a helpful structure, they can oversimplify the wide range of human experiences and influences.
For example, motivation is multifaceted—it can be conscious or unconscious, intrinsic or extrinsic, short-term or long-term. Opportunity can be physical (like access to resources) or social (such as community support), with factors interacting in complex ways that are hard to capture in a rigid system. Moreover, what motivates or is available to an individual in one cultural setting may not apply in another. The impact of social norms and physical opportunities can vary dramatically across cultures and regions.
The real challenge is not to create a one-size-fits-all solution, but to design a framework that balances the complexity of human behaviour with clear organisation. COM-B, TDF, and the Behaviour Change Wheel (BCW) aren't meant to be plug-and-play tools. Their strength lies in their flexibility and adaptability, allowing practitioners to tailor approaches to the unique needs of each situation.
Ultimately, the true power of these frameworks is not in their rigid application, but in their ability to adapt to the complexities of human behaviour, ensuring interventions remain evidence-based and contextually relevant.
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