HBM 20: COM-B Model

A city invests heavily in a cycling awareness campaign. Brochures explain the health benefits of cycling, social media posts highlight environmental impact, and local news covers success stories from other cities. After twelve months, cycling mode share has barely changed. The campaign increased knowledge — surveys confirm that residents now know cycling is healthy and sustainable — but almost nobody switched from driving. Why?

The answer often lies in a mismatch between the type of barrier and the type of intervention. If people already understand the benefits of cycling but lack safe bike lanes, secure parking, or the physical fitness to ride, then more information is the wrong lever. The COM-B model was designed to prevent exactly this kind of mismatch by diagnosing what must change before selecting how to change it.

Why Behavioral Diagnosis Matters

Transportation planning, construction safety, emergency preparedness, and sustainability policy all involve changing human behavior. Engineers build infrastructure, planners write policies, and communications teams run campaigns — but if the intervention does not address the actual barrier, the investment is wasted.

Consider a few common failures:

• A city builds a new bus rapid transit line but ridership remains low because residents do not know how the fare system works (a capability problem treated as an opportunity problem).
• A construction company posts safety posters on every wall but workers still skip harness use because the harnesses are uncomfortable and slow to put on (an opportunity problem treated as a knowledge problem).
• A transit agency offers discounted passes but commuters still drive because driving is automatic and habitual (a motivation problem treated as an opportunity problem).

Each failure reflects the same underlying issue: the intervention targeted the wrong component of behavior. COM-B provides a systematic way to identify which components are deficient before choosing an intervention.

The COM-B Model Explained

COM-B was developed by Susan Michie, Maartje van Stralen, and Robert West at University College London. The model proposes that any behavior requires the interaction of three conditions:

The model name itself encodes this logic: Capability + Opportunity + Motivation → Behavior.

This is not a prediction model. COM-B does not estimate the probability that someone will cycle to work. Instead, it is a diagnostic framework that identifies which conditions for behavior are present and which are missing. The diagnosis then points toward the right type of intervention.

Core Constructs

COM-B divides each of the three conditions into two sub-components, creating six sources of behavior:

Causal Logic

The causal structure of COM-B involves more than a simple additive relationship. The three components interact with one another:

The interactions matter. Capability can influence motivation: a person who learns to ride a bicycle confidently (capability) may develop more positive attitudes toward cycling (motivation). Opportunity can influence motivation: when a new protected bike lane opens (opportunity), residents may start to see cycling as a realistic option (motivation). And behavior itself feeds back: successfully cycling to work a few times (behavior) strengthens the habit and reinforces confidence (capability and motivation).

This interaction structure means that COM-B serves as a diagnostic tool, not a causal prediction engine. It identifies what must change but does not specify how much change is needed or what dose of intervention will produce a given effect size.

Data Needed

Because COM-B is a diagnostic framework, data collection focuses on identifying barriers and facilitators across all six sub-components:

A typical COM-B assessment involves structured questions for each component. The following illustrates what diagnostic items might look like:

COM-B DIAGNOSTIC INTERVIEW GUIDE (Cycling to Work)
CAPABILITY — Physical
“Are you physically able to cycle for [distance] to your workplace?”
“Do you have the cycling skills to ride in traffic?”
CAPABILITY — Psychological
“Do you know a safe route from your home to your workplace?”
“Do you know how to maintain a bicycle (tire pressure, brakes)?”
OPPORTUNITY — Physical
“Is there a safe cycling route available?”
“Do you have access to a working bicycle?”
“Is there secure bike parking at your workplace?”
OPPORTUNITY — Social
“Do any of your colleagues or friends cycle to work?”
“Would cycling to work be seen as normal in your workplace?”
MOTIVATION — Reflective
“Do you believe cycling to work would benefit you?”
“Have you considered or planned to cycle to work?”
MOTIVATION — Automatic
“When you think about your morning commute, what feels like the
natural thing to do?”
“How do you feel about cycling — excited, anxious, indifferent?”

Methods

COM-B analysis is primarily qualitative and diagnostic, though it can be combined with quantitative methods:

• COM-B diagnostic tool: Systematic assessment of each component using structured interview guides or survey instruments
• Behavioral analysis: Mapping the target behavior onto the six sub-components to identify which are sufficient and which are deficient
• Qualitative coding: Thematic analysis of interview or focus group transcripts, coding responses to COM-B categories
• Survey analysis: Descriptive statistics and cross-tabulations of COM-B component scores across population segments
• Mixed methods: Combining qualitative diagnosis with quantitative surveys to triangulate findings and assess the prevalence of specific barriers

The output of a COM-B analysis is a behavioral diagnosis: a structured statement about which components are adequate and which need to change. This diagnosis then guides intervention selection — a process formalized in the Behaviour Change Wheel (the subject of the next post).

Transportation Example: Why People Don’t Cycle to Work

Consider a mid-sized city that wants to increase cycling commuting from 3% to 15% mode share. A COM-B analysis interviews 60 residents who currently drive to work, along with 20 who already cycle. The analysis reveals the following pattern:

The diagnosis reveals several findings:

What the Diagnosis Means for Intervention

This diagnosis has immediate implications:

• More awareness campaigns (education alone) will not work. Most people already know cycling is beneficial. The barrier is not knowledge — it is infrastructure and habit.
• Building protected bike lanes is necessary to address the physical opportunity deficit. Without safe infrastructure, no amount of persuasion will produce mass cycling.
• Workplace cycling culture programs could address social opportunity — bike-to-work challenges, visible bike parking, employer incentives.
• Habit disruption strategies are needed for automatic motivation — trial periods, guided first rides, bike-share programs that lower the barrier to trying.
• Wayfinding and skills training can address the psychological capability gap — cycling maps, route apps, urban cycling courses.

Strengths

Limitations

COM-B is powerful as a diagnostic framework, but it has clear boundaries:

Best Use Case

COM-B is the right framework when a team needs to systematically diagnose behavioral barriers before designing an intervention. It is particularly valuable in the early stages of policy development, program planning, or research design — when the goal is to understand why a behavior is or is not occurring, and to ensure that the subsequent intervention addresses the actual constraints rather than assumed ones.

Use COM-B when:

• Planning a new transportation, safety, or sustainability program
• A previous intervention failed and the team needs to understand why
• Multiple stakeholders disagree about what the real barrier is
• The target behavior involves a complex mix of individual, social, and environmental factors
• The team needs a common language to communicate across disciplines (engineering, planning, public health, communications)

Key Takeaway

Key References

Exercises and Discussion Questions

In the next post, the Behaviour Change Wheel builds on COM-B by providing a systematic method for selecting intervention functions and policy categories that match the diagnosed barriers.