CACTIS provides a step-by-step process for developing behaviour change intervention strategies. It guides you through specifying a behavioural goal, conducting a COM-B diagnosis to identify capability, opportunity and motivation factors to target, then selecting appropriate intervention functions and behaviour change techniques. It then constructs a structured prompt for an AI tool such as Claude to generate a draft strategy.
Specify the Problem
Enter the behavioural goal, target population/group, and intervention setting(s). Be precise and observable.
Identify COM-B Targets
For each of the 27 COM-B factors, indicate relevance/room for improvement and strength of evidence. CACTIS auto-assigns priority. Expand on High priority targets to add evidence and rationale.
Select BCTs
For High priority COM-B targets, select Behaviour Change Techniques across the 9 BCW Intervention Functions. Multiple BCTs can be selected per cell.
Generate Results & Prompt
View all your selections and copy a structured LLM prompt. Paste this into Claude or another AI tool to generate a draft intervention strategy.
Download the full BCT mapping reference as an Excel workbook — includes the complete BCT list, the COM-B × Intervention Function mapping matrix, intervention function definitions, and a COM-B quick reference.
For each BCT you selected, describe what it would look like in practice and the evidence or stakeholder feedback supporting your choice. Both fields are optional and feed into the LLM prompt in Step 4.
Export everything entered — the problem definition, full COM-B assessment, selected BCTs with their implementation detail, and the generated prompt — as a formatted Word document. A complete record of the decisions made.
Copy this prompt and paste it into Claude or another AI tool to generate a draft intervention strategy.
CACTIS is developed by the Unlocking Behaviour Change CIC (unlockingbehaviourchange.com) with support from The Public Health Wales Behavioural Science Unit. It undergoes continual development in the light of evidence, theory and user experiences.