Background: The Human Behaviour-Change Project brings together behavioural, computer, and information scientists to develop an Artificial Intelligence system for extracting, synthesising, and interpreting behaviour change evidence. The lack of standardised terminology in reporting behaviour change interventions is a challenge in building such a system that Ontologies can address, by providing a formal structure that characterises and coherently organises its components (e.g., content). These components are classified in taxonomies (e.g. Behaviour Change Techniques Taxonomy v1). This study aims to develop two taxonomies that specify the contextual component of an Ontology for Behaviour Change Interventions – target population and setting.
Methods: The taxonomies were developed in an iterative process, reviewing existing taxonomies (e.g., WHO ICF), ontologies (e.g., Cochrane PICO), and behaviour change interventions evaluation reports, alongside expert discussions. Inter-rater reliability of the taxonomies was assessed using a set of 55 evaluation reports (focusing on physical activity and smoking).
Findings: The preliminary versions of the Population and Setting Taxonomies (v1) present four-level hierarchical structures containing 204 and 63 unique codes, respectively. There was variability in the inter-rater reliability across levels, reflecting the lack of systematisation in reporting the context of behaviour change interventions.
Discussion: This research has developed classification systems for describing target population and setting. Findings suggest the need for improvement in these taxonomies. Next steps include the annotation (manual and automatic) of a larger set of evaluation reports, expert consensus procedures, and the establishment of inter-relationships within the common ontological structure of behavior change interventions.