Wright, Alison J;
Finnerty Mutlu, Ailbhe N;
Norris, Emma;
Marques, Marta M;
Hastings, Janna;
West, Robert;
Michie, Susan;
(2025)
Development of an Intervention Population Ontology for specifying the characteristics of intervention participants.
Wellcome Open Research
, 10
, Article 122. 10.12688/wellcomeopenres.22788.1.
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Abstract
Background: The uptake, effectiveness and generalisability of interventions are influenced by the features of the populations targeted. However, populations exposed to interventions are not consistently specified in published reports. Purpose: To create an Intervention Population Ontology providing a clear, usable and reliable classification system to specify characteristics of populations exposed to interventions. Methods: The Intervention Population Ontology was developed in seven main stages 1) Defining the ontology’s scope, (2) identifying key entities by reviewing existing classification systems (top-down) and 100 intervention reports (bottom-up), 3) Refining the preliminary ontology by annotating ~150 intervention reports, 4) Stakeholder review by 29 behavioural science and public health experts, 5) Assessing inter-rater reliability of using the ontology by two coders familiar with the ontology and two coders unfamiliar with it, 6) Specifying ontological relationships between entities in the ontology and 7) making the Intervention Population Ontology machine-readable using Web Ontology Language (OWL) and publishing online. Results: The Intervention Population Ontology features 218 entities representing attributes of human individuals across 12 key groupings: personal attributes, geographic location, person, quality, mental capability, role, expertise, objects possessed, behaviour, personal vulnerability and personal history. It has a further 666 classes relating to how individual-level attributes are aggregated to describe groups of people. Inter-rater reliability was α=0.79 for coders familiar with the ontology and 0.85 for coders unfamiliar with the ontology. Conclusions: The Intervention Population Ontology can be applied to specify precisely information from diverse sources, annotate population characteristics in existing intervention evaluation reports and guide future reporting.
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