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Wellcome Open Research
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Brunel University Research Archive
Article . 2025 . Peer-reviewed
License: CC BY
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Development of an Intervention Population Ontology for specifying the characteristics of intervention participants

Authors: Alison J Wright; Ailbhe N Finnerty Mutlu; Emma Norris; Marta M. Marques; Janna Hastings; Robert West; Susan Michie;

Development of an Intervention Population Ontology for specifying the characteristics of intervention participants

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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    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold