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http://bura.brunel.ac.uk/handle/2438/31191| Title: | Development of an Intervention Population Ontology for specifying the characteristics of intervention participants |
| Authors: | Wright, AJ Finnerty Mutlu, AN Norris, E Marques, MM Hastings, J West, R Michie, S |
| Issue Date: | 5-Mar-2025 |
| Publisher: | F1000 Research on behalf of Wellcome |
| Citation: | Wright, A.J. et al. (2025) 'Development of an Intervention Population Ontology for specifying the characteristics of intervention participants' [version 1; peer review: 2 not approved], Wellcome Open Research, 10, 122, pp. 1 - 26. doi: 10.12688/wellcomeopenres.22788.1. |
| 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. |
| Description: | Plain language summary:
Intervening to change behaviour is key to addressing many of the most serious challenges facing the world today. However, the effectiveness of interventions varies according to the characteristics of the people taking part. We need to build our knowledge of what types of interventions work best for people with particular characteristics. This study developed a unifying framework, called an “ontology”, for describing the characteristics of intervention participants.
We developed the Intervention Population Ontology using a standardised method. This included the following steps: identifying key entities to include by reviewing intervention reports and existing classification systems; coding examples of population characteristics in studies; and asking behavioural science and public health experts for feedback on the ontology. The resulting Intervention Population Ontology has 206 entries representing different human characteristics and a further 638 classes representing how these characteristics can be aggregated to describe groups of people (e.g. mean age, percent female).
The importance of the Intervention Population Ontology lies in its ability to support users in precisely describing, comparing and integrating evidence about the human participants in different studies. Going forward, users of the ontology will be able to contribute to it by providing feedback and suggestions for improvement. First Version Published: 05 Mar 2025, 10:122 (https://doi.org/10.12688/wellcomeopenres.22788.1) Data availability statement: Underlying data: Open Science Framework: Human Behaviour-Change Project. https://doi.org/10.17605/OSF.IO/QRGC4 (West et al., 2020). The BCIO is available from: https://github.com/HumanBehaviourChangeProject/ontologies Archived version of the Intervention Population Ontology as at time of publication: https://github.com/HumanBehaviourChangeProject/ontologies/tree/master/Population Zenodo: HumanBehaviourChangeProject/ontologies: https://doi.org/10.5281/zenodo.14882463 (Schenk et al., 2025) Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Extended data Open Science Framework: Human Behaviour-Change Project. https://doi.org/10.17605/OSF.IO/QRGC4 (West et al., 2020). This project contains the following extended data: • Papers used across steps of development of the Intervention Population Ontology (https://osf.io/6xcwy) • Version 0.1 Preliminary prototype version of Intervention Population Ontology (https://osf.io/jhymg) • Version 0.2 Version of the Intervention Population Ontology after initial annotations (https://osf.io/m6udx) • Expert feedback survey; Full survey provided to behavioural science and public health experts in review of the Intervention Population Ontology (https://osf.io/64mx9) • Expert feedback on Intervention Population Ontology: Feedback received from behavioural science and public health experts together with the ontology development team’s responses (https://osf.io/6quv2) • Version 0.3 Version of the Intervention Population Ontology after expert stakeholder feedback (https://osf.io/8uw52) • Inter-rater reliability testing results – annotations by researchers from the ontology development team (https://osf.io/ywpgt) • Inter-rater reliability testing results – two behaviour change experts unfamiliar with the ontology (https://osf.io/9p5zc) • Annotation guidance manual for using the Intervention Population Ontology (https://osf.io/u9wb4) Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Software availability: Source code used to calculate alpha for inter-rater reliability available from: https://github.com/HumanBehaviourChangeProject/Automation-InterRater-Reliability Archived code at time of publication: https://doi.org/10.5281/zenodo.3833816 (Finnerty & Moore, 2020) License: GNU General Public License v3.0 |
| URI: | https://bura.brunel.ac.uk/handle/2438/31191 |
| DOI: | https://doi.org/10.12688/wellcomeopenres.22788.1 |
| Other Identifiers: | ORCiD: Alison J. Wright https://orcid.org/0000-0002-0373-5219 ORCiD: Susan Michie https://orcid.org/0000-0003-0063-6378 ORCiD: Ailbhe N Finnerty Mutlu https://orcid.org/0000-0003-2355-4332 ORCiD: Emma Norris https://orcid.org/0000-0002-9957-4025 ORCiD: Janna Hastings https://orcid.org/0000-0002-3469-4923 ORCiD: Robert West https://orcid.org/0000-0001-6398-0921 Article number: 122 |
| Appears in Collections: | Dept of Health Sciences Research Papers |
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| FullText.pdf | Copyright: © 2025 Wright AJ et al. This is an open access work distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | 648.64 kB | Adobe PDF | View/Open |
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