Ontologies are classification systems specifying entities, definitions and inter-relationships for a given domain, with the potential to advance knowledge about human behaviour change. A scoping review was conducted to: (1) identify what ontologies exist related to human behaviour change, (2) describe the methods used to develop these ontologies and (3) assess the quality of identified ontologies. Using a systematic search, 2,303 papers were identified. Fifteen ontologies met the eligibility criteria for inclusion, developed in areas such as cognition, mental disease and emotions. Methods used for developing the ontologies were expert consultation, data-driven techniques and reuse of terms from existing taxonomies, terminologies and ontologies. Best practices used in ontology development and maintenance were documented. The review did not identify any ontologies representing the breadth and detail of human behaviour change. This suggests that advancing behavioural science would benefit from the development of a behaviour change intervention ontology.
Subscribe to Journal
Get full journal access for 1 year
only $9.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
The data that support the findings of this study are available from the corresponding author upon request.
Michie, S., Van Stralen, M. M. & West, R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement. Sci. 6, 42 (2011).
Michie, S. & Johnston, M. Optimising the value of the evidence generated in implementation science: the use of ontologies to address the challenges. Implement. Sci. 12, 131 (2017).
Michie, S., West, R., Campbell, R., Brown, J. & Gainforth, H. ABC of Behaviour Change Theories (Silverback Publishing, London, UK, 2014).
Davis, R., Campbell, R., Hildon, Z., Hobbs, L. & Michie, S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol. Rev. 9, 323–344 (2015).
Michie, S. et al. The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation. Implement. Sci. 12, 121 (2017).
Ioannidis, J. P. et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383, 166–175 (2014).
Stavri, Z. & Michie, S. Classification systems in behavioural science: current systems and lessons from the natural, medical and social sciences. Health Psychol. Rev. 6, 113–140 (2012).
Hollands, G. J. et al. The TIPPME intervention typology for changing environments to change behaviour. Nat. Hum. Behav. 1, 0140 (2017).
Michie, S. et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann. Behav. Med. 46, 81–95 (2013).
Carey, R. N. et al. Describing the ‘how’ of behaviour change: a taxonomy of modes of delivery. In UK Society for Behavioural Medicine Conference http://www.kc-jones.co.uk/files/uploads/1481819318.pdf (2016).
Michie, S. et al. From theory-inspired to theory-based interventions: a protocol for developing and testing a methodology for linking behaviour change techniques to theoretical mechanisms of action. Ann. Behav. Med. 52, 501–512 (2018).
Howlett, N., Trivedi, D., Troop, N. A. & Chater, A. M. Are physical activity interventions for healthy inactive adults effective in promoting behavior change and maintenance, and which behavior change techniques are effective? A systematic review and meta-analysis. Transl. Behav. Med. https://doi.org/10.1093/tbm/iby010 (2018).
Michie, S., West, R., Sheals, K. & Godinho, C. A. Evaluating the effectiveness of behavior change techniques in health-related behavior: a scoping review of methods used. Transl. Behav. Med. 8, 212–224 (2018).
Arp, R., Smith, B. & Spear, A. D. Building Ontologies with Basic Formal Ontology (MIT Press, Cambridge, MA, 2015).
Busse, J. et al. Actually, what does “ontology” mean? J. Comput. Inf. Technol. 23, 29–41 (2015).
Blanch, A. et al. Ontologies about human behavior: a review of knowledge modeling systems. Eur. Psychol. 22, 180–197 (2017).
Larsen, K. R. et al. Behavior change interventions: the potential of ontologies for advancing science and practice. J. Behav. Med. 40, 6–22 (2017).
Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).
Bauer, S. in The Gene Ontology Handbook (eds Dessimoz, C. & Škunca, N.) 175–188 (Springer, New York City, 2017).
Kraker, P. et al. The Vienna principles: a vision for scholarly communication in the 21st century. VOB Mitteilungen 69, 436–446 (2016).
Noy, N. F. et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 37, W170–W173 (2009).
Smith, B. et al. The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat. Biotechnol. 25, 1251–1255 (2007).
Principle: overview. The OBO Foundry http://www.obofoundry.org/principles/fp-000-summary.html (2018).
Poldrack, R. A. et al. The Cognitive Atlas: toward a knowledge foundation for cognitive neuroscience. Front. Neuroinform. 5, 17 (2011).
Hastings, J., Smith, B., Ceusters, W., Jensen, M. & Mulligan, K. The mental functioning ontology. In Proc. 3rd International Conference on Biomedical Ontology (ICBO’12) (eds Cornet R. & Stevens, R.) 1–5 (2012).
Gkoutos, G. V., Schofield, P. N. & Hoehndorf, R. The neurobehavior ontology: an ontology for annotation and integration of behavior and behavioral phenotypes. Int. Rev. Neurobiol. 103, 69–87 (2012).
Ceusters, W. & Smith, B. Foundations for a realist ontology of mental disease. J. Biomed. Semantics 1, 10 (2010).
Jensen, M. et al. The neurological disease ontology. J. Biomed. Semantics 4, 42 (2013).
Schriml, L. M. et al. Disease Ontology: a backbone for disease semantic integration. Nucleic Acids Res. 40, D940–D946 (2011).
Schriml, L. M. et al. GeMInA, genomic metadata for infectious agents, a geospatial surveillance pathogen database. Nucleic Acids Res. 38, D754–D764 (2009).
Mattingly, C. J., McKone, T. E., Callahan, M. A., Blake, J. A. & Hubal, E. A. C. Providing the missing link: the expsoure science ontology. Environ. Sci. Technol. 46, 3046–3053 (2012).
Turner, J. A. & Laird, A. R. The cognitive paradigm ontology: design and application. Neuroinformatics 10, 57–66 (2012).
Gil, R., Virgili-Gomá, J., García, R. & Mason, C. Emotions ontology for collaborative modelling and learning of emotional responses. Comput. Human Behav. 51, 610–617 (2015).
Hastings, J., Ceusters, W., Smith, B. & Mulligan, K. Dispositions and processes in the Emotion Ontology. In Proc. 2nd International Conference on Biomedical Ontology 71–78 (2011).
Pesquita, C., Ferreira, J. D., Couto, F. M. & Silva, M. J. The epidemiology ontology: an ontology for the semantic annotation of epidemiological resources. J. Biomed. Semantics 5, 4 (2014).
Hicks, A., Hanna, J., Welch, D., Brochhausen, M. & Hogan, W. R. The ontology of medically related social entities: recent developments. J. Biomed. Semantics 7, 47 (2016).
Phan, N., Dou, D., Wang, H., Kil, D. & Piniewski, B. Ontology-based deep learning for human behavior prediction with explanations in health social networks. Inf. Sci. (NY) 384, 298–313 (2017).
Bickmore, T. W., Schulman, D. & Sidner, C. L. A reusable framework for health counseling dialogue systems based on a behavioral medicine ontology. J. Biomed. Inform. 44, 183–197 (2011).
Prochaska, J. O. & Velicer, W. F. The transtheoretical model of health behavior change. Am. J. Health Promot. 12, 38–48 (1997).
Hoffmann, T. C. et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ 348, g1687 (2014).
Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (American Psychiatric Association, Washington, DC, 2013).
Basic Formal Ontology. The OBO Foundry http://www.obofoundry.org/ontology/bfo.html (2018).
Ceusters, W. An information artifact ontology perspective on data collections and associated representational artifacts. Stud. Health Technol. Inform. 180, 68–72 (2012).
Courtot, M. et al. MIREOT: the minimum information to reference an external ontology term. Appl. Ontol. 6, 23–33 (2011).
Richard, M., Aimé, X., Krebs, M.-O. & Charlet, J. Enrich classifications in psychiatry with textual data: an ontology for psychiatry including social concepts. Stud. Health Technol. Inform. 210, 221–223 (2015).
Wilkinson et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
Shneiderman, B. & Plaisant, C. Designing the User Interface: Strategies for Effective Human–Computer Interaction 5th edn (Pearson Education, New York, 2010).
Arksey, H. & O’Malley, L. Scoping studies: towards a methodological framework. Int. J. Soc. Res. Methodol. 8, 19–32 (2005).
Norris, E., Finnerty, A. N., Hastings, J., Stokes, G. & Michie, S. Advancing methods to develop behaviour change interventions: a review of relevant ontologies. Prospero http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017079990 (2017).
Tricco, A. C. et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. Ann. Intern. Med. 169, 467–473 (2018).
Simera, I. et al. Transparent and accurate reporting increases reliability, utility, and impact of your research: reporting guidelines and the EQUATOR Network. BMC Med. 8, 24 (2010).
Matentzoglu, N., Malone, J., Mungall, C. & Stevens, R. MIRO: guidelines for minimum information for the reporting of an ontology. J. Biomed. Semantics 9, 6 (2018).
De Silva, T. S., MacDonald, D., Paterson, G., Sikdar, K. C. & Cochrane, B. Systematized nomenclature of medicine clinical terms (SNOMED CT) to represent computed tomography procedures. Comput. Methods Programs Biomed. 101, 324–329 (2011).
Brown, E. G., Wood, L. & Wood, S. The medical dictionary for regulatory activities (MedDRA). Drug Saf. 20, 109–117 (1999).
Thomas, J., Brunton, J. & Graziosi, S. EPPI-Reviewer 4.0: software for research synthesis (Institute of Education, University of London, 2010).
Noy, N. F. et al. Protégé 2000: an open-source ontology-development and knowledge-acquisition environment. AMIA Annu. Symp. Proc. 2003, 953 (2003).
Shearer, R., Motik, B. & Horrocks, I. HermiT: a highly-efficient OWL reasoner. OWLED 432, 91–101 (2008).
Lamy, J. B. Owlready: ontology-oriented programming in Python with automatic classification and high-level constructs for biomedical ontologies. Artif. Intell. Med. 80, 11–28 (2017).
Vrandecic, D. in Handbook on Ontologies (eds Staab, S. & Studer, R.) 293–313 (Springer, Berlin, Heidelberg, 2009).
Amith, M., He, Z., Bian, J., Antonio Lossio-Ventura, J. & Tuo, C. Assessing the practice of biomedical ontology evaluation: gaps and opportunities. J. Biomed. Inform. 80, 1–13 (2018).
Katsumi, K. & Gruninger, M. Choosing ontologies for reuse. Appl. Ontol. 12, 195–221 (2017).
Guarino, N. & Welty, C. Evaluating ontological decisions with OntoClean. Commun. ACM 45, 61–65 (2002).
McMurry, J. A. et al. Identifiers for the 21st century: how to design, provision, and reuse persistent identifiers to maximise utility and impact of life science data. PLoS Biol. 15, e2001414 (2017).
Horridge, M., Parsia, B. & Sattler, U. in Scalable Uncertainty Management. SUM 2009. Lecture Notes in Computer Science Vol. 5785 (eds Godo L. & Pugliese A.) 124–137 (Springer, Berlin, Heidelberg, 2009).
Glimm, B., Horrocks, I., Motik, B., Stoilos, G. & Wang, Z. HermiT: an OWL 2 reasoner. J. Autom. Reasoning 54, 245–269 (2014).
We thank the Wellcome Trust for funding the project: ‘The Human Behaviour-Change Project: Building the science of behaviour change for complex intervention development’ (201,524/Z/16/Z). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Thanks to E. Crayton, S. Stanton-Fay, H. Walton and A. Wright for providing comments on an earlier draft.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Norris, E., Finnerty, A.N., Hastings, J. et al. A scoping review of ontologies related to human behaviour change. Nat Hum Behav 3, 164–172 (2019). https://doi.org/10.1038/s41562-018-0511-4