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Behavior change interventions: the potential of ontologies for advancing science and practice

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Abstract

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using “ontologies.” In information science, an ontology is a systematic method for articulating a “controlled vocabulary” of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine’s Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science.

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References

  • Arp, R., Smith, B., & Spear, A. D. (2015). Building ontologies with basic formal ontology. Cambridge: The MIT Press.

    Book  Google Scholar 

  • Bosco, F. A., Aguinis, H., Singh, K., Field, J. G., & Pierce, C. A. (2015). Correlational effect size benchmarks. Journal of Applied Psychology, 100, 431–449. doi:10.1037/a0038047

    Article  PubMed  Google Scholar 

  • BCTTv1 Team. (2016). Behaviour change techniques and theory: Feedback on BCTTv1. Retrieved from: https://www.ucl.ac.uk/behaviour-change-techniques/BCTTv1Feedback

  • Cane, J., O’Connor, D., & Michie, S. (2012). Validation of the theoretical domains framework for use in behaviour change and implementation research. Implementation Science, 7, 37. doi:10.1186/1748-5908-7-37

    Article  PubMed  PubMed Central  Google Scholar 

  • Cane, J., Richardson, M., Johnston, M., Ladha, R., & Michie, S. (2015). From lists of behaviour change techniques (BCTs) to structured hierarchies: Comparison of two methods of developing a hierarchy of BCTs. British Journal of Health Psychology, 20, 130–150. doi:10.1111/bjhp.12102

    Article  PubMed  Google Scholar 

  • Chinn, P., & Kramer, M. (1991). Theory and nursing: A systematic approach (3rd ed.). St. Louis, MO: Mosby Year Book.

  • Chorpita, B. F., Rotheram-Borus, M. J., Daleiden, E. L., Bernstein, A., Cromley, T., Swendeman, D., et al. (2011). The old solutions are the new problem how do we better use what we already know about reducing the burden of mental illness? Perspectives on Psychological Science, 6, 493–497. doi:10.1177/1745691611418240

    Article  PubMed  Google Scholar 

  • Cobb, N. K., Graham, A. L., Byron, M. J., Niaura, R. S., & Abrams, D. B. (2011). Online social networks and smoking cessation: A scientific research agenda. Journal of Medical Internet Research, 13, e119. doi:10.2196/jmir.1911

    Article  PubMed  PubMed Central  Google Scholar 

  • Connell, L., Johnston, M., Carey, R., Rothman, A., Kelly, M., & De Bruin, et al. (2015). Linking behaviour change techniques with theory. In S. Michie (Ed.), Making sense of behaviour change: problems, methods and applications. Symposium conducted at the meeting of the European Health Psychology Society, Nicosia, Cyprus.

  • Davis, R. E., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015). Theories of behaviour and behaviour change across the social and behavioural sciences: A scoping review. Health Psychology Review, 9, 323–344. doi:10.1080/17437199.2014.941722

    Article  PubMed  Google Scholar 

  • Deerwester, S. C., Dumais, S. T., Landauer, T. K., Furnas, G. W., & Harshman, R. A. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science., 41, 391–407. doi:10.1002/(SICI)1097-4571(199009)41:6<391:AID-ASI1>3.0.CO;2-9

    Article  Google Scholar 

  • Fiannaca, A., La Rosa, M., Rizzo, R., Urso, A., & Gaglio, S. (2012). An ontology design methodology for knowledge-based systems with application to bioinformatics. In 2012 IEEE symposium on computational intelligence in bioinformatics and computational biology (CIBCB) (pp. 85–91). IEEE.

  • French, S. D., Green, S. E., O’Connor, D. A., McKenzie, J. E., Francis, J. J., Michie, S., et al. (2012). Developing theory-informed behaviour change interventions to implement evidence into practice: A systematic approach using the theoretical domains framework. Implementation Science, 7, 38. doi:10.1186/1748-5908-7-38

    Article  PubMed  PubMed Central  Google Scholar 

  • Gennari, J. H., Musen, M. A., Fergerson, R. W., Grosso, W. E., Crubézy, M., Eriksson, H., et al. (2003). The evolution of Protégé: an environment for knowledge-based systems development. International Journal of Human-Computer Studies, 58, 89–123. doi:10.1016/S1071-5819(02)00127-1

    Article  Google Scholar 

  • Hall, D., Huerta, M. F., McAuliffe, M. J., & Farber, G. K. (2012). Sharing heterogeneous data: The national database for autism research. Neuroinformatics, 10, 331–339. doi:10.1007/s12021-012-9151-4

    Article  PubMed  PubMed Central  Google Scholar 

  • Hanna, J., Joseph, E., Brochhausen, M., & Hogan, W. R. (2013). Building a drug ontology based on RxNorm and other sources. Journal of Biomedical Semantics, 4, 44. Retrieved from: http://www.jbiomedsem.com/content/4/1/44

  • Hardeman, W., Sutton, S., Griffin, S., Johnston, M., White, A., Wareham, N. J., et al. (2005). A causal modelling approach to the development of theory-based behaviour change programmes for trial evaluation. Health Education Research, 20, 676–687. doi:10.1093/her/cyh022

    Article  PubMed  Google Scholar 

  • Hesse, B. W., Moser, R. P., & Riley, W. T. (2015). From big data to knowledge in the social sciences. The Annals of the American Academy of Political and Social Science, 659, 16–32. doi:10.1177/0002716215570007

    Article  PubMed  PubMed Central  Google Scholar 

  • Hunter, J. (2003). Enhancing the semantic interoperability of multimedia through a core ontology. IEEE Transactions on Circuits and Systems for Video Technology, 13, 49–58. doi:10.1109/TCSVT.2002.808088

    Article  Google Scholar 

  • ICPSR. (2016). Membership in ICPSR. Retrieved from: https://www.icpsr.umich.edu/icpsrweb/content/membership/index.html

  • IOM (Institute of Medicine). (2008). Committee on reviewing evidence to identify highly effective clinical services. Knowing what works in health care: A roadmap for the nation. Washington, DC: National Academies Press. doi:10.17226/12038

    Google Scholar 

  • IOM (Institute of Medicine). (2011). Patients charting the course: Citizen engagement and the learning health system—Workshop summary. Washington, D.C.: National Academies Press.

    Google Scholar 

  • Jacobs, A. (2009). The pathologies of big data. Communications of the ACM, 52, 36–44. doi:10.1145/1536616.1536632

    Article  Google Scholar 

  • Kelder, S. H., Hoelscher, D., & Perry, C. L. (2015). How individuals, environment, and health behaviors interact. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior: Theory, research, and practice (5th ed., pp. 159–182). San Francisco: Wiley.

    Google Scholar 

  • Kelley, T. L. (1927). Interpretation of educational measurements. Oxford, England: World Book Company.

    Google Scholar 

  • Kelly, M. P., & Moore, T. A. (2012). The judgment process in evidence-based medicine and health technology assessment. Social Theory and Health, 10, 1–19. doi:10.1057/sth.2011.21

    Article  PubMed  Google Scholar 

  • Kolenikov, S., & Angeles, G. (2009). Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer? Review of Income and Wealth, 55, 128–165. doi:10.1111/j.1475-4991.2008.00309.x

    Article  Google Scholar 

  • Larsen, K. (2016). Inter-nomological network. Retrieved from: http://inn.theorizeit.org

  • Larsen, K. R., & Bong, C. H. (2016). A tool for addressing construct identity in literature reviews and meta-analyses. MIS Quarterly, 40, 529–551.

  • Larsen, K. R., Michie, S., West, R., & Gurshuny, V. (2015). Developing an interdisciplinary taxonomy of behavior. In W. T. Riley (Ed.), 37: Toward an ontology of behavior change—An innovative approach to intervention development. Symposium conducted at the annual meeting of the society of behavioral medicine, San Antonio, TX.

  • Li, J., & Larsen, K. R. (2011). Establishing nomological networks for behavioral science: A natural language processing based approach. In 2011 Proceedings of the international conference on information systems, paper 24. Available at: http://aisel.aisnet.org/icis2011/proceedings/knowledge/24

  • Litwin, M. S. (1995). How to measure survey reliability and validity. London, England: Sage Publications.

    Book  Google Scholar 

  • Liu, Y., Hinds, P. S., Wang, J., Correia, H., Du, S., Ding, J., et al. (2013). Translation and linguistic validation of the pediatric patient-reported outcomes measurement information system measures into simplified Chinese using cognitive interviewing methodology. Cancer Nursing, 36, 368–376. doi:10.1097/NCC.0b013e3182962701

    Article  PubMed  Google Scholar 

  • Lorencatto, F., West, R., Bruguera, C., Brose, L., & Michie, S. (2015). Assessing quality of goal-setting in behavioural support for smoking cessation and the association with outcomes. Annals of Behavioral Medicine,. doi:10.1007/s12160-015-9755-7

    PubMed Central  Google Scholar 

  • Lowe, H. J., & Barnett, O. G. (1994). Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches. JAMA, 271, 1103–1108. doi:10.1001/jama.1994.03510380059038

    Article  CAS  PubMed  Google Scholar 

  • McGinnis, J. M., Williams-Russo, P., & Knickman, J. R. (2002). The case for more active policy attention to health promotion. Health Affairs, 21, 78–93. doi:10.1377/hlthaff.21.2.78

    Article  PubMed  Google Scholar 

  • McGuinness, D. L., & Van Harmelen, F. (2004). OWL web ontology language overview. W3C recommendation 10 February. Retrieved from: http://www.w3.org/TR/2004/REC-owl-features-20040210/

  • Memidex. (2013). Domains. Retrieved from: http://www.memidex.com/domains

  • Meriam-Webster. (2015). Domain. Available at: http://www.merriam-webster.com/dictionary/domain

  • Michie, S., & Johnston, M. (2012). Theories and techniques of behaviour change: Developing a cumulative science of behaviour change. Health Psychology Review, 6, 1–6. doi:10.1080/17437199.2012.654964

    Article  Google Scholar 

  • Michie, S., Johnston, M., Abraham, C., Lawton, R., Parker, D., & Walker, A. (2005). Making psychological theory useful for implementing evidence based practice: A consensus approach. Quality and Safety in Health Care, 14, 26–33. doi:10.1136/qshc.2004.011155

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Michie, S., Johnston, M., Francis, J., Hardeman, W., & Eccles, M. (2008). From theory to intervention: mapping theoretically derived behavioural determinants to behaviour change techniques. Applied Psychology, 57, 660–680. doi:10.1111/j.1464-0597.2008.00341.x

    Article  Google Scholar 

  • Michie, S., Johnston, M., Rothman, A., Kelly, M., & de Bruin, M. (2014). Behaviour change techniques and theory: The theories and techniques of behavior change project. Retrieved from: https://www.ucl.ac.uk/behaviour-change-techniques

  • Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., et al. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46, 81–95. doi:10.1007/s12160-013-9486-6

    Article  PubMed  Google Scholar 

  • Michie, S., West, R., Sheals, K., Carey, R., & Connell, L. (2015a). Integrating constructs across 83 theories of behaviour change: Development of a method. Paper presented at the meeting of the society of behavioral medicine, annual meeting, San Antonio, USA.

  • Michie, S., Wood, C., Johnston, M., Abraham, C., Francis, J., & Hardeman, W. (2015b). Behaviour change techniques: The development and evaluation of a taxonomic method for reporting and describing behaviour change interventions. Health Technology Assessment,. doi:10.3310/hta19990

    Google Scholar 

  • Moser, R. P., Hesse, B. W., Shaikh, A. R., Courtney, P., Morgan, G., Augustson, E., et al. (2011). Grid-enabled measures: Using science 2.0 to standardize measures and share data. American Journal of Preventive Medicine, 40, S134–S143. doi:10.1016/j.amepre.2011.01.004

    Article  PubMed  PubMed Central  Google Scholar 

  • NCI (National Cancer Institute). (2016). GEM (Grid-enabled measures database). Retrieved from: https://www.gem-beta.org/Public/Home.aspx

  • National Research Council. (2011). Toward precision medicine: Building a knowledge network for biomedical research and a new taxonomy of disease. Washington, DC: The National Academies Press. doi:10.17226/13284

    Google Scholar 

  • Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., et al. (2015). Promoting an open research culture: Author guidelines for journals could help to promote transparency, openness, and reproducibility. Science, 348, 1422–1425. doi:10.1126/science.aab2374

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Open Geospatial Consortium. (2016). Retrieved from: http://www.opengeospatial.org

  • Open Science Framework. (2016). Open science framework: A scholarly commons to connect the entire research cycle. Retrieved from: https://osf.io

  • Oxford English Dictionary. (2016). Class. Retrieved from: http://www.oed.com/view/Entry/33874?rskey=Wk0x4G&result=1#eid

  • Paz, S. H., Spritzer, K. L., Morales, L. S., & Hays, R. D. (2013). Evaluation of the patient-reported outcomes information system (PROMIS®) Spanish-language physical functioning items. Quality of Life Research, 22, 1819–1830. doi:10.1007/s11136-012-0292-6

    Article  PubMed  Google Scholar 

  • Pennebaker, J. W., & Graybeal, A. (2001). Patterns of natural language use: Disclosure, personality, and social integration. Current Directions in Psychological Science, 10, 90–93.

    Article  Google Scholar 

  • Poldrack, R. (2016). The cognitive atlas. Available at: http://www.cognitiveatlas.org

  • President’s Council of Advisors on Science and Technology (PCAST). (2010). Designing a digital future: Federally funded research and development in networking and information technology. Washington, DC: Executive Office of the President of the United States. Retrieved from: https://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-nitrd-report-2010.pdf

  • PROsetta Stone®. (2016). What is PROsetta stone? Retrieved from: http://www.prosettastone.org

  • Schalet, B. D., Cook, K. F., Choi, S. W., & Cella, D. (2014). Establishing a common metric for self-reported anxiety: Linking the MASQ, PANAS, and GAD-7 to PROMIS Anxiety. Journal of Anxiety Disorders, 28, 89–96. doi:10.1016/j.janxdis.2013.11.006

    Article  Google Scholar 

  • Staunton, L., Gellert, P., Knittle, K., & Sniehotta, F. F. (2014). Perceived control and intrinsic vs. extrinsic motivation for oral self-care: A full factorial experimental test of theory-based persuasive messages. Annals of Behavioral Medicine, 49, 258–268. doi:10.1007/s12160-014-9655-2

    Article  Google Scholar 

  • Stavri, Z., & Michie, S. (2012). Classification systems in behavioural science: Current systems and lessons from the natural, medical and social sciences. Health Psychology Review, 6, 113–140. doi:10.1080/17437199.2011.641101

    Article  Google Scholar 

  • The Gene Ontology Consortium. (2015a). Gene ontology consortium: Going forward. Nucleic Acids Research, 43, D1049–D1056. doi:10.1093/nar/gku1179

    Article  Google Scholar 

  • The Gene Ontology Consortium. (2015b). What is the gene ontology? Retreived from: http://geneontology.org

  • Thorndike, E. (1904). An introduction to the theory of mental and social measurements. New York: The Science Press.

    Book  Google Scholar 

  • U.S. National Library of Medicine. (1999). Fact sheet: Medical subject headings (MeSH®). Available at: https://www.nlm.nih.gov/pubs/factsheets/mesh.html

  • U.S. National Library of Medicine. (2012). Common data element (CDE) resource portal. Retrieved at: https://www.nlm.nih.gov/cde/

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478. Retrieved from: http://www.jstor.org/stable/30036540

  • Walls, R. L., Athreya, B., Cooper, L., Elser, J., Gandolfo, M. A., Jaiswal, P., et al. (2012). Ontologies as integrative tools for plant science. American Journal of Botany, 99, 1263–1275. doi:10.3732/ajb.1200222

    Article  PubMed  PubMed Central  Google Scholar 

  • Weber, R. (2012). Evaluating and developing theories in the information systems discipline. Journal of the Association for Information Systems, 13, 1–30.

    Google Scholar 

  • Weisz, J. R., Ng, M. Y., & Bearman, S. K. (2014). Odd couple? Reenvisioning the relation between science and practice in the dissemination-implementation era. Clinical Psychological Science, 2, 58–74. doi:10.1177/2167702613501307

    Article  Google Scholar 

  • West, R., & Michie, S. (2016). A guide to development and evaluation of digital behaviour change interventions in healthcare (version 1). London: Silverback Publishing.

  • Wong, W., Liu, W., & Bennamoun, M. (2012). Ontology learning from text: A look back and into the future. ACM Computing Surveys (CSUR), 44, 20. doi:10.1145/2333112.2333115

    Article  Google Scholar 

  • World Health Organization. (2013). How to use the ICF: A practical manual for using the international classification of functioning. Disability and health (ICF). Exposure draft for comment. October 2013. Geneva: WHO. Retrieved from: http://www.who.int/classifications/drafticfpracticalmanual.pdf

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Acknowledgments

We are grateful for the helpful suggestions and edits provided by the metaBUS team, specifically Frank Bosco, Krista Uggerslev, and Piers Steel. We further appreciate the help from from George Alter at the Inter-University Consortium for Political and Social Research, William Riley, Office of Behavioral and Social Sciences Research, the National Institutes of Health, as well as from Robert West at the Department of Epidemiology and Public Health, University College London.

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Authors and Affiliations

  1. Leeds School of Business, University of Colorado, Boulder, CO, USA

    Kai R. Larsen

  2. Centre for Behaviour Change, University College London, London, UK

    Susan Michie

  3. School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ, USA

    Eric B. Hekler

  4. Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA

    Bryan Gibson

  5. Department of Psychology, Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA

    Donna Spruijt-Metz

  6. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    David Ahern

  7. Johnson and Johnson Health and Wellness Solutions, New Brunswick, NJ, USA

    Heather Cole-Lewis

  8. Indiana University School of Nursing, Indianapolis, IN, USA

    Rebecca J. Bartlett Ellis

  9. National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Bradford Hesse

  10. Behavioral Research Program, National Cancer Institute, Rockville, MD, USA

    Richard P. Moser

  11. Clinical Research Division, Fred Hutch, Seattle, WA, USA

    Jean Yi

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Correspondence to Kai R. Larsen.

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Kai R. Larsen, Susan Michie, Eric B. Hekler, Bryan Gibson, Donna Spruijt-Metz, David Ahern, Heather Cole-Lewis, Rebecca J. Bartlett Ellis, Bradford Hesse, Richard P. Moser, and Jean Yi declare that they do not have any conflict of interest.

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All procedures followed were in accordance with ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

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Larsen, K.R., Michie, S., Hekler, E.B. et al. Behavior change interventions: the potential of ontologies for advancing science and practice. J Behav Med 40, 6–22 (2017). https://doi.org/10.1007/s10865-016-9768-0

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