Book contents
- The Handbook of Behavior Change
- The Handbook of Behavior Change
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Sidebars
- Contributors
- 1 Changing Behavior: A Theory- and Evidence-Based Approach
- Part I Theory and Behavior Change
- Part II Methods and Processes of Behavior Change: Intervention Development, Application, and Translation
- 19 Design, Implementation, and Evaluation of Behavior Change Interventions: A Ten-Task Guide
- 20 Moving from Theoretical Principles to Intervention Strategies: Applying the Experimental Medicine Approach
- 21 Developing Behavior Change Interventions
- 22 Evaluation of Behavior Change Interventions
- 23 Implementation Science and Translation in Behavior Change
- 24 Engagement of Stakeholders in the Design, Evaluation, and Implementation of Complex Interventions
- 25 Maximizing User Engagement with Behavior Change Interventions
- 26 Cost-Effectiveness Evaluations of Behavior Change Interventions
- 27 Addressing Underserved Populations and Disparities in Behavior Change
- 28 Behavior Change in Community Contexts
- 29 Changing Behavior in the Digital Age
- 30 Critical and Qualitative Approaches to Behavior Change
- Part III Behavior Change Interventions: Practical Guides to Behavior Change
- Index
- References
25 - Maximizing User Engagement with Behavior Change Interventions
from Part II - Methods and Processes of Behavior Change: Intervention Development, Application, and Translation
Published online by Cambridge University Press: 04 July 2020
Book contents
- The Handbook of Behavior Change
- The Handbook of Behavior Change
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Sidebars
- Contributors
- 1 Changing Behavior: A Theory- and Evidence-Based Approach
- Part I Theory and Behavior Change
- Part II Methods and Processes of Behavior Change: Intervention Development, Application, and Translation
- 19 Design, Implementation, and Evaluation of Behavior Change Interventions: A Ten-Task Guide
- 20 Moving from Theoretical Principles to Intervention Strategies: Applying the Experimental Medicine Approach
- 21 Developing Behavior Change Interventions
- 22 Evaluation of Behavior Change Interventions
- 23 Implementation Science and Translation in Behavior Change
- 24 Engagement of Stakeholders in the Design, Evaluation, and Implementation of Complex Interventions
- 25 Maximizing User Engagement with Behavior Change Interventions
- 26 Cost-Effectiveness Evaluations of Behavior Change Interventions
- 27 Addressing Underserved Populations and Disparities in Behavior Change
- 28 Behavior Change in Community Contexts
- 29 Changing Behavior in the Digital Age
- 30 Critical and Qualitative Approaches to Behavior Change
- Part III Behavior Change Interventions: Practical Guides to Behavior Change
- Index
- References
Summary
This chapter describes key methods to promote intervention engagement in order to maximize uptake, prevent early dropout, and support sustained behavior change. The importance of reviewing or conducting qualitative and mixed methods research on target users’ attitudes, capabilities, and lifestyle is highlighted so that interventions can be designed to meet users’ needs. Tailoring interventions is useful to provide appropriate advice and support for the needs of the target population – especially among those who find it difficult to engage due to personal circumstances or lack of resources. Interventions should then be optimized by collecting data on how people engage with them and iteratively modifying them to improve engagement. Qualitative studies are needed to explore target users’ views of intervention elements. Quantitative usage and outcome data are valuable to analyze usage patterns and identify predictors of dropout or effective behavior change. To maintain longer-term engagement with behavior change, it can be useful to harness social support and establish environment-prompted habits that require less deliberative effort to sustain. The chapter provides examples and tools that can be used to design and optimize interventions, drawing on the “person-based approach” that has been used to develop many interventions that have proved engaging and effective.
Keywords
Information
- Type
- Chapter
- Information
- The Handbook of Behavior Change , pp. 361 - 371Publisher: Cambridge University PressPrint publication year: 2020
References
Abrahamse, W., & Steg, L. (2013). Social influence approaches to encourage resource conservation: A meta-analysis. Global Environmental Change, 23, 1773–1785. https://doi.org/https://doi.org/10.1016/j.gloenvcha.2013.07.029CrossRefGoogle Scholar
Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2007). The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. Journal of Environmental Psychology, 27, 265–276. https://doi.org/10.1016/j.jenvp.2007.08.002Google Scholar
Bauer, C., & Strauss, . (2016). Location-based advertising on mobile devices. Management Review Quarterly, 66, 159–194. https://doi.org/10.1007/s11301-015-0118-zGoogle Scholar
Baumeister, H., Reichler, L., Munzinger, M., & Lin, J. (2014). The impact of guidance on Internet-based mental health interventions: A systematic review. Internet Interventions, 1, 205–215. https://doi.org/10.1016/j.invent.2014.08.003CrossRefGoogle Scholar
Bradbury, K., Morton, K., Band, R. et al. (2018). Using the Person-Based Approach to optimise a digital intervention for the management of hypertension. PloS ONE, 13, e0196868. https://doi.org/10.1371/journal.pone.0196868CrossRefGoogle ScholarPubMed
Christakis, N. A., & Fowler, J. H. (2009). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York: Little, Brown.Google Scholar
Collins, L. M., Murphy, S. A., & Strecher, V. (2007). The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): New methods for more potent eHealth interventions. American Journal of Preventive Medicine, 32, S112–S118. https://doi.org/10.1016/j.amepre.2007.01.022.CrossRefGoogle Scholar
Corbett, T., Cheetham, T., Müller, A. M. et al. (2018). Exploring cancer survivors’ views of health behaviour change: “Where do you start, where do you stop with everything?” Psycho‐Oncology, 27, 1816–1824. https://doi.org/10.1002/pon.4732Google Scholar
Cotton, D., & Gresty, K. (2006). Reflecting on the think‐aloud method for evaluating e‐learning. British Journal of Educational Technology, 37, 45–54. https://doi.org/10.1111/j.1467-8535.2005.00521Google Scholar
Friedman, C. P., Allee, N. J., Delaney, B. C. et al. (2017). The science of learning health systems: Foundations for a new journal. Learning Health Systems, 1, e10020. https://doi.org/10.1002/lrh2.10020CrossRefGoogle ScholarPubMed
Harris, P. R., Sillence, E., & Briggs, P. (2011). Perceived threat and corroboration: Key factors that improve a predictive model of trust in internet-based health information and advice. Journal of Medical Internet Research, 13, e51. https://doi.org/10.2196/jmir.1821Google Scholar
Kreuter, M. W., Bull, F. C., Clark, E. M., & Oswald, D. L. (1999). Understanding how people process health information: A comparison of tailored and nontailored weight-loss materials. Health Psychology, 18, 487. https://doi.org/10.1037/0278-6133.18.5.487CrossRefGoogle ScholarPubMed
Krug, S. (2006). Don’t Make Me Think! A Common Sense Approach to Web Usability. (2nd ed.). New York: New Riders.Google Scholar
Little, P., Stuart, B., Hobbs, F. R. et al. (2016). An internet-based intervention with brief nurse support to manage obesity in primary care (POWeR+): A pragmatic, parallel-group, randomised controlled trial. The Lancet Diabetes and Endocrinology, 4, 821–828. https://doi.org/10.1016/S2213-8587(16)30099-7Google Scholar
Lorig, K. R., & Holman, H. R. (2003). Self-management education: History, definition, outcomes, and mechanisms. Annals of Behavioral Medicine, 26, 1–7. https://doi.org/10.1207/S15324796ABM2601_01CrossRefGoogle ScholarPubMed
Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139. https://doi.org/10.1016/S0079-7421(02)80005-6Google Scholar
Mohr, D. C., Lyon, A. R., Lattie, E. G., Reddy, M., & Schueller, S. M. (2017). Accelerating digital mental health research from early design and creation to successful implementation and sustainment. Journal of Medical Internet Research, 19, e153. https://doi.org/10.2196/jmir.7725CrossRefGoogle ScholarPubMed
Morrison, L., Moss‐Morris, R., Michie, S., & Yardley, L. (2014). Optimizing engagement with Internet‐based health behaviour change interventions: Comparison of self‐assessment with and without tailored feedback using a mixed methods approach. British Journal of Health Psychology, 19, 839–855. https://doi.org/10.1111/bjhp.12083Google Scholar
Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D. (2015). Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework. Health Psychology, 34, 1209. https://doi.org/10.1037/hea0000306CrossRefGoogle Scholar
Naughton, F., Hopewell, S., Lathia, N. et al. (2016). A context-sensing mobile phone app (Q sense) for smoking cessation: A mixed-methods study. JMIR mHealth and uHealth, 4, e106. https://doi.org/10.2196/mhealth.5787Google Scholar
Rowsell, A., Muller, I., Murray, E. et al. (2015). Views of people with high and low levels of health literacy about a digital intervention to promote physical activity for diabetes: A qualitative study in five countries. Journal of Medical Internet Research, 17, e230. https://doi.org/10.2196/jmir.4999CrossRefGoogle ScholarPubMed
Sbaffi, L., & Rowley, J. (2017). Trust and credibility in web-based health information: A review and agenda for future research. Journal of Medical Internet Research, 19, e218. https://doi.org/10.2196/jmir.7579CrossRefGoogle ScholarPubMed
Singal, A. G., Higgins, P. D., & Waljee, A. K. (2014). A primer on effectiveness and efficacy trials. Clinical and Translational Gastroenterology, 5, e45. https://doi.org/10.1038/ctg.2013.13Google Scholar
Smith, G. L., Banting, L., Eime, R., O’Sullivan, G., & van Uffelen, J. G. (2017). The association between social support and physical activity in older adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 14, 56. https://doi.org/10.1186/s12966-017-0509-8.Google Scholar
van Beurden, S. B., Greaves, C. J., Smith, J. R., & Abraham, C. (2016). Techniques for modifying impulsive processes associated with unhealthy eating: A systematic review. Health Psychology, 35, 793. https://doi.org/10.1037/hea0000337.Google Scholar
Van den Haak, M. J., De Jong, M. D., & Schellens, P. J. (2007). Evaluation of an informational web site: Three variants of the think-aloud method compared. Technical Communication, 54, 58–71.Google Scholar
Van Velsen, L., Wentzel, J., & Van Gemert-Pijnen, J. E. (2013). Designing eHealth that matters via a multidisciplinary requirements development approach. JMIR Research Protocols, 2, e21. https://doi.org/10.2196/resprot.2547Google Scholar
Yardley, L., Morrison, L., Bradbury, K., & Muller, I. (2015). The Person-Based Approach to intervention development: Application to digital health-related behavior change interventions. Journal of Medical Internet Research, 17, e30. https://doi.org/10.2196/jmir.4055CrossRefGoogle ScholarPubMed
Yardley, L., Spring, B. J., Riper, H. et al. (2016). Understanding and promoting effective engagement with digital behavior change interventions. American Journal of Preventive Medicine, 51, 833–842.Google Scholar
Accessibility standard: Unknown
Why this information is here
This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.Accessibility Information
Accessibility compliance for the HTML of this chapter is currently unknown
and may be updated in the future.