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  • Perspective
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Changing health behaviours in rheumatology: an introduction to behavioural economics

Abstract

Although the management of patients with rheumatic diseases has evolved substantially over the past 20 to 30 years, lifestyle changes (such as weight reduction, physical activity and medication adherence) remain an important and unmet challenge in improving patient outcomes. The field of behavioural economics considers the many ways that individuals behave irrationally and uses the predictability of these patterns to create opportunities to anticipate and avoid or harness these behaviours to improve patient outcomes. Existing among other motivational approaches, the concepts in behavioural economics have only been applied to health care in the past 10 to 15 years. Although few published examples have applied behavioural economic concepts in the management of patients with rheumatic diseases specifically, these concepts have been applied in other chronic diseases, and such interventions could also be applicable in rheumatology. In this Perspectives article, we introduce six principles in behavioural economics (loss aversion, framing effect, present bias, status quo bias, time inconsistency and social normalization), discuss how these concepts have been addressed in other fields and examine their potential application in rheumatology. Using physical activity as an example, we describe how these concepts could be applied to promote healthy behaviour in patients with inflammatory arthritis.

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Fig. 1: Potential interventions to increase physical activity in patients with inflammatory arthritis.

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References

  1. Rehman, T. Historical context of behavioral economics. Intellect. Econ. 10, 128–132 (2016).

    Google Scholar 

  2. Stevens, J. Behavioral economics strategies for promoting adherence to sleep interventions. Sleep Med. Rev. 23, 20–27 (2015).

    PubMed  Google Scholar 

  3. Matjasko, J. L., Cawley, J. H., Baker-Goering, M. M. & Yokum, D. V. Applying behavioral economics to public health policy: illustrative examples and promising directions. Am. J. Prev. Med. 50, S13–S19 (2016).

    PubMed  PubMed Central  Google Scholar 

  4. Loewenstein, G. H. et al. A behavioral blueprint for improving health care policy. Behav. Sci. Policy. 3, 53–66. (2017).

    Google Scholar 

  5. Volpp, K., Loewenstein, G. & Asch, D. A. in Harrison’s Principles of Internal Medicine 20th edn Vol 1, Ch. 468 (eds Jameson, J. L., Fauci, A. S., Kasper, D. L., Hauser, S. L., Longo, D. L. & Loscalzo, J.) (McGraw-Hill, 2018).

  6. Gong, Y., Trentadue, T. P., Shrestha, S., Losina, E. & Collins, J. E. Financial incentives for objectively-measured physical activity or weight loss in adults with chronic health conditions: a meta-analysis. PLoS One 13, e0203939 (2018).

    PubMed  PubMed Central  Google Scholar 

  7. Smith, K. C. et al. Cost-effectiveness of health coaching and financial incentives to promote physical activity after total knee replacement. Osteoarthr. Cartil. 26, 1495–1505 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Kahneman, D. T. & Tversky, A. Prospect Theory: an analysis of decision under risk. Econometrica 47, 263—291 (1979).

    Google Scholar 

  9. Patel, M. S. et al. Framing financial incentives to increase physical activity among overweight and obese adults: a randomized, controlled trial. Ann. Intern. Med. 164, 385–394 (2016).

    PubMed  PubMed Central  Google Scholar 

  10. McNeil, B. J., Pauker S. G., Sox, H. C. Jr & Tversky, A. in Preference, Belief and Similarity Ch. 23 (ed. Shafir, E.) 583–592 (MIT Press, 2004).

  11. Parkes, G., Greenhalgh, T., Griffin, M. & Dent, R. Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial. Br. Med. J. 336, 598–600 (2008).

    Google Scholar 

  12. Schneider, T. R. et al. The effects of message framing and ethnic targeting on mammography use among low-income women. Health Psychol. 20, 256–266 (2001).

    CAS  PubMed  Google Scholar 

  13. Lipstein, E. A. et al. High levels of decisional conflict and decision regret when making decisions about biologics. J. Pediatr. Gastroenterol. Nutr. 63, e176–e181 (2016).

    PubMed  PubMed Central  Google Scholar 

  14. Caporali, R. et al. 20 years of experience with tumour necrosis factor inhibitors: what have we learned? Rheumatology 57, Suppl 7 vii5–vii10 (2018).

    CAS  PubMed  Google Scholar 

  15. Mercer, L. K. et al. Risk of lymphoma in patients exposed to antitumour necrosis factor therapy: results from the British Society for Rheumatology Biologics Register for Rheumatoid Arthritis. Ann. Rheum. Dis. 76, 497–503 (2017).

    PubMed  PubMed Central  Google Scholar 

  16. Bickel, W. K., Johnson, M. W., Koffarnus, M. N., MacKillop, J. & Murphy, J. G. The behavioral economics of substance use disorders: reinforcement pathologies and their repair. Annu. Rev. Clin. Psychol. 10, 641–677 (2014).

    PubMed  PubMed Central  Google Scholar 

  17. Halpern, S. D. et al. Randomized trial of four financial-incentive programs for smoking cessation. N. Engl. J. Med. 372, 2108–2117 (2015).

    PubMed  PubMed Central  Google Scholar 

  18. Halpern, S. D. et al. A pragmatic trial of E-cigarettes, incentives, and drugs for smoking cessation. N. Engl. J. Med. 378, 2302–2310 (2018).

    PubMed  Google Scholar 

  19. Volpp, K. G. et al. Financial incentive-based approaches for weight loss: a randomized trial. JAMA 300, 2631–2637 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Athamneh, L. N., Stein, J. S. & Bickel, W. K. Will delay discounting predict intention to quit smoking? Exp. Clin. Psychopharmacol. 25, 273–280 (2017).

    PubMed  PubMed Central  Google Scholar 

  21. Odum, A. L. Delay discounting: I’m a k, you’re a k. J. Exp. Anal. Behav. 96, 427–439 (2011).

    PubMed  PubMed Central  Google Scholar 

  22. Thorgeirsson, T. & Kawachi, I. Behavioral economics: merging psychology and economics for lifestyle interventions. Am. J. Prev. Med. 44, 185–189 (2013).

    PubMed  Google Scholar 

  23. Patel, M. S. et al. Using wearable devices and smartphones to track physical activity: initial activation, sustained use, and step counts across sociodemographic characteristics in a national sample. Ann. Intern. Med. 167, 755–757 (2017).

    PubMed  Google Scholar 

  24. Patel, M. S. et al. A randomized, controlled trial of lottery-based financial incentives to increase physical activity among overweight and obese adults. Am. J. Health Promot. 32, 1568–1575 (2018).

    PubMed  Google Scholar 

  25. Patel, M. S. et al. Individual versus team-based financial incentives to increase physical activity: a randomized, controlled trial. J. Gen. Intern. Med. 31, 746–754 (2016).

    PubMed  PubMed Central  Google Scholar 

  26. Volpp, K. G. et al. A randomized, controlled trial of financial incentives for smoking cessation. N. Engl. J. Med. 360, 699–709 (2009).

    CAS  PubMed  Google Scholar 

  27. Mehat, P., Atiquzzaman, M., Esdaile, J. M., AviNa-Zubieta, A. & De Vera, M. A. Medication nonadherence in systemic lupus erythematosus: a systematic review. Arthritis Care Res. 69, 1706–1713 (2017).

    Google Scholar 

  28. Kui, R. et al. Presence of antidrug antibodies correlates inversely with the plasma tumor necrosis factor (TNF)-α level and the efficacy of TNF-inhibitor therapy in psoriasis. J. Dermatol. 43, 1018–1023 (2016).

    CAS  PubMed  Google Scholar 

  29. Calip, G. S. et al. Medication adherence and persistence over time with self-administered TNF-α inhibitors among young adult, middle-aged, and older patients with rheumatologic conditions. Semin. Arthritis Rheum. 47, 157–164 (2017).

    CAS  PubMed  Google Scholar 

  30. DiBenedetti, D. B., Zhou, X., Reynolds, M., Ogale, S. & Best, J. H. Assessing methotrexate adherence in rheumatoid arthritis: a cross-sectional survey. Rheumatol. Ther. 2, 73–84 (2015).

    PubMed  PubMed Central  Google Scholar 

  31. Lorish, C. D., Richards, B. & Brown, S. Missed medication doses in rheumatic arthritis patients: intentional and unintentional reasons. Arthr. Care Res. 2, 3–9 (1989).

    CAS  Google Scholar 

  32. Asch, D. A. et al. Effect of financial incentives to physicians, patients, or both on lipid levels: a randomized clinical trial. JAMA 314, 1926–1935 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Checchi, K. D., Huybrechts, K. F., Avorn, J. & Kesselheim, A. S. Electronic medication packaging devices and medication adherence: a systematic review. JAMA 312, 1237–1247 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Balkrishnan, R., Carroll, C. L., Camacho, F. T. & Feldman, S. R. Electronic monitoring of medication adherence in skin disease: results of a pilot study. J. Am. Acad. Dermatol. 49, 651–654 (2003).

    PubMed  Google Scholar 

  35. Halpern, S. D., Asch, D. A. & Volpp, K. G. Commitment contracts as a way to health. BMJ 344, e522 (2012).

    PubMed  PubMed Central  Google Scholar 

  36. Alsan, M. et al. A commitment contract to achieve virologic suppression in poorly adherent patients with HIV/AIDS. AIDS. 31, 1765–1769 (2017).

    PubMed  PubMed Central  Google Scholar 

  37. Milkman, K. L., Beshears, J., Choi, J. J., Laibson, D. & Madrian, B. C. Using implementation intentions prompts to enhance influenza vaccination rates. Proc. Natl Acad. Sci. USA 108, 10415–10420 (2011).

    CAS  PubMed  Google Scholar 

  38. Rogers, T., Milkman, K. L. & Volpp, K. G. Commitment devices: using initiatives to change behavior. JAMA 311, 2065–2066 (2014).

    CAS  PubMed  Google Scholar 

  39. Patel, M. S. et al. Generic medication prescription rates after health system-wide redesign of default options within the electronic health record. JAMA Intern. Med. 176, 847–848 (2016).

    PubMed  Google Scholar 

  40. Mehta, S. J. et al. A randomized controlled trial of opt-in versus opt-out colorectal cancer screening outreach. Am. J. Gastroenterol. 113, 1848–1854 (2018).

    PubMed  PubMed Central  Google Scholar 

  41. Halpern, S. D., Ubel, P. A. & Asch, D. A. Harnessing the power of default options to improve health care. N. Engl. J. Med. 357, 1340–1344 (2007).

    CAS  PubMed  Google Scholar 

  42. Patel, M. S., Volpp, K. G. & Asch, D. A. Nudge units to improve the delivery of health care. N. Engl. J. Med. 378, 214–216 (2018).

    PubMed  PubMed Central  Google Scholar 

  43. Patel, M. S. et al. Using active choice within the electronic health record to increase influenza vaccination rates. J. Gen. Intern. Med. 32, 790–795 (2017).

    PubMed  PubMed Central  Google Scholar 

  44. Patel MSK, G. W. & Kannan, S. Effect of an automated patient dashboard using active choice and peer comparison performance feedback to physicians on statin prescribing: the PRESCRIBE Cluster Randomized Trial. JAMA Netw. Open 1, e180818 (2018).

    Google Scholar 

  45. Delgado, M. K. et al. Association between electronic medical record implementation of default opioid prescription quantities and prescribing behavior in two emergency departments. J. Gen. Intern. Med. 33, 409–411 (2018).

    PubMed  PubMed Central  Google Scholar 

  46. Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J. & Griskevicius, V. The constructive, destructive, and reconstructive power of social norms: reprise. Perspect. Psychol. Sci. 13, 249–254 (2018).

    PubMed  Google Scholar 

  47. Asch, S. E. Studies in the principles of judgments and attitudes: II. Determination of judgments by group and by ego-standards. J. Soc. Psychol. 12, 433–465 (1940).

    Google Scholar 

  48. Hallsworth, M. et al. Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet 387, 1743–1752 (2016).

    PubMed  PubMed Central  Google Scholar 

  49. Asch, D. A. & Rosin, R. Engineering social incentives for health. N. Engl. J. Med. 375, 2511–2513 (2016).

    PubMed  Google Scholar 

  50. Meeker, D. et al. Effect of behavioral interventions on inappropriate antibiotic prescribing among primary care practices: a randomized clinical trial. JAMA 315, 562–570 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Hershey J. A., D. A., Thumasathit, T., Meszaros, J. & Waters, V. V. The roles of altruism, free riding, and bandwagoning in vaccination decisions. Org. Behav. Hum. Decis. Process. 59, 177–187 (1994).

    Google Scholar 

  52. Michael, S. S., Babu, K. M., Androski, C. Jr. & Reznek, M. A. Effect of a data-driven intervention on opioid prescribing intensity among emergency department providers: a randomized controlled trial. Acad. Emerg. Med. 25, 482–493 (2018).

    PubMed  Google Scholar 

  53. Vlaev, I., King, D., Dolan, P. & Darzi, A. Theory and practice of ‘nudging’: changing health behaviors. Public Admin. Rev. 76, 550–561 (2016).

    Google Scholar 

  54. Dolan, P. et al. Influencing behaviour: the MINDSPACE way. J. Econ. Psychol. 33, 264–277 (2012).

    Google Scholar 

  55. Dolan, P., Hallsworth, M., Halpern, D., King D. & Vlaev, I. MINDSPACE: influencing behaviour through public policy. https://www.instituteforgovernment.org.uk/sites/default/files/publications/MINDSPACE.pdf (2010).

  56. Rausch Osthoff, A. K. et al. 2018 EULAR recommendations for physical activity in people with inflammatory arthritis and osteoarthritis. Ann. Rheum. Dis. 77, 1251–1260 (2018).

    PubMed  Google Scholar 

  57. Veldhuijzen van Zanten, J. J. et al. Perceived barriers, facilitators and benefits for regular physical activity and exercise in patients with rheumatoid arthritis: a review of the literature. Sports Med. 45, 1401–1412 (2015).

    PubMed  PubMed Central  Google Scholar 

  58. Case, M. A., Burwick, H. A., Volpp, K. G. & Patel, M. S. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA 313, 625–626 (2015).

    CAS  PubMed  Google Scholar 

  59. Patel, M. S., Asch, D. A. & Volpp, K. G. Wearable devices as facilitators, not drivers, of health behavior change. JAMA 313, 459–460 (2015).

    CAS  PubMed  Google Scholar 

  60. Kurtzman, G. W. et al. Social incentives and gamification to promote weight loss: the LOSE IT randomized, controlled trial. J. Gen. Intern. Med. 33, 1669–1675 (2018).

    PubMed  PubMed Central  Google Scholar 

  61. Patel, M. S. et al. Effect of a game-based intervention designed to enhance social incentives to increase physical activity among families: the BE FIT randomized clinical trial. JAMA Intern. Med. 177, 1586–1593 (2017).

    PubMed  PubMed Central  Google Scholar 

  62. Cotton, V. & Patel, M. S. Gamification use and design in popular health and fitness mobile applications. Am. J. Health Promot. 33, 448–451 (2019).

    PubMed  Google Scholar 

  63. Dures, E. & Hewlett, S. Cognitive-behavioural approaches to self-management in rheumatic disease. Nat. Rev. Rheumatol. 8, 553–559 (2012).

    PubMed  Google Scholar 

  64. Winter, S. J., Sheats, J. L. & King, A. C. The use of behavior change techniques and theory in technologies for cardiovascular disease prevention and treatment in adults: a comprehensive review. Prog. Cardiovasc. Dis. 58, 605–612 (2016).

    PubMed  PubMed Central  Google Scholar 

  65. Kwasnicka, D., Dombrowski, S. U., White, M. & Sniehotta, F. Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories. Health Psychol. Rev. 10, 277–296 (2016).

    PubMed  PubMed Central  Google Scholar 

  66. Gneezy U. & Rustichini, A. A fine is a price. J. Legal Stud. 29, 1–17 (2000).

    Google Scholar 

  67. Kangovi, S. & Asch, D. A. Behavioral phenotyping in health promotion: embracing or avoiding failure. JAMA 319, 2075–2076 (2018).

    PubMed  PubMed Central  Google Scholar 

  68. Calixto, O. J. & Anaya, J. M. Socioeconomic status. The relationship with health and autoimmune diseases. Autoimmun. Rev. 13, 641–654 (2014).

    PubMed  Google Scholar 

  69. McCollum, L. & Pincus, T. A biopsychosocial model to complement a biomedical model: patient questionnaire data and socioeconomic status usually are more significant than laboratory tests and imaging studies in prognosis of rheumatoid arthritis. Rheum. Dis. Clin. North. Am. 35, 699–712 (2009).

    PubMed  Google Scholar 

  70. Selten, E. M. H. et al. Barriers impeding the use of non-pharmacological, non-surgical care in hip and knee osteoarthritis: the views of general practitioners, physical therapists, and medical specialists. J. Clin. Rheumatol. Pract. Rep. Rheum. Musculoskelet. Dis. 23, 405–410 (2017).

    Google Scholar 

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The authors contributed equally to all aspects of the article.

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Correspondence to Alexis Ogdie.

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A.O. has served as a consultant for Abbvie, Amgen, BMS, Celgene, Corrona, Lilly, Novartis, Pfizer and Takeda and has received grant funding to the University of Pennsylvania from Novartis and Pfizer and grant funding to the National Databank for Rheumatic Diseases from Amgen. D.A.A. is a partner and part owner of VAL Health, a behavioural economics consulting firm.

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Nature Reviews Rheumatology thanks C. Bode, I. Vlaev, E. Losina, R. Chang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Ogdie, A., Asch, D.A. Changing health behaviours in rheumatology: an introduction to behavioural economics. Nat Rev Rheumatol 16, 53–60 (2020). https://doi.org/10.1038/s41584-019-0336-1

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