Patient Preference and Adherence (May 2015)

Behavioral economics survey of patients with type 1 and type 2 diabetes

  • Emoto N,
  • Okajima F,
  • Sugihara H,
  • Goto R

Journal volume & issue
Vol. 2015, no. default
pp. 649 – 658

Abstract

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Naoya Emoto,1 Fumitaka Okajima,1 Hitoshi Sugihara,2 Rei Goto3,4 1Division of Endocrinology, Department of Medicine, Nippon Medical School Chiba Hokusoh Hospital, Chiba, 2Department of Endocrinology, Diabetes and Metabolism, Graduate School of Medicine, Nippon Medical School, Tokyo, 3Hakubi Center of Advanced Research, Kyoto University, Kyoto, 4Graduate School of Economics, Kyoto University, Kyoto, Japan Background: Adherence to treatment and the metabolic control of diabetes are challenging in many patients with diabetes. The theory of neuroeconomics can provide important clues for understanding unreasonable human behavior concerning decisions between outcomes occurring at different time points.  Objective: We investigated patients with type 1 and type 2 diabetes to determine whether patients who are at a risk of developing complications are less risk averse. We also examined whether patients with type 1 and type 2 diabetes have different behavioral traits in decision making under risk.  Methods: We conducted a behavioral economics survey of 219 outpatients, 66 with type 1 diabetes and 153 with type 2 diabetes. All patients had been referred by general practitioners or other departments in the hospital. At the time of the survey, levels of hemoglobin A1c were not significantly different between patients with type 1 and type 2 diabetes.  Results: Patients with type 2 diabetes showed a lower response rate to the survey compared with patients with type 1 diabetes (71.9% vs 87.9%, P<0.01). Logistic regression analysis indicated that diabetic retinopathy was negatively associated with risk averse in pricing of hypothetical lotteries, myopic time preference, willingness to pay for preventive medicine, and levels of satisfaction with life. Diabetic nephropathy was also negatively associated with risk averse in pricing of hypothetical lotteries. Detailed analysis revealed that a lower proportion of patients with type 2 diabetes (22.7%) were categorized as risk averse compared with patients with type 1 diabetes (43.1%, P<0.05) in hypothetical lottery risk estimation.  Conclusion: This is the first report that investigated patients with diabetes in a clinical setting using a method based on behavioral economics. The results suggest that the attitude of patients toward risk plays an important role in the progress of the complications of diabetes. Different educational and psychological approaches may be necessary to assess patients with diabetes based on whether they have traits such as risk seeking or risk averse. Keywords: neuroeconomics, hypothetical lottery, risk averse