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A Fuzzy-Trace Theory of Judgment and Decision-Making in Health Care: Explanation, Prediction, and Application

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Handbook of Health Decision Science

Abstract

We discuss how an evidence-based theory of human behavior and decision-making—Fuzzy-Trace Theory (FTT)—can be used to better understand and improve public health and medicine. We present an overview of the theory, describing its core principles as well as illustrative evidence. Applications are discussed in the areas of risk perception, prevention, detection and diagnosis of disease, and decision-making regarding treatment. We then review findings from interventions designed to improve health judgments and medical decision-making by effectively communicating risks and benefits. The theory provides guidelines for development of such interventions because it predicts reactions to health messages and explains the causal mechanisms of judgment and decision-making. We also present recommendations for future research.

Preparation of this manuscript was supported in part by the National Institutes of Health National Cancer Institute Award Number R21CA149796 and National Institute of Nursing Research R01NR014368-01 to the second author.

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References

  • Adam, M. B., & Reyna, V. F. (2005). Coherence and correspondence criteria for rationality: Experts’ estimation of risks of sexually transmitted infections. Journal of Behavioral Decision Making, 18(3), 169–186. doi:10.1002/bdm.493.

    Article  Google Scholar 

  • American Cancer Society. (2012). Cancer facts & figures 2012. Atlanta: American Cancer Society.

    Google Scholar 

  • Barbey, A. K., & Sloman, S. A. (2007). Base-rate respect: From statistical formats to cognitive structures. Behavioral and Brain Sciences, 30, 287–297.

    Google Scholar 

  • Betsch, C., Brewer, N. T., Brocard, P., Davies, P., Gaissmaier, W., Haase, N., et al. (2012). Opportunities and challenges of web 2.0 for vaccination decisions. Vaccine, 28(30), 3727–3733. doi:10.1016/j.vaccine.2012.02.025

    Google Scholar 

  • Brewer, N. T., Richman, A. R., DeFrank, J. T., Reyna, V. F., & Carey, L. A. (2012). Improving communication of breast cancer recurrence risk. Breast Cancer Research and Treatment, 133, 553–561. doi:10.1007/s10549-011-1791-9.

    Article  PubMed  Google Scholar 

  • Brewer, N. T., Tzeng, J. P., Lillie, S. E., Edwards, A. S., Peppercorn, J. M., & Rimer, B. K. (2009). Health literacy and cancer risk perception: Implications for genomic risk communication. Medical Decision Making, 29, 157–166. doi:10.1177/0272989X08327111.

    Article  PubMed  Google Scholar 

  • Brewer, N. T., Weinstein, N. D., Cuite, C. L., & Herrington, J. (2004). Risk perceptions and their relation to risk behavior. Annals of Behavioral Medicine, 27, 125–130.

    Article  PubMed  Google Scholar 

  • Brust-Renck, P. G., Royer, C. E., & Reyna, V. F. (2013). Communicating numerical risk: Human factors that aid understanding in health care. Reviews of Human Factors and Ergonomics, 8, 235–276. doi:10.1177/1557234X13492980.

    Article  Google Scholar 

  • Cuite, C. L., Weinstein, N. D., Emmons, K., & Colditz, G. (2008). A test of numeric formats for communicating risk probabilities. Medical Decision Making, 28(3), 377–384. doi:10.1177/0272989X08315246.

    Google Scholar 

  • Downs, J. S., Bruin de Bruine, W. D., & Fischhoff, B. (2008). Parents’ vaccination comprehension and decisions. Vaccine, 26, 1595–1607. doi:10.1016/j.vaccine.2008.01.011.

    Article  PubMed  Google Scholar 

  • Eddy, D. M. (1982). Probabilistic reasoning in clinical medicine: Problems and opportunities. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 249–267). Cambridge, UK: Cambridge University.

    Chapter  Google Scholar 

  • Elwyn, G., Frosch, D., & Rollnick, S. (2009). Dual equipoise shared decision making: Definitions for decision and behaviour support interventions. Implementation Science, 4, 75. doi:10.1186/1748-5908-4-75.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fagerlin, A., Pignone, M., Abhyankar, P., Col, N., Feldman-Stewart, D., Gavaruzzi, T., et al. (2013). Clarifying values: An updated review. BMC Medical Informatics and Decision Making, 13(Suppl 2), S8. doi:10.1186/1472-6947-13-S2-S8.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fagerlin, A., Zikmund-Fisher, B. J., & Ubel, P. (2005). How making a risk estimate can change the feel of that risk: Shifting attitudes toward breast cancer risk in a general public survey. Patient Education and Counseling, 57(3), 294–299.

    Article  PubMed  Google Scholar 

  • Fraenkel, L., Matzko, C. K., Webb, D. E., Oppermann, B., Charpentier, P., Peters, E., Reyna, V. F., & Newman, E. D. (2015). Use of decision support for improved knowledge, values clarification, and informed choice in patients with rheumatoid arthritis. Arthritis Care and Research, 67(11), 1496–1502. doi:10.1002/acr.22659.

    Google Scholar 

  • Fraenkel, L., Peters, E., Charpentier, P., Olsen, B., Errante, L., Schoen, R. T., et al. (2012). A decision tool to improve the quality of care in rheumatoid arthritis. Arthritis Care & Research, 64(7), 977–985. doi:10.1002/acr.21657.

    Google Scholar 

  • Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697–720. doi:10.1037/0003-066X.58.9.697.

    Article  PubMed  Google Scholar 

  • Kahneman, D. (2011). Thinking fast and slow. New York: Farrar, Strauss, Giroux.

    Google Scholar 

  • Kühberger, A., & Tanner, C. (2010). Risky choice framing: Task versions and a comparison of prospect theory and fuzzy-trace theory. Journal of Behavioral Decision Making, 23(3), 314–329. doi:10.1002/bdm.656.

    Article  Google Scholar 

  • Lloyd, A., Hayes, P., Bell, P. R. F., & Naylor, A. R. (2001). The role of risk and benefit perception in informed consent for surgery. Medical Decision Making, 21(2), 141–149. doi:10.1177/0272989X0102100207.

    Article  PubMed  Google Scholar 

  • Lloyd, F. J., & Reyna, V. F. (2001). A web exercise in evidence-based medicine using cognitive theory. Journal of General Internal Medicine, 16(2), 94–99. doi:10.1111/j.1525-1497.2001.00214.x.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lloyd, F. J., & Reyna, V. F. (2009). Clinical gist and medical education: Connecting the dots. Journal of the American Medical Association, 302(12), 1332–1333. doi:10.1001/jama.2009.1383.

    Article  PubMed  Google Scholar 

  • Mills, B., Reyna, V. F., & Estrada, S. (2008). Explaining contradictory relations between risk perception and risk taking. Psychological Science, 19, 429–433. doi:10.1111/j.1467-9280.2008.02104.x.

    Article  PubMed  Google Scholar 

  • Peters, E., Slovic, P., Västfjäll, D., & Mertz, C. K. (2008). Intuitive numbers guide decisions. Judgment and Decision Making, 3, 619–635. Retrieved from journal.sjdm.org/8827/jdm8827.html

  • Reyna, V. F. (1991). Class inclusion, the conjunction fallacy, and other cognitive illusions. Developmental Review, 11, 317–336. doi:10.1016/0273-2297(91)90017-I.

    Article  Google Scholar 

  • Reyna, V. F. (2004). How people make decisions that involve risk: A dual process approach. Current Directions in Psychological Science, 13, 60–66. doi:10.1111/j.0963-7214.2004.00275.x.

    Article  Google Scholar 

  • Reyna, V. F. (2008). A theory of medical decision making and health: Fuzzy trace theory. Medical Decision Making, 28(6), 850–865. doi:10.1177/0272989X08327066.

    Article  PubMed  PubMed Central  Google Scholar 

  • Reyna, V. F. (2011). Across the lifespan. In B. Fischhoff, N. T. Brewer, & J. S. Downs (Eds.), Communicating risks and benefits: An evidence-based user’s guide (pp. 111–119). USA: U.S. Department of Health and Human Services, Food and Drug Administration. Retrieved from http://www.fda.gov/ScienceResearch/SpecialTopics/RiskCommunication/default.htm

  • Reyna, V. F. (2012a). A new intuitionism: Meaning, memory, and development in fuzzy-trace theory. Judgment and Decision Making, 7(3), 332–359. Retrieved from journal.sjdm.org/11/111031/jdm111031.html

  • Reyna, V. F. (2012b). Risk perception and communication in vaccination decisions: A fuzzy-trace theory approach. Vaccine, 30(25), 3790–3797. doi:10.1016/j.vaccine.2011.11.070

    Google Scholar 

  • Reyna, V. F. (2013). Intuition, reasoning, and development: A fuzzy-trace theory approach. In P. Barrouillet & C. Gauffroy (Eds.), The development of thinking and reasoning (pp. 193–220). Hove, UK: Psychology Press.

    Google Scholar 

  • Reyna, V. F., & Adam, M. B. (2003). Fuzzy-trace theory, risk communication, and product labeling in sexually transmitted diseases. Risk Analysis, 23, 325–342. doi:10.1111/1539-6924.00332.

    Article  PubMed  Google Scholar 

  • Reyna, V. F., Adam, M. B., Poirier, K., LeCroy, C. W., & Brainerd, C. J. (2005). Risky decision-making in childhood and adolescence: A fuzzy-trace theory approach. In J. Jacobs & P. Klaczynski (Eds.), The development of children’s and adolescents’ judgment and decision-making (pp. 77–106). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Reyna, V. F., & Brainerd, C. J. (1994). The origins of probability judgment: A review of data and theories. In G. Wright & P. Ayton (Eds.), Subjective probability (pp. 239–272). New York: Wiley.

    Google Scholar 

  • Reyna, V. F., & Brainerd, C. J. (1995). Fuzzy-trace theory: An interim synthesis. Learning and Individual Differences, 7, 1–75. doi:10.1016/1041-6080(95)90031-4.

    Article  Google Scholar 

  • Reyna, V. F., & Brainerd, C. J. (2008). Numeracy, ratio bias, and denominator neglect in judgments of risk and probability. Learning and Individual Differences, 18(1), 89–107. doi:10.1016/j.lindif.2007.03.011.

    Article  Google Scholar 

  • Reyna, V. F., & Brainerd, C. J. (2011). Dual processes in decision making and developmental neuroscience: A fuzzy-trace model. Developmental Review, 31, 180–206. doi:10.1016/j.dr.2011.07.004.

    PubMed  PubMed Central  Google Scholar 

  • Reyna, V. F., Chapman, S., Dougherty, M., & Confrey, J. (2012). The adolescent brain: Learning, reasoning, and decision making. Washington, DC: American Psychological Association.

    Book  Google Scholar 

  • Reyna, V. F., Chick, C. F., Corbin, J. C., & Hsia, A. N. (2014). Developmental reversals in risky decision-making: Intelligence agents show larger decision biases than college students. Psychological Science, 25(1), 76–84. doi:10.1177/0956797613497022.

    Article  PubMed  Google Scholar 

  • Reyna, V. F., Estrada, S. M., DeMarinis, J. A., Myers, R. M., Stanisz, J. M., & Mills, B. A. (2011). Neurobiological and memory models of risky decision making in adolescents versus young adults. Journal of Experimental Psychology. Learning, Memory, and Cognition, 37(5), 1125–1142. doi:10.1037/a0023943.

    Article  PubMed  Google Scholar 

  • Reyna, V. F., & Farley, F. (2006). Risk and rationality in adolescent decision-making: Implications for theory, practice, and public policy. Psychological Science in the Public Interest, 7(1), 1–44. doi:10.111/j.1529-1006.2006.00026.x.

    PubMed  Google Scholar 

  • Reyna, V. F., & Hamilton, A. J. (2001). The importance of memory in informed consent for surgical risk. Medical Decision Making, 21, 152–155. doi:10.1177/0272989X0102100209.

    Article  PubMed  Google Scholar 

  • Reyna, V. F., & Lloyd, F. J. (1997). Theories of false memory in children and adults. Learning and Individual Differences, 9(2), 95–123. doi:10.1016/S1041-6080(97)90002-9.

    Article  Google Scholar 

  • Reyna, V. F., & Lloyd, F. J. (2006). Physician decision making and cardiac risk: Effects of knowledge, risk perception, risk tolerance, and fuzzy processing. Journal of Experimental Psychology, 12(3), 179–195. doi:10.1037/1076-898X.12.3.179.

    PubMed  Google Scholar 

  • Reyna, V. F., Lloyd, F. J., & Brainerd, C. J. (2003). Memory, development, and rationality: An integrative theory of judgment and decision-making. Emerging Perspectives on Judgment and Decision research (pp. 201–245). New York: Cambridge University Press.

    Google Scholar 

  • Reyna, V. F., Lloyd, F., & Whalen, P. (2001). Genetic testing and medical decision making. Archives of Internal Medicine, 161(20), 2406–2408. doi:10.1001/archinte.161.20.2406.

    Article  PubMed  Google Scholar 

  • Reyna, V. F., & Mills, B. A. (2007a). Converging evidence supports fuzzy-trace theory’s nested sets hypothesis (but not the frequency hypothesis). Behavioral and Brain Sciences, 30(3), 278–280. doi:10.1017/S0140525X07001872.

    Article  Google Scholar 

  • Reyna, V. F., & Mills, B. A. (2007b). Interference processes in fuzzy-trace theory: Aging, Alzheimer’s disease, and development. In D. Gorfein & C. MacLeod (Eds.), Inhibition in cognition (pp. 185–210). Washington: APA Press.

    Chapter  Google Scholar 

  • Reyna, V. F., Mills, B. A., & Estrada, S. M. (2008, October). Reducing risk taking in adolescence: Effectiveness of a gist-based curriculum. In Paper presented at the 30th Annual Meeting of the Society of Medical Decision Making, Philadelphia, PA.

    Google Scholar 

  • Reyna, V. F., Weldon, R. B., & McCormick, M. J. (2015). Educating intuition: Reducing risky decisions using fuzzy-trace theory. Current Directions in Psychological Science, 24(4), 392–398. doi: 10.1177/0963721415588081.

    Google Scholar 

  • Rivers, S. E., Reyna, V. F., & Mills, B. (2008). Risk taking under the influence: A fuzzy-trace theory of emotion in adolescence. Developmental Review, 28(1), 107–144. doi: 10.1016/j.dr.2007.11.002.

    Google Scholar 

  • Reyna, V. F., Nelson, W., Han, P., & Dieckmann, N. F. (2009). How numeracy influences risk comprehension and medical decision making. Psychological Bulletin, 135, 943–973. doi:10.1037/a0017327.

    Article  PubMed  PubMed Central  Google Scholar 

  • Shay, C. M., Ning, H., Daniels, S. R., & Lloyd-Jones, D. M. (2011). Prevalence of ideal cardiovascular health in U.S. children and adolescents: Findings from the national health and nutrition examination survey (2003–2008). In Paper presented at the Annual Meeting of the American Heart Association, Orlando, Florida.

    Google Scholar 

  • Stratton, K., Ford, A., Rusch, E., & Clayton, E. W. (2012). Measles, mumps, and rubella vaccine. Report of the committee to review adverse effects of vaccines, Institute of Medicine. In Adverse Effects of Vaccines: Evidence and Causality (pp. 103–237). Washington, DC: National Academy of Sciences.

    Google Scholar 

  • Wolfe, C. R., Fisher, C. R., & Reyna, V. R. (2013). Semantic coherence and inconsistency in estimating conditional probabilities. Journal of Behavioral Decision Making, 26(3), 237–246. doi:10.1002/bdm.1756.

    Article  Google Scholar 

  • Wolfe, C. R., & Reyna, V. F. (2010). Semantic coherence and fallacies in estimating joint probabilities. Journal of Behavioral Decision Making, 23(2), 203–223. doi:10.1002/bdm.650.

    Article  Google Scholar 

  • Wolfe, C. R., Reyna, V. F., Widmer, C. L., Cedillos, E. M., Fisher, C. R., Brust-Renck, P. G., & Weil, A. M. (2015). Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: A fuzzy-trace theory approach. Medical Decision Making, 35(1), 46–59. doi: 10.1177/0272989X14535983.

    Google Scholar 

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Correspondence to Valerie F. Reyna .

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Brust-Renck, P.G., Reyna, V.F., Wilhelms, E.A., Lazar, A.N. (2016). A Fuzzy-Trace Theory of Judgment and Decision-Making in Health Care: Explanation, Prediction, and Application. In: Diefenbach, M., Miller-Halegoua, S., Bowen, D. (eds) Handbook of Health Decision Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-3486-7_6

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