Valence Matters in Judgments of Stock Accumulation in Blood Glucose Control and Other Global Problems

  • Cleotilde Gonzalez (Author)
    Carnegie Mellon University, United States
    Department of Social and Decision Sciences
  • Maria-Isabel Sanchez-Segura (Author)
    Universidad Carlos III de Madrid, Spain
  • German-Lenin Dugarte-Peña (Author)
    Universidad Carlos III de Madrid, Spain
  • Fuensanta Medina-Dominguez (Author)
    Universidad Carlos III de Madrid, Spain

Identifiers (Article)

Abstract

Stock-flow failure is a reasoning error in dynamic systems that has great societal relevance: people misjudge a level of accumulation (i.e., stock) considering the information on flows that increase (i.e., inflow) or decrease (i.e., outflow) over time. Many interventions, including the use of analogies and graphical manipulations, to counteract this failure and help people integrate the flow information have been tested with little or no success. We suggest that this error relates to the valence of a problem: the framing of the inflow or outflow direction as “good” or “bad” is associated with the direction of its accumulation over time. To explore the effects of valence on accumulation judgments, we employ a scenario of a common health problem: blood glucose control through sugar consumption and insulin flows. We also investigate improvements of performance in a second scenario that result after viewing a video of a dynamic system demonstrating the effects of the correct accumulation trend. We discuss the implications of our findings for the blood glucose example and other global problems.

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References

Abdel-Hamid, T., Ankel, F., Battle-Fisher, M., Gibson, B., Gonzalez-Parra, G., Jalali, M., . . . Murphy, P. (2014). Public and health professionals’ misconceptions about the dynamics of body weight gain/loss. System Dynamics Review, 30(1–2), 58–74. doi:10.1002/sdr.1517

Booth Sweeney, L. & Sterman, J.D. (2000). Bathtub dynamics: initial results of a systems thinking in-ventory. System Dynamics Review, 16, 249–286. doi:10.1002/sdr.198

Brehmer, B. (1980). In one word: Not from experience. Acta Psychologica, 45(1-3), 223–241. doi:10.1016/0001-6918(80)90034-7

Brunstein, A., Gonzalez, C., & Kanter, S. (2010). Effects of domain experience in the stock–flow failu-re. System Dynamics Review, 26(4), 347–354. doi:10.1002/sdr.448

Cronin, M., Gonzalez, C., & Sterman, J.D. (2009). Why don’t well-educated adults understand accu-mulation? A challenge to researchers, educators and citizens. Organizational Behaviour and Human Decision Processes, 108, 116–130. doi:10.1016/j.obhdp.2008.03.003

Diehl, E., & Sterman, J. D. (1995). Effects of feedback complexity on dynamic decision making. Orga-nizational Behavior and Human Decision Processes, 62(2), 198 –215. doi:10.1006/obhd.1995.1043

Dutt, V., & Gonzalez, C. (2012a). Human control of climate change. Climatic Change, 111(3–4), 497–518. doi:10.1007/s10584-011-0202-x

Dutt, V., & Gonzalez, C. (2012b). Decisions from experience reduces misconceptions about climate change. Journal of Environmental Psychology, 32(1), 19–29. doi:10.1016/j.jenvp.2011.10.003

Dutt, V., & Gonzalez, C. (2013). Enabling eco-friendly choices by relying on the proportional-thinking heuristic. Sustainability, 5(1), 357–371. doi:10.3390/su5010357

Fischer, H., Degen, C., & Funke, J. (2015). Improving stock-flow reasoning with verbal formats. Simu-lation & Gaming, 46(3–4), 1–15. doi:10.1177/1046878114565058

Fischer, H., & Gonzalez, C. (2016). Making sense of dynamic systems: how our understanding of stocks and flows depends on a global perspective. Cognitive Science, 40, 496–512. doi:10.1111/cogs.12239

Frensch, P., & Funke, J. (Eds.). (1995). Complex problem solving: The European perspective. Hillsda-le, NJ: Lawrence Erlbaum Associates. Retrieved from http://works.bepress.com/joachim_funke/13/

Gonzalez, C., & Dutt, V. (2007). Learning to control a dynamic task: A system dynamics cognitive model of the slope effect. In Proceedings of the ICCM Eighth International Conference on Cognitive Modeling, Ann Arbor, MI.

Gonzalez, C., & Wong, H. (2012). Understanding stocks and flows through analogy. System Dynamics Review, 28(1), 3–27. doi:10.1002/sdr.470

Moxnes, E., &Saysel, A.K. (2009). Misperceptions of global climate change: Information policies. Climatic Change, 93(1–2), 15–37. doi:10.1007/s10584-008-9465-2

Newell, BR., Kary, A., Moore, C., & Gonzalez, C. (2016). Managing the budget: Stock-flow reasoning and the CO2 accumulation problem. Topics in Cognitive Science, 8(1), 138–159. doi:10.1111/tops.12176

Sterman, J.D. (2008). Risk communication on climate change: Mental models and mass balance. Sci-ence, 322, 532–533. doi:10.1126/science.1162574

Sterman, J.D., & Booth Sweeney L. (2002). Cloudy skies: Assessing public understanding of global warming. System Dynamics Review, 18(2), 207–240. doi:10.1002/sdr.242

Sterman, J.D, & Booth Sweeney, L. (2007). Understanding public complacency about climate chan-ge: Adults’ mental models of climate change violate conservation of matter. Climatic Change, 80(3–4), 213–238. doi:10.1007/s10584-006-9107-5

Sterman, J.D., Fiddaman, T., Franck, T., Jones, A., McCauley, S., Rice, P., . . . Siegel, L. (2012). Ma-nagement flight simulators to support climate negotiations. Environmental Modeling and Software, 44, 122–135. doi:10.1016/j.envsoft.2012.06.004

Sternberg, R. J. (1995). Expertise in complex problem solving: A comparison of alternative concep-tions. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European perspective (pp. 295–321). Hillsdale, NJ: Lawrence Erlbaum Associates.

Strohhecker, J., Größler, A. (2015). Performance in tangible and in cognitive stock-flow tasks: Closer than expected. Simulation & Gaming, 46(3-4), 230–254. doi:10.1177/1046878115577160

Published
2018-12-26
Language
en
Contributor or sponsoring agency
National Science Foundation
Type, method or approach
Experimental
Keywords
Correlation Heuristic, Stock-Flow Failure, System Behaviour, Valence Effect