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Predicting (un)healthy behavior: A comparison of risk-taking propensity measures

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  • Helena Szrek
  • Li-Wei Chao
  • Shandir Ramlagan
  • Karl Peltzer

Abstract

We compare four different risk-taking propensity measures on their ability to describe and to predict actual risky behavior in the domain of health. The risk-taking propensity measures we compare are: (1) a general measure of risk-taking propensity derived from a one-item survey question (Dohmen et al., 2011), (2) a risk aversion index calculated from a set of incentivized monetary gambles (Holt & Laury, 2002), (3) a measure of risk taking derived from an incentive compatible behavioral task---the Balloon Analog Risk Task (Lejuez et al., 2002), and (4) a composite score of risk-taking likelihood in the health domain from the Domain-Specific Risk Taking (DOSPERT) scale (Weber et al., 2002). Study participants are 351 clients of health centers around Witbank, South Africa. Our findings suggest that the one-item general measure is the best predictor of risky health behavior in our population, predicting two out of four behaviors at the 5% level and the remaining two behaviors at the 10% level. The DOSPERT score in the health domain performs well, predicting one out of four behaviors at the 1% significance level and two out of four behaviors at the 10% level, but only if the DOSPERT instrument contains a hypothetical risk-taking item that is similar to the actual risky behavior being predicted. Incentivized monetary gambles and the behavioral task were unrelated to actual health behaviors; they were unable to predict any of the risky health behaviors at the 10% level. We provide evidence that this is not because the participants had trouble understanding the monetary trade-off questions or performed poorly in the behavioral task. We conclude by urging researchers to further test the usefulness of the one-item general measure, both in explaining health related risk-taking behavior and in other contexts.

Suggested Citation

  • Helena Szrek & Li-Wei Chao & Shandir Ramlagan & Karl Peltzer, 2012. "Predicting (un)healthy behavior: A comparison of risk-taking propensity measures," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(6), pages 716-727, November.
  • Handle: RePEc:jdm:journl:v:7:y:2012:i:6:p:716-727
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    References listed on IDEAS

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    1. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
    2. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    3. Anderson, Lisa R. & Mellor, Jennifer M., 2008. "Predicting health behaviors with an experimental measure of risk preference," Journal of Health Economics, Elsevier, vol. 27(5), pages 1260-1274, September.
    4. Charness, Gary & Viceisza, Angelino, 2011. "Comprehension and risk elicitation in the field: Evidence from rural Senegal," IFPRI discussion papers 1135, International Food Policy Research Institute (IFPRI).
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    Citations

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    Cited by:

    1. Antonio Filippin & Paolo Crosetto, 2016. "A Reconsideration of Gender Differences in Risk Attitudes," Management Science, INFORMS, vol. 62(11), pages 3138-3160, November.
    2. repec:eee:socmed:v:185:y:2017:i:c:p:147-157 is not listed on IDEAS
    3. Liora Zimerman & Shaul Shalvi & Yoella Bereby-Meyer, 2014. "Self-reported ethical risk taking tendencies predict actual dishonesty," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(1), pages 58-64, January.
    4. Bateman, Hazel & Dobrescu, Loretti I. & Newell, Ben R. & Ortmann, Andreas & Thorp, Susan, 2016. "As easy as pie: How retirement savers use prescribed investment disclosures," Journal of Economic Behavior & Organization, Elsevier, vol. 121(C), pages 60-76.
    5. Matteo M. Galizzi, 2014. "What Is Really Behavioral in Behavioral Health Policy? And Does It Work?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(1), pages 25-60.
    6. Petrolia, Daniel R., 2016. "Risk preferences, risk perceptions, and risky food," Food Policy, Elsevier, vol. 64(C), pages 37-48.
    7. Drichoutis, Andreas C. & Vassilopoulos, Achilleas, 2016. "Intertemporal stability of survey-based measures of risk and time preferences over a three-year course," MPRA Paper 73548, University Library of Munich, Germany.
    8. Miraldo, M & Galizzi, M & Stavropoulou, C, 2013. "In sickness but not in wealth: Field evidence on patients’ risk preferences in the financial and health domain," Working Papers 31053, Imperial College, London, Imperial College Business School.
    9. Vasilios Kosteas, 2015. "Physical activity and time preference," International Journal of Health Economics and Management, Springer, vol. 15(4), pages 361-386, December.
    10. repec:imp:wpaper:12579 is not listed on IDEAS
    11. Galizzi, Matteo M. & Machado, Sara R. & Miniaci, Raffaele, 2016. "Temporal stability, cross-validity, and external validity of risk preferences measures: experimental evidence from a UK representative sample," LSE Research Online Documents on Economics 67554, London School of Economics and Political Science, LSE Library.
    12. Galizzi, Matteo M. & Miraldo, Marisa & Stavropoulou, Charitini & van der Pol, Marjon, 2016. "Doctor–patient differences in risk and time preferences: A field experiment," Journal of Health Economics, Elsevier, vol. 50(C), pages 171-182.

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