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Perception of Quantitative Information for Treatment Decisions

Author

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  • Deb Feldman-Stewart
  • Nancy Kocovski
  • Beth A. McConnell
  • Michael D. Brundage
  • William J. Mackillop

Abstract

The study was designed to determine which formats for displaying quantities, such as probabilities of treatment risks and benefits, are perceived most accurately and easily by patients. Accuracy and speed of processing were compared for six different presentation formats: pie charts, vertical bars, horizontal bars, numbers, systematic ovals, and random ovals. Quantities were used in two tasks: a choice task that required larger/smaller judgments and an estimate task that required more precise evaluation. The impacts of blue-yellow color and of a treatment-decision context on performance in the two tasks were also investigated. The study included four experiments. Taken together the results suggest that the formats best for making a choice differ from those best for estimating the size of an amount. For making a choice, vertical bars, horizontal bars, numbers, and systematic ovals were equally well perceived; pie charts and random ovals caused slower and less accurate performances. For estimating, numbers led to the most accurate estimates, followed by systematic ovals. The other four formats led to the least accurate estimates. Color and context did not alter which formats were best. Key words: decision making; quantitative information presentation; questionnaire format. (Med Decis Making 2000;20:228-238)

Suggested Citation

  • Deb Feldman-Stewart & Nancy Kocovski & Beth A. McConnell & Michael D. Brundage & William J. Mackillop, 2000. "Perception of Quantitative Information for Treatment Decisions," Medical Decision Making, , vol. 20(2), pages 228-238, April.
    • Handle: RePEc:sae:medema:v:20:y:2000:i:2:p:228-238
    DOI: 10.1177/0272989X0002000208
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    References listed on IDEAS

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    1. Sirkka L. Jarvenpaa, 1989. "The Effect of Task Demands and Graphical Format on Information Processing Strategies," Management Science, INFORMS, vol. 35(3), pages 285-303, March.
    2. Henry C. Lucas, Jr. & Norman R. Nielsen, 1980. "The Impact of the Mode of Information Presentation on Learning and Performance," Management Science, INFORMS, vol. 26(10), pages 982-993, October.
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    1. Chris M. R. Smerecnik & Ilse Mesters & Loes T. E. Kessels & Robert A. C. Ruiter & Nanne K. De Vries & Hein De Vries, 2010. "Understanding the Positive Effects of Graphical Risk Information on Comprehension: Measuring Attention Directed to Written, Tabular, and Graphical Risk Information," Risk Analysis, John Wiley & Sons, vol. 30(9), pages 1387-1398, September.
    2. Sophie Guy & Yoshihisa Kashima & Iain Walker & Saffron O’Neill, 2013. "Comparing the atmosphere to a bathtub: effectiveness of analogy for reasoning about accumulation," Climatic Change, Springer, vol. 121(4), pages 579-594, December.
    3. Isaac M. Lipkus, 2007. "Numeric, Verbal, and Visual Formats of Conveying Health Risks: Suggested Best Practices and Future Recommendations," Medical Decision Making, , vol. 27(5), pages 696-713, September.
    4. Casey Canfield & Wändi Bruine de Bruin & Gabrielle Wong-Parodi, 2017. "Perceptions of electricity-use communications: effects of information, format, and individual differences," Journal of Risk Research, Taylor & Francis Journals, vol. 20(9), pages 1132-1153, September.
    5. Kevin E. Tiede & Wolfgang Gaissmaier, 2023. "How Do People Process Different Representations of Statistical Information? Insights into Cognitive Effort, Representational Inconsistencies, and Individual Differences," Medical Decision Making, , vol. 43(7-8), pages 803-820, October.
    6. Marie-Anne Durand & Renata W Yen & James O’Malley & Glyn Elwyn & Julien Mancini, 2020. "Graph literacy matters: Examining the association between graph literacy, health literacy, and numeracy in a Medicaid eligible population," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    7. Garcia-Retamero, Rocio & Galesic, Mirta, 2010. "Who proficts from visual aids: Overcoming challenges in people's understanding of risks," Social Science & Medicine, Elsevier, vol. 70(7), pages 1019-1025, April.
    8. repec:cup:judgdm:v:6:y:2011:i:3:p:263-274 is not listed on IDEAS
    9. Rebecca Hess & Vivianne H. M. Visschers & Michael Siegrist, 2011. "Risk communication with pictographs: The role of numeracy and graph processing," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(3), pages 263-274, April.
    10. Lyndal J. Trevena & Carissa Bonner & Yasmina Okan & Ellen Peters & Wolfgang Gaissmaier & Paul K. J. Han & Elissa Ozanne & Danielle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts," Medical Decision Making, , vol. 41(7), pages 834-847, October.
    11. Schonlau Matthias & Peters Ellen, 2012. "Comprehension of Graphs and Tables Depend on the Task: Empirical Evidence from Two Web-Based Studies," Statistics, Politics and Policy, De Gruyter, vol. 3(2), pages 1-35, August.
    12. Rebecca Hess & Vivianne H.M. Visschers & Michael Siegrist & Carmen Keller, 2011. "How do people perceive graphical risk communication? The role of subjective numeracy," Journal of Risk Research, Taylor & Francis Journals, vol. 14(1), pages 47-61, January.
    13. Steven Glazerman & Ira Nichols-Barrer & Jon Valant & Jesse Chandler & Alyson Burnett, "undated". "Nudging Parents to Choose Better Schools: The Importance of School Choice Architecture," Mathematica Policy Research Reports dd5063086be143fb75deb193b, Mathematica Policy Research.
    14. Kirsten J. McCaffery & Sian K. Smith & Michael Wolf, 2010. "The Challenge of Shared Decision Making Among Patients With Lower Literacy: A Framework for Research and Development," Medical Decision Making, , vol. 30(1), pages 35-44, January.
    15. Oliver, Adam, 2003. "A quantitative and qualitative test of the Allais paradox using health outcomes," Journal of Economic Psychology, Elsevier, vol. 24(1), pages 35-48, February.

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