IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v27y2007i5p672-680.html
   My bibliography  Save this article

Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale

Author

Listed:
  • Angela Fagerlin

    (VA Health Services Research & Development Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan, Division of General Internal Medicine, University of Michigan, Ann Arbor, Michigan, fagerlin@med.umich.edu)

  • Brian J. Zikmund-Fisher

    (VA Health Services Research & Development Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan, Division of General Internal Medicine, University of Michigan, Ann Arbor, Michigan)

  • Peter A. Ubel

    (VA Health Services Research & Development Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan, Division of General Internal Medicine, University of Michigan, Ann Arbor, Michigan, Department of Psychology, University of Michigan, Ann Arbor, Michigan)

  • Aleksandra Jankovic

    (Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan)

  • Holly A. Derry

    (Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan)

  • Dylan M. Smith

    (VA Health Services Research & Development Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, Center for Behavioral and Decision Sciences in Medicine, Ann Arbor, Michigan, Division of General Internal Medicine, University of Michigan, Ann Arbor, Michigan)

Abstract

Background. Basic numeracy skills are necessary before patients can understand the risks of medical treatments. Previous research has used objective measures, similar to mathematics tests, to evaluate numeracy. Objectives. To design a subjective measure (i.e., self-assessment) of quantitative ability that distinguishes low- and high-numerate individuals yet is less aversive, quicker to administer, and more useable for telephone and Internet surveys than existing numeracy measures. Research Design. Paper-and-pencil questionnaires. Subjects. The general public (N = 703) surveyed at 2 hospitals. Measures. Forty-nine subjective numeracy questions were compared to measures of objective numeracy. Results. An 8-item measure, the Subjective Numeracy Scale (SNS), was developed through several rounds of testing. Four items measure people's beliefs about their skill in performing various mathematical operations, and 4 measure people's preferences regarding the presentation of numerical information. The SNS was significantly correlated with Lipkus and others' objective numeracy scale (correlations: 0.63—0.68) yet was completed in less time (24 s/item v. 31 s/item, P

Suggested Citation

  • Angela Fagerlin & Brian J. Zikmund-Fisher & Peter A. Ubel & Aleksandra Jankovic & Holly A. Derry & Dylan M. Smith, 2007. "Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale," Medical Decision Making, , vol. 27(5), pages 672-680, September.
  • Handle: RePEc:sae:medema:v:27:y:2007:i:5:p:672-680
    DOI: 10.1177/0272989X07304449
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X07304449
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X07304449?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Baker, D.W. & Parker, R.M. & Williams, M.V. & Clark, W.S. & Nurss, J., 1997. "The relationship of patient reading ability to self-reported health and use of health services," American Journal of Public Health, American Public Health Association, vol. 87(6), pages 1027-1030.
    2. Brian J. Zikmund-Fisher & Dylan M. Smith & Peter A. Ubel & Angela Fagerlin, 2007. "Validation of the Subjective Numeracy Scale: Effects of Low Numeracy on Comprehension of Risk Communications and Utility Elicitations," Medical Decision Making, , vol. 27(5), pages 663-671, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karen M. Davison & Vidhi Thakkar & Shen (Lamson) Lin & Lorna Stabler & Maura MacPhee & Simon Carroll & Benjamin Collins & Zachary Rezler & Jake Colautti & Chaoqun (Cherry) Xu & Esme Fuller-Thomson & B, 2021. "Interventions to Support Mental Health among Those with Health Conditions That Present Risk for Severe Infection from Coronavirus Disease 2019 (COVID-19): A Scoping Review of English and Chinese-Langu," IJERPH, MDPI, vol. 18(14), pages 1-22, July.
    2. Yaniv Hanoch & Talya Miron-Shatz & Mary Himmelstein, 2010. "Genetic testing and risk interpretation: How do women understand lifetime risk results?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(2), pages 116-123, April.
    3. Lee, Hee Yun & Zhou, Anne Q. & Lee, Richard M. & Dillon, Amy L., 2020. "Parents’ functional health literacy is associated with children’s health outcomes: Implications for health practice, policy, and research," Children and Youth Services Review, Elsevier, vol. 110(C).
    4. Teresa Bago d'Uva & Esen Erdogan Ciftci & Owen O'Donnell & Eddy van Doorslaer, 2015. "Who can predict their Own Demise? Accuracy of Longevity Expectations by Education and Cognition," Tinbergen Institute Discussion Papers 15-052/V, Tinbergen Institute.
    5. Garcia-Retamero, Rocio & Hoffrage, Ulrich, 2013. "Visual representation of statistical information improves diagnostic inferences in doctors and their patients," Social Science & Medicine, Elsevier, vol. 83(C), pages 27-33.
    6. Brian J. Zikmund-Fisher & Angela Fagerlin & Peter A. Ubel, 2010. "A Demonstration of ‘‘Less Can Be More’’ in Risk Graphics," Medical Decision Making, , vol. 30(6), pages 661-671, November.
    7. Yaniv Hanoch & Jonathan Rolison & Alexandra M. Freund, 2019. "Reaping the Benefits and Avoiding the Risks: Unrealistic Optimism in the Health Domain," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 792-804, April.
    8. Swait, J. & de Bekker-Grob, E.W., 2022. "A discrete choice model implementing gist-based categorization of alternatives, with applications to patient preferences for cancer screening and treatment," Journal of Health Economics, Elsevier, vol. 85(C).
    9. Hannah A D Keage & Tobias Loetscher, 2018. "Estimating everyday risk: Subjective judgments are related to objective risk, mapping of numerical magnitudes and previous experience," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
    10. Robert M. Hamm & David E. Bard & Elaine Hsieh & Howard F. Stein, 2007. "Contingent or Universal Approaches to Patient Deficiencies in Health Numeracy," Medical Decision Making, , vol. 27(5), pages 635-637, September.
    11. Nicolas Eber & Patrick Roger & Tristan Roger, 2024. "Finance and intelligence: An overview of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 503-554, April.
    12. repec:cup:judgdm:v:14:y:2019:i:4:p:412-422 is not listed on IDEAS
    13. Tianfeng He & Lefan Liu & Jing Huang & Guoxing Li & Xinbiao Guo, 2021. "The Community Health Supporting Environments and Residents’ Health and Well-Being: The Role of Health Literacy," IJERPH, MDPI, vol. 18(15), pages 1-22, July.
    14. Dolores J. Severtson & James E. Burt, 2012. "The Influence of Mapped Hazards on Risk Beliefs: A Proximity‐Based Modeling Approach," Risk Analysis, John Wiley & Sons, vol. 32(2), pages 259-280, February.
    15. Jakub Traczyk & Agata Sobkow & Kamil Fulawka & Jakub Kus & Dafina Petrova & Rocio Garcia-Retamero, 2018. "Numerate decision makers don't use more effortful strategies unless it pays: A process tracing investigation of skilled and adaptive strategy selection in risky decision making," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(4), pages 372-381, July.
    16. Yoshihiko Kadoya & Naheed Rabbani & Mostafa Saidur Rahim Khan, 2022. "Insurance literacy among older people in Japan: The role of socio‐economic status," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 788-805, June.
    17. Barbara K Kondilis & Ismene J Kiriaze & Anastasia P Athanasoulia & Matthew E Falagas, 2008. "Mapping Health Literacy Research in the European Union: A Bibliometric Analysis," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-6, June.
    18. Dong, Gang Nathan, 2016. "Social capital as correlate, antecedent, and consequence of health service demand in China," China Economic Review, Elsevier, vol. 37(C), pages 85-96.
    19. Guglielmo Bonaccorsi & Anna Romiti & Francesca Ierardi & Maddalena Innocenti & Marco Del Riccio & Silvia Frandi & Letizia Bachini & Patrizio Zanobini & Fabrizio Gemmi & Chiara Lorini, 2020. "Health-Literate Healthcare Organizations and Quality of Care in Hospitals: A Cross-Sectional Study Conducted in Tuscany," IJERPH, MDPI, vol. 17(7), pages 1-16, April.
    20. Alves, Luiz G.A. & Andrade, José S. & Hanley, Quentin S. & Ribeiro, Haroldo V., 2019. "The hidden traits of endemic illiteracy in cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 566-574.
    21. Moon, Graham & Aitken, Grant & Roderick, Paul & Fraser, Simon & Rowlands, Gill, 2015. "Towards an understanding of the relationship of functional literacy and numeracy to geographical health inequalities," Social Science & Medicine, Elsevier, vol. 143(C), pages 185-193.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:27:y:2007:i:5:p:672-680. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.