IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v32y2012i6p851-865.html
   My bibliography  Save this article

The Numeracy Understanding in Medicine Instrument

Author

Listed:
  • Marilyn M. Schapira
  • Cindy M. Walker
  • Kevin J. Cappaert
  • Pamela S. Ganschow
  • Kathlyn E. Fletcher
  • Emily L. McGinley
  • Sam Del Pozo
  • Carrie Schauer
  • Sergey Tarima
  • Elizabeth A. Jacobs

Abstract

Background : Health numeracy can be defined as the ability to understand and apply information conveyed with numbers, tables and graphs, probabilities, and statistics to effectively communicate with health care providers, take care of one’s health, and participate in medical decisions. Objective : To develop the Numeracy Understanding in Medicine Instrument (NUMi) using item response theory scaling methods. Design : A 20-item test was formed drawing from an item bank of numeracy questions. Items were calibrated using responses from 1000 participants and a 2-parameter item response theory model. Construct validity was assessed by comparing scores on the NUMi to established measures of print and numeric health literacy, mathematic achievement, and cognitive aptitude. Participants: Community and clinical populations in the Milwaukee and Chicago metropolitan areas. Results : Twenty-nine percent of the 1000 respondents were Hispanic, 24% were non-Hispanic white, and 42% were non-Hispanic black. Forty-one percent had no more than a high school education. The mean score on the NUMi was 13.2 ( s = 4.6) with a Cronbach α of 0.86. Difficulty and discrimination item response theory parameters of the 20 items ranged from −1.70 to 1.45 and 0.39 to 1.98, respectively. Performance on the NUMi was strongly correlated with the Wide Range Achievement Test–Arithmetic (0.73, P

Suggested Citation

  • Marilyn M. Schapira & Cindy M. Walker & Kevin J. Cappaert & Pamela S. Ganschow & Kathlyn E. Fletcher & Emily L. McGinley & Sam Del Pozo & Carrie Schauer & Sergey Tarima & Elizabeth A. Jacobs, 2012. "The Numeracy Understanding in Medicine Instrument," Medical Decision Making, , vol. 32(6), pages 851-865, November.
    • Handle: RePEc:sae:medema:v:32:y:2012:i:6:p:851-865
    DOI: 10.1177/0272989X12447239
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X12447239
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X12447239?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. Robin Shealy & William Stout, 1993. "A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF," Psychometrika, Springer;The Psychometric Society, vol. 58(2), pages 159-194, June.
    2. repec:cup:judgdm:v:7:y:2012:i:1:p:25-47 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. S. Gatobu & J. F. Arocha & L. Hoffman-Goetz, 2014. "Numeracy and Health Numeracy Among Chinese and Kenyan Immigrants to Canada," SAGE Open, , vol. 4(1), pages 21582440145, February.
    2. Hsiang-Wen Lin & Elizabeth H. Chang & Yu Ko & Chun-Yu Wang & Yu-Shan Wang & Okti Ratna Mafruhah & Shang-Hua Wu & Yu-Chieh Chen & Yen-Ming Huang, 2020. "Conceptualization, Development and Psychometric Evaluations of a New Medication-Related Health Literacy Instrument: The Chinese Medication Literacy Measurement," IJERPH, MDPI, vol. 17(19), pages 1-17, September.
    3. repec:cup:judgdm:v:9:y:2014:i:1:p:15-34 is not listed on IDEAS
    4. Saima Ghazal & Edward T. Cokely & Rocio Garcia-Retamero, 2014. "Predicting biases in very highly educated samples: Numeracy and metacognition," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(1), pages 15-34, January.

    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. Youmi Suk & Kyung T. Han, 2024. "A Psychometric Framework for Evaluating Fairness in Algorithmic Decision Making: Differential Algorithmic Functioning," Journal of Educational and Behavioral Statistics, , vol. 49(2), pages 151-172, April.
    2. Minjeong Jeon & Frank Rijmen & Sophia Rabe-Hesketh, 2013. "Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model," Journal of Educational and Behavioral Statistics, , vol. 38(1), pages 32-60, February.
    3. Omar Paccagnella, 2011. "Anchoring vignettes with sample selection due to non‐response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 665-687, July.
    4. Maria Bolsinova & Jesper Tijmstra & Leslie Rutkowski & David Rutkowski, 2024. "Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features," Journal of Educational and Behavioral Statistics, , vol. 49(2), pages 207-240, April.
    5. Ke-Hai Yuan & Hongyun Liu & Yuting Han, 2021. "Differential Item Functioning Analysis Without A Priori Information on Anchor Items: QQ Plots and Graphical Test," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 345-377, June.
    6. Denis Federiakin, 2020. "Investigating The Cross-National Comparability Of Testing Using Response Times," HSE Working papers WP BRP 57/EDU/2020, National Research University Higher School of Economics.
    7. David Magis & Francis Tuerlinckx & Paul De Boeck, 2015. "Detection of Differential Item Functioning Using the Lasso Approach," Journal of Educational and Behavioral Statistics, , vol. 40(2), pages 111-135, April.
    8. Chen, Yunxiao & Li, Chengcheng & Ouyang, Jing & Xu, Gongjun, 2023. "DIF statistical inference without knowing anchoring items," LSE Research Online Documents on Economics 119923, London School of Economics and Political Science, LSE Library.
    9. Roger Millsap, 2007. "Invariance in Measurement and Prediction Revisited," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 461-473, December.
    10. Herbert Hojtink & Ivo Molenaar, 1997. "A multidimensional item response model: Constrained latent class analysis using the gibbs sampler and posterior predictive checks," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 171-189, June.
    11. Wallin, Gabriel & Chen, Yunxiao & Moustaki, Irini, 2024. "DIF analysis with unknown groups and anchor items," LSE Research Online Documents on Economics 121991, London School of Economics and Political Science, LSE Library.
    12. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.

    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:32:y:2012:i:6:p:851-865. 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.