Show simple item record

Taxonomies for synthesizing the evidence on communicating numbers in health: Goals, format, and structure

dc.contributor.authorAncker, Jessica S.
dc.contributor.authorBenda, Natalie C.
dc.contributor.authorSharma, Mohit M.
dc.contributor.authorJohnson, Stephen B.
dc.contributor.authorWeiner, Stephanie
dc.contributor.authorZikmund-Fisher, Brian J.
dc.date.accessioned2023-02-01T18:58:05Z
dc.date.available2024-01-01 13:58:03en
dc.date.available2023-02-01T18:58:05Z
dc.date.issued2022-12
dc.identifier.citationAncker, Jessica S.; Benda, Natalie C.; Sharma, Mohit M.; Johnson, Stephen B.; Weiner, Stephanie; Zikmund-Fisher, Brian J. (2022). "Taxonomies for synthesizing the evidence on communicating numbers in health: Goals, format, and structure." Risk Analysis 42(12): 2656-2670.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/175761
dc.description.abstractMany people, especially those with low numeracy, are known to have difficulty interpreting and applying quantitative information to health decisions. These difficulties have resulted in a rich body of research about better ways to communicate numbers. Synthesizing this body of research into evidence-based guidance, however, is complicated by inconsistencies in research terminology and researcher goals. In this article, we introduce three taxonomies intended to systematize terminology in the literature, derived from an ongoing systematic literature review. The first taxonomy provides a systematic nomenclature for the outcome measures assessed in the studies, including perceptions, decisions, and actions. The second taxonomy is a nomenclature for the data formats assessed, including numbers (and different formats for numbers) and graphics. The third taxonomy describes the quantitative concepts being conveyed, from the simplest (a single value at a single point in time) to more complex ones (including a risk-benefit trade-off and a trend over time). Finally, we demonstrate how these three taxonomies can be used to resolve ambiguities and apparent contradictions in the literature.
dc.publisherETS
dc.publisherWiley Periodicals, Inc.
dc.subject.othernumeracy
dc.subject.otherdata graphics
dc.subject.otherhealth numeracy
dc.subject.otherrisk communication
dc.subject.othertaxonomy
dc.titleTaxonomies for synthesizing the evidence on communicating numbers in health: Goals, format, and structure
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175761/1/risa13875_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175761/2/risa13875.pdf
dc.identifier.doi10.1111/risa.13875
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferenceRhodes, R. E., & de Bruijn, G. J. ( 2013 ). How big is the physical activity intention-behaviour gap? A meta-analysis using the action control framework. British Journal of Health Psychology, 18 ( 2 ), 296 – 309. https://doi.org/10.1111/bjhp.12032
dc.identifier.citedreferenceKreuzmair, C., Siegrist, M., & Keller, C. ( 2016 ). High numerates count icons and low numerates process large areas in pictographs: Results of an eye-tracking study. Risk Analysis, 36 ( 8 ), 1599 – 1614. https://doi.org/10.1111/risa.12531
dc.identifier.citedreferenceLeonhardt, J. M., & Keller R., L. ( 2018 ). Do pictographs affect probability comprehension and risk perception of multiple-risk communications? Journal of Consumer Affairs, 52 ( 3 ), 756 – 769. https://doi.org/10.1111/joca.12185
dc.identifier.citedreferenceLipkus, I. M., Samsa, G., & Rimer, B. K. ( 2001 ). General performance on a numeracy scale among highly educated samples. Medical Decision Making, 21, 37 – 44.
dc.identifier.citedreferenceLokker, N., Sanders, L., Perrin, E. M., Kumar, D., Finkle, J., Franco, V., Choi, L., Johnston, P. E., & Rothman, R. L. ( 2009 ). Parental misinterpretations of over-the-counter pediatric cough and cold medication labels. Pediatrics, 123 ( 6 ), 1464 – 1471. https://doi.org/10.1542/peds.2008-0854
dc.identifier.citedreferenceMarteau, T. M., Senior, V., & Sasieni, P. ( 2001 ). Women’s understanding of a “normal smear test result”: Experimental questionnaire based study. BMJ (Clinical research ed.), 322 ( 7285 ), 526 – 528. https://doi.org/10.1136/bmj.322.7285.526
dc.identifier.citedreferenceMcAndrew, L. M., Musumeci-Szabo, T. J., Mora, P. A., Vileikyte, L., Burns, E., Halm, E. A., Leventhal, E. A., & Leventhal, H. ( 2008 ). Using the common sense model to design interventions for the prevention and management of chronic illness threats: From description to process [Research Support, N.I.H., Extramural Review]. British Journal of Health Psychology, 13 ( Pt 2 ), 195 – 204. https://doi.org/10.1348/135910708×295604
dc.identifier.citedreferenceMichie, S., van Stralen, M. M., & West, R. ( 2011 ). The behaviour change wheel: A new method for characterising and designing behaviour change interventions [journal article]. Implementation Science, 6 ( 1 ), 1 – 12. https://doi.org/10.1186/1748-5908-6-42
dc.identifier.citedreferenceNagle, C., Hodges, R., Wolfe, R., & Wallace, E. M. ( 2009 ). Reporting Down syndrome screening results: Women’s understanding of risk. Prenatal Diagnosis, 29 ( 3 ), 234 – 239. https://doi.org/10.1002/pd.2210
dc.identifier.citedreferenceNeuner-Jehle, S., Senn, O., Wegwarth, O., Rosemann, T., & Steurer, J. ( 2011 ). How do family physicians communicate about cardiovascular risk? Frequencies and determinants of different communication formats. BMC Family Practice, 12 ( 1 ), 15. https://doi.org/10.1186/1471-2296-12-15
dc.identifier.citedreferencePeters, E., Hart, P. S., & Fraenkel, L. ( 2011 ). Informing patients: The influence of numeracy, framing, and format of side effect information on risk perceptions. Medical Decision Making, 31, 432 – 436.
dc.identifier.citedreferencePeters, E., Vastfjall, D., Slovic, P., Mertz, C. K., Mazzocco, K., & Dickert, S. ( 2006 ). Numeracy and decision making. Psychological Science, 17 ( 5 ), 407 – 413.
dc.identifier.citedreferencePighin, S., Savadori, L., Barilli, E., Galbiati, S., Smid, M., Ferrari, M., & Cremonesi, L. ( 2015 ). Communicating Down syndrome risk according to maternal age: “1-in-X” effect on perceived risk. Prenatal Diagnosis, 35 ( 8 ), 777 – 782. https://doi.org/10.1002/pd.4606
dc.identifier.citedreferenceReyna, V. F. ( 2008 ). A theory of medical decision-making and health: Fuzzy trace theory. Medical Decision Making, 28, 850 – 865.
dc.identifier.citedreferenceReyna, V. F., Nelson, W. L., Han, P., & Dieckmann, N. ( 2009 ). How numeracy influences risk comprehension and medical decision-making. Psychological Bulletin, 135 ( 6 ), 943 – 973.
dc.identifier.citedreferenceSchwartz, L., Woloshin, S., Black, W., & Welch, H. ( 1997 ). The role of numeracy in understanding the benefit of screening mammography. Annals of Internal Medicine, 127 ( 11 ), 966 – 972.
dc.identifier.citedreferenceSiegrist, M., Orlow, P., & Keller, C. ( 2008 ). The effect of graphical and numerical presentation of hypothetical prenatal diagnosis results on risk perception. Medical Decision Making, 28 ( 4 ), 567 – 574. https://doi.org/10.1177/0272989×08315237
dc.identifier.citedreferenceSmerecnik, C. M. R., Mesters, I., Kessels, L. T. E., Ruiter, R. A. C., De Vries, N. K., & De Vries, H. ( 2010 ). Understanding the positive effects of graphical risk information on comprehension: Measuring attention directed to written, tabular, and graphical risk information. Risk Analysis, 30 ( 9 ), 1387 – 1398. https://doi.org/10.1111/j.1539-6924.2010.01435.x
dc.identifier.citedreferenceTrevena, L. J., Bonner, C., Okan, Y., Peters, E., Gaissmaier, W., Han, P. K. J., Ozanne, E., Timmermans, D., & Zikmund-Fisher, B. J. ( 2021 ). Current challenges when using numbers in patient decision aids: Advanced concepts. Medical Decision Making, 41 ( 7 ), 834 – 847. https://doi.org/10.1177/0272989×21996342
dc.identifier.citedreferenceTversky, A., & Kahneman, D. ( 1981 ). The framing of decisions and the psychology of choice. Science, 211, 453 – 458.
dc.identifier.citedreferencevan der Bles, A. M., van der Linden, S., Freeman, A. L. J., Mitchell, J., Galvao, A. B., Zaval, L., & Spiegelhalter, D. J. ( 2019 ). Communicating uncertainty about facts, numbers, and science. Royal Society Open Science, 6 ( 181870 ). https://doi.org/10.1098/rsos.181870
dc.identifier.citedreferenceWickens, C. D., Hollands, J. G., Banbury, S., & Parasuraman, R. ( 2013 ). Engineering psychology and human performance. Psychology Press.
dc.identifier.citedreferenceWitte, K. ( 1992 ). Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59, 329 – 349.
dc.identifier.citedreferenceYin, H., Mendelsohn, A. L., Wolf, M. S., Parker, R. M., Fierman, A., van Schaick, L., Bazan, I. S., Kline, M. D., & Dreyer, B. P. ( 2010 ). Parents’ medication administration errors: Role of dosing instruments and health literacy. Archives of Pediatrics & Adolescent Medicine, 164 ( 2 ), 181 – 186. https://doi.org/10.1001/archpediatrics.2009.269
dc.identifier.citedreferenceZikmund-Fisher, B., Smith, D., Ubel, P., & Fagerlin, A. ( 2007 ). Validation of the Subjective Numeracy Scale (SNS): Effects of low numeracy on comprehension of risk communications and utility elicitations. Medical Decision Making, 27 ( 5 ), 663 – 671. https://doi.org/10.1177/0272989×07303824
dc.identifier.citedreferenceZikmund-Fisher, B. J., Fagerlin, A., & Ubel, P. A. ( 2007 ). Mortality versus survival graphs: Improving temporal consistency in perceptions of treatment effectiveness. Patient Education and Counseling, 66 ( 1 ), 100 – 107. https://doi.org/10.1016/j.pec.2006.10.013
dc.identifier.citedreferenceZikmund-Fisher, B. J., Scherer, A. M., Witteman, H. O., Solomon, J. B., Exe, N. L., Tarini, B. A., & Fagerlin, A. ( 2017 ). Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results. Journal of the American Medical Informatics Association, 24 ( 3 ), 520 – 528. https://doi.org/10.1093/jamia/ocw169
dc.identifier.citedreferenceAjzen, I. ( 1991 ). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179 – 211.
dc.identifier.citedreferenceAncker, J. S., & Kaufman, D. ( 2007 ). Rethinking health numeracy: A multidisciplinary literature review. Journal of the American Medical Informatics Association: JAMIA, 14 ( 6 ), 713 – 721. https://doi.org/10.1197/jamia.M2464
dc.identifier.citedreferenceAncker, J. S., Senathirajah, Y., Kukafka, R., & Starren, J. B. ( 2006 ). Design features of graphs in health risk communication: A systematic review. Journal of the American Medical Informatics Association, 13 ( 6 ), 608 – 618. https://doi.org/10.1197/jamia.M2115
dc.identifier.citedreferenceAnderson, B. L., Obrecht, N. A., Chapman, G. B., Driscoll, D. A., & Schulkin, J. ( 2011 ). Physicians’ communication of Down syndrome screening test results: The influence of physician numeracy. Genetics in Medicine, 13 ( 8 ), 744 – 749. https://doi.org/10.1097/GIM.0b013e31821a370f
dc.identifier.citedreferenceBailey, S. C., Pandit, A. U., Yin, S., Federman, A., Davis, T. C., Parker, R. M., & Wolf, M. S. ( 2009 ). Predictors of misunderstanding pediatric liquid medication instructions. Family Medicine, 41 ( 10 ), 715 – 721.
dc.identifier.citedreferenceBecker, M. H. ( 1974 ). The health belief model and personal health behavior. Health Education Monographs, 2, 324 – 508.
dc.identifier.citedreferenceBonner, C., Trevena, L. J., Gaissmaier, W., Han, P. K. J., Okan, Y., Ozanne, E., Peters, E., Timmermans, D., & Zikmund-Fisher, B. J. ( 2021 ). Current best practice for presenting probabilities in patient decision aids: Fundamental principles. Medical Decision Making, 41 ( 7 ), 821 – 833. https://doi.org/10.1177/0272989×21996328
dc.identifier.citedreferenceCuite, C., Weinstein, N., Emmons, K., & Colditz, G. ( 2008 ). A test of numeric formats for communicating risk probabilities. Medical Decision Making, 28 ( 3 ), 377 – 384. https://doi.org/10.1177/0272989×08315246
dc.identifier.citedreferenceFair, A. K., Murray, P. G., Thomas, A., & Cobain, M. R. ( 2008 ). Using hypothetical data to assess the effect of numerical format and context on the perception of coronary heart disease risk. American Journal of Health Promotion, 22 ( 4 ), 291 – 296.
dc.identifier.citedreferenceFreeman, T. R., & Bass, M. J. ( 1992 ). Risk language preferred by mothers in considering a hypothetical new vaccine for their children. CMAJ: Canadian Medical Association journal = journal de l’Association medicale canadienne, 147 ( 7 ), 1013 – 1017. https://pubmed.ncbi.nlm.nih.gov/1393896. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1336288/
dc.identifier.citedreferenceGalesic, M., & Garcia-Retamero, R. ( 2011 ). Do low-numeracy people avoid shared decision making? Health Psychology, 30 ( 3 ), 336 – 341. https://doi.org/10.1037/a0022723
dc.identifier.citedreferenceGarcia-Retamero, R., Galesic, M., & Gigerenzer, G. ( 2011 ). Enhancing understanding and recall of quantitative information about medical risks: A cross-cultural comparison between Germany and Spain. The Spanish Journal of Psychology, 14 ( 1 ), 218 – 226.
dc.identifier.citedreferenceGraham, P. H., Martin, R. M., & Browne, L. H. ( 2009 ). Communicating breast cancer treatment complication risks: When words are likely to fail. Asia-Pacific Journal of Clinical Oncology, 5 ( 3 ), 193 – 199. https://doi.org/10.1111/j.1743-7563.2009.01232.x
dc.identifier.citedreferenceGrimes, D. A., & Snively, G. R. ( 1999 ). Patients’ understanding of medical risks: Implications for genetic counseling. Obstetrics and Gynecology, 93, 910 – 914. http://www.sciencedirect.com/science/article/pii/S0029784498005675
dc.identifier.citedreferenceHousten, A. J., Kamath, G. R., Bevers, T. B., Cantor, S. B., Dixon, N., Hite, A., Kallen, M. A., Leal, V. B., Li, L., & Volk, R. J. ( 2020 ). Does animation improve comprehension of risk information in patients with low health literacy? A randomized trial. Medical Decision Making: an International Journal of the Society for Medical Decision Making, 40 ( 1 ), 17 – 28. https://doi.org/10.1177/0272989×19890296
dc.identifier.citedreferenceKeller, C., Kreuzmair, C., Leins-Hess, R., & Siegrist, M. ( 2014 ). Numeric and graphic risk information processing of high and low numerates in the intuitive and deliberative decision modes: An eye-tracker study. Judgment and Decision Making, 9 ( 5 ), 420 – 432.
dc.identifier.citedreferenceKirsch, I. S. ( 2001 ). The international adult literacy survey (IALS): Understanding what was measured. ETS.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.