Quantitative literacy

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In education and literacy, Quantitative literacy (also called numeracy) is "the knowledge and skills required to apply arithmetic operations, either alone or sequentially, using numbers embedded in printed materials; for example, balancing a checkbook, figuring out a tip, completing an order form, or determining the amount of interest from a loan advertisement."[1]

Comprehension of numbers can be divided into:[2][3]

  • Verbatim comprehension: "the ability to correctly read numbers from graphs"
  • Gist comprehension: "the ability to identify the essential point of the information presented", or more specifically, correctly rank the magnitude of two or more options.

Quantitative literacy is important in politics[4][5] and health care[6][7].

Health care

Health care numeracy is problematic. Health care providers[8][9][10][11][12] and patients[13][14][15][16][17][16][18] both have problems with quantitative reasoning. Some of the difficulty is doe to interpreting relative versus absolute measures of efficacy.[19][20] The problem is confounded by scientific journals not well presenting quantitative results.[21]

Comparing benefits of two treatments

Various formats including the number needed to treat have been tested to improve comprehension of quantitative comparisons of treatment benefit by patients[20][22][23][24][25][18][26] and by health care professionals[27][28][26].

In practicing evidence-based medicine, framing bias is best avoided by using numeracy with absolute measures of efficacy.[29][30]

Pictographs (Pictograms)

Pictographs may been studied, but patients may prefer bar graphs.[31]

When designing pictograms:

  • "Risk recall was significantly higher with more anthropomorphic icons (restroom icons, head outlines, and photos) than with other icon types, and participants rated restroom icons as most preferred."[32]
  • Patients may have more trust when the characters are randomly highlighted vs highlighted in groups.[31]

Comparing accuracy of diagnostic methods

Various formats have been tested to improve comprehension of quantitative comparisons of diagnostic accuracy.[33][34] [27]

References

  1. ↑ Irwin S. Kirsch, Ann Jungeblut, Lynn Jenkins, and Andrew Kolstad. (1993). Adult Literacy in America: a first look at the findings of the National Adult Literacy Survey, (NCES 93275). U.S. Department of Education.
  2. ↑ Nelson W, Reyna VF, Fagerlin A, Lipkus I, Peters E (2008). "Clinical implications of numeracy: theory and practice". Ann Behav Med. 35 (3): 261–74. doi:10.1007/s12160-008-9037-8. PMC 3694344. PMID 18677452.
  3. ↑ Hawley ST, Zikmund-Fisher B, Ubel P, Jancovic A, Lucas T, Fagerlin A (2008). "The impact of the format of graphical presentation on health-related knowledge and treatment choices". Patient Educ Couns. 73 (3): 448–55. doi:10.1016/j.pec.2008.07.023. PMID 18755566.
  4. ↑ Best, Joel (2001). Damned lies and statistics: untangling numbers from the media, politicians, and activists. Berkeley: University of California Press. ISBN 0-520-21978-3.
  5. ↑ Best, Joel (2004). More damned lies and statistics: how numbers confuse public issues. Berkeley: University of California Press. ISBN 0-520-23830-3.
  6. ↑ Mark Kutner, Elizabeth Greenberg, Ying Jin, Christine Paulsen. (2006) The Health Literacy of America’s Adults: Results From the 2003 National Assessment of Adult Literacy. U.S. Department of Education.
  7. ↑ Schwartz, Lisa A.; Steven Woloshin (2008). Know Your Chances: Understanding Health Statistics. Berkeley: University of California Press. ISBN 0-520-25222-5.
  8. ↑ Bergman DA, Pantell RH (1986). "The impact of reading a clinical study on treatment decisions of physicians and residents". J Med Educ. 61 (5): 380–6. PMID 3701813.
  9. ↑ Berwick DM, Fineberg HV, Weinstein MC (1981). "When doctors meet numbers". Am J Med. 71 (6): 991–8. PMID 7315859.
  10. ↑ Phelps MA, Levitt MA (2004). "Pretest probability estimates: a pitfall to the clinical utility of evidence-based medicine?". Acad Emerg Med. 11 (6): 692–4. PMID 15175211.
  11. ↑ Reid MC, Lane DA, Feinstein AR (1998). "Academic calculations versus clinical judgments: practicing physicians' use of quantitative measures of test accuracy". Am J Med. 104 (4): 374–80. PMID 9576412.
  12. ↑ Steurer J, Fischer JE, Bachmann LM, Koller M, ter Riet G (2002). "Communicating accuracy of tests to general practitioners: a controlled study". BMJ. 324 (7341): 824–6. PMC 100792. PMID 11934776.
  13. ↑ Epstein RM, Alper BS, Quill TE (2004). "Communicating evidence for participatory decision making". JAMA. 291 (19): 2359–66. doi:10.1001/jama.291.19.2359. PMID 15150208.
  14. ↑ Friedmann PD, Brett AS, Mayo-Smith MF (1996). "Differences in generalists' and cardiologists' perceptions of cardiovascular risk and the outcomes of preventive therapy in cardiovascular disease". Ann Intern Med. 124 (4): 414–21. PMID 8554250.
  15. ↑ Hamm RM, Smith SL (1998). "The accuracy of patients' judgments of disease probability and test sensitivity and specificity". J Fam Pract. 47 (1): 44–52. PMID 9673608.
  16. ↑ 16.0 16.1 Malenka DJ, Baron JA, Johansen S, Wahrenberger JW, Ross JM (1993). "The framing effect of relative and absolute risk". J Gen Intern Med. 8 (10): 543–8. PMID 8271086.
  17. ↑ Naylor CD, Chen E, Strauss B (1992). "Measured enthusiasm: does the method of reporting trial results alter perceptions of therapeutic effectiveness?". Ann Intern Med. 117 (11): 916–21. PMID 1443954.
  18. ↑ 18.0 18.1 Schwartz LM, Woloshin S, Black WC, Welch HG (1997). "The role of numeracy in understanding the benefit of screening mammography". Ann Intern Med. 127 (11): 966–72. PMID 9412301.
  19. ↑ Bucher HC, Weinbacher M, Gyr K (1994). "Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration". BMJ. 309 (6957): 761–4. PMC 2541000. PMID 7950558.
  20. ↑ 20.0 20.1 Sheridan SL, Pignone MP, Lewis CL (2003). "A randomized comparison of patients' understanding of number needed to treat and other common risk reduction formats". J Gen Intern Med. 18 (11): 884–92. PMC 1494938. PMID 14687273.
  21. ↑ Nuovo J, Melnikow J, Chang D (2002). "Reporting number needed to treat and absolute risk reduction in randomized controlled trials". JAMA. 287 (21): 2813–4. PMID 12038920. Unknown parameter |month= ignored (help)
  22. ↑ Schwartz LM, Woloshin S, Welch HG (2007). "The drug facts box: providing consumers with simple tabular data on drug benefit and harm". Med Decis Making. 27 (5): 655–62. doi:10.1177/0272989X07306786. PMID 17873258.
  23. ↑ Woloshin S, Schwartz LM, Welch HG (2007). "The effectiveness of a primer to help people understand risk: two randomized trials in distinct populations". Ann. Intern. Med. 146 (4): 256–65. PMID 17310049. Unknown parameter |month= ignored (help)
  24. ↑ Stovring H, Gyrd-Hansen D, Kristiansen IS, Nexoe J, Nielsen JB (2008). "Communicating effectiveness of intervention for chronic diseases: what single format can replace comprehensive information?". BMC Med Inform Decis Mak. 8: 25. doi:10.1186/1472-6947-8-25. PMC 2467410. PMID 18565218.
  25. ↑ Dolan JG, Iadarola S (2008). "Risk communication formats for low probability events: an exploratory study of patient preferences". BMC Med Inform Decis Mak. 8: 14. doi:10.1186/1472-6947-8-14. PMC 2330036. PMID 18402680.
  26. ↑ 26.0 26.1 Wen L, Badgett R, Cornell J (2005). "Number needed to treat: a descriptor for weighing therapeutic options". Am J Health Syst Pharm. 62 (19): 2031–6. doi:10.2146/ajhp040558. PMID 16174840. Unknown parameter |month= ignored (help)
  27. ↑ 27.0 27.1 Sheridan SL, Pignone M (2002). "Numeracy and the medical student's ability to interpret data". Eff Clin Pract. 5 (1): 35–40. PMID 11874195.
  28. ↑ Gigerenzer G, Edwards A (2003). "Simple tools for understanding risks: from innumeracy to insight". BMJ. 327 (7417): 741–4. doi:10.1136/bmj.327.7417.741. PMC 200816. PMID 14512488. Unknown parameter |month= ignored (help)
  29. ↑ Perneger TV, Agoritsas T (2011). "Doctors and Patients' Susceptibility to Framing Bias: A Randomized Trial". J Gen Intern Med. doi:10.1007/s11606-011-1810-x. PMID 21792695.
  30. ↑ Woloshin S, Schwartz LM (2011). "Communicating data about the benefits and harms of treatment: a randomized trial". Ann Intern Med. 155 (2): 87–96. doi:10.1059/0003-4819-155-2-201107190-00004. PMID 21768582.
  31. ↑ 31.0 31.1 Schapira MM, Nattinger AB, McAuliffe TL (2006). "The influence of graphic format on breast cancer risk communication". J Health Commun. 11 (6): 569–82. doi:10.1080/10810730600829916. PMID 16950729.
  32. ↑ Zikmund-Fisher BJ, Witteman HO, Dickson M, Fuhrel-Forbis A, Kahn VC, Exe NL; et al. (2014). "Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs". Med Decis Making. 34 (4): 443–53. doi:10.1177/0272989X13511706. PMC 3991751. PMID 24246564.
  33. ↑ Puhan MA, Steurer J, Bachmann LM, ter Riet G (2005). "A randomized trial of ways to describe test accuracy: the effect on physicians' post-test probability estimates". Ann. Intern. Med. 143 (3): 184–9. PMID 16061916.
  34. ↑ Poses RM; et al. (1995). "You can lead a horse to water--improving physicians' knowledge of probabilities may not affect their decisions". Medical Decision Making. 15: 65–75. PMID 7898300.

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