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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]

Quantitative literacy is important in politics[2][3] and health care[4][5].

Health care

Health care numeracy is problematic. Health care providers[6][7][8][9][10] and patients[11][12][13][14][15][14][16] both have problems with quantitative reasoning. Some of the difficulty is doe to interpreting relative versus absolute measures of efficacy.[17][18] The problem is confounded by scientific journals not well presenting quantitative results.[19]

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[18][20][21][22][23][16][24] and by health care professionals[25][26][24].

In practicing evidence-based medicine, framing bias is best avoided by using numeracy with absolute measures of efficacy.[27][28]

Comparing accuracy of diagnostic methods

Various formats have been tested to improve comprehension of quantitative comparisons of diagnostic accuracy.[29][30] [25]

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. 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. 
  3. Best, Joel (2004). More damned lies and statistics: how numbers confuse public issues. Berkeley: University of California Press. ISBN 0-520-23830-3. 
  4. 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.
  5. Schwartz, Lisa A.; Steven Woloshin (2008). Know Your Chances: Understanding Health Statistics. Berkeley: University of California Press. ISBN 0-520-25222-5. 
  6. 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[e]
  7. Berwick DM, Fineberg HV, Weinstein MC (1981). "When doctors meet numbers.". Am J Med 71 (6): 991-8. PMID 7315859[e]
  8. 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[e]
  9. 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[e]
  10. 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. PMID 11934776. PMC PMC100792[e]
  11. 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. Research Blogging.
  12. 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[e]
  13. 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[e]
  14. 14.0 14.1 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[e]
  15. 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[e]
  16. 16.0 16.1 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[e]
  17. 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. PMID 7950558. PMC PMC2541000[e]
  18. 18.0 18.1 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. PMID 14687273. PMC PMC1494938[e]
  19. Nuovo J, Melnikow J, Chang D (June 2002). "Reporting number needed to treat and absolute risk reduction in randomized controlled trials". JAMA 287 (21): 2813–4. PMID 12038920[e]
  20. 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. Research Blogging.
  21. Woloshin S, Schwartz LM, Welch HG (February 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[e]
  22. 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. PMID 18565218. PMC 2467410. Research Blogging.
  23. 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. PMID 18402680. PMC 2330036. Research Blogging.
  24. 24.0 24.1 Wen L, Badgett R, Cornell J (October 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. Research Blogging.
  25. 25.0 25.1 Sheridan SL, Pignone M (2002). "Numeracy and the medical student's ability to interpret data". Eff Clin Pract 5 (1): 35–40. PMID 11874195[e]
  26. Gigerenzer G, Edwards A (September 2003). "Simple tools for understanding risks: from innumeracy to insight". BMJ 327 (7417): 741–4. DOI:10.1136/bmj.327.7417.741. PMID 14512488. PMC 200816. Research Blogging.
  27. 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. Research Blogging.
  28. 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. Research Blogging.
  29. 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[e]
  30. 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[e]