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Citing this Article

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Published on 08.08.14 in Vol 16, No 8 (2014): August

This paper is in the following e-collection/theme issue:

Works citing "Numeracy and Literacy Independently Predict Patients’ Ability to Identify Out-of-Range Test Results"

Brian J Zikmund-Fisher, Nicole L Exe, Holly O Witteman

J Med Internet Res 2014 (Aug 08); 16(8):e187 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.3241):

(note that this is only a small subset of citations)

  1. Zikmund-Fisher BJ, Scherer AM, Witteman HO, Solomon JB, Exe NL, Fagerlin A. Effect of Harm Anchors in Visual Displays of Test Results on Patient Perceptions of Urgency About Near-Normal Values: Experimental Study. Journal of Medical Internet Research 2018;20(3):e98
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  2. Reading Turchioe M, Grossman LV, Myers AC, Baik D, Goyal P, Masterson Creber RM. Visual analogies, not graphs, increase patients' comprehension of changes in their health status. Journal of the American Medical Informatics Association 2020;27(5):677
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  3. Grossman LV, Masterson Creber RM, Benda NC, Wright D, Vawdrey DK, Ancker JS. Interventions to increase patient portal use in vulnerable populations: a systematic review. Journal of the American Medical Informatics Association 2019;26(8-9):855
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  4. Grossman LV, Choi SW, Collins S, Dykes PC, O’Leary KJ, Rizer M, Strong P, Yen P, Vawdrey DK. Implementation of acute care patient portals: recommendations on utility and use from six early adopters. Journal of the American Medical Informatics Association 2018;25(4):370
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  5. Zikmund-Fisher BJ, Solomon JB, Scherer AM, Exe NL, Tarini BA, Fagerlin A, Witteman HO. Primary Care Providers’ Preferences and Concerns Regarding Specific Visual Displays for Returning Hemoglobin A1c Test Results to Patients. Medical Decision Making 2019;39(7):796
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  6. Tao D, Yuan J, Qu X. Effects of presentation formats on consumers’ performance and perceptions in the use of personal health records among older and young adults. Patient Education and Counseling 2019;102(3):578
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  7. Tao D, Yuan J, Qu X. Presenting self-monitoring test results for consumers: the effects of graphical formats and age. Journal of the American Medical Informatics Association 2018;25(8):1036
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  8. Perrotta PL, Karcher DS. Validating Laboratory Results in Electronic Health Records: A College of American Pathologists Q-Probes Study. Archives of Pathology & Laboratory Medicine 2016;140(9):926
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  9. Kerr D, Axelrod C, Hoppe C, Klonoff DC. Diabetes and technology in 2030: a utopian or dystopian future?. Diabetic Medicine 2018;35(4):498
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  10. Scherer AM, Witteman HO, Solomon J, Exe NL, Fagerlin A, Zikmund-Fisher BJ. Improving the Understanding of Test Results by Substituting (Not Adding) Goal Ranges: Web-Based Between-Subjects Experiment. Journal of Medical Internet Research 2018;20(10):e11027
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  11. Lockwood MB, Dunn-Lopez K, Pauls H, Burke L, Shah SD, Saunders MA. If you build it, they may not come: modifiable barriers to patient portal use among pre- and post-kidney transplant patients. JAMIA Open 2018;1(2):255
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  12. Fraccaro P, Vigo M, Balatsoukas P, Buchan IE, Peek N, van der Veer SN. The influence of patient portals on users’ decision making is insufficiently investigated: A systematic methodological review. International Journal of Medical Informatics 2018;111:100
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  13. Sveshnikova AN, Panteleev MA, Dreval AV, Shestakova TP, Medvedev OS, Dreval OA. Theoretical evaluation of the parameters of glucose metabolism on the basis of continuous glycemia monitoring data using mathematical modeling. Biophysics 2017;62(5):842
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  14. Gopalan A, Kellom K, McDonough K, Schapira MM. Exploring how patients understand and assess their diabetes control. BMC Endocrine Disorders 2018;18(1)
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  15. Neter E, Brainin E. Association Between Health Literacy, eHealth Literacy, and Health Outcomes Among Patients With Long-Term Conditions. European Psychologist 2019;24(1):68
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  16. Lyles C, Schillinger D, Sarkar U. Connecting the Dots: Health Information Technology Expansion and Health Disparities. PLOS Medicine 2015;12(7):e1001852
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  17. . Patient views on understanding laboratory results. Clinical Chemistry and Laboratory Medicine (CCLM) 2019;57(3):371
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  18. . Capsule Commentary on Shultz et al., Patient Preferences for Test Result Notification. Journal of General Internal Medicine 2015;30(11):1698
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  19. Struikman B, Bol N, Goedhart A, van Weert JCM, Talboom-Kamp E, van Delft S, Brabers AEM, van Dijk L. Features of a Patient Portal for Blood Test Results and Patient Health Engagement: Web-Based Pre-Post Experiment. Journal of Medical Internet Research 2020;22(7):e15798
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  20. Shaffer VA, Wegier P, Valentine K, Belden JL, Canfield SM, Patil SJ, Popescu M, Steege LM, Jain A, Koopman RJ. Patient Judgments About Hypertension Control: The Role of Variability, Trends, and Outliers in Visualized Blood Pressure Data. Journal of Medical Internet Research 2019;21(3):e11366
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  21. Fox B, Felkey B. Tech Trends We Are Watching in 2015: Health Information Technology Developments. Hospital Pharmacy 2015;50(1):084
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  22. Tieu L, Sarkar U, Schillinger D, Ralston JD, Ratanawongsa N, Pasick R, Lyles CR. Barriers and Facilitators to Online Portal Use Among Patients and Caregivers in a Safety Net Health Care System: A Qualitative Study. Journal of Medical Internet Research 2015;17(12):e275
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  23. Giardina TD, Baldwin J, Nystrom DT, Sittig DF, Singh H. Patient perceptions of receiving test results via online portals: a mixed-methods study. Journal of the American Medical Informatics Association 2018;25(4):440
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  24. Fox BI, Felkey BG. Tech Trends We Are Watching in 2015: Health Information Technology Developments. Hospital Pharmacy 2015;50(1):084
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  25. Gopalan A, Suttner L, Troxel AB, McDonough K, Schapira MM. Testing patient-informed approaches for visually depicting the hemoglobin A1c value to patients with poorly controlled diabetes: a randomized, controlled trial. BMC Health Services Research 2020;20(1)
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  26. Zikmund-Fisher BJ, Scherer AM, Witteman HO, Solomon JB, Exe NL, Tarini BA, Fagerlin A. Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results. Journal of the American Medical Informatics Association 2017;24(3):520
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  27. Bellini SG, Shields J, Eggett DL. Validating an Evaluation Tool for Nutrition Education Handouts in the Clinical Setting. Topics in Clinical Nutrition 2018;33(4):311
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  28. Fraccaro P, Vigo M, Balatsoukas P, van der Veer SN, Hassan L, Williams R, Wood G, Sinha S, Buchan I, Peek N. Presentation of laboratory test results in patient portals: influence of interface design on risk interpretation and visual search behaviour. BMC Medical Informatics and Decision Making 2018;18(1)
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  29. Kiernan F, Rahman F. Measuring surgical performance: A risky game?. The Surgeon 2015;13(4):213
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  30. Reyna VF, Brust‐Renck PG. How representations of number and numeracy predict decision paradoxes: A fuzzy‐trace theory approach. Journal of Behavioral Decision Making 2020;33(5):606
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  31. Grady M, Katz LB, Cameron H, Levy BL. A Comprehensive Evaluation of a Novel Color Range Indicator in Multiple Blood Glucose Meters Demonstrates Improved Glucose Range Interpretation and Awareness in Subjects With Type 1 and Type 2 Diabetes. Journal of Diabetes Science and Technology 2016;10(6):1324
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  32. Delanoë A, Lépine J, Turcotte S, Leiva Portocarrero ME, Robitaille H, Giguère AM, Wilson BJ, Witteman HO, Lévesque I, Guillaumie L, Légaré F. Role of Psychosocial Factors and Health Literacy in Pregnant Women’s Intention to Use a Decision Aid for Down Syndrome Screening: A Theory-Based Web Survey. Journal of Medical Internet Research 2016;18(10):e283
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  33. Kruse CS, Bolton K, Freriks G. The Effect of Patient Portals on Quality Outcomes and Its Implications to Meaningful Use: A Systematic Review. Journal of Medical Internet Research 2015;17(2):e44
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  34. Kaziunas E, Hanauer DA, Ackerman MS, Choi SW. Identifying unmet informational needs in the inpatient setting to increase patient and caregiver engagement in the context of pediatric hematopoietic stem cell transplantation. Journal of the American Medical Informatics Association 2016;23(1):94
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  35. Sheon AR, Bolen SD, Callahan B, Shick S, Perzynski AT. Addressing Disparities in Diabetes Management Through Novel Approaches to Encourage Technology Adoption and Use. JMIR Diabetes 2017;2(2):e16
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  36. Gartrell K, Trinkoff A, Storr C, Wilson M, Gurses A. Testing the Electronic Personal Health Record Acceptance Model by Nurses for Managing Their Own Health. Applied Clinical Informatics 2015;06(02):224
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  37. . Top of Scope Practice. Critical Values 2016;9(1):28
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  38. . Direct patient access to test results: implications for the laboratory. Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 2015;52(5):525
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  39. Wilkins CH, Mapes BM, Jerome RN, Villalta-Gil V, Pulley JM, Harris PA. Understanding What Information Is Valued By Research Participants, And Why. Health Affairs 2019;38(3):399
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  40. Delanoë A, Lépine J, Leiva Portocarrero ME, Robitaille H, Turcotte S, Lévesque I, Wilson BJ, Giguère AMC, Légaré F. Health literacy in pregnant women facing prenatal screening may explain their intention to use a patient decision aid: a short report. BMC Research Notes 2016;9(1)
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  41. Watson ID, Wilkie P, Hannan A, Beastall GH. Role of laboratory medicine in collaborative healthcare. Clinical Chemistry and Laboratory Medicine (CCLM) 2018;57(1):134
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  42. Bar-Lev S, Beimel D. Numbers, graphs and words – do we really understand the lab test results accessible via the patient portals?. Israel Journal of Health Policy Research 2020;9(1)
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  43. Zhang Z, Citardi D, Xing A, Luo X, Lu Y, He Z. Patient Challenges and Needs in Comprehending Laboratory Test Results: Mixed Methods Study. Journal of Medical Internet Research 2020;22(12):e18725
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  44. Neter E, Brainin E, Baron-Epel O. Group differences in health literacy are ameliorated in ehealth literacy. Health Psychology and Behavioral Medicine 2021;9(1):480
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  45. Scalia P, Schubbe DC, Lu ES, Durand M, Frascara J, Noel G, O’Malley AJ, Elwyn G, von Wagner C. Comparing the impact of an icon array versus a bar graph on preference and understanding of risk information: Results from an online, randomized study. PLOS ONE 2021;16(7):e0253644
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  46. Vromans RD, Pauws SC, van de Poll-Franse LV, Krahmer EJ. Effects of comparative information when communicating personalized risks of treatment outcomes: an experimental study. Journal of Risk Research 2023;26(3):324
    CrossRef
  47. Katz LB, Aparicio M, Cameron H, Ceppa F. Use of a Meter With Color-Range Indicators and a Mobile Diabetes Management App Improved Glycemic Control and Patient Satisfaction in an Underserved Hispanic Population: “Tu Salud”—A Randomized Controlled Partial Cross-Over Clinical Study. Diabetes Spectrum 2022;35(1):86
    CrossRef
  48. Queraltó J, Brady J, Carobene A, Homšak E, Wieringa G. The European Register of Specialists in Clinical Chemistry and Laboratory Medicine: code of conduct, version 3 – 2023. Clinical Chemistry and Laboratory Medicine (CCLM) 2023;61(6):981
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  49. Zhang Z, Kmoth L, Luo X, He Z. User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study. JMIR Human Factors 2021;8(4):e26017
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  50. Hefner JL, Sieck CJ, Walker DM. Patient and physician perspectives on training to improve communication through secure messaging. Health Care Management Review 2022;47(1):3
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  51. Fooks N, Hadad B, Rubinsten O. Nonsymbolic-Magnitude Deficit in Adults With Developmental Dyscalculia: Evidence of Impaired Size Discrimination but Intact Size Constancy. Psychological Science 2021;32(8):1271
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  52. Witteman HO, Zikmund-Fisher BJ. Communicating laboratory results to patients and families. Clinical Chemistry and Laboratory Medicine (CCLM) 2019;57(3):359
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  53. Reynolds TL, Zhang J, Zheng K, Chen Y. Unpacking the Use of Laboratory Test Results in an Online Health Community throughout the Medical Care Trajectory. Proceedings of the ACM on Human-Computer Interaction 2022;6(CSCW2):1
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  54. Arcia A, Spiegel-Gotsch N, George M. Design of tailored asthma control status infographics. Information Design Journal 2023;28(2):115
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  55. Franco J, Morris NS, Fung MK. Defining and identifying laboratory literacy as a component of health literacy: An assessment of existing health literacy tools. Academic Pathology 2023;10(4):100096
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  56. Silverstein MC, Bjälkebring P, Shoots-Reinhard B, Peters E. The numeric understanding measures: Developing and validating adaptive and nonadaptive numeracy scales. Judgment and Decision Making 2023;18
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  57. Su P, Liu K. Effects of anthropomorphic design on comprehension of self-monitoring test results: Integrating evidence of eye-tracking and event-related potential. Displays 2024;82:102664
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  58. He Z, Bhasuran B, Jin Q, Tian S, Hanna K, Shavor C, Arguello LG, Murray P, Lu Z. Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study. Journal of Medical Internet Research 2024;26:e56655
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.3241):

  1. Tao D, Yuan J, Qu X, Wang T, Chen X. Engineering Psychology and Cognitive Ergonomics. 2018. Chapter 40:490
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  2. Durst AL, Mills R. Genetic Counseling Practice. 2020. :271
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  3. Lu Y, Zhang Z, Min K, Luo X, He Z. Diversity, Divergence, Dialogue. 2021. Chapter 2:18
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  4. Turchioe MR, Creber RM. Personal Health Informatics. 2022. Chapter 18:371
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  5. Bender J, Jackson SL. The Patient-Centered Approach to Medical Note-Writing. 2023. Chapter 15:197
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