Understanding and Bridging the Language and Terminology Gap Between Health Professionals and Consumers Using Social Media



The advancement of the Internet and the social media has engaged the general public in their own healthcare more than ever. People actively seek health information online, form online patient communities to share experiences, and seek social support. Nevertheless, the limited health literacy of lay people makes it difficult for them to find the relevant health information, understand and reconcile conflicting findings. To improve health literacy and reduce the language barriers for lay people, it is important to understand the language and terminology gap between health professionals and consumers. eHealth literacy, which is defined as the ability to seek, find, understand, and appraise health information from electronic sources and apply the knowledge gained to addressing or solving a health problem, is an important factor of the gap. This chapter discusses eHealth literacy, its measurements, as well as methods and practice of harnessing social media to understand and bridge the terminology gap between professionals and consumers. This chapter also discusses future opportunities for developing health applications for consumers that are more adaptive to their health literacy level while preserving the accuracy of the information.


Health vocabulary Consumer Health literacy 


  1. 1.
    Hibbard JH, Greene J. What the evidence shows about patient activation: better health outcomes and care experiences; fewer data on costs. Health Aff (Millwood). 2013;32(2):207–14. PMID: 23381511.CrossRefGoogle Scholar
  2. 2.
    Hibbard JH, Greene J, Overton V. Patients with lower activation associated with higher costs; delivery systems should know their patients’ ‘scores’. Health Aff (Millwood). 2013;32(2):216–22. PMID: 23381513.PubMedCrossRefGoogle Scholar
  3. 3.
    Lopez-Campos G, Ofoghi B, Martin-Sanchez F. Enabling self-monitoring data exchange in participatory medicine. Stud Health Technol Inform. 2015;216:1102. PMID: 26262401.PubMedGoogle Scholar
  4. 4.
    OpenNotes and AMIA join forces to improve patient access to health records. 2017.
  5. 5.
    Homepage of OpenNotes.
  6. 6.
    Grossman LV, Creber RM, Restaino S, Vawdrey DK. Sharing clinical notes with hospitalized patients via an acute care portal. AMIA Annu Symp Proc. 2017;2017:800–9.PubMedGoogle Scholar
  7. 7.
    Koerber A, Still SX. Guest editors’ introduction: online health communication. Tech Commun Q. 2008;17(3):259–63.CrossRefGoogle Scholar
  8. 8.
    Fox S. The social life of health information 2014. 2017.
  9. 9.
    Fox S. Health topics: 80% of internet users look for health information online 2011. 2017.Google Scholar
  10. 10.
    Bientzle M, Griewatz J, Kimmerle J, Kuppers J, Cress U, Lammerding-Koeppel M. Impact of scientific versus emotional wording of patient questions on doctor-patient communication in an internet forum: a randomized controlled experiment with medical students. J Med Internet Res. 2015;17(11):e268. PMID: 26607233.PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    Otte-Trojel T, de Bont A, van de Klundert J, Rundall TG. Characteristics of patient portals developed in the context of health information exchanges: early policy effects of incentives in the meaningful use program in the United States. J Med Internet Res. 2014;16(11):e258. PMID: 25447837.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Yoon H, Sohn M, Choi M, Jung M. Conflicting online health information and rational decision making: implication for cancer survivors. Health Care Manag (Frederick). 2017;36(2):184–91. PMID: 28383314.Google Scholar
  13. 13.
    Rew L, Saenz A, Walker LO. A systematic method for reviewing and analyzing health information on consumer-oriented websites. J Adv Nurs. 2018. PMID: 29845648.Google Scholar
  14. 14.
    Messai R, Simonet M, Bricon-Souf N, Mousseau M. Characterizing consumer health terminology in the breast cancer field. Stud Health Technol Inform. 2010;160(Pt 2):991–4. PMID: 20841832.PubMedGoogle Scholar
  15. 15.
    Poikonen T, Vakkari P. Lay persons’ and professionals’ nutrition-related vocabularies and their matching to a general and a specific thesaurus. J Inf Sci. 2009;35(2):232–43.CrossRefGoogle Scholar
  16. 16.
    Smith CA, Wicks PJ. PatientsLikeMe: consumer health vocabulary as a folksonomy. AMIA Annu Symp Proc. 2008:682–6. PMID: 18999004.Google Scholar
  17. 17.
    Rajah R, Hassali MA, Lim CJ. An interprofessional evaluation of health literacy communication practices of physicians, pharmacists, and nurses at public hospitals in Penang, Malaysia. Ann Pharmacother. 2017:1060028017739031. PMID: 29078711.Google Scholar
  18. 18.
    Chen J, Zheng J, Yu H. Finding important terms for patients in their electronic health records: a learning-to-rank approach using expert annotations. JMIR Med Inform. 2016;4(4):e40. PMID: 27903489.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Seedorff M, Peterson KJ, Nelsen LA, Cocos C, McCormick JB, Chute CG, Pathak J. Incorporating expert terminology and disease risk factors into consumer health vocabularies. Pac Symp Biocomput. 2013:421–32. PMID: 23424146.Google Scholar
  20. 20.
    Gross T, Taylor A. What have we got to lose? The effect of controlled vocabulary on keyword searching results. C&RL. 2005;66(3):212–30.CrossRefGoogle Scholar
  21. 21.
    Lewis D, Chang B, Friedman C. Consumer health informatics. Consumer health informatics. Pittsburgh, PA: Springer; 2005.CrossRefGoogle Scholar
  22. 22.
    Lustria MLA. Message tailoring in health and risk messaging communication and technology, health and risk communication, mass communication. Oxford University Press; 2017.Google Scholar
  23. 23.
    Norman CD, Skinner HA. eHealth literacy: essential skills for consumer health in a networked world. J Med Internet Res. 2006;8(2):e9. PMID: 16867972.PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    ALA. Presidential Committee on Information Literacy: Final Report 1989. 2018.
  25. 25.
    Feuerstein M. Media literacy in support of critical thinking. J Educ Media. 1999;24(1):43–54.CrossRefGoogle Scholar
  26. 26.
    Hsu W, Chiang C, Yang S. The effect of individual factors on health behaviors among college students: the mediating effects of eHealth literacy. J Med Internet Res. 2014;16(12):e287. PMID: 25499086.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Stellefson M, Paige SR, Tennant B, Alber JM, Chaney BH, Chaney D, Grossman S. Reliability and validity of the telephone-based ehealth literacy scale among older adults: cross-sectional survey. J Med Internet Res. 2017;19(10):e362.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Norman CD, Skinner HA. eHEALS: the eHealth literacy scale. J Med Internet Res. 2006;8(4):e27. PMID: 17213046.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Nguyen J, Moorhouse M, Curbow B, Christie J, Walsh-Childers K, Islam S. Construct validity of the eHealth Literacy Scale (eHEALS) among two adult populations: a rasch analysis. JMIR Public Health Surveill. 2016;2(1):e24. PMID: 27244771.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Chung SY, Nahm ES. Testing reliability and validity of the eHealth Literacy Scale (eHEALS) for older adults recruited online. Comput Inform Nurs. 2015;33(4):150–6. PMID: 25783223.PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Paige SR, Krieger JL, Stellefson ML. The influence of eHealth literacy on perceived trust in online health communication channels and sources. J Health Commun. 2017;22(1):53–65. PMID: 28001489.PubMedCrossRefGoogle Scholar
  32. 32.
    Diviani N, Dima AL, Schulz PJ. A psychometric analysis of the Italian version of the eHealth literacy scale using item response and classical test theory methods. J Med Internet Res. 2017;19(4):e114. PMID: 28400356.PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Bowling A. Mode of questionnaire administration can have serious effects on data quality. J Public Health (Oxf). 2005;27(3):281–91. PMID: 15870099.CrossRefGoogle Scholar
  34. 34.
    Sudbury-Riley L, FitzPatrick M, Schulz PJ. Exploring the measurement properties of the eHealth Literacy Scale (eHEALS) among baby boomers: a multinational test of measurement invariance. J Med Internet Res. 2017;19(2):e53. PMID: 28242590.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Neter E, Brainin E. Perceived and performed eHealth literacy: survey and simulated performance test. JMIR Hum Factors. 2017;4(1):e2. PMID: 28096068.PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Meillier A, Patel S. Readability of healthcare literature for gastroparesis and evaluation of medical terminology in reading difficulty. Gastroenterology Res. 2017;10(1):1–5. PMID: 28270870.PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Park A, Eckert TL, Zaso MJ, Scott-Sheldon LAJ, Vanable PA, Carey KB, Ewart CK, Carey MP. Associations between health literacy and health behaviors among urban high school students. J Sch Health. 2017;87(12):885–93. PMID: 29096408.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Woudstra AJ, Timmermans DRM, Uiters E, Dekker E, Smets EMA, Fransen MP. Health literacy skills for informed decision making in colorectal cancer screening: perceptions of screening invitees and experts. Health Expect. 2018;21(3):636–46. PMID: 29266661.PubMedCrossRefGoogle Scholar
  39. 39.
    Deniz SS, Ozer O, Songur C. Effect of health literacy on health perception: an application in individuals at age 65 and older. Soc Work Public Health. 2018;32(2):85–95. PMID: 29257934.CrossRefGoogle Scholar
  40. 40.
    Waite MC, Theodoros DG, Russell TG, Cahill LM. Assessment of children’s literacy via an internet-based telehealth system. Telemed J E Health. 2010;16(5):564–75. PMID: 20575724.PubMedCrossRefGoogle Scholar
  41. 41.
    Feng L, Jansche, M, Huenerfauth M, Elhadad N. A comparison of features for automatic readability assessment. In: Proceedings of the 23rd International Conference on Computational Linguistics, Stroudsburg, PA; 2010. p. 276–84.Google Scholar
  42. 42.
    Flesch RF. How to write plain english: a book for lawyers and consumers: with 60 before-and-after translations from legalese. 1st ed. New York: Harpercollins; 1979.Google Scholar
  43. 43.
    Gunning R. The technique of clear writing: Mcgraw-Hill; 1968.Google Scholar
  44. 44.
    McLaughlin GH. SMOG grading: a new readability formula. J Read. 1969;12(8):639–46.Google Scholar
  45. 45.
    Hedman AS. Using the SMOG formula to revise a health-related document. Am J Health Educ. 2008;39(1):61–4.CrossRefGoogle Scholar
  46. 46.
    Fitzsimmons PR, Michael BD, Hulley JL, Scott GO. A readability assessment of online Parkinson’s disease information. J R Coll Physicians Edinb. 2010;40(4):292–6. PMID: 21132132.PubMedCrossRefGoogle Scholar
  47. 47.
    ThoughtCo. Content and Function Words. 2017.
  48. 48.
    Beare K. Content and function words. Accessed 2 Aug 2018.
  49. 49.
    Razon A, Barnden J. A new approach to automated text readability classification based on concept indexing with integrated part-of-speech n-gram features. In: Proceedings of the International Conference Recent Advances in Natural Language Processing Hissar, Bulgaria INCOMA Ltd. Shoumen, Bulgaria. 2015. p. 521–528.Google Scholar
  50. 50.
    Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 2004;32(Database issue):D267–70. PMID: 14681409.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Sperzel WD, Tuttle MS, Olson NE, Erlbaum MS, Saurez-Munist O, Sherertz DD, Fuller LF. The Meta-1.2 engine: a refined strategy for linking biomedical vocabularies. Proc Annu Symp Comput Appl Med Care. 1992:304–8. PMID: 1482887.Google Scholar
  52. 52.
    Schuyler PL, Hole WT, Tuttle MS, Sherertz DD. The UMLS metathesaurus: representing different views of biomedical concepts. Bull Med Libr Assoc. 1993;81(2):217–22. PMID: 8472007.PubMedPubMedCentralGoogle Scholar
  53. 53.
    McCray AT, Nelson SJ. The representation of meaning in the UMLS. Methods Inf Med. 1995;34(1–2):193–201. PMID: 9082131.PubMedGoogle Scholar
  54. 54.
    Leroy G, Helmreich S, Cowie JR, Miller T, Zheng W. Evaluating online health information: beyond readability formulas. AMIA Annu Symp Proc. 2008;2008:394–8. PMID: 18998902.PubMedCentralGoogle Scholar
  55. 55.
    Roberts K, Demner-Fushman D. Interactive use of online health resources: a comparison of consumer and professional questions. J Am Med Inform Assoc. 2016;23(4):802–11. PMID: 27147494.PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Zeng Q, Kogan S, Ash N, Greenes RA. Patient and clinician vocabulary: how different are they? Stud Health Technol Inform. 2001;84(Pt 1):399–403. PMID: 11604772.PubMedGoogle Scholar
  57. 57.
    Plovnick RM, Zeng QT. Reformulation of consumer health queries with professional terminology: a pilot study. J Med Internet Res. 2004;6(3):e27. PMID: 15471753.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Park M, He Z, Chen Z, Oh S, Bian J. Consumer’s use of UMLS concepts on social media: diabetes-related textual data analysis in blog and social Q&A sites. JMIR Med Inform. 2016;4(4):e41.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Yu B, He Z, editors. Exploratory textual analysis of consumer health languages for people who are D/deaf and hard of hearing. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM); 13–16 Nov 2017; Kansas City, MO. IEEE; 2017.Google Scholar
  60. 60.
    Messai R, Simonet M, Bricon-Souf N, Mousseau M. Characterizing consumer health terminology in the breast cancer field. Stud Health Technol Inform. 2010;160(1):991–4.PubMedGoogle Scholar
  61. 61.
    Smith CA, Stavri PZ, Chapman WW. In their own words? A terminological analysis of e-mail to a cancer information service. Proc AMIA Symp. 2002:697–701. PMID: 12463914.Google Scholar
  62. 62.
    Brennan PF, Aronson AR. Towards linking patients and clinical information: detecting UMLS concepts in e-mail. J Biomed Inform. 2003;36(4-5):334–41. PMID: 14643729.PubMedCrossRefGoogle Scholar
  63. 63.
    Agrawal A, He Z, Perl Y, Wei D, Halper M, Elhanan G, Chen Y. The readiness of SNOMED problem list concepts for meaningful use of electronic health records. Artif Intell Med. 2013;58(2):73–80. PMID: 23602702.PubMedCrossRefGoogle Scholar
  64. 64.
    Matney SA, Warren JJ, Evans JL, Kim TY, Coenen A, Auld VA. Development of the nursing problem list subset of SNOMED CT(R). J Biomed Inform. 2012;45(4):683–8. PMID: 22202620.PubMedCrossRefGoogle Scholar
  65. 65.
    Rector A, Qamar R, Marley T. Binding ontologies and coding systems to electronic health records and messages. Appl Ontol. 2009;4(1):51–69.Google Scholar
  66. 66.
    Finnegan R. ICD-9-CM coding for physician billing. J Am Med Rec Assoc. 1989;60(2):22–3. PMID: 10303229.PubMedGoogle Scholar
  67. 67.
    Bodenreider O. Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb Med Inform. 2008:67–79. PMID: 18660879.CrossRefGoogle Scholar
  68. 68.
  69. 69.
  70. 70.
    Zeng QT, Tse T. Exploring and developing consumer health vocabularies. J Am Med Inform Assoc. 2006;13(1):24–9. PMID: 16221948.PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med. 1998;37(4-5):394–403. PMID: 9865037.PubMedPubMedCentralGoogle Scholar
  72. 72.
    Cimino JJ. High-quality, standard, controlled healthcare terminologies come of age. Methods Inf Med. 2011;50(2):101–4. PMID: 21416108.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Arts DG, Cornet R, de Jonge E, de Keizer NF. Methods for evaluation of medical terminological systems—a literature review and a case study. Methods Inf Med. 2005;44(5):616–25. PMID: 16400369.PubMedCrossRefGoogle Scholar
  74. 74.
    Greenberg J. Metadata and the World Wide Web. Encyclopedia of Library and Information Science. New York, NY: Marcel Dekker. p. 1876–88.Google Scholar
  75. 75.
    Mathes A. Folksonomies—cooperative classification and communication through shared metadata. Comput Med Commun. 2004;47(10).Google Scholar
  76. 76.
    Zeng QT, Tse T, Divita G, Keselman A, Crowell J, Browne AC, Goryachev S, Ngo L. Term identification methods for consumer health vocabulary development. J Med Internet Res. 2007;9(1):e4. PMID: 17478413.PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Apelon. Consumer Health Vocabulary of Apelon. 2018. Data Sheet.pdf.
  78. 78.
    Wu DT, Hanauer DA, Mei Q, Clark PM, An LC, Proulx J, Zeng QT, Vydiswaran VG, Collins-Thompson K, Zheng K. Assessing the readability of J Am Med Inform Assoc. 2016;23(2):269–75. PMID: 26269536.PubMedCrossRefGoogle Scholar
  79. 79.
    Ibrahim AM, Vargas CR, Koolen PG, Chuang DJ, Lin SJ, Lee BT. Readability of online patient resources for melanoma. Melanoma Res. 2016;26(1):58–65. PMID: 26479217.PubMedCrossRefGoogle Scholar
  80. 80.
  81. 81.
    MacLean DL, Heer J. Identifying medical terms in patient-authored text: a crowdsourcing-based approach. J Am Med Inform Assoc. 2013;20(6):1120–7. PMID: 23645553.PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Doing-Harris KM, Zeng-Treitler Q. Computer-assisted update of a consumer health vocabulary through mining of social network data. J Med Internet Res. 2011;13(2):e37. PMID: 21586386.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Jiang L, Yang C, editors. Using co-occurrence analysis to expand consumer health vocabularies from social media data. In: Healthcare Informatics (ICHI), 2013 IEEE International Conference on. Philadelphia, PA: IEEE; 2013.Google Scholar
  84. 84.
    Keselman A, Smith CA, Divita G, Kim H, Browne AC, Leroy G, Zeng-Treitler Q. Consumer health concepts that do not map to the UMLS: where do they fit? J Am Med Inform Assoc. 2008;15(4):496–505. PMID: 18436906.PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Vydiswaran VG, Mei Q, Hanauer DA, Zheng K. Mining consumer health vocabulary from community-generated text. AMIA Annu Symp Proc. 2014;2014:1150–9. PMID: 25954426.PubMedPubMedCentralGoogle Scholar
  86. 86.
    He Z, Chen Z, Oh S, Hou J, Bian J. Enriching consumer health vocabulary through mining a social Q&A site: a similarity-based approach. J Biomed Inform. 2017;69:75–85. PMID: 28359728.PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Chen J, Yu H. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients. J Biomed Inform. 2017;68:121–31. PMID: 28267590.PubMedPubMedCentralCrossRefGoogle Scholar
  88. 88.
    Chen J, Jagannatha AN, Fodeh SJ, Yu H. Ranking medical terms to support expansion of lay language resources for patient comprehension of electronic health record notes: adapted distant supervision approach. JMIR Med Inform. 2017;5(4):e42. PMID: 29089288.PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    Tartir S, Arpinar IB, Sheth AP. Ontological evaluation and validation. In: Poli R, Healy M, Kameas A, editors. Theory and applications of ontology: computer applications. Dordrecht: Springer; 2010.Google Scholar
  90. 90.
    Vrandecic D. Ontology evaluation. In: Staab S, Studer R, editors. Handbook on ontologies. 2nd ed. Berlin, Heidelberg: Springer; 2009. p. 293–313.CrossRefGoogle Scholar
  91. 91.
    Kamdar MR, Tudorache T, Musen MA. A systematic analysis of term reuse and term overlap across biomedical ontologies. Semantic Web. 2017;8(6):853–71.PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Zeng-Treitler Q, Goryachev S, Kim H, Keselman A, Rosendale D. Making texts in electronic health records comprehensible to consumers: a prototype translator. AMIA Annu Symp Proc. 2007:846–50. PMID: 18693956.Google Scholar
  93. 93.
    Qenam B, Kim TY, Carroll MJ, Hogarth M. Text simplification using consumer health vocabulary to generate patient-centered radiology reporting: translation and evaluation. J Med Internet Res. 2017;19(12):e417. PMID: 29254915.PubMedPubMedCentralCrossRefGoogle Scholar
  94. 94.
    Goldberg L, Lide B, Lowry S, Massett HA, O’Connell T, Preece J, Quesenbery W, Shneiderman B. Usability and accessibility in consumer health informatics current trends and future challenges. Am J Prev Med. 2011;40(5 Suppl 2):S187–97. PMID: 21521594.PubMedCrossRefGoogle Scholar
  95. 95.
    Quesenbery W. Dimensions of usability. In: Albers M, Mazur B, editors. Content and complexity: information design in technical communication. Mahwah, NJ: Erlbaum; 2003.Google Scholar
  96. 96.
    Adlin T, Pruitt J. The persona lifecycle: Morgan-Kaufmann; 2006.Google Scholar
  97. 97.
    Shneiderman B, Plaisant C. Designing the user interface: strategies for effective human–computer interaction. 5th ed. Boston MA: Addison-Wesley; 2009.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of InformationFlorida State UniversityTallahasseeUSA

Personalised recommendations