Literacy Demands and Information to Cancer Patients

  • Dimitrios Kokkinakis
  • Markus Forsberg
  • Sofie Johansson Kokkinakis
  • Frida Smith
  • Joakim Öhlen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7499)


This study examines language complexity of written health information materials for patients undergoing colorectal cancer surgery. Written and printed patient information from 28 Swedish clinics are automatically analyzed by means of language technology. The analysis reveals different problematic issues that might have impact on readability. The study is a first step, and part of a larger project about patients’ health information seeking behavior in relation to written information material. Our study aims to provide support for producing more individualized, person centered information materials according to preferences for complex and detailed or legible texts and thus enhance a movement from receiving information and instructions to participating in knowing. In the near future the study will continue by integrating focus groups with patients that may provide valuable feedback and enhance our knowledge about patients’ use and preferences of different information material.


Health literacy Readability Natural Language Processing 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mishel, M.H., Clayton, M.F.: Uncertainty in Illness Theory. In: Smith, M.J., Liehr, P. (eds.) Middle Range Theory for Nursing. Spring Publications (2003)Google Scholar
  2. 2.
    Shieh, C., Hosei, B.: Printed Health Information Materials: Evaluation of Readability and Suitability. J. Community Health Nurs. 25(2), 73–90 (2008)CrossRefGoogle Scholar
  3. 3.
    Weintraub, D., et al.: Suitability of prostate cancer education materials: applying a standardized assessment tool to currently available materials. J PatEduCouns 55(2), 275–280 (2004)Google Scholar
  4. 4.
    Weert, J.C., et al.: Tailored information for cancer patients on the Internet: Effects of visual cues and language complexity on information recall & satisfaction. J. PatEduCouns (2011)Google Scholar
  5. 5.
    Helitzer, D., et al.: Health literacy demands of written health information materials: an assessment of cervical cancer prevention materials. Cancer Control 16(1), 70–78 (2009)Google Scholar
  6. 6.
    Doak, C.C., Doak, L.G., Root, J.H.: Assessing Suitability of Materials. In: Teaching Patients with Low Literacy Skills. Lippincott Williams & Wilkins (1996)Google Scholar
  7. 7.
    Ownby, R.L.: Influence of vocabulary & sentence complexity & passive voice on the readability of consumer-oriented mental health info on the internet. In: AMIA Symp., pp. 585–588 (2005)Google Scholar
  8. 8.
    Hack, T.F., Degner, L.F., Parker, P.A.: The communication goals and needs of cancer patients: a review. Psychooncology 14(10), 831–845 (2005)CrossRefGoogle Scholar
  9. 9.
    Leroy, G., Eryilmaz, E., Laroya, B.T.: Health Information Text Characteristics. In: AMIA Symp., pp. 479–483 (2006)Google Scholar
  10. 10.
    Leroy, G., Helmreich, S., Cowie, J.R., Miller, T., Zheng, W.: Evaluating Online Health Information: Beyond Readability Formulas. In: AMIA Symp., pp. 394–398 (2008)Google Scholar
  11. 11.
    Heilman, M., et al.: Combining Lexical and Grammatical Features to Improve Readability Measures for 1st and 2nd Language Texts. In: HLT-NAACL, Rochester, NY, pp. 460–467 (2007)Google Scholar
  12. 12.
    Barzilay, R., Lapata, M.: Modeling local coherence: an entity-based approach. In: 43rd Annual Meeting on Association for Comp. Ling, USA, pp. 141–148 (2005)Google Scholar
  13. 13.
    Borin, L., et al.: Empowering the patient with language technology. SemanticMining NoE 507505: D27.2 (2007),
  14. 14.
    Kokkinakis, D., Johansson Kokkinakis, S.: A Cascaded Finite-State Parser for Syntactic Analysis of Swedish. In: The 9th EACL, Norway, pp. 245–248 (1999)Google Scholar
  15. 15.
    Björnsson, C.-H.: Läsbarhet. Stockholm. Liber (1968)Google Scholar
  16. 16.
    Laufer, B., Nation, P.: Vocabulary size and use: Lexical richness in L2 written production. Applied Linguistics 16(3), 307–329 (1995)CrossRefGoogle Scholar
  17. 17.
    Mühlenbock, K., Johansson Kokkinakis, S.: LIX 68 revisited – An extended readability measure. Corpus Linguistics. U. of Liverpool, UK (2009)Google Scholar
  18. 18.
    Johansson Kokkinakis, S., Magnusson, U.: Computer based quantitative methods applied to 1st & 2nd language student writing. In: Göteborgsstudier i nordisk spräakvet, GNS (2011)Google Scholar
  19. 19.
    Melin, L., Lange, S.: Att analysera text. Studentlitteratur AB (2000) (in Swedish)Google Scholar
  20. 20.
    Miller, T., Leroy, G.: Dynamic generation of a Health Topics Overview from consumer health information documents. J. Biomed. Eng. and Tech. 1(4), 395–414 (2008)CrossRefGoogle Scholar
  21. 21.
    Oosten, P., Tanghe, D., Hoste, V.: Towards an Improved Methodology for Automated Readability Prediction. In: Conf. on Lang. Resources and Eval., LREC, Malta, pp. 775–782 (2010)Google Scholar
  22. 22.
    Lustria, M.L., et al.: Computer-tailored health interventions delivered over the web: Review and analysis of key components. Patient Edu. and Counseling 74(2), 156–173 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dimitrios Kokkinakis
    • 1
  • Markus Forsberg
    • 1
  • Sofie Johansson Kokkinakis
    • 1
  • Frida Smith
    • 1
  • Joakim Öhlen
    • 1
  1. 1.University of GothenburgGothenburgSweden

Personalised recommendations