The Effect of User Factors on Consumer Familiarity with Health Terms: Using Gender as a Proxy for Background Knowledge About Gender-Specific Illnesses

  • Alla Keselman
  • Lisa Massengale
  • Long Ngo
  • Allen Browne
  • Qing Zeng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4345)


An algorithm estimating vocabulary complexity of a consumer health text can help improve readability of consumer health materials. We had previously developed and validated an algorithm predicting lay familiarity with health terms on the basis of the terms’ frequency in consumer health texts and experimental data. Present study is part of the program studying the influence of reader factors on familiarity with health terms and concepts. Using gender as a proxy for background knowledge, the study evaluates male and female participants’ familiarity with terms and concepts pertaining to three types of health topics: male-specific, female-specific and gender-neutral. Of the terms / concepts of equal predicted difficulty, males were more familiar with those pertaining to neutral and male-specific topics (the effect was especially pronounced for “difficult” terms); no topic effect was observed for females. The implications for tailoring health readability formulas to various target populations are discussed.


consumer health informatics readability formulas consumer health vocabularies 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alla Keselman
    • 1
    • 2
  • Lisa Massengale
    • 1
  • Long Ngo
    • 3
  • Allen Browne
    • 1
  • Qing Zeng
    • 4
  1. 1.LHNCBC, National Library of Medicine, NIH, DHHSBethesda
  2. 2.Aquilent, Inc.Laurel
  3. 3.DSG, Brigham and Women’s Hospital, Harvard Medical SchoolBoston
  4. 4.Harvard Medical SchoolDSG, Beth Israel Deaconess Medical CenterBoston

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