Processing Speed and Vocabulary are Related to Older Adults’ Internet Experiences

  • Jennifer Romano BergstromEmail author
  • Erica Olmsted-Hawala
  • Wendy A. Rogers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9193)


Some cognitive declines commonly occur with aging; yet they are seldom taken into account by Website designers and User Experience (UX) researchers. In this empirical study, we compared younger adults, middle-age adults, high-functioning older adults, and low-functioning older adults to examine whether there is a relationship between aspects of cognition and performance when using a Website. Performance was measured by accuracy (percent of tasks completed successfully), efficiency (mean time to complete tasks) and self-rated satisfaction, three commonly used usability metrics. Results suggest that processing speed and vocabulary may be related to Internet performance. Specifically, older adults with faster processing speed and/or high vocabulary may perform better than their lower-functioning counterparts. More importantly, these older adults perform similar to younger adults.


Usability Cognition Aging Computers Internet Technology 


  1. 1.
    O’Connell, T.A.: The why and how of senior-focused design. In: Lazar, J. (ed.) Universal Usability: Designing Computer Interfaces for Diverse Users, pp. 43–92. Wiley, West Sussex (2007)Google Scholar
  2. 2.
    Pew Internet & American Life Project (2009).
  3. 3.
    US Census Bureau: Computer and Internet Use in the United States: 2003 (2005).
  4. 4.
    US Census Bureau: Reported Internet Usage for Households, by Selected Householder Characteristics: 2009. Source: Current Population Survey, US Census Bureau (2010)Google Scholar
  5. 5.
    US Census Bureau: Computer and Internet Use in the United States: 2010 (2010).
  6. 6.
    Ball, K.K., Beard, B.L., Roenker, D.L., Miller, R.L., Griggs, D.S.: Age and visual search: expanding the useful field of view. J. Opt. Soc. Am. 5, 2210–2219 (1988)CrossRefGoogle Scholar
  7. 7.
    Birren, J.E., Shaie, K.W.: Handbook of the Psychology of Aging. Elsevier, Burlington (2006)Google Scholar
  8. 8.
    Craik, F.I.M., Salthouse, T.A.: The Handbook of Aging and Cognition. Lawrence Erlbaum Associates, Mahwah (2000)Google Scholar
  9. 9.
    Fisk, A.D., Rogers, W.A.: Handbook of Human Factors and the Older Adult. Academic Press, San Diego (1997)Google Scholar
  10. 10.
    Fisk, A.D., Rogers, W.A., Charness, N., Czaja, S.J., Sharit, J.: Designing for Older Adults: Principles and Creative Human Factors Approaches, 2nd edn. CRC Press, Boca Raton (2009)CrossRefGoogle Scholar
  11. 11.
    Park, D., Schwarz, N.: Cognitive Aging: A Primer, 2nd edn. Psychology Press, Philadelphia (2008)Google Scholar
  12. 12.
    Loos, E., Romano Bergstrom, J.C.: Older adults. In: Romano Bergstrom, J., Schall, A. (eds.) Eye Tracking in User Experience Design. Morgan Kaufmann, San Francisco (2014)Google Scholar
  13. 13.
    Pernice, K., Nielsen, J.: Web Usability for Senior Citizens. Design Guidelines Based on Usability Studies with People Age 65 and Older. Nielsen Norman Group, Fremont (2002)Google Scholar
  14. 14.
    Rogers, W.A., Badre, A.: The Web user: Older adults. In: Badre, A. (ed.) Shaping Web Usability: Interaction Design in Context, pp. 91–108. Addison-Wesley, Boston (2002)Google Scholar
  15. 15.
    Van Deursen, A., Van Dijk, J.: Measuring digital skills. Performance tests of operational, formal, information and strategic internet skills among the Dutch population. Presented at the ICA Conference, Montreal, Canada (2008)Google Scholar
  16. 16.
    Nichols, T.A., Rogers, W.A., Fisk, A.D.: Do you know how old your participants are? recognizing the importance of participant age classifications. Ergon. Des. 11, 22–26 (2003)Google Scholar
  17. 17.
    Czaja, S.J., Charness, N., Fisk, A.D., Hertzog, C., Nair, S.N., Rogers, W.A., Sharit, J.: Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychol. Aging 21, 333–352 (2006)CrossRefGoogle Scholar
  18. 18.
    Frøkjaer, E., Herzum, M., Hornbaek, K.: Measuring usability: are effectiveness, efficiency, and satisfaction correlated? In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, The Haag (2000)Google Scholar
  19. 19.
    Wechsler, D.: Wechsler Adult Intelligence Scale: (WAIS-III), 3rd edn. The Psychological Corporation, New York (1997)Google Scholar
  20. 20.
    Shipley, W.: Shipley Institute of Living Scale. Western Psychological Press, Los Angeles (1986)Google Scholar
  21. 21.
    Olmsted-Hawala, E., Romano Bergstrom, J.: Think-aloud protocols: does age make a difference? In: Proceedings of Society for Technical Communication (STC) Summit, Chicago, IL, May 2012Google Scholar
  22. 22.
    Grahame, M., Laberge, J., Sciafla, C.T.: Age differences in search of Web pages: The effects of link size, link number, and clutter. Hum. Factors J. Hum. Factors Ergon. Soc. 46(3), 385–398 (2004)CrossRefGoogle Scholar
  23. 23.
    Romano Bergstrom, J., Olmsted-Hawala, E., Jans, M.: Eye tracking and website usability in older adults: age-related differences in eye tracking and usability performance: website usability for older adults. Int. J. Hum.-Comput. Interact. 29(8), 541–548 (2013)CrossRefGoogle Scholar
  24. 24.
    Stronge, A.J., Rogers, W.A., Fisk, A.D.: Web-based information search and retrieval effects of strategy use and age on search success. Hum. Factors 48, 443–446 (2006)CrossRefGoogle Scholar
  25. 25.
    Salthouse, T.: When does age-related cognitive decline begin? Neurobiol. Aging 30(4), 507–514 (2009)CrossRefGoogle Scholar
  26. 26.
    Olmsted-Hawala, E., Romano Bergstrom, J.C., Rogers, W.A.: Age-related differences in search strategy and performance when using a data-rich web site. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2013, Part II. LNCS, vol. 8010, pp. 201–210. Springer, Heidelberg (2013)Google Scholar
  27. 27.
    Olmsted-Hawala, E., Holland, T.: Age related differences when using smartphones for Census enumeration. In: Zhou, J., Salvendy, G. (eds.) HCII 2015. LNCS, vol. 9193, pp. 475–483. Springer, Heidelberg (2015)Google Scholar

Copyright information

© International Copyright, 2015, U.S. Department of Commerce, U.S. Government 2015

Authors and Affiliations

  • Jennifer Romano Bergstrom
    • 1
    Email author
  • Erica Olmsted-Hawala
    • 2
  • Wendy A. Rogers
    • 3
  1. 1.FacebookMenlo ParkUSA
  2. 2.Center for Survey MeasurementU.S. Census BureauWashington, DCUSA
  3. 3.School of PsychologyGeorgia Institute of TechnologyAtlantaUSA

Personalised recommendations