Age-Related Differences in a Usability Study Measuring Accuracy, Efficiency, and User Satisfaction in Using Smartphones for Census Enumeration: Fiction or Reality?

  • Erica Olmsted-Hawala
  • Temika Holland
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9193)


Age-related differences were investigated in a usability study of an application developed for U.S. Census Bureau enumerators to collect survey data and automate their time and expenses. Accuracy, efficiency and satisfaction measures were collected as participants used a smartphone to answer typical tasks. Usability flaws were also identified with the application. Results indicate that in general there were no differences with task accuracy and efficiency when comparing all tasks, however when looking at individual tasks, the task that had the most usability flaws also revealed age-related differences for accuracy and efficiency – that is older adults were less accurate and took longer to complete. Surprisingly, there were age-related differences with the user satisfaction of the application such that older adults were less satisfied with the application than younger adults. Tying age-related differences to usability flaws highlights the importance of designing optimal applications for all users.


Usability Accuracy Efficiency Satisfaction Age-related differences NRFU Census bureau 


  1. 1.
    US Census Bureau: Internal Census Report on Age Range of Enumerators. Field Division. (2010)Google Scholar
  2. 2.
    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
  3. 3.
    Johnson, R., Kent, S.: Designing universal access: web application for the elderly and disabled. Cogn. Tech. Work 9, 209–218 (2007)CrossRefGoogle Scholar
  4. 4.
    Loos, E.F., Mante-Meijer, E.A.: Navigatie van ouderen en jongeren in beeld. Explorerend onderzoek naar de rol van leeftijd voor het informatiezoekgedrag van websitegebruikers [Older and younger adults’ navigation: Explorative study on the role of age for website users’ information search behaviour], Den Haag, Boom/Lemma (2009)Google Scholar
  5. 5.
    Loos, E.: In search of information on websites: a question of age? In: Stephanidis, C. (ed.) Universal Access in HCI, Part II, HCII 2011. LNCS, vol. 6766, pp. 196–204. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Loos, E.F., Bergstrom, J.R.: Older adults. In: Bergstrom, J.R., Schall, A.J. (eds.) Eye Tracking in User Experience Design, pp. 313–329. Elsevier, Amsterdam (2014)CrossRefGoogle Scholar
  7. 7.
    Brébion, G.: Language processing, slowing, and speed/accuracy trade-off in the elderly. Exp. Aging Res. 27(2), 137–150 (2001)CrossRefGoogle Scholar
  8. 8.
    Howard, J.H., Howard, D.V., Dennis, N.A., Yankovich, H.: Event timing and age deficits in higher-order sequence learning. Aging, Neuropsychol. Cogn. 14(6), 647–668 (2007)CrossRefGoogle Scholar
  9. 9.
    Rabbitt, P.: How old and young subjects monitor and control responses for accuracy and speed. Br. J. Psychol. 70, 305–311 (1979)CrossRefGoogle Scholar
  10. 10.
    Salthouse, T.: Adult age and the speed–accuracy trade-off. Ergonomics 22(7), 811–821 (1979)CrossRefGoogle Scholar
  11. 11.
    Bergstrom, J.R., Olmsted-Hawala, E., Jans, M.: Eye tracking and Web site usability in older adults: age-related differences in eye tracking and usability performance: web site usability for older adults. Int. J. Hum. Comput. Interact. 29(8), 541–548 (2013)CrossRefGoogle Scholar
  12. 12.
    Olmsted-Hawala, E., Bergstrom, J.R.: Think-aloud protocols: does age make a difference? In: Proceedings of Society for Technical Communication (STC) Summit, Chicago, IL (2012)Google Scholar
  13. 13.
    Chin, J.P., Diehl, V.A., Norman, K.L.: Development of an instrument measuring user satisfaction of the human-computer interface. In: Proceedings of SIGCHI 1988, pp. 213–218 (1988)Google Scholar
  14. 14.
    Olmsted-Hawala, E., Bergstrom, J.R., 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
  15. 15.
    Fukuda, R., Bubb, H.: Eye tracking study on web-use: comparison between younger and elderly users in case of search task with electronic timetable service. PsychNology J. 1(3), 202–288 (2003)Google Scholar
  16. 16.
    Bashore, T.R., Ridderinkhof, K.R., Molen, M.W.V.D.: The decline of cognitive processing speed in old age. Curr. Dir. Psychol. Sci. 6(6), 163–169 (1997)CrossRefGoogle Scholar
  17. 17.
    Nielsen, J.: Estimating the number of subjects needed for a thinking aloud test. Int. J. Hum. Comput. Stud. 41, 385–397 (1994)CrossRefGoogle Scholar
  18. 18.
    Nielsen, J., Landauer, T.K.: A mathematical model of the finding of usability problems. In: Proceedings of ACM INTERCHI 1993, pp. 206–213 (1993)Google Scholar
  19. 19.
    Hill, R.L., Dickinson, A., Arnott, J.L., Gregor, P., McIver, L.: Older web users’ eye movements: experience counts. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems ACM, pp. 1151–1160 (2011)Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Center for Survey MeasurementU.S. Census BureauWashington DCUSA

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