Abstract
Research has shown that older adults take more time to perform tasks and have higher satisfaction than younger adults for a variety of activities. Through a series of controlled experiments at the U.S. Census Bureau, we confirm that older adults do take longer to complete surveys on smartphones, but the increase in satisfaction compared to younger adults is only marginally significant. In these experiments, we also found that the age effects do not vary by the smartphone survey designs tested, suggesting that designers could focus on improving designs for older adults and younger adults would benefit from those changes.
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References
Craik, F.I.M., Salthouse, T.A.: The Handbook of Aging and Cognition, 3rd edn. Psychology Press, NewYork (2008)
Hofer, S.M., Alwin, D.F.: Handbook of Cognitive Aging: Interdisciplinary Perspectives. SAGE Publications Inc., Thousand Oaks (2008). https://doi.org/10.4135/9781412976589
Karlamangla, A.S., Miller-Martinez, D., Aneshensel, C.S., Seeman, T.E., Wight, R.G., Chodosh, J.: Trajectories of cognitive function in late life in the United States: demographic and socioeconomic predictors. Am. J. Epidemiol. 170, 331–342 (2009). https://doi.org/10.1093/aje/kwp154
Bashore, T.R., Osman, A., Heffley III, E.F.: Mental slowing in elderly persons: a cognitive psychophysiological analysis. Psychol. Aging 4(2), 235–244 (1989). https://doi.org/10.1037//0882-7974.4.2.235
Salthouse, T.: When does age-related cognitive decline begin? Neurobiol. Aging 30(4), 507–514 (2009)
Hultsch, D.F., Hertzog, C., Dixon, R.A.: Ability correlates of memory performance in adulthood and aging. Psychol. Aging 5(3), 356–368 (1990). https://doi.org/10.1037/0882-7974.5.3.356
Kester, J.D., Benjamin, A.S., Castel, A.D., Craik, F.I.M.: Memory in elderly people. In: Baddely, A.D., Kopelman, M.D., Wilson, B.A. (eds.) The Handbook of Memory Disorders, pp. 543–568. Wiley (2002)
Zhang, H., Eppes, A., Diaz, M.T.: Task difficulty modulates age-related differences in the behavioral and neural bases of language production. Neuropsychologia 124, 254–273 (2019)
Head, D., Isom, M.: Age effects on wayfinding and route learning skills. Behav. Brain Res. 209(1), 49–58 (2010)
Tun, P.A., Lachman, M.E.: Age differences in reaction time and attention in a national telephone sample of adults: education, sex, and task complexity matter. Dev. Psychol. 44(5), 1421–1429 (2008)
Murata, A., Iwase, M.: Usability of touch-panel interfaces for older adults. Hum. Fact. 47(4), 767–776 (2005)
Sultana, A., Moffatt, K.: Effects of aging on small target selection with touch input. ACM Trans. Access. Comput. 12(1), 1–35 (2019)
Findlater, L., Froehlich, J.E., Fattal, K., Wobbrock, J.O., Tanya Dastyar, T.: Age-related differences in performance with touchscreens compared to traditional mouse input. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2013), pp. 343–346. ACM, New York (2013)
Wood, E., Willoughby, T., Rushing, A., Bechtel, L., Gilbert, J.: Use of computer input devices by older adults. J. Appl. Gerontol. 24(5), 419–438 (2005)
Jin, Z.X., Plocher, T., Kiff, L.: Touch screen user interfaces for older adults: button size and spacing. In: UAHCI 2007 Proceedings of the 4th International Conference on Universal Access in Human Computer Interaction: Coping with Diversity, pp. 933–941 (2007)
Loos, E.F., Romano Bergstrom, J.: Older adults. In: Romano Bergstrom, J., Schall, A.J. (eds.) Eye Tracking in User Experience Design, Elsevier, Amsterdam, pp. 313–329 (2014)
Al-Showarah, S., AL-Jawad, N., Sellahewa, H.: Effects of user age on smartphone and tablet use, measured with an eye-tracker via fixation duration, scan-path duration, and saccades proportion. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2014. LNCS, vol. 8514, pp. 3–14. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07440-5_1
Grewal, S., Sahni, R.K.: Effect of smartphone addiction on reaction time in geriatric population. J. Novel Physiotherapy Phys. Rehabil. 6(1), 005–009 (2019)
Xiong, J., Muraki, S.: Thumb performance of elderly users on smartphone touchscreen. SpringerPlus 5(1), 1218 (2016)
Kennedy, Q., Mather, M., Carstensen, L.L.: The role of motivation in the age-related positivety effect in autobiographical memory. Psychol. Sci. 15, 208–214 (2004)
Carstensen, L.L.: Integrating cognitive and emotion paradigms to address the paradox of aging. Cogn. Emot. 33(1), 119–125 (2018)
Reed, A.E., Chan, L., Mikels, J.A.: Meta-analysis of the age-related positivity effect: age differences in preferences for positive over negative information. Psychol. Aging 29(1), 1–15 (2014)
Sasse, L.K., Gamer, M., Büchel, C., Brassen, S.: Selective control of attention supports the positivity effect in aging. PLoS One 9(8) (2014)
Mikels, J.A., Larkin, G.R., Reuter-Lorenz, P.A., Carstensen, L.L.: Divergent trajectories in the aging mind: changes in working memory for affective versus visual information with age. Psychol. Aging 20(4), 542–553 (2005)
Mammarella, N., Di Domenico, A., Palumbo, R., Fairfield, B.: When green is positive and red is negative: aging and the influence of color on emotional memories. Psychol. Aging 31(8), 914–926 (2016)
Schryer, E., Ross, M.: Does the age-related positivity effect in autobiographical recall reflect differences in appraisal or memory? J. Gerontol. Ser. B: Psychol. Sci. Soc. Sci. 69(4), 548–556 (2014)
Nichols, E., Olmsted-Hawala, E., Wang, L.: Optimal designs of text input fields in mobile web surveys for older adults. In: Zhou, J., Salvendy, G. (eds.) HCII 2019. LNCS, vol. 11592, pp. 463–481. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22012-9_34
Olmsted-Hawala, E., Nichols, E., Falcone, B., Figueroa, I.J., Antoun, C., Wang, L.: Optimal data entry designs in mobile web surveys for older adults. In: Zhou, J., Salvendy, G. (eds.) ITAP 2018. LNCS, vol. 10926, pp. 335–354. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92034-4_26
Wang, L., et al.: Experimentation for developing evidence-based UI standards of mobile survey questionnaires. In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2998–3004, Colorado. ACM Press (2017)
Hughes, M., Agrigoroaei, S., Jeon, M., Bruzzese, M., Lachman, M.: Change in cognitive performance from midlife into old age: findings from the midlife in the United States (MIDUS) study – erratum. J. Int. Neuropsychol. Soc. 24(8), 891 (2018)
Acknowledgements
The study was supported by the U.S. Census Bureau’s Innovation and Operational Efficiency Program. We thank Russell Sanders, Christopher Antoun, Brian Falcone, Ivonne Figueroa, Alda Rivas, Joanna Lineback, Sabin Lakhe, Kevin Younes, and the MetroStar team. We also thank Eugene Loos, Jenny Childs, Thomas Mathew, Shaun Genter, Paul Beatty, and Joanne Pascale for reviews of the paper.
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Nichols, E., Olmsted-Hawala, E., Raim, A., Wang, L. (2020). Attitudinal and Behavioral Differences Between Older and Younger Adults Using Mobile Devices. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Technologies, Design and User Experience. HCII 2020. Lecture Notes in Computer Science(), vol 12207. Springer, Cham. https://doi.org/10.1007/978-3-030-50252-2_25
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DOI: https://doi.org/10.1007/978-3-030-50252-2_25
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