Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-24T04:49:23.224Z Has data issue: false hasContentIssue false
  • English
  • Français

The effects of ageing and website ergonomic quality on internet information searching

Published online by Cambridge University Press:  15 May 2012

ALINE CHEVALIER ,
AURÉLIE DOMMES  and
DANIEL MARTINS
ALINE CHEVALIER*
Affiliation:
Cognition, Ergonomics and Language Research Laboratory, University of Toulouse, Toulouse, France. Department of Psychology, Paris-Ouest University, Nanterre, France.
AURÉLIE DOMMES
Affiliation:
Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux, Versailles, France.
DANIEL MARTINS
Affiliation:
Department of Psychology, Paris-Ouest University, Nanterre, France.
*
Address for correspondence: Aline Chevalier, Laboratoire CLLE-LTC, Université Toulouse Le Mirail, Maison de la Recherche, 5 allées Antonio Machado, F-31058 Toulouse Cedex 9, France. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Since the 1990s, the number of websites and web users, especially older users, has increased extensively. Despite the rapid growth in the number of websites, a significant number of ergonomic violations still hinder the information search activity performed by web users. As ageing is associated with reduced working memory capacity, inhibition failure, slowing of processing speed and more generally impaired executive functioning, older adult web users may experience difficulties while searching for information, especially when the website includes ergonomic violations, such as usability and accessibility violations. In this experiment, the navigation activities of younger and older web users were compared while they were searching for information on a website that met ergonomic guidelines and on a website that included ergonomic violations. The participants then performed a free, delayed-recall task to assess their mental representation of the website they had just navigated. The main findings showed that ageing had a negative impact on search performance but few effects on mental representation built by participants. On the contrary, the ergonomic quality of the website had an impact on search performance and mental representation built by the participants.

Keywords

ageingergonomicsinformation searchingmental representationwebsite
Type
Articles
Information
Ageing & Society , Volume 33 , Issue 6 , August 2013 , pp. 1009 - 1035
Copyright
Copyright © Cambridge University Press 2012 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, J. R., Matessa, M. and Lebiere, C. 1998. The visual interface. In Anderson, J.R. and Lebiere, C. (eds), The Atomic Components of Thought. Lawrence Erlbaum Associates, Mahwah, New Jersey, 143–68.Google Scholar
Aula, A. 2005. User study on older adults’ use of Web and search engines. Universal Access in the Information Society, 4, 1/2, 67–81.Google Scholar
Bastien, C., Scapin, D. and Leulier, C. 1999. The ergonomic criteria and the ISO/DIS 9241–10 dialogue principles: a pilot comparison in an evaluation task. Interacting with Computers, 11, 3, 299–322.Google Scholar
Becker, S. A. 2005. A study of web usability for older adults seeking online health resources. ACM Transactions on Computer Human Interaction, 11, 4, 387–406.Google Scholar
Blackmon, M. H., Polson, P. G., Kitajima, M. and Lewis, C. 2002. Cognitive Walkthrough for the Web. CHI Letters, 4, 463–70.Google Scholar
Bonnardel, N. and Piolat, A. 2003. Design activities: how to analyze cognitive effort associated to cognitive treatments? The International Journal of Cognitive Technology, 8, 1, 6–15.Google Scholar
Cegarra, J. and Chevalier, A. 2008. The use of Tholos software for combining measures of mental workload: towards theoretical and methodological improvements. Behavior Research Methods, 40, 4, 988–1000.CrossRefGoogle Scholar
Chaytor, N. and Schmitter-Edgecombe, M. 2004. Working memory and aging: a cross-sectional and longitudinal analysis using a self-ordered pointing task. Journal of the International Neuropsychological Society, 10, 4, 489–503.Google Scholar
Chevalier, A. and Bonnardel, N. 2007. Articulation of web site design constraints: effects of the task and designers’ expertise. Computers in Human Behavior, 23, 5, 2455–72.Google Scholar
Chevalier, A. and Kicka, M. 2006. Web designers and web users: influence of the ergonomic quality of the web site on the information search. International Journal of Human–Computer Studies, 64, 10, 1031–48.CrossRefGoogle Scholar
Chevalier, A. and Ivory, M. Y. 2003. Web site designs: influence of designer's experience and design constraints. International Journal of Human–Computer Studies, 58, 1, 57–87.Google Scholar
Chin, J., Fu, W.-T. and Kannampallil, T. 2009. Adaptive information search: age-dependent interactions between cognitive profiles and strategies. In Olsen, D. R., Arthur, R. B., Hinckley, K., Morris, M. R., Hudson, S. and Greenberg, S. (eds), Proceedings of the 27th Annual Conference of ACM Computer Human Interaction (CHI) Conference, Boston, Massachusetts. ACM, New York, 1683–92.Google Scholar
Czaja, S. J., Sharit, J., Ownby, R., Roth, D. and Nair, S. 2001. Examining age differences in performance in a complex information search and retrieval task. Psychology and Aging, 16, 4, 564–79.Google Scholar
De Luca, C. R., Wood, S. J., Anderson, V., Buchanan, J.-A., Proffitt, T. M., Mahony, K. and Pantelis, C. 2003. Normative data from the CANTAB. I: Development of executive function over the lifespan. Journal of Clinical and Experimental Neuropsychology, 25, 2, 242–54.Google Scholar
Denney, N. W. and Lennon, M. L. 1972. Classification: a comparison of middle and old age. Developmental Psychology, 7, 2, 210–3.Google Scholar
Denney, N. W., Tozier, T. L. and Schlotthauer, C. A. 1992. The effect of instructions on age differences in practical problem solving. Journals of Gerontology, 47, 3,142–5.Google Scholar
DeStefano, D. and LeFevre, J.-A. 2007. Cognitive load in hypertext reading: a review. Computers in Human Behavior, 23, 3, 1616–41.Google Scholar
Dommes, A., Chevalier, A. and Lia, S. 2011. The role of cognitive flexibility and vocabulary abilities of younger and older users in searching for information on the Web. Applied Cognitive Psychology, 25, 5, 717–26.Google Scholar
Fu, W.-T. and Pirolli, P. 2007. SNIF-ACT: a cognitive model of user navigation on the World Wide Web. Human–Computer Interaction, 22, 4, 355–412.Google Scholar
Grey, S. H. 1990. Using protocol analyses and drawings to study mental model construction during hypertext navigation. International Journal of Human–Computer Interaction, 2, 4, 359–77.Google Scholar
Hanson, V. L. 2010. Influencing technology adoption by older adults. Interacting with Computers, 22, 6, 502–9.CrossRefGoogle Scholar
Hardt, J. H. and Hollis-Sawyer, L. 2007. Older adults seeking healthcare information on the Internet. Educational Gerontology, 33, 7, 561–72.Google Scholar
Hasher, L., Lustig, C. and Zacks, R. T. 2007. Inhibitory mechanisms and the control of attention. In Conway, A., Jarrold, C., Kane, M., Miyake, A. and Towse, J. (eds), Variation in Working Memory. Oxford University Press, New York, 227–49.Google Scholar
Hasher, L. and Zacks, R. T. 1988. Working memory, comprehension, and aging: a review and a new view? In Bower, G. H. (ed.), The Psychology of Learning and Motivation. Academic Press, San Diego, 193–225.Google Scholar
Hong, W., Thong, J. Y. L. and Tam, K. Y. 2004. Designing product listing pages on e-commerce websites: an examination of presentation mode and information format. International Journal of Human–Computer Studies, 61, 4, 481–503.Google Scholar
Hornbæk, K. 2006. Current practice in measuring usability: challenges to usability studies and research. International Journal of Human–Computer Studies, 64, 2, 79–102.Google Scholar
Kellogg, R. T. 1987. Effects of topic knowledge on the allocation of processing time and cognitive effort to writing processes. Memory & Cognition, 15, 3, 256–66.Google Scholar
Kim, J. 2009. Describing and predicting information-seeking behavior on the Web. Journal of the American Society for Information Science and Technology, 60, 4, 679–93.CrossRefGoogle Scholar
Kirakowski, J., Claridge, N. and Whitehand, R. 1998. Human Centered Measures of Success in Web Site Design. In Proceedings of the Human Factors and the Web Workshop, Basking Ridge, AT&T Labs, Basking Ridge, NJ.Google Scholar
Kogan, N. 1974. Categorizing and conceptualizing styles in younger and older adults. Human Development, 17, 3, 218–30.Google Scholar
Kubeck, J. E., Miller-Albrecht, S. A. and Murphy, M. 1999. Finding information on the World Wide Web: exploring older adults’ exploration. Educational Gerontology, 25, 2, 167–83.Google Scholar
Kurniawan, S. H., Ellis, R. D. and Zaphiris, P. 2002. Comparing older and younger adults’ traversal time in expandable and non-expandable hierarchical structures. In Proceedings of the Human Factors and Ergonomics Society Conference. Human Factors and Ergonomics Society, Baltimore, Maryland, 185–8.Google Scholar
Ling, J. and van Schaik, P. 2006. The influence of font type and line length on visual search and information retrieval in web pages. International Journal of Human–Computer Studies, 64, 5, 395–404.Google Scholar
Mata, R. and Nunes, L. 2010. When less is enough: cognitive aging, information search, and decision quality in consumer choice. Psychology and Aging, 25, 2, 289–98.CrossRefGoogle ScholarPubMed
Mata, R., Schooler, L. J. and Rieskamp, J. 2007. The aging decision-maker: cognitive aging and the adaptive selection of decision strategies. Psychology and Aging, 22, 4, 796–810.Google Scholar
Mead, S. E., Batsakes, P., Fisk, A. D. and Mykityshyn, A. 1999. Application of cognitive theory to training and design solutions for age-related computer use. International Journal of Behavioural Development, 23, 3, 553–73.CrossRefGoogle Scholar
Mellor, D., Firth, L. and Moore, K. 2008. Can the Internet improve the well-being of the elderly? Aging International, 32, 1, 25–42.CrossRefGoogle Scholar
McConatha, D., McConatha, J. T. and Dermigny, R. 1994. The use of interactive computer services to enhance the quality of life for long term care residents. Gerontologist, 34, 4, 553–6.Google Scholar
Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., Dijkstra, K., Fisk, A. D., Rogers, W. A. and Sharit, J. 2010. Older adults talk technology: technology usage and attitudes. Computers in Human Behavior, 26, 6, 1710–21.Google Scholar
Morrell, R. W. 2005. The process of construction and revision in the development of a model web site for use by older adults. Universal Access in the Information Society, 4, 1, 24–38.CrossRefGoogle Scholar
Myerson, J., Hale, S., Wagstaff, D., Poon, L. W. and Smith, G. A. 1990. The information-loss model: a mathematical theory of age-related cognitive slowing. Psychological Review, 97, 4, 475–87.Google Scholar
National Institute on Aging 2001. Making Your Web Site Senior Friendly: A Checklist. National Institute on Aging and the National Library of Medicine, Bethesda, MD.Google Scholar
Navarro-Prieto, R., Scaife, M. and Rogers, Y. 1999. Cognitive strategies in web searching. In Proceedings of 5th Conference on Human Factors & the Web. Gaithersburg, Maryland. Available online at http://zing.ncsl.nist.gov/hfweb/proceedings/navarro-prieto/index.html.Google Scholar
Nielsen, J. 2002. E-commerce User Experience. 207 Guidelines for E-commerce Sites. Nielsen Norman Group Report Series.Google Scholar
Nielsen, J. and Loranger, H. 2006. Prioritizing Web Usability. New Riders Press, Berkeley, California.Google Scholar
Norman, D. 1983. Mental Models. Lawrence Erlbaum Associates, Hillsdale, New Jersey.Google Scholar
Otter, M. and Johnson, H. 2000. Lost in hyperspace: metrics and mental models. Interacting with Computers, 13, 1, 1–40.CrossRefGoogle Scholar
Oulasvirta, A. 2004. Task demands and memory in web interaction: a level of processing approach. Interacting with Computers, 16, 2, 217–41.Google Scholar
Pak, R., Czaja, S. J., Sharit, J., Rogers, W. A. and Fisk, A. D. 2008. The role of spatial abilities and age in performance in auditory computer navigation task. Computers in Human Behavior, 24, 6, 3045–51.Google Scholar
Pak, R. and Price, M. M. 2008. Designing an information search interface for younger and older adults. Human Factors, 50, 4, 614–28.Google Scholar
Plude, D. J. and Hoyer, W. J. 1981. Adult age difference in visual search as a function of stimulus mapping and information load. Journal of Gerontology, 36, 5, 598–604.Google Scholar
Rouet, J.-F., Ros, C., Jégou, G. and Metta, S. 2004. Chercher des informations dans les menus web: interaction entre tâche, type de menu et variables individuelles. Le Travail Humain, 67, 4, 379–95.Google Scholar
Rouse, W. and Morris, N. 1986. On looking into the black box: prospects and limits in the search for mental models. Psychological Bulletin, 100, 3, 349–63.Google Scholar
Rozencwajg, P. and Bertoux, M. L. 2008. Categorization and aging. Current Psychology Letters: Behaviour, Brain & Cognition, 24, 2, 82–97.Google Scholar
Salthouse, T. A., Atkinson, T. M. and Berish, D. E. 2003. Executive functioning as a potential mediator of age-related cognitive decline in normal adults. Journal of Experimental Psychology: General, 132, 4, 566–94.Google Scholar
Scialfa, C. T. and Joffe, K. M. 1998. Response times and eye movements in feature and conjuction search as a function of target eccentricity. Perception & Psychophysics, 60, 6, 1067–82.Google Scholar
Sharit, J., Hernandez, M. A., Czaja, S. J. and Pirolli, P. L. 2008. Investigating the roles of knowledge and cognitive abilities in older adult information seeking on the Web. ACM Transactions on Computer–Human Interaction, 15, 1, 1–25.CrossRefGoogle ScholarPubMed
Slegers, K., Van Boxtel, M. P. J. and Jolles, J. 2009. The efficiency of using everyday technological devices by older adults: the role of cognitive functions. Ageing & Society, 29, 2, 309–25.Google Scholar
Sloutsky, V. M. 2003. The role of similarity in the development of categorization. Trends in Cognitive Sciences, 7, 6, 246–51.Google Scholar
Stronge, A. J., Rogers, W. A. and Fisk, A. D. 2006. Web-based information search and retrieval: effects of strategy use and age on search success. Human Factors, 48, 3, 434–46.Google Scholar
Sum, S., Mathews, R. M., Hughes, I. and Campbell, A. 2008. Internet use and loneliness in older adults. CyberPsychology & Behavior, 11, 2, 208–11.Google Scholar
Thuring, M., Hanneman, H. and Haake, J. M. 1995. Hypermedia and cognition: designing for comprehension. Communication of the ACM, 38, 8, 57–66.CrossRefGoogle Scholar
Wagner, N., Hassanein, K. and Head, M. 2010. Computer use by older adults: a multidisciplinary review. Computers in Human Behavior, 26, 5, 870–82.Google Scholar
Whiting, W. L., Madden, D. J. and Babcock, K. J. 2007. Overriding age differences in attentional capture with top-down processing. Psychology and Aging, 22, 2, 223–32.Google Scholar
Wickens, C. D. and Hollands, J. G. 2000. Engineering Psychology and Human Performance. Third edition, Prentice-Hall, Upper Saddle River, New Jersey.Google Scholar
Zacks, R. T., Hasher, L. and Li, K. Z. H. 2000. Human memory. In Salthouse, T. A. and Craik, F. I. M. (eds), Handbook of Aging and Cognition. Second edition, Lawrence Erlbaum Associates, Mahwah, New Jersey, 293–357.Google Scholar
Zaphiris, P., Kurniawan, S. and Ghiawadwala, M. 2007. A systematic approach to the development of research-based web design guidelines for older people. Universal Access in the Information Society Journal, 6, 1, 59–75.Google Scholar